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The relationship between leisure and mental wellbeing in
middle-aged women who care for more than 20 hours per week:
A secondary analysis using data from a national survey
Angela Clarke
Submitted for the Degree of
Doctor of Psychology
(Clinical Psychology)
School of PsychologyFaculty of Health and Medical Sciences
University of SurreyGuildford, SurreyUnited KingdomSeptember 2018
Page 1 of 197
Abstract
Background: Research has found that carers have limited leisure engagement
compared with non-carers and they have reduced mental wellbeing. Middle aged
women who are intensive carers (>20 hours a week) are at particular risk and were
therefore the focus for this study.
Objectives: The cross-sectional part of this study aimed to explore whether there
was an association between leisure time satisfaction, variety, sporting engagement
and frequency of leisure with carer wellbeing. The longitudinal part of this study
aimed to explore whether becoming an intensive carer was associated with reduced
leisure engagement and reduced wellbeing. Further, whether leisure engagement
predicts wellbeing.
Method: This study used data from a national UK study (UKLHS) that stratified
sampling across the country. Data was collected annually and waves two and five
were used for this study as they included a module about leisure and culture.
Wellbeing was assessed through the GHQ-12. Secondary analysis of this data
included general linear modelling and chi square.
Results: Generally, cross sectional hypotheses were supported although frequency of
leisure engagement was less relevant for wellbeing than variety and satisfaction (the
latter of which explained 12% of the variance). Individuals who did sport had better
wellbeing than those who did not. Individuals who became carers did not reduce
their leisure engagement more than non-carers. Change in satisfaction and variety
predicted change in wellbeing but change in frequency did not. Unexpectedly,
Page 2 of 197
individuals who were not carers at wave two, but were at wave five had poorer
wellbeing at both time points compared to the non-carers.
Conclusions: Leisure is a key contributor to emotional wellbeing, in particular,
carer’s satisfaction with the amount of leisure time they have and whether they
engage in physical activities. This has important implications for services that work
with carers at a local level, and at a policy level.
Page 3 of 197
AcknowledgementsThis has not been an easy endeavour and therefore I owe huge thanks to the many
individuals who offered help, support, and expertise throughout the completion of
this doctorate including all of my supervisors along the way.
Of particular note are my supervisors, Linda Morison and Kate Gleeson. They have
both endured my distress, supported me through the difficulties, and enthused at the
work as it came closer and closer to completion. Their wealth of experience has been
both practically, and emotionally invaluable and without either of them this project
would not have been the same. I thank them both wholeheartedly and am truly
grateful for all their time, energy, patience and enthusiasm.
I would also like to thank Sarah Warrell Phillips for all of her peer supervision and
support throughout the research project.
I would like to that my parents as their support over the years has been invaluable.
Without their unwavering practical and emotional support, I would not even have
made it onto the doctorate in the first place.
Finally, I would like to thank my partner, Michael King, for being a rock of strength.
He has been there to listen to my difficulties, bounce ideas off, and support me in all
my problem solving endeavours.
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Table of contents
Abstract......................................................................................................................................Acknowledgements....................................................................................................................Table of contents........................................................................................................................Declaration.................................................................................................................................Overview of portfolio.................................................................................................................
Empirical Paper..........................................................................................................................Statement of journal choice........................................................................................................Abstract......................................................................................................................................Introduction................................................................................................................................Hypotheses...............................................................................................................................Method.....................................................................................................................................Results: Cross sectional study..................................................................................................Results: Longitudinal study......................................................................................................Discussion................................................................................................................................References................................................................................................................................List of Appendices:..................................................................................................................
Literature review....................................................................................................................Statement of journal choice....................................................................................................Abstract..................................................................................................................................Introduction............................................................................................................................Method...................................................................................................................................Results....................................................................................................................................Discussion..............................................................................................................................Conclusion..............................................................................................................................References..............................................................................................................................
Clinical Experience................................................................................................................Table of assessments completed during training...................................................................
The relationship between leisure and mental wellbeing in middle-aged
women who care for more than 20 hours per week: A secondary analysis
using data from a national survey
By
Angela Clarke
Submitted in partial fulfilment of the degree of Doctor of Psychology (Clinical
Psychology)
School of Psychology
Faculty of Health and Medical Sciences
University of Surrey
April 2018
© Angela Clarke 2018
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Declaration
I confirm that the submitted work is my own work and that I have clearly identified and fully acknowledged all material that is entitled to be attributed to others (whether published or unpublished) using the referencing system set out in the programme handbook/other programme research guidance. I agree that the University may submit my work to means of checking this, such as the plagiarism detection service Turnitin® UK. I confirm that I understand that assessed work that has been shown to have been plagiarised will be penalised.
Signature:
Name: Angela Clarke
Date: 5/4/18
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Overview of portfolioBeing a carer is rich and rewarding, however it can also present many challenges
particularly for those providing many hours of care each week. These carers are at
risk of losing time for leisure pursuits and also of having poorer wellbeing. This
portfolio aimed to explore the relationship between leisure engagement and
wellbeing for carers who spend over 20 hours a week providing care.
The first part is an empirical paper that used secondary data analysis to answer
whether poorer leisure engagement is associated with poorer wellbeing, specifically
for women carers in their midlife. Analysis explored this relationship cross-
sectionally and longitudinally. The findings from the empirical paper suggest that
poorer leisure engagement is associated with poorer wellbeing for women. Change in
leisure participation over a three-year period predicted change in wellbeing over the
same time. Part two presents a structured literature review that aimed to critically
examine and summarise the existing literature on the extent to which leisure
influences well-being among those who spend a significant amount of time caring for
others. Poorer leisure engagement was associated with increased depression, poorer
general wellbeing, reduced positive affect, increased negative affect and fewer
positive attitudes to caregiving.
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Empirical Paper
The relationship between leisure and mental wellbeing in
middle-aged women who care for more than 20 hours per week:
A secondary analysis using data from a national survey
Word Count: 1040
Statement of journal choice
This paper will be submitted to “Social Science & Medicine” whose aim is to publish
“original research articles…to inform current research, policy and practice in all
areas of common interest to social scientists, health practitioners, and policy
makers”. It accepts articles from the field of psychology and has an interest in mental
health, as stated in the scope of the journal. This paper explores issues pertaining to
carers, who are commonly at risk of becoming mental health service users and
therefore fits within the remit of this journal. Findings are relevant to clinicians and
policy makers alike.
The impact factor of the journal is 2.32 (October 2017).
If this article is not accepted by the first choice journal, it will then be submitted to
“Health and Social Care in the Community” and “Health and Quality of Life
Outcomes”.
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Abstract
Background: Research has found that carers have limited leisure engagement
compared with non-carers and they have reduced mental wellbeing. Middle aged
women who are intensive carers (>20 hours a week) are at particular risk and were
therefore the focus for this study.
Objectives: The cross-sectional part of this study aimed to explore whether there
was an association between leisure time satisfaction, variety, sporting engagement
and frequency of leisure with carer wellbeing. The longitudinal part of this study
aimed to explore whether becoming an intensive carer was associated with reduced
leisure engagement and reduced wellbeing. Further, whether leisure engagement
predicts wellbeing.
Method: This study used data from a national UK study (UKLHS) that stratified
sampling across the country. Data was collected annually and waves two and five
were used for this study as they included a module about leisure and culture.
Wellbeing was assessed through the GHQ-12. Secondary analysis of this data
included general linear modelling and chi square.
Results: Generally, cross sectional hypotheses were supported although frequency of
leisure engagement was less relevant for wellbeing than variety and satisfaction (the
latter of which explained 12% of the variance). Individuals who did sport had better
wellbeing than those who did not. Individuals who became carers did not reduce
their leisure engagement more than non-carers. Change in satisfaction and variety
predicted change in wellbeing but change in frequency did not. Unexpectedly,
Page 5 of 197
individuals who were not carers at wave two, but were at wave five had poorer
wellbeing at both time points compared to the non-carers.
Conclusions: Leisure is a key contributor to emotional wellbeing, in particular,
carer’s satisfaction with the amount of leisure time they have and whether they
engage in physical activities. This has important implications for services that work
with carers at a local level, and at a policy level.
Page 6 of 197
Introduction
Carer Wellbeing
Providing care to a loved one is reported to be a rewarding experience that adds
positive aspects to a relationship (Szmukler et al., 1996), and improves family bonds,
love, hope and support for the person cared for (Treasure et al., 2001). The
opportunity to learn and experience reciprocity have also been identified as valuable
consequences (Stern, Doolan, Staples, Szmukler, & Eisler, 1999).
However, carers are more likely to have reduced wellbeing compared to those who
do not have a caregiving role (Cooper, Balamurali, Selwood, & Livingston, 2007;
LoGiudice et al., 1998; Mausbach, Coon, Patterson, & Grant, 2008; Schulz, O’Brien,
Bookwala, & Fleissner, 1995; Smith et al., 2014; Williamson & Schulz, 1992).
In particular, carers who spend more than 20 hours per week caring are at increased
risk of mental health difficulties when compared with people who spend less than 10
hours caring (Smith et al., 2014). Such individuals are also more likely to find that
their caring role interferes with their work and leisure. Indeed, there is a large body
of research indicating that carers often have to either reduce or cease employment
(Mosher et al., 2013; Ory, Hoffman, Yee, Tennstedt, & Schulz, 1999; Otis-Green &
Juarez, 2012), and that becoming a carer is associated with a reduction in leisure
engagement (Magliano, Fiorillo, Rosa, & Maj, 2006; Martin, 2015; Morais et al.,
2012; Rochette, Desrosiers, Bravo, Tribble, & Bourget, 2007). In one recent study as
many as 90% of caregivers had difficulties with their leisure activities as a result of
their caregiving responsibilities (Peña-Longobardo & Oliva-Moreno, 2015).
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The stress-process model provides a framework for conceptualising the relationships
between caregiving, work, leisure and wellbeing (Pearlin, 2009; Pearlin, Mullan,
Semple, & Skaff, 1990). It suggests that individuals have limited resources and when
the demands placed on them exceed these, individuals experience stress and mental
illness. Primary stressors (such as becoming a carer) exist within a background of
contextual factors (such as age, gender and socio-economic background) which can
affect one’s ability to cope. Additionally, primary stressors can have a knock-on
effect for other areas of life. For example, the time demands of caring may affect the
ability to engage in leisure activities which may have previously been an important
stress coping mechanism (secondary stressor). This model also recognises the
importance of social relationships in maintaining or exacerbating wellbeing. This
model holds face validity and has been used widely within the caregiving literature
(e.g. Papastavrou, Kalokerinou, Papacostas, Tsangari, & Sourtzi, 2007; Stansfeld et
al., 2014).
Leisure and carers
Leisure is the engagement in activities which are neither required for financial gain,
nor for day to day living (Voss, 1967), activities that are chosen and intrinsically
motivated rather than necessary (Neulinger, 1981). Judgement about whether or not
an activity is necessary is inevitably subjective, therefore some also describe leisure
as a “state of mind” (Parr & Lashua, 2004). For example, cooking might be a form of
employment for some, a daily necessity for others, and a pleasurable pastime
(leisure) for others.
The impact of leisure on carer wellbeing has been widely researched. For example,
caregivers of the elderly who were less satisfied with their leisure time were also
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more likely to be more anxious, and more depressed than caregivers who were more
satisfied (Del-Pino-Casado & Ordóñez-Urbano, 2016). Leisure satisfaction was also
related to quality of life for parents of children with learning disabilities (Hsieh,
2011). Similar findings emerged from a study with carers of individuals with spina
bifida (Grosse, Flores, Ouyang, Robbins, & Tilford, 2009), with a lack leisure days
being associated with lower wellbeing and “feeling blue”. An association between
leisure and wellbeing was also found in caregivers of individuals with mental health
difficulties (Grover & Dutt, 2011), and in a more general sample of caregivers
(White-Means & Chang, 1994). These studies were all questionnaire based. A study
using daily diary methodology found that the total number of activities was related
to positive affect (Mausbach, Coon, et al., 2008), engaging in more activities being
associated with greater positive affect.
Although there is a large body of evidence to suggest that leisure is associated with
wellbeing in carers, there is also some research with contradictory findings. For
example, Loi and colleagues (2016) did not find a relationship between physical
leisure activity and depression in older carers despite this relationship being
evidenced in this population in other studies (Del-Pino-Casado & Ordóñez-Urbano,
2016). Neither was a relationship found between leisure participation and wellbeing
in another study (Rizk, Pizur-Barnekow, & Darragh, 2011). The mix of findings
could be due to the complex nature of the constructs and measurements of leisure.
Dimensions of Leisure
Different types of leisure may have different levels of impact on carer wellbeing. For
example, exploration, domestic and nature related leisure pursuits were all associated
with fewer depressive symptoms (Thompson, Solano, & Kinoshita, 2002). Outside
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leisure activities were related to improvements in life satisfaction but not to
depression and home leisure and social engagement were related to reduced
depression and increased life satisfaction respectively (Wakui, Saito, Agree, & Kai,
2012). Interestingly, monthly engagement in home leisure had a greater impact on
carer satisfaction than more frequent participation. This might suggest that while
leisure can lead to positive outcomes, there can be burdens associated with making
time for it and arranging it.
Support for the role of sport and exercise in maintaining carer wellbeing comes in
part from intervention studies. A 6 month intervention study found that a supported
physical activity programme for carers improved their symptoms of depression (Hill,
Smith, Fearn, Rydberg, & Oliphant, 2007). A home exercise programme led to
improvement in depression scores (Vincente, Delgado, Fuertes, & Prieto, 2009). A
yoga intervention resulted in reduced depression and anxiety in caregivers (Waelde,
Thompson, & Gallagher-Thompson, 2004). However there has been less work
investigating the impact of increasing other types of leisure activities.
A very commonly used measure of leisure is satisfaction with leisure time (Bedini,
Gladwell, & Dudley, 2011; Mausbach, Harmell, Moore, & Chattillion, 2011;
Williams, 2005). Some of these studies have been mentioned in more detail above.
Leisure satisfaction has frequently been shown to be positively correlated with
wellbeing in carers.
As described above, the literature in this field has explored facets of engagement
such as satisfaction with leisure time (Bedini et al., 2011; Williams, 2005), frequency
of participation in different types of leisure activities (Ficker, 2011; Wakui et al.,
2012), whether people are engaging with physical exercise (Hill et al., 2007;
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Vincente et al., 2009) and overall engagement with leisure activities. However, most
studies do not measure engagement in a range of leisure activities, and only measure
one dimension of leisure engagement (e.g. either satisfaction with leisure time, or
frequency of participation). Therefore, further research is warranted to better
understand the roles each of these factors play in the relationship between leisure
engagement and the emotional wellbeing of carers.
Sociodemographic factors
Gender
There is good evidence that sociodemographic variables are important in affecting
the leisure engagement and wellbeing of carers. For example, women are less likely
than men to take part in physical activity and this was affected by gender-based time
negotiation and ethic of care (prioritising the needs of others over their own needs)
(Miller & Brown, 2005). This finding is consistent with another study that found that
males were more likely to be working full time and therefore to perform the role of
secondary carer (Grant & Whittell, 2000). Women rated their role to care for others
as a higher priority than their responsibility to meet their own self care needs,
including their right to leisure time (Bedim & Guinan, 1996; Miller & Brown, 2005).
In one study women rated the barriers to leisure more highly than men in the
following areas: “difficult to find others [to participate with], too busy with family,
no physical ability, don't know where to participate, lack of transportation, don't
know where to learn, not at ease in social situations, and physically unable to
participate” (Jackson & Henderson, 1995, p40). Differences in preferred leisure
activities have also been found between men and women, and across different
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perceived social classes, however the quality of these differences (i.e. how and in
what ways they were different) was not explored (Iso-Ahola, Jackson, & Dunn,
1994).
Finally, there is evidence that women carers experience reduced wellbeing compared
with men. One meta-analysis found that caregivers were more impaired than non-
caregivers in terms of depression and subjective wellbeing when the studies had a
higher percentage of female participants (Pinquart & Sörensen, 2003). Another study
showed that carers who were women had higher psychiatric morbidity (Raj,
Manigandan, & Jacob, 2006).
Therefore, there are many factors differentiating male and female leisure
engagement. Women are more likely to be primary caregivers, report more barriers
to leisure than men, have reduced wellbeing, and have difficulty in prioritising their
own self-care needs over the care needs of others. Given these factors, and the
evidence that leisure can affect wellbeing, it seems important to better understand the
relationship between leisure engagement and wellbeing for female caregivers.
Age
There is evidence that both leisure habits and wellbeing change across the life-span.
Iso-Ahola and colleagues (1994) found that people are more likely to start new
activities earlier in adult life and that, for women, there is a steady decrease in variety
of leisure activities over the life course. Another study found that perception of a lack
of skills increased as people got older, and family and work commitments peaked in
mid-life (Jackson & Henderson, 1995). These were barriers to engaging in leisure
activities.
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Defining distinct age stages is a challenge within the literature which has not been
fully resolved, however “midlife” can be considered as occurring from the
approximate range of 40-60 (Staudinger & Bluck, 2001) These individuals often fall
within the so-called ‘sandwich generation’, named for the position they hold caring
for those in both the generation above (often parents or in-laws), and the generation
below themselves (Chassin, Macy, Seo, Presson, & Sherman, 2010; Hamill &
Goldberg, 1997). Individuals within this group are less likely to engage in healthy
behaviours such as physical leisure activities (Chassin et al., 2010).
Other relevant variables
According to the stress process model other variables may be relevant to the
relationship between carers’ leisure engagement and their wellbeing. Evidence from
the literature supports the idea that socioeconomic status is a key contextual factor or
carer characteristic that might impact on wellbeing (Lee & Bhargava, 2004).
Primary stressors can include whether the individual lives with the cared-for person
and how many hours per week they spend caregiving (Pearlin et al., 1990).
Secondary stressors include other demands on a caregivers’ time which may be
affected by the caregiving role including employment status and childcare
responsibilities (Lee & Bhargava, 2004; Pearlin et al., 1990). Finally, social support
can be a protective factor for carers (Gallo, 1990; Goode, Haley, Roth, & Ford,
1998). Therefore, any research exploring the relationship between leisure and
wellbeing would need to take these other factors into account.
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Summary
Female carers in midlife are at risk of having decreased wellbeing due to the
competing demands on their time which may exceed their resources (Staudinger &
Bluck, 2001). In the UK, state pension can be claimed from the age of 65 which
indicates that work as a competing demand is likely to continue until at least that age.
The stress process model provides a framework for understanding how these
competing demands on carer time, leisure engagement and other relevant variables
impact on carer wellbeing (Pearlin, 2009; Pearlin et al., 1990).
Engaging in leisure activities is often used as a coping mechanism to manage the
stress of competing demands and research shows that carers who engage in leisure
activities are likely to have a better wellbeing than those who don’t (Azman, Jamir
Singh, & Sulaiman, 2017; Orgeta & Miranda-Castillo, 2014). Although there is some
recent research which conflicts with this notion (Loi et al., 2016), and research
looking specifically at women who care for more than 20 hours per week is limited.
Throughout the literature, many different aspects of leisure have been measured and
it is not clear which facets are most strongly related to wellbeing. There has been
some indication that satisfaction with leisure time, overall leisure engagement,
frequency of leisure engagement, and whether people do sport, may each be related
to wellbeing. No studies were found that explored the relative effects of all of these
factors.
Additionally, the literature regarding carers and leisure activities is often limited in
terms of participant sample sizes, frequently only explore a limited number of leisure
activities and rarely explore relationships longitudinally (Clarke, 2018; Loi et al.,
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2014). Therefore, further research is needed to better understand how the wellbeing
of females in midlife is affected by their engagement in leisure activities.
Understanding Society
In 2009 a national longitudinal project in the UK called Understanding Society was
launched with its first full wave of data collection. It aimed to be representative of
the UK population taking a stratified sample of 40,000 households. Questionnaires
were administered annually to each of the residents within those households (See
Knies [2015] for more details). The study includes a variety of topics ranging from
leisure engagement to financial circumstances, and includes questions relating to key
demographic characteristics, including whether the individual cares for anyone
within or outside of their home and factors described in the stress process model.
Although restricted to the measures that were determined by the Understanding
Society team, the survey provides a good opportunity to explore the relationship
between leisure and wellbeing. Measures being repeated at multiple time points
allowed for both cross sectional and longitudinal exploration of relationships.
Additionally, as with any longitudinal study, attrition rates may bias the sample in
later waves of data collection. Fortunately, with such a large starting sample, and
with new participants regularly being incorporated into the project, attrition rates are
likely to have a reduced impact compared with smaller projects of a similar nature.
Therefore, the Understanding Society project provides a good opportunity to
examine this area of interest with a large participant sample which is representative
of the UK population. The study reported here is a secondary analysis of this dataset.
It aimed to examine leisure activities as a predictor of well-being and the impact of
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becoming a 20+ hours carer on wellbeing and leisure activities for female carers in
mid-life.
Hypotheses
1. At a cross sectional level, lower leisure engagement will predict poorer wellbeing
for women aged between 40 and 65 who care for 20 hours or more each week.
a. Lower frequency, variety, and satisfaction of leisure activities, will predict
lower levels of wellbeing.
b. Those not involved in moderate to high intensity sporting activities will have
poorer wellbeing than those who are involved in sporting activities.
2. Becoming a carer who cares for 20 hours or more each week will affect leisure
engagement and wellbeing for women aged between 40 and 65.
a. Becoming a carer who spends 20 or more hours per week caring will be
associated with reduced frequency, variety, and satisfaction with leisure
activities. These relationships will be moderated by changes in the number of
competing demands (employment and childcare), such that the decrease in
frequency, variety and satisfaction will be stronger in those with an increase
in competing demands, and weaker for those who have had a reduction in
competing demands.
b. Becoming a carer who spends 20 or more hours caring a week will be
associated with reduced wellbeing when compared with wellbeing prior to
becoming a carer.
c. Change in leisure will predict change in wellbeing.
Changes over time for carers will be explored in relation to non-carers to
control for general temporal changes.
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Method
Participants
Participants were selected from a larger sample of participants who were part of the
UK Household Longitudinal Study (UKHLS) also known as Understanding Society
(University of Essex, 2017). Original members were selected for the study based on a
random sample of households which was stratified by location, and totalled
approximately 40,000 in number at its first wave of data collection. UKHLS aimed to
interview all members of the household. Sample stratification took into account the
population density, ethnic minority density and proportion of households with non-
manual workers. Although the population sample is largely stable (Lynn & Knies,
2016), temporary and permanent members have been recruited depending on new
members (e.g. children, and partners) joining or leaving households. The survey
aimed to keep members who were in the original sample even if they moved house.
Data for participants who were female, between the ages of 40 and 65 and who
reported being a carer were used. A “carer” was defined as someone who provides
special help and support to individuals who are sick, disabled or elderly living within
or outside of the household. Parents of children without additional needs were not
classed as carers. This definition is in keeping with the wording used within
Understanding Society (see Appendix B for exact wording of the question).
Design
Data from the UKHLS were used and details of the study are widely available
(Knies, 2015). To summarise here, it is an annual cross-sectional survey of the same
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people. The data is collected in face to face interviews with trained interviewers
using Computer Aided Personal Interview (CAPI).
Core modules are asked at every wave and rotating modules are asked at one off time
points, or at regular intervals greater than one year. The rotating module that was of
interest to this study was the Leisure, Culture and Sport module which was repeated
at waves two (W2) and five (W5), and therefore data from these time points were
used to explore the research questions. Data were also taken from core modules to
identify participants who met the criteria for this study (see above) and to explore the
impact of relevant variables from the stress process model. See “Measures” section
for further details.
This study had a cross sectional component which looked at the relationship between
levels of leisure and wellbeing using data from W2. It also had a longitudinal aspect
which looked at the effects of becoming a carer using W2 and W5 which were 3
years apart. In order to control for general temporal changes, non-carers were used as
a comparison group in the longitudinal analysis.
Ethical Issues
The Understanding Society study received ethical approval from the University of
Essex Ethics Committee. All data has been anonymised (names, contact information,
and dates of birth were removed) and is stored electronically with the UK Data
Archive based at the University of Essex. Full participant consent was obtained at
each wave of data collection and participants were provided with a £10 Love2Shop
High Street voucher as a token of appreciation for taking part. Participants had the
opportunity to specify the most appropriate times to receive contact from the
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researchers. Data is freely available for social researchers to access however is not
available to commercial companies. Further discussion about ethical issues
associated with UKLHS and how these have been addressed can be found in the
Understanding Society Quality Profile (Lynn & Knies, 2016).
For the purpose of this study only data from relevant waves were accessed and used.
Data were stored on a password protected computer. An online self-assessment form
was completed through the University of Surrey to ensure it was not necessary to
gain further ethics approval for this secondary analysis study (see Appendix A).
Measures
Outcome measure: Wellbeing
In order to measure wellbeing this study used the 12 item version of the General
Health Questionnaire (GHQ-12). The GHQ-12 is a screening tool for minor
psychiatric conditions within the general population and is based on the original 60
item measure (Goldberg, 1972). It has good reliability and convergent validity
(Hardy, Shapiro, Haynes, & Rick, 1999), with the alpha coefficient being .88 and a
test re-test correlation of .73. Hardy and colleagues also found a good correlation
between the GHQ-12 and a range of other mental health measures (e.g. Clinical
Interview Schedule – Revised). Cronbach’s alpha for cross sectional analysis for this
study was .93, and for the longitudinal analysis was .93.
Although GHQ-12 is sometimes used to report on caseness, it was not in this study
due to the researcher’s ethical stance not to propagate narratives that mental
wellbeing is a binary construct. It was decided to report only on findings from likert
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data as this was felt to more accurately represent real world experiences of mental
wellbeing lying on a continuum.
For the longitudinal analysis, change in wellbeing was calculated by subtracting
GHQ-12 at W2 from GHQ-12 at W5. Negative scores represented an improvement
in wellbeing from W2 to W5.
Leisure Variables
Satisfaction with leisure time
This was taken from the response to one item asking participants to indicate on a
scale of 1-7 (with 1 being “not at all satisfied” and 7 being “highly satisfied”) how
they feel about the amount of leisure time they have. For the longitudinal analysis,
change in satisfaction was calculated by subtracting satisfaction at W2 from
satisfaction at W5. Positive values represented an increase in the amount of
satisfaction with leisure time from W2 to W5.
Variety of leisure activities
Participants were asked to indicate which activities they had undertaken in the last 12
months from a provided list (e.g. “event connected with books or writing” (Appendix
C)). The affirmative responses were summed to assess the variety of leisure activities
undertaken. For the longitudinal analysis, change in variety over time was calculated
by subtracting variety at W2 from variety at W5. Positive values represented an
increase in the number of different leisure activities from W2 to W5.
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Frequency of leisure engagement
The Leisure, Sport and Culture module included eight categories: arts activities, arts
events, museum, library, archives, historical sites, sporting activities, and mild
intensity sporting activities (see Appendix C). Participants were given response
options for how frequently they engaged in each category e.g. “once a week”, “once
in the last year”. The categories of sporting activities and low intensity sporting
activities had an additional response option of “3+ times per week”.
Attempts were made to make this a single continuous variable, however because the
response options were broad, differed for sporting activities, and were not at regular
intervals it was not felt to be a reliable measure of leisure frequency. Therefore, the
eight separate leisure categories were analysed separately. In the longitudinal
analysis there was not enough data to analyse “Archives” frequency (how frequently
a participant had been to an archive centre or records office) and therefore this was
removed. For the longitudinal analysis, change in frequency was calculated by
determining whether participants had increased, reduced or maintained their
frequency within that category.
In the cross-sectional analysis, participant numbers for each of the frequency ratings
was variable across the different leisure categories. When participant numbers were
too low, frequency ratings were collapsed in order to make analysis viable, e.g. for
archives frequency the three categories of “not at all”, “once last year” and “twice
last year” were used.
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Sporting activities
Two questions addressed sporting activities. As seen in Appendix C, participants
were asked about various high/moderate and low intensity sporting activities. From
this data three groups were identified for comparison: participants who had taken
part in High/Moderate intensity sporting activities, individuals who had engaged in
mild intensity sporting activities, and those who had not participated in sporting
activities.
Another indication of engagement with sporting activities was taken from the
questions asking how frequently participants had engaged in moderate intensity
sporting activities, and mild intensity sporting activities. Responses fell into 5
categories: not at all, once or twice in the last year, three or four times in the last
year, at least monthly but less than weekly, and once a week or more.
Other variables in the stress process model
Carer Characteristics
In keeping with research that has found income, employment status and age are
related to leisure engagement (Lee & Bhargava, 2004), these factors were all
adjusted for. Income was explored through one question relating to subjective
financial situation (good, just about managing, or finding things difficult). This and
highest qualification also serve as some indication of socioeconomic status (SES)
which has been found to impact on leisure engagement (Hallal, Victora, Wells, &
Lima, 2003). Although job type is often used as an indicator of SES, only around
half of the carers in this participant sample were employed and therefore this was not
felt to be a useful way of understanding the SES of participants in this group. It is
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common for high proportions of carers to not be working (e.g. Bittman, Hill, &
Thomson, 2007; Mosher et al., 2013; Thompson et al., 2002). Household income is
also commonly used however, due to the complexities of the Understanding Society
dataset, it was not possible to calculate this.
Primary Stressors
Primary stressors included the number of hours spent caring, and whether the carer
lived with the person for whom they were providing care. Information about how
many hours of care was addressed in one question which offered 9 response options
e.g. (“0-4 hours”). For the purpose of the cross-sectional study, only responses that
were greater than 20 hours per week were included and these were condensed into 3
categories: “20-49 hours”, “50 hours or more”, and “varies over 20 hours”.
Whether someone lived with the individual for whom they were providing care was
calculated from the responses to two items: whether they provided additional help to
someone within the household, and whether they cared for someone outside the
household. It was a binary variable.
Secondary Stressors (Competing Demands)
According to the stress process model it is likely that having competing time
demands would be a secondary stressor, carers often giving up leisure activities due
to the time constraints (Dunn & Strain, 2001). Women with children are also less
likely to engage with leisure than women without children (Miller & Brown, 2005).
Therefore, participant data about employment status and whether they were
responsible for children under the age of 15 were used.
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In cross sectional analysis employment status was grouped into four categories:
Working, looking after family/health/home, retired, and unemployed or doing
something else. This enabled the data to be explored in terms of the likely cultural
and personal meaning related to a particular employment status. It was also deemed
that within these categories people might have different opportunities for leisure.
However, for the longitudinal analysis employment status was a binary variable
(employed/not employed) as this was more appropriate for the statistical methods
used.
Change in competing demands was calculated by adding up how many competing
demands each participant had at W5 (i.e. work or childcare), and subtracting it from
how many competing demands they had at W2. Positive scores indicated an increase
in competing demands from W2 to W5.
Social Support
Finally, social support has been shown to be influential in carers’ wellbeing (Gallo,
1990; Goode et al., 1998). Additionally women who do not live with a partner have
lower levels of physical activity (Hallal et al., 2003). Therefore, two indicators of
social support were included: living with a partner, and relationship quality.
Relationship quality was determined through a relationship quality rating scale
relating to each of the following: their partner (Cronbach’s alpha for the cross
sectional study was .82, and for the longitudinal study was .81), best friend (.73
and .79 respectively), and closest family member (.81 and .71 respectively). Not
every participant was able to rate a person from each category and therefore the
highest rating across the three evaluated relationships was taken as an indicator of
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social support. This variable was described as “relationship quality” throughout the
analysis.
See Figure 1 for a diagrammatic representation of variables considered, and the
direction of the effects.
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Data analysis
Cross sectional study
Participants who were female, between the ages of 40 and 65 and who identified as
carers were selected from the overall dataset. Individuals with missing data for
leisure and outcome variables were excluded leaving a total of 710 participants for
this analysis. See Figure 2 for a diagram representing the participant exclusion
process.
The data were assessed to see the extent to which the assumptions for parametric
testing were met (Appendix D). Levene’s and Hartley’s Fmax (Field, 2013) were
examined to assess homogeneity of variances but the large sample sizes meant their
results were not a good indicator of whether the validity of the results was likely to
Figure 1: A diagrammatic representation of variables considered in this study. Based on Pearlin's (2009) stress process model. Within the diagram only effects and variables that were explored in this study are labelled
Secondary Stressors (competing demands)
Employment.Childcare.
Social Support
Highest quality relationship.Living with partner.
Wellbeing
GHQ-12 (MCS).
Primary Stressors
Hours per week spent caring.Living with the cared for individual.
Leisure
Frequency.Variety.Sport/No sport.Leisure time satisfaction.
Carer characteristics
Age.Socioeconomic status:
Highest qualification Subjective finances
Page 26 of 197
be affected by heterogeneity of variance (Field, 2013; Lumley, Diehr, Emerson, &
Chen, 2002). With these sample sizes anything other than exactly equal variances
(i.e. variance ratio=1) was significant using Levenes or the F test and therefore
heterogeneity of variances was assessed by inspection of the observed standard
deviations. Histograms, and Q-Q plots were used to assess normality and again the
large sample meant that only marked non-normality was likely to affect the validity
of the results (Motulsky, 2014). Some positive skew was apparent so in order to
examine robustness of the results from parametric tests, equivalent non-parametric
and robust tests were also conducted. Results from robust and non-parametric tests
were consistent with results from parametric tests (Appendix E). Results that were
statistically significant from parametric tests were also significant when using non-
parametric and robust tests.
The General Linear Modelling (GLM) in SPSS was used to examine the extent to
which each of the leisure variables predicted GHQ-12. GLM was used as it allows
for categorical predictors as well as continuous predictors. In this analysis the aim
was to focus on the relationship between leisure and well-being rather than trying to
fit the whole stress process model. Therefore, the other measured variables in the
stress process model were added separately to the above GLM to examine their
individual impact on the relationship between leisure and wellbeing. Where the
addition of the variables substantially altered the relationship between leisure and
wellbeing further analysis was conducted to examine how that variable was related to
the leisure variable and wellbeing (using GLM).
Page 27 of 197
Longitudinal study
Participants who were female and between the ages of 40 and 65 at both waves were
selected from the overall dataset. Participants who were providing 20 or more hours
of care per week at both waves, or who were carers at W2 but not at W5 were
excluded. Those who had stopped providing care were not included because they
could have been affected by issues of role loss or bereavement that could impact on
findings.
Participants were then grouped by caregiving status into: those providing less than 20
hours of care at W2 and more than 20 hours of care at W5 (increased caring), those
not providing care at W2 and providing more than 20 hours of care at W5 (new
carer), and those not providing any care at either time point (non-carer). The non-
carer group was included to control for temporal changes (i.e. changes occurring for
the whole cohort over time, not because of caring). Participants with missing leisure
and wellbeing data were excluded, leaving a total number of 109 women who had
increased their caring, 103 who were new carers, and 4224 women in the comparison
group of non-carers. See Figure 3 for a diagram representing the participant selection
process.
The data was assessed to see the extent to which the assumptions for parametric
testing were met. Histograms were used to assess normality (Appendix H). As with
the cross-sectional study, non-parametric equivalents tests were used to assess the
robustness of findings from parametric tests (Appendix I).
Repeated measures analysis was used to explore the extent to which wellbeing,
variety and satisfaction decreased over time. This allows examination of between-
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subjects effect of being a carer, main effect of time, and the interaction between time
and carer group. The latter is the effect of most interest as it tests whether changes
over time were different between carer groups. Additional models were fitted to
examine effects of competing demands and other variables from the stress process
model (Appendix J).
Chi square tests were used to explore whether changes in frequency of leisure
changed differentially over time. In general, sample sizes were large enough to meet
assumptions of this test, and where cell counts were low, frequency categories were
collapsed to mitigate this. Due to very low numbers of participants reporting using
archives, this variable was not included in the analysis process.
GLM was also used to explore the extent to which a change in leisure predicted a
change in wellbeing. GLM was used as it allows for categorical predictors as well as
continuous predictors.
Bonferroni corrections were not used in this study because evidence suggests that
they are unnecessary and may cause problems such as increasing the likelihood of
type II errors (Perneger, 1998).
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Figure 2: Flow chart depicting the participant exclusion process for the cross-sectional study.
Total sample W2
Total n = 54597
Select women
Total n = 29551
Select people who were 40-65
Total n = 12931
Select carers 20+ hours per week
Total n = 876
Exclude people where relationship to cared for
person is described as “client” (n=3)
Total n = 873
Exclude people who care for more than 3 people
(n = 8)
Total n = 865
Exclude people with “missing” data for wellbeing
(n=145)
Total n = 720
Exclude people with no data for leisure
satisfaction (n=10)
Total n = 710
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Total participants who
meet inclusion criteria
N=5490
Non-carers n = 5215
Increased caring n = 131
New carers n = 144
Select people who were not carers at either wave,
increased care from <20 hours per week (hpw) to >20
hpw, or became carers (>20 hpw).
Total n = 5492
Exclude people with “missing” data for wellbeing at
either wave (n=926)
Total n = 4564
Total sample W2 and W5
Total n = 62095
Select women
Total n = 20521
Exclude people with missing data for leisure
satisfaction (n=51)
Total n = 4513
Select people who were 40-65 at both W2 and W5
Total n = 8577
Exclude people with missing data from other relevant
variables (n=15)
4435
Exclude people with relationship to cared for
described as “client” (n=2)
Total n = 5490
Exclude people with missing data for leisure
frequency/variety (n=63)
Total n = 4450
Non-carers n = 4340
Increased caring n = 113
New carers n = 111
Non-carers n = 4296
Increased caring n = 113
New carers n = 104
Non-carers n = 4238
Increased caring n = 109
New carers n = 103
Non-carers n = 4224
Increased caring n = 109
New carers n = 103
Figure 3: Flow chart depicting participant exclusion process for longitudinal hypotheses.
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Results: Cross sectional study
Participant characteristics
A total of 710 women were included in this study through the selection process
described above. Most participants were White-British (66%), were living with the
individual they were caring for (71%), living with a partner (72%) and were not
responsible for a child under the age of 15 (73%). Only 39% of participants were
working and 34% reported they were not working for either health, caregiving or
home care reasons (Table 1).
Table 1: Participant demographic information for cross section participant sample. Total n = 710.
N %Age M= 52.4, SD=7.4
40-44 139 2045-49 134 1950-54 140 2055-59 133 1960-65 164 23
Ethnicity British, Irish or other White backgroundOther ethnic groupData not provided
46874168
661024
Subjective Finances GoodJust about managingThings are difficult
327251132
463519
Hours per week spent caring 20-49 hours50 or more hoursVaries over 20 hours
296282132
424018
Children under 15 YesNo
189521
2773
Highest qualification Degree or higherLess than degree but higher than GCSEGCSE and other school certificatesNone of the aboveInapplicable
6280180241147
911253421
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N %
Living with a partner YesNo
514196
7228
Employment status WorkingFamily/health/home careRetiredUnemployed or doing something else
27924712163
3935179
Living with the person for whom they provide care
Cares at homeCares outside homeBoth
41420690
582913
Study Measures
The range of GHQ-12 scores within this study was 0-36 which is the same as the
possible range for this measure. The mean was 13.9 with a standard deviation of 6.7.
The means and standard deviations for satisfaction with leisure time and variety of
leisure activities can be seen in Table 2. The range of possible responses for
satisfaction was 0-7 which were all represented within this sample. For variety, the
possible range was broader (0-71) and the range observed in this study was 0-43.
Some of the response options for frequency variables were collapsed to mitigate for
low cell counts in some of the categories. Frequency categories and the number and
percentage of participants indicating each response can be seen in Table 2.
Hypothesis 1a: Less satisfaction, variety, and frequency of leisure
activities, will predict lower levels of wellbeing.
General Linear Models (GLMs) were used to examine the extent to which each
leisure variable predicted GHQ-12 score. The relationship between satisfaction with
leisure time and wellbeing was statistically significant (p<.001). People who were
less satisfied with their leisure time also had poorer wellbeing than those who
reported higher levels of satisfaction. The regression coefficient showed an estimated
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decrease of 1.317 in the GHQ-12 for every point increase in satisfaction. Further,
satisfaction accounted for 12.4% of the variance in GHQ-12 scores (Table 2).
There was a significant main effect of variety on wellbeing (p=.015). The regression
coefficient showed an estimated decrease of .093 in the GHQ-12 for every additional
type of activity.
For arts events, such as the theatre and carnivals, there was a significant main effect
of frequency of on wellbeing (p=.013). Individuals who took part in these activities
monthly had the best wellbeing (M=11.875, SE=.785), and those who took part in
activities once in the past year or not at all had the poorest wellbeing (M=14.791,
SE=.718 and M=14.687, SE=.409 respectively). There was no significant main effect
of frequency of arts activities (e.g. drawing), library, archives, museum or historical
sites on wellbeing (Table 2). Frequency variables were also fitted as a trend, and
results were consistent with previous findings, that individuals who take part in arts
events more frequently had better wellbeing than those who took part less frequently.
Most of the other frequency variables showed non-significant negative relationships
with GHQ-12 scores.
Table 2: Associations between leisure variables and the GHQ-12. Total n = 710.
M (SD) b (SE) F P R2
Satisfaction 4.17 (1.79) -1.317 (.132)
100.278 <.001 .124
Variety 7.03 (6.57) -.093 (.038) 5.947 .015 .008
% (N) M (SD) b (SE) PArts Activities -.147 (.146) .314 . 546 .702 .003
Not at all 25.8% (183) 14.21 (6.78)1-2 times last year 3.1% (22) 14.91 (7.95)At least 3/4 times 7.0% (50) 14.48 (7.50)At least monthly 8.2% (58) 13.17 (6.00)Weekly 55.9% (397) 13.73 (6.70)
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% (N) M (SD) b (SE) P F P R2
Arts Events -.793 (.230) .001 3.488 .008 .019Not at all 37.3% (265) 14.69 (7.01)1-2 times last year 25.6% (181) 14.38 (6.81)At least 3/4 times 25.2% (179) 13.10 (6.02)Monthly 10.1% (72) 11.88 (6.46)Weekly 1.8% (13) 13.38 (6.33)
Library -.309 (.197) .117 1.213 .304 .007Not at all 64.9% (461) 14.16 (6.66)1-2 times last year 7.6% (54) 13.06 (6.74)At least 3/4 times 9.7% (69) 14.38 (7.22)Monthly 13.8% (98) 13.34 (6.75)Weekly 3.9% (28) 12.00 (6.70)
Archives .868 (.775) .263 .695 .499 .002Not at all 95.3% (677) 13.83 (6.64)once last year 2.5% (18) 15.22 (8.25)Twice last year 2.1% (15) 15.27 (7.76)
Museum -.447 (.316) .158 .882 .474 .005Not at all 70.4% (500) 14.12 (6.56)1-2 times last year 16.6% (118) 13.21 (6.61)At least 3/4 times 10.3% (73) 13.84 (7.33)Monthly 2.7% (19) 11.95 (7.75)Weekly 3.9% (28) 12.00 (5.72)
Historical sites -.264 (.243) .278 2.251 .062 .013Not at all 46.2% (328) 14.30 (6.82)1-2 times last year 26.4% (188) 13.97 (6.61)At least 3/4 times 18.6% (132) 12.45 (5.70)Monthly 7.0% (50) 14.26 (7.78)Weekly 1.7% (12) 16.25 (6.70)
MI = moderate intensity; LI= low intensity; F, P and R2 are reported for when frequency was included in the model as a categorical variable. B(SE) and P are reported for when the frequency variables were fitted as a trend.
Adjusting for other stress process model variables
The other variables in the stress-process model were considered as potentially
influencing leisure, or the relationship between measures of leisure and GHQ-12. To
examine this each variable was included in the model with the leisure variable to
examine whether its inclusion altered the relationship between the leisure variable
and GHQ-12 (Tables 4 and 6).
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The relationship between leisure satisfaction and wellbeing remained robust when
other variables from the stress process model were input into the regression model.
The relationship between the number of different activities and wellbeing remained
similar when most of the other variables were controlled for. Exceptions to this were
when finances were controlled for which substantially altered the regression
coefficient and the p-value (Table 3). Smaller alterations were seen when considering
whether the carer lived with the cared for and whether they were employed.
Due to the large effect of adding finances into the model this was explored further
(Table 4). People who had more money did more leisure activities (p<.001).
Comparisons of means showed that people whose financial situation was “good”
were doing significantly more (M=8.569, SE=.355) than people who were “just
about managing” (M=5.821, SE=.406) and those who were “finding things difficult”
(M=5.538, SE=.559) (Table 4). In summary, those who felt they had a good
financial situation generally had a greater variety of leisure activities which is likely
to be one route through which they experienced better well-being.
For most of the frequency variables the addition of the other stress process variables
made little difference (Table 5). The relationship between frequency of arts events
was affected by finances (p=.268) and, to a lesser degree, by childcare (p=.070).
Further, frequency of going to the library emerged as having a significant
relationship with wellbeing when hours per week of care were taken into account
(p=.023).
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Table 3: Statistics from the GLM for Variety and Satisfaction with GHQ-12.
Adjusted for Variety Satisfaction
b F P R2 b F P R2
Unadjusted -.093 5.95 .015 .008 -1.317 100.28 <.001 .124
Carer characteristicsAge -.104 7.39 .007 .020 -1.293 92.98 <.001 .125Finances -.038 1.05 .307 .099 -1.074 2401.52 <.001 .173Qualification -.099 5.67 .018 .016 -1.342 103.80 <.001 .135
Primary stressorsCares at home -.071 3.35 .068 .019 -1.292 3784.41 <.001 .133HPW caregiving
-.080 4.36 .037 .019 -1.287 94.78 <.001 .130
Competing demandsWork -.065 2.87 .091 .050 -1.300 10.59 <.001 .162Childcare -.094 5.97 .015 .008 -1.337 101.97 <.001 .126
Social supportRelationship quality
-.083 5.16 .023 .096 -1.133 75.40 <.001 .177
Relationship status
-.092 5.91 .015 .019 -1.294 4.79 <.001 .130
HPW = hours per week; Figures shown represent the values for variety/satisfaction when the additional variables were added into the model.
Table 4: Variety as DV and finances as IV in GLM with pairwise comparisons.
N M (SE) F P17.380 <.001
Good 8.57 (.355)Managing 5.82 (.406)Difficult 5.54 (.559)
Pairwise comparisons: MD (SE) PGood / Managing 2.75 (.539) p<.001Good / Difficult 3.03 (.663) p<.001Managing / Difficult .283 (.691) p=.682
MD = Mean difference.
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Table 5: Associations between frequency of leisure engagement and wellbeing adjusting for variables from the stress process model.
Arts Activities Arts Events Library Archives Museum Historical sitesF P, R2 F P, R2 F P, R2 F P, R2 F PP, R2 F P, R2
Unadjusted .546 .702, .003 3.488 .008, .014 1.213 .304, .007 .695, .499, .002 .882 .474, .005 2.251 .062, .013
Carer characteristicsAge .493 .741, .013 4.038 .003, .032 1.418 .226, .018 .713 .490, .012 .911 .457, .015 2.274 .060, .023Finances .537 .708, .106 1.919 .106, .115 1.254 .287, .116 .120 .811, .102 1.023 .395, .112 .840 .500, .109Qualification .486 .746, .032 2.569 .037, .051 .685 .603, .032 1.113 .329, .033 .707 .588, .035 1.984 .095, .061
Primary stressorsCares at home
.635 .637, .021 2.438 .046, .034 .635 .637, .027 1.561 .211, .021 .589 .671, .025 1.698 .149, .026
HPW caregiving
.550 .699, .025 2.721 .029, .037 2.848 .023, .046 .805 .522, .020 .547 .701, .022 2.110 .078, .031
Competing demandsWork .403 .807, .059 4.566 .001, .078 1.461 .212, .072 .054 .947, .053 1.127 .342, .036 .920 .452, .065Childcare .335 .855, .013 2.106 .078, .022 .873 .480, .010 1.334 .264, .006 1.114 .349, .010 1.468 .210, .020
Social supportRelationship quality
.417 .797, .091 2.688 .030, .103 1.060 .375, .095 .978 .377, .092 .782 .537, .093 1.806 .126, .099
Relationship status
.576 .680, .015 3.062 .016, .032 1.923 .105, .035 .108 .898, .015 1.232 .296, .029 1.754 .136, .029
HPW = hours per week.
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Hypothesis 1b: Those not involved in moderate to high intensity sporting
activities will have poorer wellbeing than those not involved in sporting
activities.
Firstly, the relationship between sports participation and wellbeing was explored by
comparing three groups: those engaging in moderate intensity sports in the last year,
those participating in mild intensity sport in the last year, and those who did not
participate in sport. As can be seen in Table 6, results of the GLM showed there was
a significant main effect of participation in sport on wellbeing (p=.002). Pairwise
comparisons showed that those who took part in moderate or low intensity sports had
better well-being than those who did no sport (Table 6). There was no difference
between those who did mild intensity sport and those who did moderate intensity
sport (p=.706).
Other variables from the stress process model were hypothesised to have an
influence in this relationship and therefore they were entered into the GLM one at a
time. This relationship was affected when childcare was entered into the model
(p=.210). Otherwise, the relationship was relatively unaffected by the other factors in
the stress process model (Table 7).
Secondly, the relationship between frequency of participation and wellbeing was
explored. GLMs explored the relationship between the frequency of low intensity
sport and moderate intensity sport (e.g. weekly, monthly etc.) and wellbeing. The
GLMs exploring the frequency of engagement in sporting activities showed no main
effect of frequency of moderate intensity sport (p=.078) or low intensity sport
(p=.167) on wellbeing (Table 9). However, when fitted as a trend there was a
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significant negative relationship between frequency of both types of sport and GHQ-
12 (b=-.398, p=.12 and b=-.352, p=.017 respectively) (Table 9). Carers who did
sports less regularly had higher GHQ scores (indicating poorer wellbeing). Overall,
this suggests some evidence for the relationship between frequency of participation
and wellbeing.
When the other variables from the stress process model were entered into the GLM
one at a time, both age and employment status impacted on the relationship between
frequency of moderate intensity sport and wellbeing (Table 9). Inspection of the
estimated marginal means when these variables were adjusted for (Appendix G),
broadly speaking, showed wellbeing was poorer for those who took part less
frequently. Otherwise, the relationships were relatively unaffected by the other
factors in the stress process model.
Table 6: Associations between levels of sport and GHQ-12 with pairwise comparisons.
N M (SE) F P R2
6.106 .002 .017MI sport 324 13.142 (.370)LI sport 113 13.416 (.626)No sport 273 14.996 (.403)
Pairwise comparisons:
MD (SE) P
MI sport / LI sport .274 (.727) .706MI sport / No sport 1.854 (.547) .001LI sport / No sport 1.580 (.744) .034
MI = Moderate intensity; LI = Low intensity.
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Table 7: Associations between participating in some or no sport with GHQ-12.
Adjusted for SportF P R2
Unadjusted 6.106 .002 .017
Carer characteristicsAge 8.033 <.001 .032Finances 3.605 .028 .109Qualification 7.641 .001 .040
Primary stressorsCares at home 3.003 .050 .028HPW caregiving 6.350 .002 .031
Competing demandsWork 7.470 .001 .076Childcare 1.566 .210 .019
Social SupportRelationship quality
6.371 .002 .105
Relationship status 4.946 .007 .030HPW = hours per week. Figures shown represent the values for sport participation when the additional variables were added into the model.
Table 1: Associations between frequency of sporting activities and GHQ-12.
% (N) M(SD) b (SE) P F P R2
MI sport -.398 (.154) .012 2.111 .078 .012Not at all 54.4% (386) 14.53 (7.03)1-2 times last year 6.9% (49) 13.73 (6.70)At least 3 / 4 times 8.0 %(57) 12.60 (5.18)Monthly 12.4% (88) 13.05 (6.38)Weekly 18.3% (130) 13.22 (6.35)
LI sport -.352 (.148) .017 1.623 .167 .009Not at all 54.4% (386) 14.32 (6.83)1-2 times last year 6.9% (49) 14.24 (7.03)At least 3 / 4 times 6.9% (49) 14.39 (7.24)Monthly 8.9% (63) 13.54 (6.71)Weekly 23.0% (163) 12.80 (6.04)
MI sport = Moderate intensity sport; LI sport=Low intensity sport. F, P and R2 values are reported for the model when frequency was modelled as a categorical variable, and b(SE) and p values are reported for when the frequency was fitted as a trend.
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Table 9: Associations between frequency of sports and GHQ-12, adjusted for the variables in the stress process model.
MI Sport LI SportF P R2 F P R2
Unadjusted 2.111 .078 .012 1.623 .167 .009
Carer characteristicsAge 2.981 .019 .027 1.644 .161 .019Finances 1.441 .219 .112 .792 .531 .109Qualification 1.577 .179 .038 2.216 .066 .043
Primary stressorsCares at home 1.048 .381 .026 .920 .452 .022HPW caregiving 2.351 .053 .031 1.934 .103 .034
Competing demandsWork 2.942 .020 .079 1.406 .230 .071Childcare 1.189 .314 .014 .551 .699 .016
Social supportRelationship quality
2.385 .050 .101 1.056 .377 .095
Relationship status 1.378 .240 .028 1.378 .240 .022MI sport = Moderate intensity sport; LI sport=Low intensity sport.
Results: Longitudinal study
Participant characteristics
The sample for this analysis consisted of women whose data could be linked between
waves 2 and 5 of the survey (three years apart) as described previously. Over this
time 109 women had increased their caring hours to over 20 a week (increased
caring) and 103 had become a carer for over 20 hours a week (new carers). The
comparison group consisted of 4224 women who were not carers at either time.
Table 10 shows participant characteristics by carer group.
Across the increased caring and new carer groups, many of the participants reported
having a good financial situation (56.9%, and 49.6% respectively), most did not have
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a child under 15 (87.2%, and 81.6% respectively), and most were living with a
partner (64.2%, and 68% respectively). Around half of the carers at wave 5 were
employed, whereas 70.2% of non-carers had a job. The majority of participants were
from British, Irish, or other White backgrounds (91.7%, and 85.4% respectively).
Most characteristics did not vary significantly across groups (Table 10). In general,
those who became carers for more than 20 hours a week tended to be older, have
poorer subjective finances and were less likely to be employed than those who did
not become carers. New carers were more likely to be living with the person for
whom they were providing care than those who had increased their caregiving.
Table 10: Demographic information and between group comparisons for the longitudinal participant sample.
WAVE 5 Not a carer: % (n)
Increased caring: % (n)
New carer:% (n)
F P
Total n 4224 109 103
Age M= 49.9SD=6.7
M=52.2SD=6.4
M=50.4SD=6.6
6.207 .002
40-44 11.2% (474) 4.6% (5) 14.6% (15)45-49 26% (1099) 21.1% (23) 11.7% (12)50-54 22% (928) 15.6% (17) 31.1% (32)55-59 18.3% (774) 26.6% (29) 21.4% (22)60-65 3.9% (166) 32.1% (35) 14.6% (15)
χ2 PEthnicity 3.39 .185
British, Irish, or other white background
90% (3829) 91.7% (100) 85.4% (88)
Other 9.4% (395) 8.3% (9) 14.6% (15)
Subjective Finances 22.15 <.001Good 64.7% (2735) 56.9% (62) 45.6% (47)Just about managing 23.9% (1009) 26.6% (29) 32% (33)Things are difficult 11.4% (480) 16.5% (18) 11.4% (480)
WAVE 5 Not a carer: Increased New carer: χ2 P
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% (n) caring: % (n) % (n)Hours per week spent caring *1.57 .456
20-49 hours n/a 55% (60) 46.6% (48)50 or more hours n/a 24.8% (27) 28.2% (29)Varies over 20 hours n/a 20.2% (22) 25.2% (26)
Children under 15 4.5 .106Yes 20.9% (882) 12.8% (14) 18.4% (19)No 79.1% (3342) 87.2% (95) 81.6% (84)
Highest qualification 7.77 .256Degree or higher 25.1% (1061) 17.4% (19) 18.4% (19)Less than degree but higher than GCSE
14% (592) 16.5%) (18) 14.6% (15)
GCSE and other school certificates
23.4% (987) 25.7% (28) 31.1% (32)
None of the above / Inapplicable
37.5% (1584) 40.4% (44) 35.9% (37)
Living with a partner 2.18 .337Yes 70.4% (2973) 64.2% (70) 68% (70)No 29.6% (1251) 35.8% (39) 32% (33)
Employed 35.07 <.001Yes 70.2% (2964) 50.5% (55) 51.5% (53)No 29.8% (1260) 49.5% (54) 48.5% (50)
Living with the person for whom they provide care *5.69 .017Yes n/a 46.8% (51) 63.1% (65)No n/a 53.2% (58) 36.9% (38)
M=mean; SD=standard deviation; *=non-carer group removed from chi square analysis.
Study measures
The means and standard deviations for satisfaction with leisure time and variety of
leisure activities at each wave can be seen in Table 11. The range of possible
responses for satisfaction was 0-7 which were all represented within this sample. For
variety, the possible range was 0-71 and the range observed in this study was 0-40 at
both waves.
Due to the frequency variables being ordinal and at irregular intervals, three
categories were derived in order to explore change in frequency over time: less, the
Page 44 of 197
same, and more. Numbers and percentages for each category across the frequency
variables are in Table 13.
The range of GHQ-12 scores within this study at both waves was 0-36 which is the
same as the possible range for this measure. See Table 14 for a summary of the
means and standard errors for each carer group at each wave.
Hypothesis 2a: Becoming a carer who spends 20 or more HPW caring will
be associated with reduced frequency, variety, and satisfaction with
leisure activities.
This relationship will be moderated by changes in number of competing demands
(employment and childcare).
Results from the repeated measures analysis suggested that overall, the level of
satisfaction in leisure time decreased by .03 over the three years (p=.001). Inspection
of Figure 5 appears to show the decrease in satisfaction with leisure time was slightly
more for new carers than for non-carers, however this interaction did not reach
significance (p=.096), indicating no strong evidence that carer groups were affected
differentially over time (Table 11). However, it can be noted from Figure 4 and
Table 11 that at both time points, the mean satisfaction was lower for new carers than
for non-carers (p=.009).
Results from the repeated measures analysis suggested that overall, the number of
different types of leisure activities undertaken decreased by 0.45 over the three years
(p=.027) (Table 11). The interaction between time and carer group was not
significant providing no evidence that this decrease was greater for those who
became carers for more than 20 hours a week (Table12). This is also clear from
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inspection of Figure 5. However, Table 11 and Figure 5 show that the mean variety
over both time points was significantly different between the carer groups, being
lowest among new carers and similar for those who increased their caring and the
comparison group. Results were robust when other variables from the stress process
model were adjusted for (Appendix J).
It was hypothesised that decreases in variety and satisfaction in the carer groups
would be greater where there were also increases in the competing demands of work
and childcare. The three-way interaction in Table 12 shows that the interaction
between time and carer group was not moderated by a measure of competing
demands. There is therefore no evidence that competing demands affected the
reductions in either variety of activities or satisfaction with leisure.
Table 13 shows changes in frequency of each of the different leisure activities by
carer group. The chi-square results show there were no significant differences in
patterns of change over the three groups and therefore there was no evidence that
those who became carers for 20 or more hours reduced the frequency of activities
more than the comparison group.
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W2 W53.9
4
4.1
4.2
4.3
4.4
4.5
4.6
4.7
New carer Increased caring Non-carer
Satis
facti
on
Figure 4: Graph showing the change in satisfaction with leisure over time for each of the three carer groups.
W2 W56
6.5
7
7.5
8
8.5
9
9.5
10
10.5
New carer Increased caring Non-carer
Varie
ty
Figure 5: Graph showing change in variety over time for each of the three carer groups.
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Table 21: Associations between Variety and Satisfaction over time and carer group.
ME time ME Care Status IE Time * Care status
M(SE) F P M(SE) F P M(SE) F P
Satisfaction W2: 4.509 (.076)W5: 4.205 (.079)
11.704 .001 NeC: 4.189 (.136)IC: 4.330 (.132)NoC: 4.552 (.021)
4.741 .009 W2 NeC: 4.398 (.163)IC: 4.523 (.159)NoC: 4.606 (.025)
W5 NeC: 3.981 (.168)IC: 4.138 (.164)NoC: 4.498 (.026)
2.345 .096
Variety W2: 8.899 (.314)W5: 8.450 (.8.457)
4.882 .027 NeC: 6.626 (.639)IC: 9.624 (.621)NoC: 9.785 (.100)
11.950 <.001 W2 NeC: 6.981 (.672)IC: 9.697 (.653)NoC: 10.020 (.105)
W5 NeC: 6.272 (.675)IC: 9.550 (.656)NoC: 9.549 (.105)
.458 .633
ME = Main effect; IE = Interaction effect; W2 = Wave 2; W5 = Wave 5; NeC = New carer; IC = Increased caring; NoC = Non- carer.
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Table 32:Associations between variety and satisfaction over times when change in competing demands was included in the models.
Time Care T*Care T*Change T*Ca*ChF P F P F P F P F P
Variety 4.66 .031 12.11 <.001 .46 .633 .15 .692 1.63 .164
Satisfaction 15.41 <.001 4.79 .008 2.50 .082 26.73 <.001 4.22 .231
Time = Main effect of time; Care = Main effect of care status; T*Care = Time by care status interaction effect; T*Change = Time by Change in competing demands interaction effect; T*Ca*Ch = three-way interaction effect. Where three-way interaction effects were not significant, they were removed from the model to explore other effects in more detail, and these are reported below.
Table 13: Associations between change in frequency of activities over time, with care status.
Carer StatusNew Increased Non χ2 pn (%) n (%) n (%)
Arts Less 19.4% (20) 19.3% (21) 20.4% (862) .927 .921Activities Same 56.3% (58) 58.7% (64) 58.9% (2488)
More 24.3% (25) 22.0% (24) 20.7% (874)
Arts Events Less 31.1% (32) 22% (24) 28.8% (1215) 4.646 .326Same 42.7% (44) 54.1%(59) 44.3% (1873)More 26.2% (27) 23.9% (27) 26.9% (1136)
Library Less 26.2% (27) 21.1% (23) 23.9% (1009) 1.111 .892Same 60.2% (62) 66.1% (72) 64% (2703)More 13.6% (14) 12.8% (14) 12.1% (512)
Museum Less 21.4% (22) 19.3% (21) 22.9% (967) 5.403 .283Same 65% (67) 57.8% (63) 56.1% (2370)More 13.6% (14) 22.9% (25) 21.0% (887)
MI Sport Less 26.2% (27) 25.7% (28) 28.8% (1215) .893 .926Same 47.6%(49) 48.6% (53) 47.1% (1988)More 26.2% (27) 25.7% (28) 24.2% (1021)
LI Sport Less 22.3% (23) 27.5% (30) 27.7% (1169) 3.263 .515Same 53.4% (55) 46.8% (51) 44.8% (1893)More 24.3% (25) 25.7% (28) 27.5% (1162)
Historical Less 26.2% (27) 24.8% (27) 29.2% (1232) 1.971 .741Sites Same 42.&% (44) 46.8% (51) 44% (1858)
More 31.1% (32) 28.4% (31) 26.8% (1134)MI sport = moderate intensity sport; LI sport = low intensity sport. Percentages relate to the proportion of individuals within each carer group who did less, the same, or more activities at wave 5 compared with wave 2.
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Hypothesis 2b: Becoming a carer who spends 20 or more hours caring
will be associated with reduced wellbeing when compared with prior to
becoming a carer, and to non-carers.
It was hypothesised that GHQ-12 scores in the two groups who became intensive
carers would increase, relative to little change being found for the comparison group.
Overall there was very little change in GHQ-12 scores between the two waves with
Table 14 showing a nonsignificant mean fall of .01 (p=.963). There was also no
evidence that the change in GHQ-12 scores over the three years was different
between the three carer groups (p=.747). Table 14 and Figure 6 show that the GHQ-
12 scores averaged over both time points did vary by carer group, being highest for
the new carer group and lowest for the comparison (non-carer) group. A surprising
finding is that the “new carer” group showed the worst GHQ-12 score prior to
becoming carers whereas at this point they would be expected to have similar values
to the comparison (non-carer) group. Results were relatively unaffected by other
variables from the stress process model (Appendix J).
W2 W511.5
12
12.5
13
13.5
14
14.5
15
New carer Increased caringNon-carer
Wel
lbei
ng
Figure 6: Graph showing change in wellbeing over time for each of the carer groups. Note: higher scores represent poorer wellbeing.
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Table 4: Associations between wellbeing over time and carer group.
ME time ME Care Status IE Time * Care status
M(SE) F P M(SE) F P M(SE) F P
GHQ-12 W2: 13.283 (.270)W5: 13.270 (.274)
.002 .963 NeC: 14.335 (.502)IC: 13.693 (.488)NoC: 11.802 (.078)
19.301 <.001 W2 NeC: 14.505 (.578)IC: 13.550 (.562)NoC: 11.794 (.090)
W5 NeC: 14.165 (.586)IC: 13.385 (.570)NoC: 11.811 (.092)
.292 .747
ME = Main effect; IE = Interaction effect; W2 = Wave 2; W5 = Wave 5; NeC = New carer; IC = Increased caring; NoC = Non- carer.
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Hypothesis 2c: Change in leisure will predict change in wellbeing for
individuals who become a carer who spends 20 or more hours caring.
It was hypothesised that change in satisfaction would predict change in wellbeing,
which was supported by the results from the GLM analysis (p=.013) (Table 15).
When carer status was added into the model as a main effect, there were no between
group differences (p=.699). Figure 7 shows that although the fitted line is slightly
steeper for new carers, there was no statistically significant interaction between
change in satisfaction and carer status (p=.740) (Table 16).
Results from the GLM support the hypothesis that change in variety predicts change
in wellbeing (b=-.049, p=.017) (Table 15). When carer status was included in the
model as a main effect, there were no between group differences (p=.728). Figure 8
shows that although the fitted line is steeper for increased carers, there was no
statistically significant interaction effect between change in variety and carer status
(p=.375).
The above described models, although showing some significant relationships, had
very small effect sizes and accounted for only small amounts of the overall variance
(Tables 16 and 17).
A GLM was used to examine how change in GHQ-12 scores varied by whether the
frequency of that activity was less, the same, or more over the time period. None of
the frequency variables had a significant main effect on change in wellbeing when
entered into models independently, giving little evidence of any association between
changes in frequency of specific activities and wellbeing (Table 15). Results were
largely unaffected when care status was entered into the model (Table 16).
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-6 -4 -2 0 2 4 6
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
Non-carer Increased caring New Carer
Change in satisfaction
Chan
ge in
wel
lbei
ng
Figure 7: Associations between change in wellbeing and change in satisfaction for each carer group.
Note: Higher scores represent poorer wellbeing.
-20 -15 -10 -5 0 5 10 15 20
-6
-4
-2
0
2
4
6
New carer Non carer Increased caring
Change in variety
Chan
ge in
wel
lbei
ng
Figure 8: Associations between change in wellbeing and change in variety for each carer group.
Note: Higher scores represent poorer wellbeing.
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Table 5: Associations between change in leisure and change in wellbeing
b (SE) F P R2
Variety -.049 (.021) 5.694 .017 .001
Satisfaction -.357 (.046) 59.211 <.001 .013
n M (SD)Arts activities .322 .725 .000
Less 903 .1362 (5.942)Same 2610 .0096 (5.760)More 923 -.0878 (6.620)
Arts events .035 .966 .000Less 1271 -.017 (6.242)
Same 1976 .017 (5.975)More 1189 .046 (5.718)
Library .984 .374 .000Less 1059 .174 (5.517)
Same 2837 .010 (6.050)More 540 -.269 (6.497)
Museum 2.359 .095 .001Less 1010 .348 (5.789)
Same 2500 -.032 (6.235)More 926 -.221 (5.474)
MI sport .100 .905 .000Less 1270 -.047 (5.985)
Same 2090 .034 (5.959)More 1076 .053 (6.038)
LI sport .808 .446 .000Less 1222 .196 (5.861)
Same 1999 -.077 (6.232)More 1215 -.105 (5.686)
Historical Sites 1.845 .158 .001Less 1286 .222 (6.116)
Same 1953 .033 (5.957)More 1197 -.237 (5.882)
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Table 6: Associations between change in leisure and change in wellbeing considering care status. Main effect Care status IE R2
b (SE) F P M (SE) F P F PVariety -.050 (.021) 5.743 .017 NeC -.352 (.589) .318 .728 .981 .375 .001
IC .300 (.573)NoC .017 (.092)
Satisfaction -.357 (.046) 59.320 <.001 NeC -.445 (.586) .359 .699 .301 .740 .013IC .190 (.570)NoC .022 (.091)
n M (SE)Arts activities Less 903 .111 (.329) .320 .726 NeC -.331 (.591) .289 .749 1.675 .153 .000
Same 2610 -.016 (.286) IC .291 (.575)More 923 -.112 (.325) NoC .021 (.103)
Arts events Less 1271 -.043 (.312) .033 .968 NeC -.338 (.590) .289 .749 2.249 .061 .001Same 1976 -.013 (.292) IC .284 (.575)More 1189 -.019 (.315) NoC .017 (.094)
Library Less 1059 .150 (.319) .989 .372 NeC -.383 (.593) .297 .743 1.371 .241 .001Same 2837 -.017 (.284) IC .248 (.577)More 540 -.294 (.365) NoC -.026 (.114)
Museum Less 1010 .323 (.323) 2.381 .093 NeC -.333 (.593) .315 .730 1.486 .204 .001Same 2500 -.056 (.285) IC .317 (.575)More 926 -.250 (.329) NoC -.032 (.101)
MI sport Less 1270 -.077 (.312) .101 .904 NeC -.344 (.590) .292 .747 .563 .690 .000Same 2090 -.004 (.292) IC .280 (.574)More 1076 .024 (.317) NoC .015 (.096)
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Main effect Care status IE R2
b (SE) F P M (SE) F P F PLI sport Less 1222 .172 (.314) .792 .453 NeC -.305 (.591) .276 .759 2.392 .059 .000
Same 1999 -.098 (.291) IC .305 (.574)More 1215 -.038 (.314) NoC .036 (.094)
Historical Sites Less 1286 .199 (.318) 1.838 .159 NeC -.332 (.590) .285 .752 1.660 .156 .001Same 1953 .020 (.299) IC .288 (.574)More 1197 -.322 (.317) NoC -.007 (.094)
ME = Main effect; IE = Interaction effect; NeC = New carer; IC = Increased caring; NoC = Non- carer. Where interaction effects were not significant, main effects were explored using models without interaction effects, and these are the values reported in the table below.
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DiscussionGiven that research has found carers to experience limitations in their leisure
activities, and that they experience reduced wellbeing when compared to non-
caregivers, this research sought to further understand the relationship between leisure
and wellbeing for this group of individuals (Magliano et al., 2006; Mausbach,
Patterson, & Grant, 2008). Of interest were women who care for more than 20 hours
a week as there is evidence to suggest that they are at particular risk of having poorer
wellbeing (Bedim & Guinan, 1996; Smith et al., 2014). The cross-sectional study
explored whether leisure predicts wellbeing. The longitudinal study explored
whether carers experienced a decline in their leisure engagement and in their
wellbeing. It further asked whether change in leisure predicts change in wellbeing.
Data from the UK Longitudinal Household Study (UKLHS), also known as
Understanding Society, were used (University of Essex, 2017). Although there are
limitations to this study, it provided access to a large, nationally representative
sample. Further, it allowed for exploration of associations over time which is a lesser
researched area when compared with cross-sectional studies (Clarke, 2018).
Overall, hypotheses were mostly supported and poorer levels of leisure engagement
were associated with poorer levels of wellbeing. These findings are consistent with
results from studies with men and women, and from participant samples with broader
age ranges (Ficker, 2011; Hatzmann, Maurice-Stam, Heymans, & Grootenhuis,
2009; Mausbach, Roepke, et al., 2011; Williams, 2005). Among the participant
samples in both studies the range of wellbeing scores reported were broad, and carers
reported engaging in a wide range of leisure activities. This indicates that for women
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who provide care for over 20 hours a week it is possible to have a varied and
satisfying quality of leisure and a good wellbeing.
Although the relationship between leisure and wellbeing tended to be robust when
taking into consideration other key factors in the stress-process model, subjective
financial situation may be one variable which does affect this relationship. Findings
showed that people who had a greater variety of activities had better wellbeing, and
there was no relationship independent of perceived financial situation. Individuals
who perceived themselves to have more money took part in a wider variety of
activities than those who felt their financial situation was difficult. Similarly, the
relationship between frequency of arts events and wellbeing was not independent of
finances and employment, suggesting that frequency of arts events alone may not be
the cause of improved wellbeing.
Other research has linked leisure activities to SES, finding that women from a lower
SES undertake significantly less leisure activity than women from a higher SES
(Ford et al., 1991). Other research has found that finances allow carers to fund care
for their loved ones, enabling the carer to engage in leisure activities (Gladwell &
Bedini, 2004). This could be one mechanism through which finances affect the
relationship between leisure and wellbeing. More research would be helpful in better
understanding whether finances mediate, moderate or confound the effect of variety
of leisure on wellbeing, and this could be done using the UKLHS dataset.
In the cross-sectional study it was found that satisfaction with leisure time was more
relevant to wellbeing than the other leisure variables, explaining 12% of the variance.
This finding might suggest that how someone feels about their leisure engagement is
more important for wellbeing than how much leisure they are actually engaging in.
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Similarly, studies which use measures of restriction on leisure engagement (i.e.
wanting to do more but not being able to), have found significant relationships with
wellbeing, with medium to large effect sizes for some of their comparisons (Cramm
& Nieboer, 2011; Loucks-Atkinson, Kleiber, & Williamson, 2006; Mausbach,
Roepke, et al., 2011).
In line with projected findings, there was a reduction in variety and satisfaction with
leisure over time for women who became carers for more than 20 hours per week. A
strength of this study was the inclusion of a non-carer group to control for temporal
changes across the cohort, and this group also experienced the same decline. It is
possible to speculate as to reason for this. For example, research suggests that there
is an association between getting older and poorer wellbeing and therefore changes
could be attributable in some part to the increase in age of participants from W2 to
W5 (Hallal et al., 2003). Alternatively, there may have been broader social and
economic changes that affected the whole cohort, for example the recession.
Unexpectedly, becoming a carer was not associated with reduced wellbeing, which
remained stable for all groups between W2 and W5 and, surprisingly, those who
became carers had the highest GHQ-12 score at W2 prior to reporting doing caring
activities. These findings were unaffected when adjusting for change in competing
demands. Although (to the authors knowledge) these findings have not been found
elsewhere in the literature, another unpublished dissertation using UKLHS data has
had similar findings when looking at male caregivers (Warrell-Phillips, 2018).
Another related issue is whether the individual identifies with the label of “carer”,
and the impact of this on responses. However, a strength of the Understanding
Society study is the wording of questions exploring this. Participants were asked
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whether they “look after” or “provide special help” to a family member, friend,
relative or neighbour. This reduces the chance of people responding negatively to the
question because they do not identify with the label “carer” which has been found to
describe the role poorly (Hughes, Locock, & Ziebland, 2013; Molyneaux, Butchard,
Simpson, & Murray, 2011). More qualitative studies exploring the process of
becoming a carer may also be helpful in better understanding when becoming a carer
starts to impact on wellbeing.
Change in satisfaction and change in variety of leisure activities predicted change in
wellbeing. In a recent review of the literature (Clarke, 2018), Loucks-Atkinson et al.
(2006) were the only researchers to explore the relationship between leisure
engagement and wellbeing longitudinally in carers who spend a lot of time providing
care. They found that restriction with activities at time one was associated with more
symptoms of depression one and two years later. Given the limited range of
longitudinal studies in this population, further longer-term studies would be helpful
in developing understanding about the impact of leisure engagement over time, and
whether this relationship is causal.
As expected, engagement in sports was related to wellbeing as those who took part in
sports had better wellbeing than those who didn’t. Additionally, change in mild
intensity sports frequency over time was associated with change in wellbeing in the
expected direction. This is consistent with a recent literature review that found that
physical activity is associated with better wellbeing (Lambert et al., 2016). However,
causality can’t be inferred and feeling better might mean people have more energy
and are more motivated to do some sport.
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In general, there was limited evidence from the cross-sectional study of an
association between frequency of leisure and wellbeing, and surprisingly, frequency
of leisure activities remained stable over time for all groups. However, a limitation of
this study is that it was not possible to consider the magnitude of change in
frequency. This might have been more relevant to predicting the change in
wellbeing. For example, an individual who reduced their frequency of going to the
library from once a week to once a month would be in the category of “reduced
frequency” with an individual who had stopped going weekly and only went once in
the last year. Clearly the reduction in frequency was much greater for the latter
participant, however it was not possible to capture this in the analysis for this study.
Therefore, it may be of interest to explore this in greater detail.
Another limitation of this study is that some potentially relevant variables were not
able to be considered due to the quality of information gathered by the UKLHS. For
example, for female carers, there is a strong link between having to manage difficult
behaviours expressed by their husbands and activity restriction, and a link between
the behaviour and depressive symptoms (Bookwala & Schulz, 2000). It would have
benefited this study to have been able to adjust for behaviours that carers find
challenging.
There is also some evidence that feelings of guilt play a role in the relationship
between leisure and wellbeing. Romero-Moreno et al. (2012) found that (caregiving)
daughters who do not engage in leisure activities may be especially vulnerable to low
mood if they also have high feelings of guilt. This could be linked to cultural
narratives such as ethic of care (for example expectations around whose
responsibility it is to provide care) (Miller & Brown, 2005), which were not explored
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in this study. Self-esteem and self-efficacy have also been shown to be mediators and
moderators in one Asian literature review (Isa et al., 2016). Therefore, further models
that include guilt, self-esteem and self-efficacy would be helpful alongside
exploratory studies around issues around ethic of care and the impact this may have
on leisure engagement.
There is also some evidence to suggest there are qualitative differences within the
caregiving experience depending on the difficulty experienced by the cared for
individual. For example, one study found that dementia caregivers experience greater
levels of employment difficulties, mental and physical health problems, and
disruption to leisure activities than other caregivers (Ory et al., 1999). These effects
remained after intensity of caregiving demands was taken into account. Another
study compared caregivers of people with cancer, dementia, diabetes or frail elderly
(Kim & Schulz, 2008). They found higher levels of physical burden and
psychological distress for the cancer and dementia groups, even when
sociodemographic factors and caregiving involvement were controlled for.
Therefore, being able to explore the impact of this variable on the relationship
between leisure and wellbeing would be an interesting extension to this study.
Further useful extensions to this study would include the use of additional outcome
measures such as those that focus specifically on symptoms of low mood, anxiety or
stress. This would allow for a stronger understanding of the robustness of findings
from this study and help to identify whether there are differences between the
relationship between leisure engagement and specific constructs of mental wellbeing
for female carers in this group.
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Although many of the research hypotheses were supported, it is important to consider
that use of large sample sizes can result in small differences achieving statistical
significance. Further, effect sizes were small and small amounts of variance were
explained, suggesting that other factors also play a role in wellbeing for carers.
Structural equation modelling and path analysis of the variables considered in this
study may help to develop a better understanding of the range of contributing factors
to carer wellbeing and model complex pathways between variables. Other studies
have begun to develop more comprehensive models. For example, Hsieh (2011)
found that leisure time satisfaction did not moderate the relationship between
caregiving demands and quality of life. However, satisfaction and participation in
leisure buffered the effects of stress on quality of life. Also, Ficker (2011) used path
analysis and found that work disruption affected financial strain, which affected
leisure, which in turn affected depression (accounting for 12.3% of the variance in
depression).
Implications of findings
For individuals concerned with developing policy and guidelines for carers, this
study lends support for consideration of leisure as a key contributor to emotional
wellbeing for female carers in midlife who spend a significant amount of time caring.
In particular, the satisfaction that this group of carers have with the amount of leisure
time they have and whether they do physical activities. There is some research into
the barriers people face when attempting to engage in leisure activities (e.g. Gladwell
& Bedini, 2004; Innes, Page, & Cutler, 2016), however, a more nuanced
understanding for this population may be helpful for informing interventions.
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At a local level, clinicians should be aware that sport and leisure is linked with better
wellbeing for female carers in midlife who care for 20 hours a week or more. This
would enable them to develop their assessment, formulation and interventions. For
example, they might pass this knowledge on to this group of carers, and support them
to problem solve barriers to sport and leisure engagement.
Conclusions
Leisure is a key contributor to emotional wellbeing for female carers in midlife who
spend 20 or more hours a week providing care. In particular, the satisfaction that they
have with the amount of leisure time they have and whether they do physical
activities is associated with better wellbeing. This has important implications for
working with this group of carers at a local level, and at a policy level.
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ReferencesAzman, A., Jamir Singh, P. S., & Sulaiman, J. (2017). Caregiver coping with the
mentally ill: a qualitative study. Journal of Mental Health, 26(2), 98–103. https://doi.org/10.3109/09638237.2015.1124395
Bedim, L. A., & Guinan, D. M. (1996). “If I could just be selfish …”: Caregivers’ perceptions of their entitlement to leisure. Leisure Sciences, 18(3), 227–239. https://doi.org/10.1080/01490409609513284
Bedini, L., Gladwell, N., & Dudley, W. (2011). Mediation analysis of leisure, perceived stress, and quality of life in informal caregivers. Journal of Leisure, 43(2), 153–175. https://doi.org/10.1080/00222216.2011.11950231
Bittman, M., Hill, T., & Thomson, C. (2007). The Impact of Caring on Informal Carers’ Employment, Income and Earnings: a Longitudinal Approach. Australian Journal of Social Issues, 42(2), 255–272. https://doi.org/10.1002/j.1839-4655.2007.tb00053.x
Bookwala, J., & Schulz, R. (2000). A comparison of primary stressors, secondary stressors, and depressive symptoms between elderly caregiving husbands and wives: The caregiver health effects study. Psychology and Aging, 15(4), 607–616. https://doi.org/10.1037/0882-7974.15.4.607
Chassin, L., Macy, J. T., Seo, D.-C., Presson, C. C., & Sherman, S. J. (2010). The association between membership in the sandwich generation and health behaviors: A longitudinal study. Journal of Applied Developmental Psychology, 31(1), 38–46. https://doi.org/10.1016/J.APPDEV.2009.06.001
Clarke, A. (2018). Leisure influences on wellbeing among those who spend a significant amount of time caring for others: A systematic review. (Unpublished doctoral dissertation). University of Surrey, Guildford.
Cooper, C., Balamurali, T. B. S., Selwood, A., & Livingston, G. (2007). A systematic review of intervention studies about anxiety in caregivers of people with dementia. International Journal of Geriatric Psychiatry, 22(3), 181–188. https://doi.org/10.1002/gps.1656
Cramm, J. M., & Nieboer, A. P. (2011). Psychological well-being of caregivers of children with intellectual disabilities: Using parental stress as a mediating factor. Journal of Intellectual Disabilities, 15(2), 101–113. https://doi.org/10.1177/1744629511410922
Del-Pino-Casado, R., & Ordóñez-Urbano, C. (2016). Effects of satisfaction with leisure time in family carers of elderly dependents. Atencion Primaria / Sociedad Española De Medicina De Familia Y Comunitaria, 48(5), 295–300. https://doi.org/10.1016/j.aprim.2015.06.005
Dunn, N., & Strain, M. A. (2001). Caregivers at risk?: Changes in leisure
Page 65 of 197
participation. Caregivers at Risk?: Changes in Leisure Participation, 33(1), 32–55. Retrieved from https://search.proquest.com/docview/201221814?OpenUrlRefId=info:xri/sid:primo&accountid=17256
Ficker, L. J. (2011). The role of employment status, work disruption, leisure, and resources in the mental health of dementia caregiving daughters. Dissertation Abstracts International: Section B: The Sciences and Engineering. Retrieved from http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3433474%5Cnhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=psyc7&NEWS=N&AN=2011-99160-365
Field, A. P. (2013). Discovering statistics using IBM SPSS statistics: and sex and drugs and rock “n” roll (4th ed.). London: Sage.
Ford, E. S., Merritt, R. K., Heath, G. W., Powell, K. E., Washburn, R. A., Kriska, A., & Haile, G. (1991). Physical Activity Behaviors in Lower and Higher Socioeconomic Status Populations. American Journal of Epidemiology, 133(12), 1246–1256. https://doi.org/10.1093/oxfordjournals.aje.a115836
Gallo, J. J. (1990). The effect of social support on depression in caregivers of to the elderly. Journal of Family Practice, 30(4), 430–437. Retrieved from http://go.galegroup.com/ps/anonymous?id=GALE%7CA9023155&sid=googleScholar&v=2.1&it=r&linkaccess=fulltext&issn=00943509&p=AONE&sw=w&authCount=1&isAnonymousEntry=true
Gladwell, N. J., & Bedini, L. A. (2004). In search of lost leisure: the impact of caregiving on leisure travel. Tourism Management, 25(6), 685–693. https://doi.org/10.1016/J.TOURMAN.2003.09.003
Goode, K. T., Haley, W. E., Roth, D. L., & Ford, G. R. (1998). Predicting longitudinal changes in caregiver physical and mental health: A stress process model. Health Psychology, 17(2), 190–198. https://doi.org/10.1037/0278-6133.17.2.190
Grant, G., & Whittell, B. (2000). Differentiated Coping Strategies in Families with Children or Adults with Intellectual Disabilities: the Relevance of Gender, Family Composition and the Life Span. Journal of Applied Research in Intellectual Disabilities, 13(4), 256–275. https://doi.org/10.1046/j.1468-3148.2000.00035.x
Grosse, S. D., Flores, A. L., Ouyang, L., Robbins, J. M., & Tilford, J. M. (2009). Impact of Spina Bifida on Parental Caregivers: Findings from a Survey of Arkansas Families. Journal of Child and Family Studies, 18(5), 574–581. https://doi.org/10.1007/s10826-009-9260-3
Grover, S., & Dutt, A. (2011). Perceived burden and quality of life of caregivers in obsessive-compulsive disorder. Psychiatry and Clinical Neurosciences, 65(5), 416–422. https://doi.org/10.1111/j.1440-1819.2011.02240.x
Page 66 of 197
Hallal, P. C., Victora, C. G., Wells, J. C. K., & Lima, R. C. (2003). Physical inactivity: prevalence and associated variables in Brazilian adults. Medicine and Science in Sports and Exercise, 35(11), 1894–900. https://doi.org/10.1249/01.MSS.0000093615.33774.0E
Hamill, S. B., & Goldberg, W. A. (1997). Between adolescents and aging grandparents: Midlife concerns of adults in the “Sandwich generation.” Journal of Adult Development, 4(3), 135–147. https://doi.org/10.1007/BF02510593
Hardy, G. E., Shapiro, D. A., Haynes, C. E., & Rick, J. E. (1999). Validation of the General Health Questionnaire-12: Using a sample of employees from England’s health care services. Psychological Assessment, 11(2), 159–165. https://doi.org/10.1037/1040-3590.11.2.159
Hatzmann, J., Maurice-Stam, H., Heymans, H. S. A., & Grootenhuis, M. A. (2009). A predictive model of Health Related Quality of life of parents of chronically ill children: the importance of care-dependency of their child and their support system. Health and Quality of Life Outcomes, 7(72). https://doi.org/10.1186/1477-7525-3-34
Hill, K., Smith, R., Fearn, M., Rydberg, M., & Oliphant, R. (2007). Physical and Psychological Outcomes of a Supported Physical Activity Program for Older Carers. Journal of Aging and Physical Activity, 15(3), 257–271. https://doi.org/10.1123/japa.15.3.257
Hsieh, P.-C. (2011). Contributions of leisure participation in predicting stress coping and quality of life among parental caregivers of children with developmental disabilities. Indiana University.
Hughes, N., Locock, L., & Ziebland, S. (2013). Personal identity and the role of “carer” among relatives and friends of people with multiple sclerosis. Social Science & Medicine, 96, 78–85. https://doi.org/10.1016/j.socscimed.2013.07.023
Innes, A., Page, S. J., & Cutler, C. (2016). Barriers to leisure participation for people with dementia and their carers: An exploratory analysis of carer and people with dementia’s experiences. Dementia, 15(6), 1643–1665. https://doi.org/10.1177/1471301215570346
Isa, S. N. I., Ishak, I., Ab Rahman, A., Mohd Saat, N. Z., Che Din, N., Lubis, S. H., & Mohd Ismail, M. F. (2016). Health and quality of life among the caregivers of children with disabilities: A review of literature. Asian Journal of Psychiatry, 23, 71–77. https://doi.org/10.1016/j.ajp.2016.07.007
Iso-Ahola, S. E., Jackson, E., & Dunn, E. (1994). Starting, ceasing, and replacing leisure activities over the life-span. Journal of Leisure Reseach, 26(3), 227–249. Retrieved from https://search.proquest.com/docview/201177494/58068194B8CC4410PQ/1?accountid=17256
Jackson, E. L., & Henderson, K. A. (1995). Gender‐based analysis of leisure
Page 67 of 197
constraints. Leisure Sciences, 17(1), 31–51. https://doi.org/10.1080/01490409509513241
Kim, Y., & Schulz, R. (2008). Family Caregivers’ Strains. Journal of Aging and Health, 20(5), 483–503. https://doi.org/10.1177/0898264308317533
Knies, G. (2015). Understanding Society - UK Household Longitudinal Study: Wave 1-5, 2009-2014, User Manual. Colchester: University of Essex.
Lambert, S. D., Duncan, L. R., Kapellas, S., Bruson, A.-M., Myrand, M., Santa Mina, D., … Lambrou, A. (2016). A Descriptive Systematic Review of Physical Activity Interventions for Caregivers: Effects on Caregivers’ and Care Recipients’ Psychosocial Outcomes, Physical Activity Levels, and Physical Health. Annals of Behavioral Medicine, 50(6), 907–919. https://doi.org/10.1007/s12160-016-9819-3
Lee, Y., & Bhargava, V. (2004). Leisure time: Do married and single individuals spend it differently? Family and Consumer Sciences, 32(3), 254–274. https://doi.org/10.1177/1077727X03261631
LoGiudice, D., Kerse, N., Brown, K., Gibson, S. J., Burrows, C., Ames, D., … Flicker, L. (1998). The Psychosocial Health Status of Carers of Persons with Dementia: A Comparison with the Chronically Ill. Quality of Life Research, 7(4), 345–351. https://doi.org/10.1023/A:1024990131445
Loi, S. M., Dow, B., Ames, D., Moore, K., Hill, K., Russell, M., & Lautenschlager, N. (2014). Physical activity in caregivers: What are the psychological benefits? Archives of Gerontology and Geriatrics, 59(2), 204–210. https://doi.org/10.1016/j.archger.2014.04.001
Loi, S. M., Dow, B., Moore, K., Hill, K., Russell, M., Cyarto, E., … Lautenschlager, N. (2016). Factors associated with depression in older carers. International Journal of Geriatric Psychiatry, 31(3), 294–301. https://doi.org/10.1002/gps.4323
Loucks-Atkinson, A., Kleiber, D. a., & Williamson, G. M. (2006). Activity restriction and well‐being in middle‐aged and older caregivers. Topics in Geriatric Rehabilitation, 22(4), 269–282.
Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002). The Importance of the Normality Assumption in Large Public Health Data Sets. Annual Review of Public Health, 23(1), 151–169. https://doi.org/10.1146/annurev.publhealth.23.100901.140546
Lynn, P., & Knies, G. (2016). Understanding Society: The UK Household Longitudinal Study, waves 1-5, quality profile. Colchester: University of Essex.
Magliano, L., Fiorillo, A., Rosa, C., & Maj, M. (2006). Family burden and social network in schizophrenia vs. physical diseases: preliminary results from an Italian national study. Acta Psychiatrica Scandinavica, 113(s429), 60–63. https://doi.org/10.1111/j.1600-0447.2005.00719.x
Page 68 of 197
Martin, S. C. (2015). Psychosocial Challenges Experienced by Partners of People With Parkinson Disease. Journal of Neuroscience Nursing, 47(4), 211–222. https://doi.org/10.1097/JNN.0000000000000141
Mausbach, B. T., Coon, D. W., Patterson, T. L., & Grant, I. (2008). Engagement in Activities Is Associated With Affective Arousal in Alzheimer’s Caregivers: A Preliminary Examination of the Temporal Relations Between Activity and Affect. Behavior Therapy, 39(4), 366–374. https://doi.org/10.1016/J.BETH.2007.10.002
Mausbach, B. T., Harmell, A. L., Moore, R. C., & Chattillion, E. A. (2011). Influence of caregiver burden on the association between daily fluctuations in pleasant activities and mood: A daily diary analysis. Behaviour Research and Therapy, 49(1), 74–79. https://doi.org/10.1016/j.brat.2010.11.004
Mausbach, B. T., Patterson, T. L., & Grant, I. (2008). Is depression in Alzheimer’s caregivers really due to activity restriction? A preliminary mediational test of the Activity Restriction Model. Journal of Behavior Therapy and Experimental Psychiatry, 39(4), 459–466. https://doi.org/10.1016/J.JBTEP.2007.12.001
Mausbach, B. T., Roepke, S. S. K., Depp, C. A. C., Moore, R., Patterson, T. L., & Grant, I. (2011). Integration of the Pleasant Events and Activity Restriction Models: Development and Validation of a “PEAR” Model of Negative Outcomes in Alzheimer’s Caregivers. Behavior Therapy, 42(1), 78–88. https://doi.org/10.1016/j.beth.2009.11.006
Miller, Y. D., & Brown, W. J. (2005). Determinants of Active Leisure for Women with Young Children—an “Ethic of Care” Prevails. Leisure Sciences, 27(5), 405–420. https://doi.org/10.1080/01490400500227308
Molyneaux, V., Butchard, S., Simpson, J., & Murray, C. (2011). Reconsidering the term “carer”: a critique of the universal adoption of the term “carer.” Ageing & Society, 31(3), 422–437. https://doi.org/10.1017/S0144686X10001066
Morais, H. C. C., Soares, A. M. de G., Oliveira, A. R. de S., Carvalho, C. M. de L., Silva, M. J. da, & Araujo, T. L. de. (2012). Burden and modifications in life from the perspective of caregivers for patients after stroke. Revista Latino-Americana de Enfermagem, 20(5), 944–953.
Mosher, C. E., Champion, V. L., Azzoli, C. G., Hanna, N., Jalal, S. I., Fakiris, A. J., … Ostroff, J. S. (2013). Economic and social changes among distressed family caregivers of lung cancer patients. Supportive Care in Cancer, 21(3), 819–826. https://doi.org/10.1007/s00520-012-1585-6
Motulsky, H. (2014). Intuitive biostatistics: a nonmathematical guide to statistical thinking (3rd ed.). USA: Oxford University Press.
Neulinger, J. (1981). The Psychology of Leisure (2nd ed.). Springfield, Ill.: C. C. Thomas.
Orgeta, V., & Miranda-Castillo, C. (2014). Does physical activity reduce burden in
Page 69 of 197
carers of people with dementia? A literature review. International Journal of Geriatric Psychiatry, 29(8), 771–783. https://doi.org/10.1002/gps.4060
Ory, M. G., Hoffman, R. R., Yee, J. L., Tennstedt, S., & Schulz, R. (1999). Prevalence and Impact of Caregiving: A Detailed Comparison Between Dementia and Nondementia Caregivers. The Gerontologist, 39(2), 177–186. https://doi.org/10.1093/geront/39.2.177
Otis-Green, S., & Juarez, G. (2012). Enhancing the Social Well-Being of Family Caregivers. Seminars in Oncology Nursing, 28(4), 246–255. https://doi.org/10.1016/J.SONCN.2012.09.007
Papastavrou, E., Kalokerinou, A., Papacostas, S. S., Tsangari, H., & Sourtzi, P. (2007). Caring for a relative with dementia: family caregiver burden. Journal of Advanced Nursing, 58(5), 446–457. https://doi.org/10.1111/j.1365-2648.2007.04250.x
Parr, M. G., & Lashua, B. D. (2004). What is Leisure? The Perceptions of Recreation Practitioners and Others: EBSCOhost. Leisure Sciences, 26(1), 1–17. Retrieved from http://web.b.ebscohost.com/ehost/detail/detail?vid=2&sid=b510ebe7-4a78-4d63-ae09-c6be73274f13%40pdc-v-sessmgr01&bdata=JkF1dGhUeXBlPWlwLHNoaWImc2l0ZT1laG9zdC1saXZl#AN=11985262&db=s3h
Pearlin, L. I. (2009). The Life Course and the Stress Process: Some Conceptual Comparisons. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65B(2), 207–215. https://doi.org/10.1093/geronb/gbp106
Pearlin, L. I., Mullan, J. T., Semple, S. J., & Skaff, M. M. (1990). Caregiving and the Stress Process: An Overview of Concepts and Their Measures. The Gerontologist, 30(5), 583–594. https://doi.org/10.1093/geront/30.5.583
Peña-Longobardo, L. M., & Oliva-Moreno, J. (2015). Caregiver Burden in Alzheimer’s Disease Patients in Spain. Journal of Alzheimer’s Disease, 43(4), 1293–1302. https://doi.org/10.3233/JAD-141374
Pinquart, M., & Sörensen, S. (2003). Differences between caregivers and noncaregivers in psychological health and physical health: a meta-analysis. Psychology and Aging, 18(2), 250–267. https://doi.org/10.1037/0882-7974.18.2.250
Raj, J., Manigandan, C., & Jacob, K. (2006). Leisure satisfaction and psychiatric morbidity among informal carers of people with spinal cord injury. Spinal Cord, 44(11), 676–679. https://doi.org/10.1038/sj.sc.3101899
Rizk, S., Pizur-Barnekow, K., & Darragh, A. R. (2011). Leisure and Social Participation and Health-Related Quality of Life in Caregivers of Children with Autism. OTJR: Occupation, Participation and Health, 31(4), 164–171. https://doi.org/10.3928/15394492-20110415-01
Rochette, A., Desrosiers, J., Bravo, G., Tribble, D. S.-C., & Bourget, A. (2007).
Page 70 of 197
Changes in participation level after spouse’s first stroke and relationship to burden and depressive symptoms. Cerebrovascular Diseases (Basel, Switzerland), 24(2–3), 255–60. https://doi.org/10.1159/000104487
Romero-Moreno, R., Márquez-González, M., Mausbach, B. T., & Losada, A. (2012). Variables modulating depression in dementia caregivers: a longitudinal study. International Psychogeriatrics, 24(8), 1316–1324. https://doi.org/10.1017/S1041610211002237
Schulz, R., O’Brien, A. T., Bookwala, J., & Fleissner, K. (1995). Psychiatric and Physical Morbidity Effects of Dementia Caregiving: Prevalence, Correlates, and Causes. The Gerontologist, 35(6), 771–791. https://doi.org/10.1093/geront/35.6.771
Smith, L., Onwumere, J., Craig, T., McManus, S., Bebbington, P., & Kuipers, E. (2014). Mental and physical illness in caregivers: results from an English national survey sample. The British Journal of Psychiatry, 205(3), 197–203. https://doi.org/10.1192/bjp.bp.112.125369
Stansfeld, S., Smuk, M., Onwumere, J., Clark, C., Pike, C., McManus, S., … Bebbington, P. (2014). Stressors and common mental disorder in informal carers – An analysis of the English Adult Psychiatric Morbidity Survey 2007. Social Science & Medicine, 120, 190–198. https://doi.org/10.1016/J.SOCSCIMED.2014.09.025
Staudinger, U. M., & Bluck, S. (2001). A View on Midlife Development from Life-Span Theory. In M. E. Lachman (Ed.), Handbook of Midlife Development (pp. 3–39). New York: John Wiley & Sons, Inc.
Thompson, L., Solano, N., & Kinoshita, L. (2002). Pleasurable activities and mood: Differences between Latina and Caucasian dementia family caregivers. Journal of Mental Health and Ageing, 8(3), 211–224. Retrieved from https://asu.pure.elsevier.com/en/publications/pleasurable-activities-and-mood-differences-between-latina-and-ca
University of Essex. Institute for Social and Economic Research, NatCen Social Research, K. P. (2017). Understanding Society: Waves 1-7, 2009-2016 and Harmonised BHPS: Waves 1-18, 1991-2009. [data collection]. (9th ed.). SN: 6614: UK Data Service. Retrieved from https://www.understandingsociety.ac.uk/documentation/citation
Vincente, M. M., Delgado, M. G., Fuertes, N., & Prieto, J. P. (2009). Effects of a program of physical exercise at home in carers of Alzheimer’s patients: a pilot study. Revista de Psicología Del Deporte, 18(2), 255–270. Retrieved from https://ddd.uab.cat/record/62733
Voss, J. (1967). The definition of leisure. Journal of Economic Issues, 1(1), 91–106. https://doi.org/10.1080/00213624.1967.11502742
Waelde, L. C., Thompson, L., & Gallagher-Thompson, D. (2004). A pilot study of a yoga and meditation intervention for dementia caregiver stress. Journal of
Page 71 of 197
Clinical Psychology, 60(6), 677–687. https://doi.org/10.1002/jclp.10259
Wakui, T., Saito, T., Agree, E. M., & Kai, I. (2012). Effects of home, outside leisure, social, and peer activity on psychological health among Japanese family caregivers. Aging & Mental Health, 16(4), 500–506. https://doi.org/10.1080/13607863.2011.644263
Warrell-Phillips, S. (2018). What factors affect the mental health and wellbeing of Middle Aged Male Carers? (Unpublished doctoral dissertation). University of Surrey, Guildford.
White-Means, S. I., & Chang, C. F. (1994). Informal caregivers’ leisure time and stress. Journal of Family and Economic Issues, 15(2), 117–136. https://doi.org/10.1007/BF02353636
Williams, I. C. (2005). Emotional Health of Black and White Dementia Caregivers: A Contextual Examination. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60(6), 287–295. https://doi.org/10.1093/geronb/60.6.P287
Williamson, G. M., & Schulz, R. (1992). Pain, Activity Restriction, and Symptoms of Depression Among Community-residing Elderly Adults. Journal of Gerontology, 47(6), P367–P372. https://doi.org/10.1093/geronj/47.6.P367
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List of Appendices:
Appendix A: Ethical approval................................................................................................Appendix B: Questions from Understanding Society............................................................Appendix C: Leisure activities mentioned and their respective categories...........................Appendix D: Testing assumptions cross section....................................................................Appendix E: Non-parametric and robust tests for cross sectional hypotheses......................Appendix F: Frequency variables fitted as a trend in the GLM.............................................Appendix G: estimated marginal means for frequency of mild and moderate intensity sport when age and employment were adjusted for...............................................................Appendix H: Testing assumptions for longitudinal data........................................................Appendix I: Non-parametric and robust tests for longitudinal hypotheses............................Appendix J: Longitudinal analysis adjusting for other variables in the stress process model......................................................................................................................................
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Appendix A: Ethical approval
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Appendix B: Questions from Understanding Society
Carer characteristics (age, qualification, finances)Pos. = 1275 Variable = b_age_cr Variable label = age corrected
Value label information for b_age_cr
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Primary stressors (hours per week caring, living with the cared for individual)
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Competing demands (work, childcare)
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Social support (relationship quality, living with partner)
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Leisure (frequency, variety, sport/not sport, leisure time satisfaction)
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Wellbeing
Questions used from the mainstage questionnaire.
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Appendix C: Leisure activities mentioned and their respective categories
Arts activities Arts events
Museum library archive Historical sites
Dance, including ballet
Sang to an audience or rehearsed for a performance (not karaoke)
Played a musical instrument
Written musicRehearsed or performed in a play/drama, opera/operetta or musical theatre
Taken part in a carnival or street arts event (e.g. as a musician, dancer, or costume maker)
Painting, drawing, printmaking or sculpture
Photography, film or video making as an artistic activity (not family or holidays)
Used a computer to create original artworks or animation
Textile crafts, wood crafts or any other crafts such as embroidery, knitting, wood turning, furniture making, pottery or jewellery
Read for pleasure (not newspapers, magazines, or comics)
Written any stories, plays or poetry
Been a member of a book
Film at cinema or other venue
exhibition or collection of art, photography or sculpture or arts exhibition (not crafts market)
Event which included video or electronic art
Event connected with books or writing
Street arts or a public arts display or installation ~(art in everyday surroundings, or an art work such as sculpture that is outdoors or in a public place)
Carnival or culturally specific festival (for example Mela, Baisakhi, Navrati, Feis)
Play/drama, pantomime or a musical
Opera/operettaClassical musical performance
Rock, pop or jazz performance
Ballet
Contemporary dance
African people's dance or South Asian and Chinese dance
Used a public library service
Been to an archive centre or records office
Visited a museum or gallery
A city or town with historic character
A historic building open to the public (non-religious)
A historic park or garden open to the public
A place connected with industrial history (e.g. an old factory, dockyard or mine) or historic transport system (e.g. an old ship or railway)
A historic place of worship attended as a visitor (not to worship)
A monument such as a castle, fort or ruin.
A site of archaeological interest (e.g. roman villa, ancient burial site)
A site connected with sports heritage (e.g. Wimbledon) (not visited for the purposes of watching sport)
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club where people meet up to discuss and share books Circus (not animals)
Sporting activities Mild intensity sporting activities
Health, fitness, gym or conditioning activities (including aerobics, keep fit classes, weight-training or weight-lifting)
Gymnastics
Swimming or diving
Cycling, BMX or mountain biking (for sport or recreation)
Football (including 5 or 6-a-side)
Rugby (union or league) or American footballTrack and field athletics
Jogging, cross country, road-runningHill trekking, backpacking, climbing or mountaineering
Golf (including pitch and putt)
Boxing
Martial arts (including tai chi, taekwondo, karate, and judo)
Basketball
Netball
Volleyball
Cricket
Hockey (exclude ice, roller, or street hockey but include in "other")
Baseball, softball or rounders
Racquet sports such as table tennis, tennis, badminton or squash
Ice-skating
Skiing (on snow or an artificial surface: on slopes or grass)
Motor sports
Angling or fishing
Archery (if age > 64)
Yoga or Pilates (if age > 64)
Bowls (indoors or outdoors) (if age > 64)
Snooker, pool or billiards
Darts
Ten-pin bowling
Rambling, walking for pleasure or recreation
Shooting
Archery (if age < 65)
Yoga or Pilates (if age < 65)
Bowls (indoors or outdoors) (if age < 65)
Croquet (if age < 65)
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Water sports including yachting, dinghy sailing, canoeing, rowing, windsurfing, water-skiing etc.Horse riding
Croquet (if age > 64)
Other sporting activity such as triathlon, fencing, lacrosse, orienteering, curling, Gaelic sports, skateboarding, parachuting or scuba diving or anything else
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Appendix D: Testing assumptions cross section
Distribution
DescriptivesStatistic Std. Error
Subjective wellbeing (GHQ):
Likert
Mean 13.90 .252
Median 12.00
Variance 44.923
Std. Deviation 6.702
Minimum 0
Maximum 36
Range 36
Interquartile Range 8
Skewness 1.102 .092
Kurtosis .929 .183
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SPSS output: histograms for GHQ-12 MCS at wave 2 split across the three levels of
sporting activity, with the normal distribution curve overlayed.
No Sport:
Mean = 15Standard Deviation = 7.2N = 273
Mild intensity sport:
Mean = 13.4Standard Deviation = 6.4N = 113
Moderate intensity sport:
Mean = 13.1Standard Deviation = 6.2N = 324
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Q-Q plots
SPSS output: Q-Q plots for GHQ-12 MCS split across the three levels of sport:
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Appendix E: Non-parametric and robust tests for cross sectional hypothesesCorrelations between Wellbeing and independent variables.
Correlationssatisfaction
with amount
of leisure time
Subjective
wellbeing
(GHQ): Likert
Spearman's
rho
satisfaction with
amount of leisure time
Correlation Coefficient 1.000 -.371**
Sig. (1-tailed) . .000
N 710 710
Subjective wellbeing
(GHQ): Likert
Correlation Coefficient -.371** 1.000
Sig. (1-tailed) .000 .
N 710 710
Subjective
wellbeing
(GHQ): Likert
Total number
of activties
Spearman's
rho
Subjective wellbeing
(GHQ): Likert
Correlation Coefficient 1.000 -.106**
Sig. (1-tailed) . .002
N 710 710
Variety of activities Correlation Coefficient -.106** 1.000
Sig. (1-tailed) .002 .
N 710 710
Kruskal-Wallis Tests exploring the relationship between frequency variables and
wellbeing:
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Robust tests: Satisfaction and wellbeing
Variety and wellbeing
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Appendix F: Frequency variables fitted as a trend in the GLM
Arts Activities
Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert
Source
Type III Sum of
Squares df Mean Square F Sig.
Partial Eta
Squared
Corrected Model 45.521a 1 45.521 1.013 .314 .001
Intercept 42838.399 1 42838.399 953.605 .000 .574
b_artsAct_freq 45.521 1 45.521 1.013 .314 .001
Error 31805.177 708 44.923
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .001 (Adjusted R Squared = .000)
Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B
Std.
Error t Sig.
95% Confidence Interval
Partial Eta
Squared
Lower
Bound
Upper
Bound
Intercept 14.290 .463 30.881 .000 13.381 15.198 .574
b_artsAct_freq -.147 .146 -1.007 .314 -.435 .140 .001
Archives
Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert
Source
Type III Sum
of Squares df Mean Square F Sig.
Partial Eta
Squared
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Corrected Model 56.288a 1 56.288 1.253 .263 .002
Intercept 130338.051 1 130338.051 2902.376 .000 .804
b_archive_freq 56.288 1 56.288 1.253 .263 .002
Error 31794.411 708 44.907
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .002 (Adjusted R Squared = .000)
Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B Std. Error t Sig.
95% Confidence Interval
Partial Eta
Squared
Lower
Bound
Upper
Bound
Intercept 13.840 .257 53.874 .000 13.336 14.344 .804
b_archive_freq .868 .775 1.120 .263 -.654 2.389 .002
Museum
Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
Corrected Model 152.301a 4 38.075 .847 .496 .005
Intercept 43259.347 1 43259.347 962.126 .000 .577
b_museum_freq 152.301 4 38.075 .847 .496 .005
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Error 31698.397 705 44.962
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .005 (Adjusted R Squared = -.001)
Parameter Estimates
Dependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B
Std.
Error t Sig.
95% Confidence
Interval
Partial Eta
Squared
Lower Bound
Upper
Bound
Intercept 11.947 1.538 7.766 .000 8.927 14.968 .079
[b_museum_freq=.00] 2.175 1.567 1.388 .166 -.902 5.252 .003
[b_museum_freq=1.00] 1.018 1.772 .574 .566 -2.462 4.498 .000
[b_museum_freq=2.00] 1.686 1.765 .955 .340 -1.780 5.152 .001
[b_museum_freq=3.00] 1.888 1.727 1.093 .275 -1.502 5.279 .002
[b_museum_freq=4.00] 0a . . . . . .
a. This parameter is set to zero because it is redundant.
Arts events
Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert
Source
Type III Sum of
Squares df Mean Square F Sig.
Partial Eta
Squared
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Corrected Model 526.218a 1 526.218 11.894 .001 .017
Intercept 74148.821 1 74148.821 1675.921 .000 .703
b_artsEve_freq 526.218 1 526.218 11.894 .001 .017
Error 31324.480 708 44.244
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .017 (Adjusted R Squared = .015)
Parameter Estimates
Dependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B
Std.
Error t Sig.
95% Confidence
Interval
Partial
Eta
Square
d
Lower
Bound
Upper
Bound
Intercept 14.800 .362 40.938 .000 14.091 15.510 .703
b_artsEve_freq -.793 .230 -3.449 .001 -1.245 -.342 .017
Library
Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert
Source
Type III Sum of
Squares df Mean Square F Sig.
Partial Eta
Squared
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Corrected Model 110.439a 1 110.439 2.463 .117 .003
Intercept 99149.623 1 99149.623 2211.637 .000 .758
b_lib_freq 110.439 1 110.439 2.463 .117 .003
Error 31740.259 708 44.831
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .003 (Adjusted R Squared = .002)
Parameter Estimates
Dependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B Std. Error t Sig.
95% Confidence
Interval
Partial Eta
Squared
Lower
Bound
Upper
Bound
Intercept 14.159 .301 47.028 .000 13.568 14.750 .758
b_lib_freq -.309 .197 -1.570 .117 -.696 .078 .003
Historical Sites
Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert
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Source
Type III Sum of
Squares df Mean Square F Sig.
Partial Eta
Squared
Corrected Model 53.000a 1 53.000 1.180 .278 .002
Intercept 79750.775 1 79750.775 1775.712 .000 .715
b_hx_freq 53.000 1 53.000 1.180 .278 .002
Error 31797.699 708 44.912
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .002 (Adjusted R Squared = .000)
Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B Std. Error t Sig.
95% Confidence Interval
Partial Eta
Squared
Lower
Bound
Upper
Bound
Intercept 14.140 .336 42.139 .000 13.481 14.799 .715
b_hx_freq -.264 .243 -1.086 .278 -.740 .213 .002
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Moderate intensity sport
Tests of Between-Subjects EffectsDependent Variable: Subjective wellbeing (GHQ): Likert
Source
Type III Sum of
Squares df Mean Square F Sig.
Partial
Eta
Squared
Corrected Model 284.873a 1 284.873 6.390 .012 .009
Intercept 88379.318 1 88379.318 1982.288 .000 .737
b_MIsport_freq 284.873 1 284.873 6.390 .012 .009
Error 31565.825 708 44.584
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .009 (Adjusted R Squared = .008)
Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B
Std.
Error t Sig.
95% Confidence Interval
Partial Eta
Squared
Lower Bound Upper Bound
Intercept 14.417 .324 44.523 .000 13.781 15.053 .737
b_MIsport_freq -.389 .154 -2.528 .012 -.691 -.087 .009
Mild intensity sport
Tests of Between-Subjects Effects
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Dependent Variable: Subjective wellbeing (GHQ): Likert
Source
Type III Sum of
Squares df Mean Square F Sig.
Partial Eta
Squared
Corrected Model 254.047a 1 254.047 5.693 .017 .008
Intercept 87906.483 1 87906.483 1969.759 .000 .736
b_LIsport_freq 254.047 1 254.047 5.693 .017 .008
Error 31596.651 708 44.628
Total 169002.000 710
Corrected Total 31850.699 709
a. R Squared = .008 (Adjusted R Squared = .007)
Parameter EstimatesDependent Variable: Subjective wellbeing (GHQ): Likert
Parameter B
Std.
Error t Sig.
95% Confidence Interval
Partial Eta
Squared
Lower Bound Upper Bound
Intercept 14.389 .324 44.382 .000 13.753 15.026 .736
b_LIsport_freq -.352 .148 -2.386 .017 -.642 -.062 .008
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Appendix G: estimated marginal means for frequency of mild and moderate intensity sport when age and employment were adjusted for.Moderate intensity sport and wellbeing when employment status was adjusted for:
2. b_MIsport_freqDependent Variable: Subjective wellbeing (GHQ): Likert
b_MIsport_freq Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
Not at all 15.241 .394 14.467 16.015
Once or twice in the past
year
14.175 1.268 11.685 16.664
at least 3/4 times in the past
year
12.658 1.011 10.674 14.642
less than weekly and at least
monthly
13.507 .901 11.738 15.277
at least once per week 13.217 .658 11.925 14.508
Moderate intensity sport and wellbeing when age was adjusted for:
2. b_MIsport_freqDependent Variable: Subjective wellbeing (GHQ): Likert
b_MIsport_freq Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
Not at all 14.677a .341 14.009 15.346
Once or twice in the past
year
13.416a .953 11.544 15.287
at least 3/4 times in the past
year
12.427a .880 10.698 14.156
less than weekly and at least
monthly
12.890a .709 11.498 14.282
at least once per week 13.096a .583 11.951 14.241
a. Covariates appearing in the model are evaluated at the following values: age corrected =
52.43.
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Appendix H: Testing assumptions for longitudinal data
Equality of variances
Levene's Test of Equality of Error Variancesa
F df1 df2 Sig.
Subjective wellbeing (GHQ):
Likert (Wave 2)
13.655 2 4433 .000
Subjective wellbeing (GHQ):
Likert (Wave 5)
7.057 2 4433 .001
Tests the null hypothesis that the error variance of the dependent variable is
equal across groups.
a. Design: Intercept + care_status
Within Subjects Design: time
Levene's Test of Equality of Error Variancesa
F df1 df2 Sig.
satisfaction with amount of
leisure time (wave 2)
.204 2 4433 .816
satisfaction with amount of
leisure time (wave 5)
.919 2 4433 .399
Tests the null hypothesis that the error variance of the dependent variable is
equal across groups.
a. Design: Intercept + care_status
Within Subjects Design: time
Levene's Test of Equality of Error Variancesa
F df1 df2 Sig.
b_variety_total
(wave 2)
5.047 2 4433 .006
e_variety_total
(wave 5)
3.772 2 4433 .023
Tests the null hypothesis that the error variance of the dependent
variable is equal across groups.
a. Design: Intercept + care_status
Within Subjects Design: time
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Distribution
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Appendix I: Non-parametric and robust tests for longitudinal hypotheses.Results from Kruskal-Wallis tests exploring the relationship between change in
variety, satisfaction, frequency and wellbeing over time for the different carer groups
(results are consistent with results from parametric tests).
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Results from Wolcoxon Signed Rank tests to explore the relationship between variety, satisfaction and wellbeing at Wave 2 and Wave 5. Results were consistent with the results from parametric tests.
Variety
Satisfaction with leisure time
Wellbeing
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Appendix J: Longitudinal analysis adjusting for other variables in the stress process model
Results from repeated measures GLM exploring satisfaction with leisure time over time between care groups, with other factors from the stress process entered into the model one at a time.
Time Carer Status Time* Carer statusF, P F,P F, P
Unadjusted 11.704, .001 4.741, .009 2.345, .096
Carer CharacteristicsAge 10.901, .001 6.453, .002 2.366, .094Qualification 16.561, <.001 1.991, .137 3.983, .019Finances 6.779, .009 2.446, .087 1.421, .242
Competing demandsEmployment 121.062, .001 8.933, <.001 2.847, .058Childcare 5.108, .024 2.308, .100 1.060, .347
Social SupportPartner 9.532, .002 3.575, .028 2.026, .132Relationship quality 11.414, .001 4.669, .009 2.425, .089
Results from repeated measures GLM exploring variety over time between care groups, with other factors from the stress process entered into the model one at a time.
Time Carer Status Time* Carer statusF, P F,P F, P
Unadjusted 4.882, .027 11.950, <.001 .458, .633
Carer CharacteristicsAge 5.816, .016 11.546, <.001 .535, .586Qualification 5.847, .016 11.636, <.001 .563, .569Finances 3.625, .057 6.248, .002 .778, .459
Competing demandsEmployment 4.426, .035 9.096, <.001 .458, .633Childcare 4.565, .003 13.231, <.001 .194, .824
Social SupportPartner 4.896, .027 7.397, .001 .641, .527Relationship quality 4.874, .027 11.768, <.001 .459, .632
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Results from repeated measures GLM exploring GHQ over time between care groups, with other factors from the stress process entered into the model one at a time.
Time Carer Status Time* Carer statusF, P F,P F, P
Unadjusted .002, .963 19.301, <.001 .292, .747
Carer CharacteristicsAge .087, .768 19.241, <.001 .266, .767Qualification .022, .883 18.698, <.001 .306, .736Finances .002, .963 19.301, <.001 .292, .747
Social SupportPartner .275, .600 13.395, <.001 .680, .507Relationship quality
.022, .882 19.225, <.001 .208, .812
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Literature review
Leisure influences on wellbeing among those who spend a
significant amount of time caring for others: A systematic
review
Word count: 7446
Statement of journal choiceThis paper will be submitted to “Social Science & Medicine”. This journal has been
selected as its aim is to publish “original research articles…to inform current
research, policy and practice in all areas of common interest to social scientists,
health practitioners, and policy makers”. It accepts articles from the field of
psychology and has an interest in mental health and material which “is of interest to
an international readership”, as stated in the scope of the journal (Appendix A).
This portfolio fits within the remit as it explores issues pertaining to carers who are
commonly at risk of becoming mental health service users. This is a field of interest
internationally to professionals from a range of backgrounds such as health
practitioners and social scientists. Implications of findings may also be relevant for
policy makers with an interest in improving carer wellbeing nationally and wishing
to develop an understanding of the complex mechanisms underlying wellbeing
within this valued group in society.
The impact factor of the journal is 2.32 (October 2017).
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If this article is not accepted by the first choice journal, it will then be submitted to
“Health and Social Care in the Community” and “Health and Quality of Life
Outcomes”.
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AbstractBecoming a carer can result in a lack of leisure opportunities and reduction in leisure
is associated with reduced psychological wellbeing for carers. Studies in this area
often do not differentiate between those who spend only a few hours and those who
spend many hours caregiving. Therefore, this review aimed to critically examine and
summarise the existing literature on the extent to which leisure influences wellbeing
among those who spend a significant amount of time caring for others. Seven
databases were searched for terms relevant to caregiving, leisure and wellbeing and
this resulted in identification of nine papers relevant for this review. Wellbeing
measures fell into four categories: depression, positive or negative affect, general
wellbeing and positive attitudes to caregiving. Studies that explored the relationship
between depression and leisure had findings that were consistent with the idea that
lower levels of engagement with leisure activities are associated with depression.
Additionally, positive affect, general wellbeing and positive feelings relating to
caregiving were associated with higher leisure engagement and satisfaction. Number
of hours spent in leisure may be less relevant to understanding the relationship
between leisure engagement and wellbeing than other dimensions of leisure
engagement. Limitations to this review included a lack of papers exploring mediators
and moderators of the relationship, limited methodological designs (largely cross-
sectional questionnaire studies) and lack of consideration of the caregiver and cared
for individual engaging in leisure activities together. Further research in these areas
would be beneficial.
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Introduction
Informal Caregiving
There are 6.5 million unpaid carers in the UK and this figure is expected to rise to 9
million over the next 20 years (Carers UK, 2015). Carers are individuals who provide
support to another including with activities which are required in order to live
independently. The types of activities they do are varied and include practical help
(e.g. preparing meals, laundry, shopping), keeping an eye on the cared for, keeping
them company, taking them out, aspects of personal care, providing physical help,
and supporting them to deal with care services, benefits, and finances (Carers UK,
2015). Unpaid carers are also called “informal” or “volunteer” carers.
The term “carer” is not always considered truly reflective of the (often reciprocal)
relationships which are characterised by one partner supporting the other in their day
to day tasks (Hughes, Locock, & Ziebland, 2013; Molyneaux, Butchard, Simpson, &
Murray, 2011). Further, there has been some suggestion that the term “carer” carries
an assumption of burden, and it would be preferable to use relationship descriptors
that existed prior to the start of the caring role (e.g. husband, wife, daughter, son,
parent). For the purpose of narrative eloquence this review will use the terms “carer”
and “caregiver” to capture the broad range of relationships held within this group.
However, wherever possible, pre-existing relationship descriptors will be used as
synonymous alternatives.
Levels of care
Those who care for more than 20 hours per week (HPW) are more likely to provide
physical help, personal care, and support with medications than those caring less than
20 HPW (Carers UK, 2015). This suggests that people who spend more time caring
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are likely to be performing different or additional caregiving tasks compared with
those who spend less time caring.
Measuring the number of hours an individual spends caring is one way of
understanding the level of care provided. However, considering time in isolation
from the type and quality of tasks carried out provides a limited picture of the actual
demands and rewards of the caregiving experience. Carers who do not live with the
individual they are caring for may have significant travel times to get to the person
cared for to fulfil their responsibilities. Caregivers may also spend time planning for
others to assist with the caregiving responsibilities (e.g. other family members or
paid professionals). Within research it is not always clear to what extent these caring
components are considered.
Another way to understand the demands of caregiving is to examine the type and
quality of caregiving tasks. Often the kinds of activities required for independence
are categorised into Activities of Daily Living (ADLs; S. Katz, Ford, Moskowitz,
Jackson, & Jaffe, 1963) and Instrumental Activities of Daily Living (IADLs; Lawton
& Brody, 1970). ADLs include basic and essential self-care tasks such as washing,
toileting and eating. In contrast to this IADLs include tasks such as shopping,
cooking and managing finances. Counting the number of ADLs and IADLs that a
carer supports someone with and the extent to which support is provided is a
common method of understanding the level of care that a carer provides. These offer
a way of understanding one aspect of the caregiving demands although do not
provide a detailed picture of the complexities of the caregiving experience (Levine,
Reinhard, Feinberg, Albert, & Hart, 2003).
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Many carers are spouses, offspring, parents, other relatives, neighbours and friends.
Some are carers from the start of the relationship (e.g. parents of children with
special needs) and others experience caregiving as a change within the existing
relationship dynamic (Gautam & Nijhawan, 1984; López, López-Arrieta, & Crespo,
2005). Carers meet the practical needs of another, and also form an important part of
the emotional and relational world of the cared for individual, often in a reciprocal
way (Hughes et al., 2013). This means that the relationship is not only beneficial for
the individual being cared for, but also for the carer themselves (e.g. gaining
satisfaction from the role, receiving emotional support from the individual they care
for, experiencing them as fun to be with, or as having a sense of humour; Nolan,
2001). All of these things contribute to the complexities of the caregiving role,
caregiving relationship and the emotional health and wellbeing of the carer.
Emotional Health and Wellbeing of Carers
Given the value of carers and their significant contribution to society it seems
important to be able to understand and support their wellbeing. Caring can be
rewarding and add to their relationship with the cared for individual (Szmukler et al.,
1996). Individuals report improved family bonds, love, hope and support for the
individual they are caring for (Treasure et al., 2001). The opportunity to learn and the
chance for reciprocity have also been identified as valuable consequences (Stern,
Doolan, Staples, Szmukler, & Eisler, 1999). Positive psychological states can exist in
caregivers alongside stressful circumstances and feelings of distress (Folkman,
1997).
Additionally, this role can be associated with challenges. The caregiving population
is at greater risk of both physical and mental health problems than non-caregivers
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(Haley, Roth, Hovater, & Clay, 2015; Peña-Longobardo & Oliva-Moreno, 2015;
Pinquart & Sörensen, 2003). This therefore makes them at risk of not being able to
continue their caregiving role or perhaps requiring care themselves. Notably in one
study, people who spent more hours caring were at greater risk, and those who cared
more than 20 HPW had a twofold increase in psychiatric symptoms when compared
with non-caregivers (L. Smith et al., 2014). One important component that is used to
understand the caregiving experience is burden, which takes into consideration some
of the negative psychological impacts of caregiving.
Burden is sometimes divided into “subjective” vs “objective (Magliano, Fiorillo,
Rosa, & Maj, 2006) or “Practical” vs “psychological” (Magliano et al., 2002)
however the distinction between these are not always well defined. The concept of
burden is very broad and, according to measurement tools such as the Zarit Burden
Interview ((Zarit, Reever, & Bach-Peterson, 1980) a commonly used measure of
burden), includes psychological components (such as feeling stressed or angry),
practical impact of caring (such as on privacy or finances), and cognitive evaluations
of caring ability (such as “should be doing a better job”).
Burden is a widely-researched concept and has been repeatedly shown to negatively
impact on the leisure experiences of caregivers (Ausserhofer, Mantovan, Pirhofer,
Huber, & Them, 2009; Chakrabarti, Raj, Kulhara, Avasthi, & Verma, 1995; Eric
Hwang, Rivas, Fremming, Rivas, & Crane, 2009), particularly in leisure reduction.
However, because burden is a broad multi-faceted concept, which includes
information additional to psychological wellbeing it was not included in this
literature review.
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Components of psychological wellbeing may include, mood or affect, worry, stress,
anxiety, or satisfaction. These ideas may be measured from a deficit oriented model
e.g. through questionnaires exploring diagnosable conditions such as depression and
anxiety. Alternatively, it may be approached from a positive psychology framework
asking more broadly about psychological wellbeing (as in quality of life measures),
or about how good people feel about their caregiving role.
Theories such as Pearlin’s Stress Process model (Pearlin, Mullan, Semple, & Skaff,
1990) seek to explain how caregiving experiences contribute to reduced wellbeing.
Pearlin suggests that primary stressors (e.g. becoming a carer) result in secondary
stressors (e.g. having limited time for engaging in hobbies) which then impact on an
individual’s wellbeing (e.g. reduced mood). This holds face validity and has been
supported through some of the caregiving research (Haley, LaMonde, Han, Burton,
& Schonwetter, 2004; Infurna, Gerstorf, & Zarit, 2012; Pearlin, 2009; Romero-
Moreno, Márquez-González, Mausbach, & Losada, 2012). This model suggests that
there may be different (or more accentuated) secondary stressors for individuals who
spend more of their time caring. Particularly in view of the fact that there are limited
hours in a week and a greater proportion of these are taken up for caregiving
potentially means fewer hours for other usual commitments such as self-care or
leisure. They may also have increased financial strain if they have had to reduce their
working hours to accommodate for an increase in their caring hours.
Theories and measures of leisure
Voss (1967) defines leisure in terms of time allocation. Activities are either
economically motivated (called work), non-economically motivated but integral to
the maintenance of life (e.g. childcare, cleaning etc.) or discretionary (meaning one
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has the freedom of choice). Leisure is the latter of the three. This theory is similar to
Neulinger’s (1981) theory that perceived freedom of choice is integral to the
definition and so too is the need to be intrinsically motivated to do the activity.
These broad definitions pose dilemmas within research as some activities may fall
into different categories depending on the individual and the wider context of the
situation. For example, one individual may choose to spend their free time cooking
(leisure), whereas another may complete this activity only because it is integral to the
maintenance of life (not leisure), and another may cook for the financial reward
(work). It also opens up the possibility of an enormous number of specific activities
being defined as possible leisure activities. Therefore, generating exhaustive
checklists of leisure activities may not be feasible. Some researchers have attempted
to overcome this by allowing respondents to add their own activities to their checklist
(Rizk, Pizur-Barnekow, & Darragh, 2011). However, unfortunately, the validation
study for this particular checklist remains unpublished and therefore there are
challenges for researchers interested in using this measure/approach.
An alternative solution is to divide leisure activities into categories and ask about
those, or ask broader questions about leisure engagement. For example, Lee &
Bhargava (2004) divide leisure into passive, active, and social with each of these
providing different benefits to the individual (e.g. physical health and intellectual
development). Similarly, a national American study called Resources for Enhancing
Alzheimer’s Caregiver Health (REACH; Wisniewski et al., 2003) used a 7-item
measure which asked about items such as “having quiet time to yourself”, “going out
for meals”, and “taking part in hobbies”. Participants rated their engagement on a
scale from “not at all”, to “a lot”. This allows for a broader assessment of people’s
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participation in pleasant activities than those studies which use only one question,
and are quicker to administer than those that list a broad range of activities.
Other considerations within this area might be access to facilities, and practical
barriers to leisure. One theory frames this using the terms “Place-centred” and
“person centred” components of leisure (Lloyd & Auld, 2002). Their theory suggests
that access to and use of leisure facilities (“place-centred”) as well as personal
satisfaction or reward obtained from engaging with leisure activities (“person
centred”) are important. The latter component may sometimes be measured using the
Leisure Time Satisfaction questionnaire (Stevens et al., 2004). This approach may
also include measurement of the level of engagement with leisure activities (i.e.
frequency or duration of activities). Practical barriers may also fall within the
secondary stressors part of the stress process model mentioned previously.
Barriers such as time limitations, financial strain, and access to facilities may lead to
a feeling of being unable to engage as fully with leisure interests as the individual
may like. This concept has been explored using the Activity Restriction Scale (ARS;
Williamson & Schulz, 1992). The scale asks about “sports and recreation”, “visiting
friends”, “working on hobbies” and “maintaining friendships” which were
conceptualised as being “expressive activities”. Similar to Neulinger’s definition of
leisure, expressive activities were considered to be intrinsically motivated. Another
study used two alternative measures: the Satisfaction with Time for Leisure scale and
the Satisfaction with Quality of Leisure scale (Bedini, Gladwell, & Dudley, 2011).
This illustrates the variety and quantity of measures that exist within the leisure
literature. There are few measures that are widely used and there are many ways of
approaching the topic, depending on the specific research question and wider
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context. Given that leisure is such a broad concept it is important to be able to break
it down into quantifiable concepts (e.g. frequency, restriction and satisfaction) as this
enables empirical research to better understand the relationship between leisure and
wellbeing.
Impact of leisure on the wellbeing of carers
Engaging in leisure activities could be a protective factor for carers. For example,
wives who participated in a telephone based exercise intervention had reduced stress
when compared with controls (Connell & Janevic, 2009). Studies have also found
that for some individuals’ leisure activities are used as a helpful coping mechanism
and as a way of holding onto one’s sense of self (Azman, Jamir Singh, & Sulaiman,
2017; Gahagan, Loppie, Rehman, Maclellan, & Side, 2007). Within the caregiving
literature there is evidence for a link between yoga and relaxation, and reduced
anxiety (Cooper, Balamurali, Selwood, & Livingston, 2007). Additionally, there is
some evidence that satisfaction with leisure time may be associated with reduced
biological indicators associated with stress (Chattillion et al., 2012).
There is evidence that reducing leisure leads to emotional stress and reduced life
satisfaction for carers (White-Means & Chang, 1994). Carers who are more satisfied
with their leisure time experience lower levels of anxiety and depression (Del-Pino-
Casado & Ordóñez-Urbano, 2016). However, the relationship between leisure and
wellbeing for carers is not straight forwards. One study has shown that restriction in
leisure activities results in reduced wellbeing and that this relationship is mediated by
perceived stress (Cramm & Nieboer, 2011). Another model described leisure
reduction as a secondary stressor and sought to understand pathways from primary
stressors, through secondary stressors to symptoms of low mood. They found that the
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primary stressors (behaviours that challenge and amount of help needed)
significantly predicted activity restriction, however activity restriction did not
significantly predict low mood (Bookwala & Schulz, 2000).
A further model by Bedini et al (2011) explored the effects of three different leisure
variables: leisure participation, satisfaction with leisure time, and satisfaction with
quality of leisure time which were all found to be associated with quality of life.
Additionally, for the latter two leisure variables, this relationship was found to be
mediated through perceived stress.
This illustrates the complexities in understanding the impact of leisure on
individuals, and therefore the challenges for researchers seeking to develop their
understanding of the relevant processes and mechanisms involved. A limitation of
the above described literature is that there is minimal clarity over whether these
findings are applicable to those carers who spend only a few hours a week caring,
and those who spend a significant amount of their time caregiving. Therefore, it will
be helpful to establish whether there is a clear association between wellbeing and
leisure engagement for carers who spend a significant amount of time providing care.
Caregiving around the world
It has been noted that there are significant differences in how different cultures
understand mental illness, how people seek and engage with treatment and support
(Kealey, 2005; Mojaverian, Hashimoto, & Kim, 2012), and their emotional
experiences of caregiving. There are differences in how individuals perceive the
family unit and therefore caring responsibilities within that family unit. For example,
Youn and colleagues (1999) found that family values are prioritised over the needs of
individual family members more in Korean families, than in American families.
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They also found higher levels of embarrassment and anger in offspring from Korean
families than White (American) families. Another study found that Chinese
caregivers have comparable levels of psychological wellbeing to non-caregivers, in
contrast to other cultures in which caregivers have reduced psychological wellbeing
when compared to their non-caregiving counterparts (Shaw et al., 1997). These
differences might suggest that culturally derived expectations about free time play a
role in psychological wellbeing, a component that is notably missing from common
definitions of leisure described above.
Therefore, although there is a large body of literature coming out of Asia
investigating various aspects of caregiving experiences (W.-T. Chien & Norman,
2009; W. T. Chien, Chan, Morrissey, & Thompson, 2005; Oshio & Kan, 2016) it is
unclear to what extent their findings are applicable to individuals within the UK.
This is particularly the case when methodology within these studies incorporates
structures that are underpinned by theory specific to Asian cultures. With this in
mind, studies which focus outside of Westernised cultures are considered outside of
the scope of this literature review.
Summary
It has been widely evidenced that a lack of leisure opportunities can result from
becoming a carer for individuals experiencing a range of challenges including
dementia, stroke, Parkinson’s disease, cancer, schizophrenia and mood disorders
(Chakrabarti et al., 1995; Flores, Berbis, Chinot, & Auquier, 2014; Martin, 2015;
Ory, Hoffman, Yee, Tennstedt, & Schulz, 1999; Rochette, Desrosiers, Bravo,
Tribble, & Bourget, 2007). It has also been shown that reduction in leisure is
associated with reduced psychological wellbeing for carers of a range of ailments
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such as individuals who have experienced spinal cord injury, dementia, cancer, liver
and lung transplant (Flores et al., 2014; Mausbach, Coon, Patterson, & Grant, 2008;
Meltzer & Rodrigue, 2001; Raj, Manigandan, & Jacob, 2006). However, it is often
the case that studies do not differentiate between those who spend only a few hours a
week caring and those who spend many hours each day caregiving. These two
groups are likely to have significant differences in their caregiving experiences
(Carers UK, 2015). Therefore, this review aimed to critically examine and
summarise the existing literature on the extent to which leisure influences well-being
among those who spend a significant amount of time caring for others.
MethodPreliminary searches were carried out using search terms identified by the researcher
with use of a thesaurus. A collection of terms were identified to represent the
concepts of “carer”, “wellbeing”, and “leisure”. This general searching of relevant
fields yielded additional terms which are commonly used throughout the literature.
The final search terms are shown below in Table 1.
Table 1: Search terms used
Database (date of search)
Caregiving search terms
Wellbeing search terms
Leisure search terms
Hits Other specifiers
Web of science (18/12/2016)
caregivers or carers or caring or caregiver or carer or caregiving or spouse or sibling(IN TOPIC)
“Wellbeing” or “well being” or “health” or “mental health” or depression or anxiety or stress or burden or “quality of life”(IN TOPIC)
“social activit*” or “leisure activit*” or "leisure time" or “recreation” or “activity theory” or leisure(IN TOPIC)
2,597 1970+, English
Web of science (18/12/2016)
1,236 As above AND("behavior sciences" OR "Geriatrics & Gerontology" OR
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Database (date of search)
Caregiving search terms
Wellbeing search terms
Leisure search terms
Hits Other specifiers
"Health Care Sciences & Services" OR "nursing" OR Psychiatry OR "Public, Environmental & Occupational Health" OR "Arts & Humanities" Or "social sciences") (in SUBJECT)
Psychology cross search:PsycINFO, PsycARTICLES, Psychology and Behavioral Sciences Collection, PsycBOOKS, MEDLINE (18/12/2016)
caregivers or carers or caring or caregiver or carer or caregiving or spouse or sibling
“Wellbeing” or “well being” or “health” or “mental health” or depression or anxiety or stress or burden or “quality of life”
“social activit*” or “leisure activit*” or "leisure time" or “recreation” or “activity theory” or leisure
1,148 In title or abstract
Data Sources
PsycINFO, PsycARTICLES, Psychology and Behavioral Sciences Collection,
PsycBOOKS, MEDLINE and Web of Science were searched using the terms
identified in table 1 on 18th December 2016. This generated a list of 1851 titles (after
duplicates had been excluded), of which 1715 were assessed as not relevant based on
the title. The abstracts of the remaining 136 papers were assessed to determine
whether they met the inclusion criteria. In the case of 61 of these papers it was not
clear from the abstract whether the inclusion criteria had been met and therefore the
full paper was searched. Nine additional papers were identified through hand
searching reference lists from relevant studies that were identified in the searches and
undertaking citation searches for relevant studies. Details of how many papers were
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excluded at each stage and on what basis they were excluded are represented in
Figure 1.
Figure 1: PRISMA 2009 flow diagram showing the selection process.
Inclusion/Exclusion criteria
Papers were included in this review if the participant sample was comprised of
individuals providing a moderate to high level of care (20 HPW or more, or the cared
Full-text articles excluded,
Records excluded as the title was not relevant
(n = 1715)
Records excluded as abstract was not relevant
(n = 96)
Abstracts screened
(n = 136)
Records after duplicates removed (all titles screened; n=1851)
(n = 1851)
Additional records identified through other sources
(n = 0)
Identification
Screening
Records identified through database searching
(n = 2384)
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for individual required support with at least one ADL or two IADLs), if the cared for
individual was living at their home (rather than a residential or nursing facility), and
if it explored the relationship between leisure and psychological wellbeing.
Papers were selected if the participant sample was drawn from “Western” cultures,
and if the paper was accessible in English. Articles were all peer reviewed and were
considered to contribute new knowledge to the existing literature base. Where papers
included caregivers providing a range of levels of care, only those which
disaggregated the results by time spent caring were included.
Where levels of care were not specified, they were assumed to be high if the carer
required respite, or if they were a parent caring for a child with additional needs.
Many studies reported mean hours of care above the 20 HPW cut off for this review.
However, a significant proportion of these also reported a range which indicated at
least one participant in the study was caring for less than 20 HPW. Therefore, it was
felt that the mean hours of care across participants was not a good enough indication
of the studies meeting eligibility criteria for this review, and studies were only
included if they also reported a range above 20 HPW.
Papers were also excluded if they were not available in English and if the carers were
paid staff members. Papers which explored a leisure intervention combined with
another intervention (such as psychoeducation) as a key component were not
included in this review. This is because it was not possible to separate out the effects
of leisure and the additional intervention.
Finally, wellbeing outcome measures were considered carefully. If they included
measures of physical health, the environment, or other components that were not
Full-text articles excluded,
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separated in the analysis from psychological wellbeing, they were not considered
relevant for this review.
The first author completed the screening process independently and consulted with
two other researchers on a selection of 9 papers to check for inter-rater agreement.
Where there was disagreement the paper was discussed between the researchers until
all parties reached a consensus.
Data Extraction
Initial data extraction consisted of general study characteristics as presented in tables
2 and 3. This was followed by more detailed extraction of results from each of the
studies.
Data Analysis
All papers were evaluated for quality using Qual Syst (Kmet, Lee, & Cook, 2004), to
ensure a consistent approach to the review process. This tool was selected as it is
widely used within caregiving literature (e.g. Greenwood, Habibi, Smith, &
Manthorpe, 2015; Greenwood & Smith, 2015; Kuo, Sun, & Tang, 2017; R. Smith &
Greenwood, 2014), and it can be used with a range of different study designs.
However, the guidelines were at times vague. NICE guidelines which were designed
for use with intervention studies and so largely not applicable, did have some more
specific advice about how to consider reliability and validity (NICE, 2012).
Therefore, this was used in conjunction with the Qual Syst checklist.
Ratings from the QualSyst were not used as inclusion or exclusion criteria for this
review. Rather, the tool was used as a starting point to guide qualitative evaluation
and make relative comparisons across the included studies.
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For analysis, papers were divided based on which psychological wellbeing
component was investigated. Tables including extracted data from the studies were
critically reviewed and summarised to provide a clear synthesis of results.
ResultsA total of 9 papers met the inclusion criteria, most were from the USA (7 papers),
and 2 papers came from Europe. A total of 2,605 participants took part across all of
the studies with the smallest participant sample being 25, and the largest being 720.
Each of the studies’ participant samples were over 70% female, and two included
women only. When ethnicity was reported, all studies had a greater proportion of
Caucasian participants than from any other ethnic group. One study compared
Caucasian experiences with that of Latinas and one compared experiences of
“White” people and “Black” people. Two studies did not report on the ethnicities of
their participants.
Where reported, the ages of participants ranged from 19 to 95. The mean ages for
each study ranged from 39 to 74. In most of the studies carers were caring for
individuals with probable Alzheimer’s Disease and Related Disorders (ADRD) and
these carers tended to be spouses or off-spring. Three studies deviated from this
pattern as their participants were parents of children who had chronic illness,
disabilities, and autism. Further details relating to the studies are in tables 2-4.
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Table 2: Summary of participant characteristics
Authors (year) n
Females n (%)
Reason care is required
Relationship to cared for n (%)
Ethnicityn (%)
Educationn (%)
Employment status n
(%)
Level of caregiving need
Age range; mean; standard deviation
Cramm & Nieboer (2011)
123 98 (79.7) Children with a disability
Father = 25 (20.3)Mother = 90 (73.2)other family = 4 (3.3)Foster mother = 3 (2.4)Other = 1 (0.8)
- - - carers required additional support
27-49; M=38.6; -
Ficker (2011)
486 486 (100) ADRD, or cognitive impairment.
Daughter = 444 (91.4), Daughter-in-law = 27 (5.5),Granddaughters = 15 (3.1)
White non-hispanic = 44.9%, African American = 29.8%, Latino = 24.3%
M 13.1 years of education, SD 2.5
Full-time = 118 (40.8)Part-time = 25 (8.7)Homemaker = 59 (20.4)Retired = 49 (17.0)Unemployed = 37 (12.8)
4 or more hours per day, including help with at least 2 IADLs or 1 ADL
19-79; M=51.8; SD=10.09
Hatzmann et al. (2009)
543 452 (83) Chronically ill children
parent = 452 (100) - Primary education, Lower and Middle General Secondary education: 140 (26%)Middle Vocational education,Higher Secondary education, Pre-university education: 220 (41%)Higher Vocational Education, University = 175 (33%)
- out of 8 specified tasks required support with M=3.2, SD=2.5
M=42; SD=6.5
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Authors (year) n
Females n (%)
Reason care is required
Relationship to cared for n (%)
Ethnicityn (%)
Educationn (%)
Employment status n
(%)
Level of caregiving need
Age range; mean; standard deviation
Loucks-Atkinson et al. (2006)
t1=310, T2=214, T3=159
T1 – (77.1) aged 60 or over, 41% had ADRD
Spouse = (45.8); Children = 38.7)
79% Caucasian university/ college 60.3%
- At least 1 ADL or 2 IADLs.Mean number of ADLs = 10.44, SD=4.45
M=62.8; SD=14.23
Mausbach, Harmell et al. (2011)
25 24 (96) AD Spouses = 17 (68)Non-Spouses = 8 (32)
Caucasians = 21 (84%)Latina/Hispanic = 4 (16%)
- - at least 8 hours per day and at least 1 ADL or 2 IADLs.Mean hours of care per week = 56.7, SD 51.4
M=63.2; SD=11.4
Mausbach, Roepke et al. (2011)
108 77 (71.3) probable AD
Spouses = 108 (100) - University/ college graduates = 50 (46.3%), <High school = 2 (1.9%), High school equivalent = 19 (17.6), some college = 37 (34.3%)
- Total ADLs/IADLs requiring support with M=9.29, SD = 3.64
M=73.88; SD=8.02
Rizk et al. (2011)
33 33 (100) Child with autism
Mother = 33 (100) - - Employed = 21 (67.7)Unemployed = 10 (32.3)
Parent of child with additional needs
27-49; M=38.6;
Thompson et al. (2002)
257 257 (100) ADRD, or cognitive impairment.
Wife = 100 (38.9), Daughter = 157 (61.1)
Caucasians = 147Latinas = 110
White: less than HS = 6 (4%), HS Graduate = 141 (96%); Hispanic: less than High school = 48 (44%), High School graduate = 62 (56%)
Employed = 53 (36)unemployed = 94 (64%)
4 or more hours per day, including help with at least 2 IADLs or 1 ADL
Caucasian: M=61.45; SD=13.03Latina: M=51.76; SD=12.89
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Authors (year) n
Females n (%)
Reason care is required
Relationship to cared for n (%)
Ethnicityn (%)
Educationn (%)
Employment status n
(%)
Level of caregiving need
Age range; mean; standard deviation
Williams (2005)
720 Black (82) White (73)
ADRD, or cognitive impairment.
Black: Spouse = (26) Child = (55)Other relative = (16)Other = (3); White: Spouse = (61), Child = (35), Other relative = (3), Other = (1)
Black = 295 (41), White = 425 (59),
Black: >= High School = (77), <High School = (23); White: >=High School = (85), <High School = (15)
Black: Employed = (36), Homemaker = (12), unemployed = (52)White: Employed = (26), Homemaker = (21), Unemployed = (52)
4 or more hours per day, including help with at least 2 IADLs or 1
range: 23-95Black: M=58.1, SE = 0.75White: M=65, SE = 0.62
Table 3: Summary of study characteristics, quality ratings and limitations.
Authors (year)
Location Study design & sampling method
Study aims relevant to this review
Leisure measure (Reported reliability of measure)
Wellbeing measure (reported reliability of
measure)
Quality rating and key limitations
Cramm & Nieboer (2011)
Netherlands
Cross section, questionnaires
Identify which factors affect the psychological wellbeing of caregivers of children with learning disabilities
6-point rating scale for the number of times in the last 4 weeks that social activities had been hindered by caregiving tasks
HADS (Cronbach’s alpha = .86)
95%No consideration of the education level and ethnicity of participants which affects the generalisability of findings.
Ficker (2011)
USA Cross section To understand the extent to which restrictions in leisure activities mediate the
7 item scale devised by REACH to measure leisure/pleasant events
CES-D (Cronbach’s alpha = .86)PAC (Cronbach’s alpha = .88)
86% Cronbach’s alphas were not reported for all measures, there was limited consideration of
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Authors (year)
Location Study design & sampling method
Study aims relevant to this review
Leisure measure (Reported reliability of measure)
Wellbeing measure (reported reliability of
measure)
Quality rating and key limitations
relationship between work reduction and mental health in daughter caregivers.
variance, and exact p values were not reported.
Hatzmann et al. (2009)
Netherlands
Cross section To explore leisure time and holidays as mediators of health related quality of life of parents of chronically ill children.
HPW spent doing leisure activitiesNumber of holiday days in the past year
TAAQOL (not reported)MCS (not reported – reference supplied)
86%Ethnicity of participants not reported, no Cronbach’s alpha for outcome measures in this study, diagram of paths and variance not included.
Loucks-Atkinson et al. (2006)
USA Cross section andLongitudinal/ prospective cohortquestionnaires
To assess the ability of activity restriction to predict the wellbeing of carers.
ARS (Cronbach’s alpha= .89),
CES-D (Cronbach’s alpha=.91)
100%
Mausbach Harmell et al. (2011)
USA Cross section, activity diary self-report over a week and questionnaires
To explore the relationship between affect and activity in caregivers.
PES-AD (Cronbach’s alpha=.83)
PANAS (PA Cronbach’s alpha >.86, and NA Cronbach’s alpha >.84)
91%Level of education of participants not reported, not all confounding variables controlled for.
Mausbach, Roepke, et
USA Cross section To test an integrated “pleasant events” and
ARS (Cronbach’s alpha = .76),
CES-D 10 (coefficient alpha = .76)
95%Ethnicity not reported.
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Authors (year)
Location Study design & sampling method
Study aims relevant to this review
Leisure measure (Reported reliability of measure)
Wellbeing measure (reported reliability of
measure)
Quality rating and key limitations
al. (2011) “activity restriction” (PEAR) model.
PES-AD (Cronbach’s alpha = .75)
PANAS (PA Cronbach’s alpha = .88; NA Cronbach’s alpha = .82)
Rizk et al. (2011)
USA Cross section To examine the association between leisure and social participation and health related quality of life of mothers of children with ASC.
LICL (weighted kappa coefficients = .76)
MCS (reliability coefficient = 0.86)
77%Limited reliability and validity data for the main outcome measure.The methodology for calculating leisure participation may lack validity.Ethnicity and education not reported.
Thompson et al. (2006)
USA Cross section To compare the impact of pleasant activities on levels of depression across ethnicities.
OPPES-A (alphas for the subscales ranged from .60 to .82)
CES-D (not reported) 100%
Williams (2005)
USA Cross section To determine what contextual factors predict emotional health.
LTS (Cronbach’s alpha = .80)
CES-D (Cronbach’s alpha = .72)PAC (Cronbach’s alpha = .90)
95%p values/ranges for correlations were not reported.
CES-D: Centre for Epidemiologic Studies - Depression Scale; PANAS: Positive and Negative Affect Scale; PAC: Positive aspects of caregiving; MCS: Mental Component Score from the SF12; LICL: Lin Interest Checklist; OPPES-A: Older Persons Pleasant Events Scale; ARS: Activity Restriction Scale; PES-AD: Pleasant Events Schedule- Alzheimer’s Disease; HADS: Hospital Anxiety and Depression Scale; LTS: Leisure Time Satisfaction; TAAQOL: TNO-AZL Questionnaire for Adult's Health Related Quality of Life; HPW: Hours per week.
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Table 4: Summary of study results, organised by dependent variable
Authors (year)
Independent variable Dependent variable
Mediator/ moderator
Statistical test Result and effect size P value
Depression:Ficker (2011)
Frequency of leisure Frequency of leisure (low vs high)Frequency of leisure (low vs high) for people with no work disruptionFrequency of leisure (low vs high) for people whose work was disrupted by caregiving demands.
DepressionDepressionDepression
Depression
- CorrelationT-testT-test
T-test
r=-.35 t=-5.35t=5.09
t=5.35
p<.001p≤.001p<.001
p≤.001
Mausbach, Roepke et al. (2011)
Pleasant events / activity restriction Depression - ANOVA FM (SD) [95% CI]
Cohen’s d
F=10.89HPLR: 5.61 (5.65) [3.65-7.56]HPHR/LPLR: 8.07 (4.61) [6.49-9.65]LPHR: 11.58 (5.52) [9.88-13.28]LPHR vs HPLR = 1.07LPHR vs HPHR/LPLR = 0.7
-
Loucks-Atkinson
T1: Expressive activity restrictionT1: Expressive activity restrictionT1: Instrumental activity restrictionT1: Expressive activity restrictionT1: Expressive activity restriction
T1: depressionT1: depressionDepressionT2: depressionT3: depression
- CorrelationRegressionRegressionRegressionRegression
0.39β=.34, ΔR2 =.08β=.39, ΔR2 =.15β=.34, ΔR2 =.08β=.26, ΔR2 =.0.05
p<.001p=.001p=.001p=.001p=.005
Thompson (2002)
Leisure exploration
Leisure domestic
Nature
Depression
Depression
Depression
- Regression
Regression
Regression
Caucasians: r=-.326Latinas: r=-.165Z=-1.353Pooled: r=-.259Caucasians: r=.300Latinas: r=-.123z=1.464Pooled: r=-.226Caucasians: r=-.199Latinas: r=-.189Z=-.082Pooled: r=-.195
p<.01n.s.
p<.01p<.01n.s.
p<.01p<.05p<.05
p<.01
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Authors (year)
Independent variable Dependent variable
Mediator/ moderator
Statistical test Result and effect size P value
Williams (2005)
Social activities
Social activities
Social activities
Depression
Depression
Depression
Model 1 - w/o race interaction termsModel 2 - w race interaction terms
Correlation
Regression
Regression
r=-0.34
β=-.15 (SE=.12)F=17.38 (for the model)r2=.36
β=-.14 (SE=.17)F=9.76 (for the model)r2=0.36
n.s.
p<.001
p<.01
Positive and negative affect:Mausbach Harmell et al. (2011)
Leisure satisfactionLeisure satisfaction
Leisure satisfactionLeisure satisfaction
Positive affectPositive affect
Negative affectPositive affect
-Burden (moderator)-Burden (moderator)
RegressionRegression
RegressionRegression
β=.420 (SE=.041), t=10.30β=.016 (SE=.007), t=2.44
β=-.102 (SE=.025), t=-4.08β=-.008 (SE=.004), t=-2.07
p<.001p=.026
p<.001p=.047
Mausbach, Roepke et al. (2011)
Leisure restriction / Pleasant events
Leisure restriction / Pleasant events
Positive affect
Negative affect
- ANOVA FM (SD) [95 % CI]
Cohen’s d
ANOVA FM (SD) [95 % CI]
Cohen’s d
F=3.48HPLR: 33.64 (8.35) [30.88-36.41]HPHR/LPLR: 32.33 (6.47) [30.10-34.55]LPHR: 29.05 (7.59) [26.65-31.46]LPHR vs HPLR=-0.58LPHR vs HPHR/LPLR=-0.47F=10.12HPLR: 15.18 (4.58) [13.21-17.14]HPHR/LPLR: 16.98 (4.37) [15.39-18.56]LPHR: 20.81 (6.50) [19.10-22.52]LPHR vs HPLR=0.99LPHR vs HPHR/LPLR=0.72
-
-
General WellbeingCramm (2011) Activity restriction General wellbeing Correlation r=0.286 p=.002
Hatzmann et al. (2009)
Leisure time/weekHolidays
General wellbeingGeneral wellbeing
RegressionRegression
β=.07β=.21
p>.05p<.05
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Authors (year)
Independent variable Dependent variable
Mediator/ moderator
Statistical test Result and effect size P value
Rizk et al. (2011)
Overall activity participationsports/physical activities/ naturehobbiescraftsgamessociocultural/entertainmentcommunity/education
General wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeingGeneral wellbeing
- CorrelationCorrelationCorrelationCorrelationCorrelationCorrelationCorrelation
r=-.066r=-.060r=.032r=-.226r=.294r=-.130r=.251
p=.714p=.758p=.858p=.458p=.184p=.485p=.189
Positive feelings towards caregiving:Ficker (2011)
LeisureLeisure (Low vs High)Frequency of leisure (low vs high) for people with no work disruptionFrequency of leisure (low vs high) for people whose work was disrupted by caregiving demands.
Positive affectPositive affectPositive affect
Positive affect
- CorrelationT-testT-test
T-test
r=0.17t=-2.01t=-1.75
t=-2.01
p<.001p<0.05*n.s.
p<.05
Williams (2005)
Social activities Positive affect - Correlation r=.22 -
*to control for type 1 errors, this was not considered to reach statistical significance.
Note:HPLR=high pleasant events and low activity restriction; HPHR/LPLR=high pleasant events and high restriction or low pleasant events and low restriction; LPHR=low pleasant events and high restriction; w/o=without; w=with.
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To aid synthesis of the findings, the results are presented according to the type of
psychological wellbeing measure that was used as the dependent variable. The
wellbeing measures fell into four categories (some papers included more than one of
these measures): Five measured depression, two measured positive and negative
affect, three measured general wellbeing, and two measured feelings towards
caregiving. Measures used are summarised in Table 5.
Table 5: Summary of leisure and wellbeing questionnaires
Name Items Response scaleLeisure measures:Activity Restriction Scale (ARS)
How restricted people felt in the last month in each of nine listed activities such as “having quiet time to yourself”, “going out for meals”, “doing fun things with other people”, and “taking part in hobbies”.
5 response options from “Never or seldom did this” to “greatly restricted”
REACH scale to measure leisure/pleasant events
Frequency of participation in 7 pleasant activities e.g. “going out for meals”
3 response options from “not at all” to “a lot”.
Cramm’s Activity Restriction Scale
1 item:“How many times during the past 4 weeks did the caregiving task for your child hinder your social activities, such as visiting friends or family?”
6 response options from “all of the time” to “never”.
Lin Interest Checklist (LICL)
123 activities (e.g. boxing, ceramics, reading) from 6 categories: sports/physical activities/nature, crafts, hobbies, games, sociocultural/entertainment, community/education.Participants could add their own items.Each item rated for level of interest, frequency of engagement, and history.
Interest: 3 response options from “like a little” to “like very much”.Frequency: 3 response options from “occasionally” to “frequently”.History: 3 response options: “past”, “present”, “future” (in the coming month).
Leisure Time Satisfaction (LTS)
Satisfaction with amount of time spent on 6 specified leisure activities over the last month.
3 response options from “not at all” to “a lot”.
Older Persons Pleasant Events Scale (OPPES-A)
Frequency and perceived pleasure from each activity (whether or not they had done the activity) over the past month.Divided into 7 subscales: social recognition, nature, social intimacy, leisure domestic, reflection, spirituality, leisure exploration.Examples of leisure exploration: “getting out of the city” and “planning
Frequency: 3 response options from “not at all (this has not happened in the past 30 days)” to “often (seven or more times)”.Pleasure: 3 response options from “somewhat pleasant” to “very pleasant”.
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Name Items Response scaletrips or vacations”.Examples of leisure domestic: “baking because I feel creative” and “creative crafts”.Examples of nature: “listening to the sounds of nature” and “seeing beautiful scenery”.
Pleasant Events Schedule- Alzheimer’s Disease (PES-AD)
Over the last 4 hours.Rating frequency of engaging in each of 20 common leisure activities e.g. “listening to music”.
3 response options from “not at all” to “2 or more times”.
Wellbeing measures:Centre for Epidemiological Studies Depression (CES-D & CESD-10)
CES-D – experience over the last week of 20 items relating to symptoms of depression.CESD-10 – 10 items from the original scale.
4 response options from “rarely or none of the time (<1 day)” to “most or almost all the time (5-7 days)”.
Positive and Negative Affect Scale (PANAS)
Ratings based on either “the present moment” or “over the past week”.10 single word items relating to energy levels, excitement and enthusiasm to reflect positive affect (e.g. “interested”, “strong”, “excited”.And 10 single word items relating to distress to reflect negative affect e.g. “distressed”, “upset”, “guilty”.
5 response options from “very slightly or not at all” to “Extremely”.
Hospital Anxiety and Depression Scale (HADS)
Experience over the last week. Frequency of 7 items relating to symptoms of depression and 7 items relating to symptoms of anxiety.
4 different response options relating to frequency of experience depending on each question e.g. from “not at all” to “most of the time”.
Mental Component Score (MCS) from the Short Form 12 (SF12)
Over the last 4 weeks.6 items relating to mental wellbeing such as energy levels, feeling peaceful, and feeling “down-hearted”.
Response options vary from binary “yes”/”no” to a 6 point scale from “all of the time” to “none of the time”.
Mental Component Score (MCS) of TNO-AZL Questionnaire for Adult's Health Related Quality of Life (TAAQoL)
Items have two parts: prevalence of problem, emotional impact of problem.The scales vitality, positive emotions, and aggressiveness pertain to experiences over the last month.
4 response options.
Positive Aspects of Caregiving (PAC)
11 items relating to positive impact of caregiving on emotional wellbeing e.g. “providing help to [care recipient] has made me feel good about myself”.
5 response options from “agree” to “disagree”.
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Depression
Of the five papers which used depression as an outcome variable, all were cross-
sectional studies using correlational analysis, and one (Loucks-Atkinson, Kleiber, &
Williamson, 2006) included a longitudinal component (Ficker, 2011; Loucks-
Atkinson, Kleiber, & Williamson, 2006; Mausbach, Roepke, et al., 2011; Thompson,
Solano, & Kinoshita, 2002; Williams, 2005). Three of the papers used baseline
measures from the same national intervention study in the USA, although improved
homogeneity for their analysis by selecting subsamples, e.g. by gender and location.
Two of the studies only used female participants (Ficker, 2011; Thompson et al.,
2002), and two of the studies made comparisons across ethnicities (Thompson et al.,
2002; Williams, 2005). All of the studies pertained to caregivers of individuals with
ADRD.
The results of the formal quality assessment showed that the studies were of a similar
quality. Three of them achieved the highest rating of one, and two achieved a rating
of 0.95 because the level of detail in reporting results was not quite as good, with
categorised rather than exact p values provided.
The five articles tended to report thoroughly on the demographic characteristics of
the participants and needs of the individual in receipt of care. This is important in
understanding the extent to which findings can be generalised outside of the study.
Given that the majority of participants were female and had at least some experience
of college and university, results are most likely to be generalisable to individuals
with these characteristics. The studies were also able to use this information to
control for potentially confounding variables during the analysis process.
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One study found significant differences in demographic factors between different
Latinas and Caucasians (Thompson et al., 2002) which suggests that for those studies
whose participant pool were predominantly Caucasian, caution should be taken when
attempting to apply findings to other ethnicities. It is also important to consider that
despite these demographic differences, Thompson and colleagues did not find
between group differences in their overall outcomes.
They used an abbreviated version of the Older Persons Pleasant Events Schedule
(OPPES-ABV). Of particular relevance to this review, were the three subscales
“leisure exploration”, “leisure domestic” and “nature”. Participants rated both
frequency of activity and level of enjoyment. They found significant correlations
between depression and both leisure exploration, domestic leisure, and nature
activities in the expected directions.
Loucks-Atkinson (2006) measured leisure as a predictor using the ARS. Participants
rated whether they felt their caregiving role impacted on their ability to engage in 9
activities such as “sports and recreation”. These were conceptualised as being in the
category of “expressive activities”, which are intrinsically motivated. In contrast to
this, Ficker (2011) used a 7 item REACH scale which asked people to rate their
frequency of engagement with pleasant events.
These two studies assessed the relationship between reduction or restriction in leisure
activities and depression using a cross section design although one of them also had a
longitudinal component (Loucks-Atkinson et al., 2006). Both studies found
significant correlations between activity restriction and depression (p<.001),
indicating that increased restriction was associated with increased depression scores.
Loucks-Atkinson also found that restriction in leisure activities at time one
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significantly correlated with increased depression scores one and two years later
(p<.005).
Ficker also explored whether this relationship existed for individuals who had
experienced work disruption (i.e. reduction or cessation of employment hours)
because of caregiving, and those who had maintained their employment. They found
that there was a significant relationship between restriction in leisure activities and
depression for both groups, which were examined separately and not compared.
Another study by Williams (2005) used a 6-item Leisure Time Satisfaction scale
(LTS). The correlation coefficient for the relationship between leisure satisfaction
and depression was r=-.34 and the p value or range was not reported. The primary
aims of this paper included a comparison between Black and White caregivers. They
devised a model to explore a range of factors to learn whether they were different
between the two groups, and whether they were associated with low mood. They
used two models: the first did not include race interaction terms and the second did.
Model 1 found satisfaction with social activities to be a predictor of depression
(β=-.15, p<.001) with higher satisfaction being associated with lower levels of
depression. This relationship was unaffected by the addition of race interaction
terms.
The final study divided participants into three groups depending on their reported
levels of pleasant events and activity restriction (Mausbach, Roepke, et al., 2011).
The groups were: high pleasant events and low activity restriction (HPLR), high
pleasant events and high activity restriction or low pleasant events and low activity
restriction (HPHR/LPLR), and low pleasant events and high restriction (LPHR).
Engagement with pleasant events was measured through the Pleasant Events
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Schedule – Alzheimer’s Disease (PES-AD) which lists 20 activities and asks people
to rate how much they have engaged in that activity over the last month on a three-
point scale. Activity restriction was measured using the ARS. They found a
significant main effect of group on depression. Individuals with more pleasant events
and less restriction had lower depression scores than individuals with low pleasant
events and high activity restriction.
Participants were asked to rate their activities over the last month and therefore some
bias could have been introduced through inaccurate memory and reporting.
Additionally, their measure for pleasant events was a modified version of a validated
measure. However, this study reported Cronbach’s alpha values for its measures
which indicated they had good internal reliability.
Positive and Negative Affect
Two studies explored the impact of leisure using the Positive and Negative Affect
scale (PANAS; Mausbach, Roepke, et al., 2011; Mausbach, Harmell, Moore, &
Chattillion, 2011). There was some variability in methodology between these studies,
where one administered retrospective questionnaires at one time point (Mausbach,
Roepke, et al., 2011), and the other used live recording over several time points in a
week (Mausbach, Harmell, et al., 2011).
Both of the studies were of a similar quality and suffered from the limitation that
they did not record as much information about participant characteristics as some of
the other papers included in this review. One paper also did not control for all
confounding variables (Mausbach, Harmell, et al., 2011). In general, it was found
that the papers were clear in their aims and methodologies, had conclusions that
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followed from the results, used validated measures, and Cronbach’s alphas were
reported.
One study asked people to complete an activity diary and questionnaires at regular
times throughout the day for a week (Mausbach, Harmell, et al., 2011). The
questionnaires included the PANAS which lists 20 mood adjectives, half of which
are associated with positive affect (e.g. interested, excited), and half with negative
affect (e.g. distressed, scared). Participants rated the degree to which they felt that
way over the last 4 hours. They also completed measures of leisure satisfaction
where 20 common activities were listed (e.g. listening to music, exercising) and
participants rated the number of times they had engaged with each activity over the
last 4 hours, and the level of enjoyment they got from each one. They found that
individuals with greater leisure satisfaction over the week had higher levels of
positive affect. They also noted a negative relationship between leisure satisfaction
and negative affect. These relationships were moderated by burden. When burden
was low, negative affect was not associated with leisure satisfaction, however when
burden was high there was a significant association. The relationship between
positive affect and leisure satisfaction was also stronger when burden was high.
The previously mentioned study which divided participants into three groups (HPLR,
HPHR/LPLR, and LPHR) also measured positive and negative affect (Mausbach,
Roepke, et al., 2011). They found that people with more pleasant events and less
restriction experienced more positive affect and less negative affect. The reverse was
true for individuals with low pleasant events and high restriction.
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General Wellbeing
Three studies explored general “mental” wellbeing using cross sectional
questionnaires in order to test out hypothesised models (Cramm & Nieboer, 2011;
Hatzmann, Maurice-Stam, Heymans, & Grootenhuis, 2009; Rizk et al., 2011).
Outcome measures used in these studies included the Health Related Quality of Life
(HRQoL) and the Hospital Anxiety and Depression Scale (HADS). These studies
included participants other than carers of people with probable ADRD: one included
parents of children with a disability (Cramm & Nieboer, 2011), one focused on
carers of children with Autism Spectrum Conditions (ASC; Rizk et al., 2011), and
the other included parents of chronically ill children (Hatzmann et al., 2009). One of
these studies was carried out in the USA and the other two in the Netherlands.
In general, these three studies did not provide as much information about the sample
characteristics as some of the other studies in this review. Additional details about
the sample characteristics may help others to contextualise their findings, however
this does not affect the validity of their statistical outcomes. Hatzmann et al (2009)
could have provided a more detailed presentation of their model as this would have
allowed for improved interpretation of results. Additionally, there were some
methodological issues with one paper (Rizk et al., 2011) which may have impacted
on their findings. These are discussed in more detail below.
Hatzmann et al. (2009) used a model in which leisure was hypothesised to be a
mediator between background variables (demographic and disease related factors)
and wellbeing. Leisure was measured by self-report of number of hours spent in
leisure per week, and holiday was measured through number of days the family spent
on holiday over the last year. General wellbeing was measured through the MCS
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component of the TNO-AZL Questionnaire for Adult's Health Related Quality of
life' (TAAQOL).
Structural Equation Modelling (SEM) was used to refine the originally suggested
model based on the findings from the dataset. They found that holidays and
emotional support both played mediating roles such that parents who had more days
on holiday had better wellbeing. No effect of leisure was found (r=.07, p value not
provided). Inclusion of a diagram of the model with variance values and error
measurements would have been helpful in further understanding this mediation.
Another study was from the USA and had a participant sample comprised of mothers
of children with ASC (Rizk et al., 2011). They measured leisure using the Lin
Interest Checklist (LICL) which categorises 123 activities into six areas:
Sports/Physical Activities/Nature, Crafts, Hobbies, Games,
Sociocultural/Entertainment, and Community/Education. Individuals rated their level
of interest, and frequency and history of participation. They were given the
opportunity to add activities onto the list if they were not already mentioned. The
authors cited an unpublished thesis for the LICL and did not report exact reliability
and validity measures. Unfortunately, due to the thesis being unpublished, it was not
possible to access details relating to the reliability and validity of this measure and
this poses a challenge when interpreting findings from this measure. Wellbeing was
measured through the mental component summary (MCS) of the SF-12.
Rizk and colleagues divided the number of activities of interest in which mothers
participated frequently with the total number of activities of interest. They suggest
that higher scores indicated greater participation. They used The Pearson Product
Moment Correlation to explore the 6 areas of leisure and their relationship to MCS,
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and found no significant associations. The relationships between MCS and leisure
categories of Games (r=.294, p=.184) and Community/Education (r=.251, p=.189)
came the closest to achieving significance. They also combined all subscales to
achieve an “overall activity participation” score which also did not have a significant
relationship with MCS (r=-.066, p=.714).
The validity of their participation calculation was not made clear within the paper as
there was no clear justification as to why they calculated it in this manner.
Theoretically, two individuals engaging in the same number of activities and for the
same amount of time could achieve different participation scores if one of them had a
greater variety of interests which they were not currently participating in. Therefore,
it is questionable to what extent their participation measure was reflective of actual
level of engagement with leisure activities. This could account for the null findings.
Further information about power calculations could also help in assessing whether a
small sample size could have contributed to the null findings.
In the Netherlands, Cramm and Nieboer (2011) ascertained restriction in leisure
activities by asking their participants “how many times during the past 4 weeks did
the caregiving task for your child hinder your social activities, such as visiting
friends or family?”. They responded on a 6-point scale from “all the time” to
“never”. They used the HADS to measure psychological wellbeing. They found a
significant positive correlation between restriction in social activities and
psychological wellbeing (r=0.286, p=0.002). This shows that increased restriction is
associated with reduced wellbeing. They also evidenced that this relationship was
mediated through parental stress.
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Positive feelings relating to caregiving
Two studies (Ficker, 2011; Williams, 2005) conceptualised their outcomes as
positive affect, and their measurement tool for this was the Positive Aspects of
Caregiving questionnaire (PAC). This has been considered in a separate section from
“positive affect” in this literature review as it was considered to be focused on a
specific area whereas the other studies measured general affect. During the quality
assessment, Ficker’s study had the limitations that Cronbach’s alpha was not
reported for all measures, there was limited consideration of variance, and exact p
values were not reported. However, this is more likely to affect nuanced
interpretations of their results than it is to have affected the main substance of their
findings.
This study used data from REACH and aimed to understand the impact of finances
and work disruption on leisure, and the overall impact this had on feelings about
being a carer. Questionnaires were completed at one time point and this included the
PAC and the 7 questions about leisure restriction as discussed previously. Findings
were that there was a trend (which did not reach statistical significance) for
caregivers with fewer leisure activities to experience less positive feelings about
being a carer.
The other study by Williams (2005), discussed previously, correlated social activities
with PAC and found an association between the two (r=.22). Unfortunately, the p
values or ranges were not provided in this paper and this raises a challenge for
readers attempting to understand the statistical significance of this finding.
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DiscussionStudies that explored the relationship between depression and leisure had findings
that were consistent with the idea that lower levels of engagement and satisfaction
with leisure activities are associated with depression in caregivers who provide a
moderate to high level of care. This is consistent with findings from other studies
exploring this issue with non-caregiving participant groups (Katz & Yelin, 2001;
Paffenbarger, Lee, & Leung, 1994). Further, two studies (Thompson et al., 2002;
Williams, 2005) found that this relationship was not affected by race, and another
(Ficker, 2011) found that the relationship was observable for those whose working
hours had been affected and those whose working hours had not been affected.
However, due to the nature of these studies being largely cross-sectional it is not
possible to infer causality. Only one study looked at the association longitudinally
which might suggest more work needs to be done using longitudinal designs,
however it does support the possibility that the data represents a causal relationship.
The studies exploring positive and negative affect (Mausbach, Roepke, et al., 2011;
Mausbach, Harmell, et al., 2011), taken together, were of comparable quality and
showed similar patterns of results. They indicate that frequency of leisure
experiences is associated with increased positive affect and that satisfaction with
leisure is also related to positive affect. The use of live recording in one of the studies
reduces bias introduced by methods that rely on accurate recall of past events, and
therefore the mixture of methodologies is helpful in understanding how reliable the
findings are. However, as there are only two studies in this category it would be
helpful for additional studies to support these findings. It would be helpful if
experimental or longitudinal studies could be designed to attempt to establish
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causality. For example, a comparison could be made before and after becoming a
caregiver.
In the category of general wellbeing, the collection of studies reported mixed
findings. Cramm (2011) found that a restriction of leisure activities was associated
with reduced anxiety and depression. Hatzmann (2009) found that individuals who
had more holiday days tended to have better general wellbeing (mental component
score). However, Hatzmann did not find a relationship between the number of hours
of leisure and wellbeing. In keeping with previous studies with non-caregivers, this
might suggest that hours of leisure may be less useful than, for example, satisfaction
with leisure time in understanding the relationship between leisure and wellbeing
(Kuykendall, Tay, & Ng, 2015). Kuykendall, Tay and Ng suggested that leisure is
effective at improving wellbeing through meeting a variety of needs. In this theory,
leisure is more likely to be beneficial if one is spending 20 hours a week on a variety
of leisure activities (therefore meeting a variety of needs), than if an individual is
spending 20 hours on the same leisure activity (therefore only meeting a limited
number of needs). Findings from their meta-analysis supported this theory as time
was found to be less associated with subjective wellbeing than other leisure
measures.
Rizk (2011) did not find a relationship between leisure participation and wellbeing.
This could be due to methodological issues in relation to the calculation of “leisure
participation”. The limited explanation about the validity of their rationale for the
calculation makes it a challenge for readers to understand, given the lack of face
validity.
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The final two studies in this review noted a pattern in the expected direction when
comparing leisure engagement with feelings about caregiving but the results were not
statistically significant in one, and the statistical significance of the other was not
reported. A limitation of this review is that there were only two papers investigating
the impact of leisure on feelings about caregiving. Given literature that caregiving
can be rewarding, and that this can occur through having fun with the cared for
individual, it may be pertinent for research to explore this further (Nolan, 2001). In
fact, none of the literature considered in this review assessed whether leisure
activities were being completed with the individual for whom they provide support.
There is some evidence that joint leisure activities may support carer wellbeing
(Searson, Hendry, Ramachandran, Burns, & Purandare, 2008), and therefore the field
may benefit from researching this further.
In general, most of the papers in this review included caregivers of individuals with
ADRD, with the exception of three which used general wellbeing measures and
focused on parents of children with chronic illness and disabilities (Cramm &
Nieboer, 2011; Hatzmann et al, 2009, Rizk et al 2011). Some research indicates there
are qualitative differences in the caregiving experience depending on the difficulties
experienced by the cared for (Ory et al., 1999). Therefore, findings from this review
are most likely to be generalisable to the groups of individuals included in this
review. Further research would be helpful in determining if the findings are
applicable to other types of carers.
ConclusionThese studies investigated a wide range of aspects of the leisure experience such as
number of hours, satisfaction, frequency, and restriction. Based on these findings it is
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possible that each of these components plays its own role in the relationship of
leisure and wellbeing, though this may be less the case for number of hours spent in
leisure. In order to better understand these findings, it would be helpful for additional
studies to compare the impact of leisure participation, leisure satisfaction, and
number of hours of leisure. More robust studies are required in this area including a
range of methodologies and with clear reporting of variance, effect sizes, and
statistical power. It is also important for studies to use published validated measures.
Research into carers who spend a significant amount of time in their caregiving role
and the relationship between leisure and wellbeing is less well developed than the
research within the non-caregiving population. Perhaps one of the most
comprehensive examples of this is a meta-analysis by Kuykendall, Tay and Ng
(2015) who reviewed 69 studies, and concluded that leisure engagement and
subjective wellbeing in non-caregivers are moderately associated with leisure
satisfaction. They also found a mediation effect of leisure satisfaction on the
relationship between leisure engagement and subjective wellbeing. Other mediators
and moderators of the relationships between leisure engagement and wellbeing have
begun to be explored within the wider caregiving literature including two of the
papers in this review (Bedini et al., 2011; Bookwala & Schulz, 2000; Cramm &
Nieboer, 2011; Thompson et al., 2002). For example, Thompson et al used path
analysis and found that work disruption affected financial strain, which affected
leisure, which in turn affected depression (accounting for 12.3% of the variance in
depression).
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Therefore, another limitation of this review is that the broader complexities of these
relationships have not been clarified and further research (in particular, with those
who spend a significant amount of their time caregiving) would be beneficial.
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ReferencesAusserhofer, D., Mantovan, F., Pirhofer, R., Huber, M., & Them, C. (2009). [The
burden of parents caring for their children and adolescents with severe disabilities in South Tyrol]. Pflege, 22(3), 184–192. https://doi.org/10.1024/1012-5302.22.3.184
Azman, A., Jamir Singh, P. S., & Sulaiman, J. (2017). Caregiver coping with the mentally ill: a qualitative study. Journal of Mental Health, 26(2), 98–103. https://doi.org/10.3109/09638237.2015.1124395
Bedini, L., Gladwell, N., & Dudley, W. (2011). Mediation analysis of leisure, perceived stress, and quality of life in informal caregivers. Journal of Leisure, 43(2), 153–175. https://doi.org/10.1080/00222216.2011.11950231
Bookwala, J., & Schulz, R. (2000). A comparison of primary stressors, secondary stressors, and depressive symptoms between elderly caregiving husbands and wives: The caregiver health effects study. Psychology and Aging, 15(4), 607–616. https://doi.org/10.1037/0882-7974.15.4.607
Carers UK. (2015). Facts about carers 2015. Retrieved from https://www.carersuk.org/for-professionals/policy/policy-library/facts-about-carers-2015
Chakrabarti, S., Raj, L., Kulhara, P., Avasthi, A., & Verma, S. K. (1995). Comparison of the extent and pattern of family burden in affective disorders and schizophrenia. Indian Journal of Psychiatry, 37(3), 105–112. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21743729
Chattillion, E. A., Mausbach, B. T., Roepke, S. K., von Känel, R., Mills, P. J., Dimsdale, J. E., … Grant, I. (2012). Leisure activities, caregiving demands and catecholamine levels in dementia caregivers. Psychology & Health, 27(10), 1134–1149. https://doi.org/10.1080/08870446.2011.637559
Chien, W.-T., & Norman, I. (2009). The effectiveness and active ingredients of mutual support groups for family caregivers of people with psychotic disorders: A literature review. International Journal of Nursing Studies, 46(12), 1604–1623. https://doi.org/10.1016/J.IJNURSTU.2009.04.003
Chien, W. T., Chan, S., Morrissey, J., & Thompson, D. (2005). Effectiveness of a mutual support group for families of patients with schizophrenia. Journal of Advanced Nursing, 51(6), 595–608. https://doi.org/10.1111/j.1365-2648.2005.03545.x
Connell, C. M., & Janevic, M. R. (2009). Effects of a Telephone-Based Exercise Intervention for Dementia Caregiving Wives. Journal of Applied Gerontology, 28(2), 171–194. https://doi.org/10.1177/0733464808326951
Page 176 of 197
Cooper, C., Balamurali, T. B. S., Selwood, A., & Livingston, G. (2007). A systematic review of intervention studies about anxiety in caregivers of people with dementia. International Journal of Geriatric Psychiatry, 22(3), 181–188. https://doi.org/10.1002/gps.1656
Cramm, J. M., & Nieboer, A. P. (2011). Psychological well-being of caregivers of children with intellectual disabilities: Using parental stress as a mediating factor. Journal of Intellectual Disabilities, 15(2), 101–113. https://doi.org/10.1177/1744629511410922
Del-Pino-Casado, R., & Ordóñez-Urbano, C. (2016). Effects of satisfaction with leisure time in family carers of elderly dependents. Atencion Primaria / Sociedad Española De Medicina De Familia Y Comunitaria, 48(5), 295–300. https://doi.org/10.1016/j.aprim.2015.06.005
Eric Hwang, J.-L., Rivas, J. G., Fremming, R., Rivas, M. M., & Crane, K. R. (2009). Relationship Between Perceived Burden of Caring for a Family Member with Alzheimer’s Disease and Decreased Participation in Meaningful Activities. Occupational Therapy In Health Care, 23(4), 249–266. https://doi.org/10.3109/07380570903214788
Ficker, L. J. (2011). The role of employment status, work disruption, leisure, and resources in the mental health of dementia caregiving daughters. Dissertation Abstracts International: Section B: The Sciences and Engineering. Retrieved from http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3433474%5Cnhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=psyc7&NEWS=N&AN=2011-99160-365
Flores, P. M., Berbis, J., Chinot, O., & Auquier, P. (2014). Assessing the quality of life among caregivers of patients with gliomas. Neuro-Oncology Practice, 1(4), 191–197. https://doi.org/10.1093/nop/npu027
Folkman, S. (1997). Positive psychological states and coping with severe stress. Social Science & Medicine, 45(8), 1207–1221. https://doi.org/10.1016/S0277-9536(97)00040-3
Gahagan, J., Loppie, C., Rehman, L., Maclellan, M., & Side, K. (2007). “Far as I Get Is the Clothesline”: The Impact of Leisure on Women’s Health and Unpaid Caregiving Experiences in Nova Scotia, Canada. Health Care for Women International, 28(1), 47–68. https://doi.org/10.1080/07399330601003408
Gautam, S., & Nijhawan, M. (1984). Burden on families of schizophernic and chronic lung disease patients. Indian Journal of Psychiatry, 26(2), 156–9. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21965975
Greenwood, N., Habibi, R., Smith, R., & Manthorpe, J. (2015). Barriers to access and minority ethnic carers’ satisfaction with social care services in the community: a systematic review of qualitative and quantitative literature.
Page 177 of 197
Health & Social Care in the Community, 23(1), 64–78. https://doi.org/10.1111/hsc.12116
Greenwood, N., & Smith, R. (2015). Barriers and facilitators for male carers in accessing formal and informal support: A systematic review. Maturitas, 82(2), 162–169. https://doi.org/10.1016/j.maturitas.2015.07.013
Haley, W. E., LaMonde, L. A., Han, B., Burton, A. M., & Schonwetter, R. (2004). Predictors of Depression and Life Satisfaction Among Spousal Caregivers in Hospice: Application of a Stress Process Model. Journal of Palliative Medicine, 6(2), 215–224. https://doi.org/10.1089/109662103764978461
Haley, W. E., Roth, D. L., Hovater, M., & Clay, O. J. (2015). Long-term impact of stroke on family caregiver well-being: a population-based case-control study. Neurology, 84(13), 1323–9. https://doi.org/10.1212/WNL.0000000000001418
Hatzmann, J., Maurice-Stam, H., Heymans, H. S. A., & Grootenhuis, M. A. (2009). A predictive model of Health Related Quality of life of parents of chronically ill children: the importance of care-dependency of their child and their support system. Health and Quality of Life Outcomes, 7(72). https://doi.org/10.1186/1477-7525-3-34
Hughes, N., Locock, L., & Ziebland, S. (2013). Personal identity and the role of “carer” among relatives and friends of people with multiple sclerosis. Social Science & Medicine, 96, 78–85. https://doi.org/10.1016/j.socscimed.2013.07.023
Infurna, F. J., Gerstorf, D., & Zarit, S. H. (2012). Substantial Changes in Mastery Perceptions of Dementia Caregivers With the Placement of a Care Recipient. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 68(2), 202–214. https://doi.org/10.1093/geronb/gbs063
Katz, P. P., & Yelin, E. H. (2001). Activity loss and the onset of depressive symptoms: Do some activities matter more than others? Arthritis & Rheumatology, 44(5), 1194–1202. https://doi.org/10.1002/1529-0131(200105)44:5<1194::AID-ANR203>3.0.CO;2-6
Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A., & Jaffe, M. W. (1963). Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. Jama, 185(12), 914–919. https://doi.org/10.1001/jama.1963.03060120024016
Kmet, L. M., Lee, R. C., & Cook, L. S. (2004). Standard quality assessment criteria for evaluating primary research papers from a variety of fields. Alberta Heritage Foundation for Medical Research Edmonton. Retrieved from https://www.ihe.ca/publications/standard-quality-assessment-criteria-for-evaluating-primary-research-papers-from-a-variety-of-fields
Kuo, S. C., Sun, J. L., & Tang, S. T. (2017). Trajectories of depressive symptoms for bereaved family members of chronically ill patients: a systematic review. Journal of Clinical Nursing. https://doi.org/10.1111/jocn.13720
Page 178 of 197
Kuykendall, L., Tay, L., & Ng, V. (2015). Leisure engagement and subjective well-being: A meta-analysis. Psychological Bulletin, 141(2), 364–403. https://doi.org/10.1037/a0038508
Lawton, M. P., & Brody, E. M. (1970). Assessment of older people: self-maintaining and instrumental activities of daily living. Nursing Research, 19(3), 179-186. Retrieved from http://www.eurohex.eu/bibliography/pdf/Lawton_Gerontol_1969-1502121986/Lawton_Gerontol_1969.pdf
Lee, Y., & Bhargava, V. (2004). Leisure time: Do married and single individuals spend it differently? Family and Consumer Sciences.32(3), 254-274. https://doi.org/10.1177/1077727X03261631
Levine, C., Reinhard, S., Feinberg, L. F., Albert, S., & Hart, A. (2003). Family caregivers on the job: Moving beyond ADLs and IADLs. Generations, 27(4), 17–23. Retrieved from http://web.b.ebscohost.com/ehost/detail/detail?vid=2&sid=f971ede8-b347-43f5-87ff-fa3fe2b93bf7%40sessionmgr120&bdata=JkF1dGhUeXBlPWlwLHNoaWImc2l0ZT1laG9zdC1saXZl#AN=106758911&db=c8h
Lloyd, K. M., & Auld, C. J. (2002). The role of leisure in determining quality of life: Issues of content and measurement. Social Indicators Research, 57(1), 43–71. https://doi.org/10.1023/A:1013879518210
López, J., López-Arrieta, J., & Crespo, M. (2005). Factors associated with the positive impact of caring for elderly and dependent relatives. Archives of Gerontology and Geriatrics, 41(1), 81–94. https://doi.org/10.1016/j.archger.2004.12.001
Loucks-Atkinson, A., Kleiber, D. a., & Williamson, G. M. (2006). Activity restriction and well‐being in middle‐aged and older caregivers. Topics in Geriatric Rehabilitation, 22(4), 269–282.
Magliano, L., Fiorillo, A., Rosa, C., & Maj, M. (2006). Family burden and social network in schizophrenia vs. physical diseases: preliminary results from an Italian national study. Acta Psychiatrica Scandinavica, 113(s429), 60–63. https://doi.org/10.1111/j.1600-0447.2005.00719.x
Magliano, L., Marasco, C., Fiorillo, A., Malangone, C., Guarneri, M., & Maj, M. (2002). The impact of professional and social network support on the burden of families of patients with schizophrenia in Italy. Acta Psychiatrica Scandinavica, 106(4), 291–298. https://doi.org/10.1034/j.1600-0447.2002.02223.x
Martin, S. C. (2015). Psychosocial Challenges Experienced by Partners of People With Parkinson Disease. Journal of Neuroscience Nursing, 47(4), 211–222. https://doi.org/10.1097/JNN.0000000000000141
Mausbach, B. T., Coon, D. W., Patterson, T. L., & Grant, I. (2008). Engagement in Activities Is Associated With Affective Arousal in Alzheimer’s Caregivers: A
Page 179 of 197
Preliminary Examination of the Temporal Relations Between Activity and Affect. Behavior Therapy, 39(4), 366–374. https://doi.org/10.1016/J.BETH.2007.10.002
Mausbach, B. T., Harmell, A. L., Moore, R. C., & Chattillion, E. A. (2011). Influence of caregiver burden on the association between daily fluctuations in pleasant activities and mood: A daily diary analysis. Behaviour Research and Therapy, 49(1), 74–79. https://doi.org/10.1016/j.brat.2010.11.004
Mausbach, B. T., Roepke, S. S. K., Depp, C. A. C., Moore, R., Patterson, T. L., & Grant, I. (2011). Integration of the Pleasant Events and Activity Restriction Models: Development and Validation of a “PEAR” Model of Negative Outcomes in Alzheimer’s Caregivers. Behavior Therapy, 42(1), 78–88. https://doi.org/10.1016/j.beth.2009.11.006
Meltzer, L. J., & Rodrigue, J. R. (2001). Psychological Distress in Caregivers of Liver and Lung Transplant Candidates. Journal of Clinical Psychology in Medical Settings, 8(3), 173–180. https://doi.org/10.1023/A:1011317603415
Molyneaux, V., Butchard, S., Simpson, J., & Murray, C. (2011). Reconsidering the term “carer”: a critique of the universal adoption of the term “carer.” Ageing & Society, 31(3), 422–437. https://doi.org/10.1017/S0144686X10001066
Neulinger, J. (1981). The Psychology of Leisure (2nd ed.). Springfield, Ill.: C. C. Thomas.
NICE. (2012). Quality appraisal checklist - quantitative intervention studies. In Methods for the development of NICE public health guidance (3rd ed.). National Institute for Health and Care Excellence. Retrieved from https://www.nice.org.uk/process/pmg4/chapter/appendix-f-quality-appraisal-checklist-quantitative-intervention-studies
Nolan, M. (2001). Positive aspects of Caring. In S. Payne & C. Ellis-Hill (Eds.), Chronic and terminal illness: New perspectives on caring and carers (pp. 22–43). Oxford: Oxford University Press.
Ory, M. G., Hoffman, R. R., Yee, J. L., Tennstedt, S., & Schulz, R. (1999). Prevalence and Impact of Caregiving: A Detailed Comparison Between Dementia and Nondementia Caregivers. The Gerontologist, 39(2), 177–186. https://doi.org/10.1093/geront/39.2.177
Oshio, T., & Kan, M. (2016). How do social activities mitigate informal caregivers’ psychological distress? Evidence from a nine-year panel survey in Japan. Health and Quality of Life Outcomes, 14(117). https://doi.org/10.1186/s12955-016-0521-8
Paffenbarger, R. S., Lee, I. ‐M., & Leung, R. (1994). Physical activity and personal characteristics associated with depression and suicide in American college men. Acta Psychiatrica Scandinavica, 89(s377), 16–22. https://doi.org/10.1111/J.1600-0447.1994.TB05796.X
Page 180 of 197
Pearlin, L. I. (2009). The Life Course and the Stress Process: Some Conceptual Comparisons. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 65B(2), 207–215. https://doi.org/10.1093/geronb/gbp106
Pearlin, L. I., Mullan, J. T., Semple, S. J., & Skaff, M. M. (1990). Caregiving and the Stress Process: An Overview of Concepts and Their Measures. The Gerontologist, 30(5), 583–594. https://doi.org/10.1093/geront/30.5.583
Peña-Longobardo, L. M., & Oliva-Moreno, J. (2015). Caregiver Burden in Alzheimer’s Disease Patients in Spain. Journal of Alzheimer’s Disease, 43(4), 1293–1302. https://doi.org/10.3233/JAD-141374
Pinquart, M., & Sörensen, S. (2003). Differences between caregivers and noncaregivers in psychological health and physical health: a meta-analysis. Psychology and Aging, 18(2), 250–267. https://doi.org/10.1037/0882-7974.18.2.250
Raj, J., Manigandan, C., & Jacob, K. (2006). Leisure satisfaction and psychiatric morbidity among informal carers of people with spinal cord injury. Spinal Cord, 44(11), 676–679. https://doi.org/10.1038/sj.sc.3101899
Rizk, S., Pizur-Barnekow, K., & Darragh, A. R. (2011). Leisure and Social Participation and Health-Related Quality of Life in Caregivers of Children with Autism. OTJR: Occupation, Participation and Health, 31(4), 164–171. https://doi.org/10.3928/15394492-20110415-01
Rochette, A., Desrosiers, J., Bravo, G., Tribble, D. S.-C., & Bourget, A. (2007). Changes in participation level after spouse’s first stroke and relationship to burden and depressive symptoms. Cerebrovascular Diseases (Basel, Switzerland), 24(2–3), 255–60. https://doi.org/10.1159/000104487
Romero-Moreno, R., Márquez-González, M., Mausbach, B. T., & Losada, A. (2012). Variables modulating depression in dementia caregivers: a longitudinal study. International Psychogeriatrics, 24(8), 1316–1324. https://doi.org/10.1017/S1041610211002237
Searson, R., Hendry, A. M., Ramachandran, R., Burns, A., & Purandare, N. (2008). Activities enjoyed by patients with dementia together with their spouses and psychological morbidity in carers. Aging & Mental Health, 12(2), 276–282. https://doi.org/10.1080/13607860801956977
Shaw, W. S., Patterson, T. L., Semple, S. J., Grant, I., Yu, E. S. H., Zhang, M. Y., … Wu, W. Y. (1997). A Cross-Cultural Validation of Coping Strategies and Their Associations With Caregiving Distress. The Gerontologist, 37(4), 490–504. https://doi.org/10.1093/geront/37.4.490
Smith, L., Onwumere, J., Craig, T., McManus, S., Bebbington, P., & Kuipers, E. (2014). Mental and physical illness in caregivers: results from an English national survey sample. The British Journal of Psychiatry, 205(3), 197–203. https://doi.org/10.1192/bjp.bp.112.125369
Page 181 of 197
Smith, R., & Greenwood, N. (2014). The impact of volunteer mentoring schemes on carers of people with dementia and volunteer mentors: a systematic review. American Journal of Alzheimer’s Disease & Other Dementias®, 29(1), 8–17. https://doi.org/10.1177/1533317513505135
Stern, S., Doolan, M., Staples, E., Szmukler, G. L., & Eisler, I. (1999). Disruption and Reconstruction: Narrative Insights into the Experience of Family Members Caring for a Relative Diagnosed with Serious Mental Illness. Family Process, 38(3), 353–369. https://doi.org/10.1111/j.1545-5300.1999.00353.x
Stevens, A. B., Coon, D., Wisniewski, S., Vance, D., Arguelles, S., Belle, S., … Haley, W. (2004). Measurement of leisure time satisfaction in family caregivers. Aging & Mental Health, 8(5), 450–459. https://doi.org/10.1080/13607860410001709737
Szmukler, G. I., Burgess, P., Herrman, H., Bloch, S., Benson, A., & Colusa, S. (1996). Caring for relatives with serious mental illness: the development of the Experience of Caregiving Inventory. Social Psychiatry and Psychiatric Epidemiology, 31(3–4), 137–148. https://doi.org/10.1007/BF00785760
Thompson, L., Solano, N., & Kinoshita, L. (2002). Pleasurable activities and mood: Differences between Latina and Caucasian dementia family caregivers. Journal of Mental Health and Ageing, 8(3), 211–224. Retrieved from https://asu.pure.elsevier.com/en/publications/pleasurable-activities-and-mood-differences-between-latina-and-ca
Treasure, J., Murphy, T., Szmukler, T., Todd, G., Gavan, K., & Joyce, J. (2001). The experience of caregiving for severe mental illness: a comparison between anorexia nervosa and psychosis. Social Psychiatry and Psychiatric Epidemiology, 36(7), 343–347. https://doi.org/10.1007/s001270170039
Voss, J. (1967). The definition of leisure. Journal of Economic Issues, 1(1), 91–106. https://doi.org/10.1080/00213624.1967.11502742
White-Means, S. I., & Chang, C. F. (1994). Informal caregivers’ leisure time and stress. Journal of Family and Economic Issues, 15(2), 117–136. https://doi.org/10.1007/BF02353636
Williams, I. C. (2005). Emotional Health of Black and White Dementia Caregivers: A Contextual Examination. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60(6), 287–295. https://doi.org/10.1093/geronb/60.6.P287
Williamson, G. M., & Schulz, R. (1992). Pain, Activity Restriction, and Symptoms of Depression Among Community-residing Elderly Adults. Journal of Gerontology, 47(6), P367–P372. https://doi.org/10.1093/geronj/47.6.P367
Wisniewski, S. R., Belle, S. H., Coon, D. W., Marcus, S. M., Ory, M. G., Burgio, L. D., … Schulz, R. (2003). The Resources for Enhancing Alzheimer’s Caregiver Health (REACH): Project design and baseline characteristics. Psychology and Aging, 18(3), 375–384. https://doi.org/10.1037/0882-7974.18.3.375
Page 182 of 197
Youn, G., Knight, B. G., Jeong, H.-S., & Benton, D. (1999). Differences in familism values and caregiving outcomes among Korean, Korean American, and White American dementia caregivers. Psychology and Aging, 14(3), 355–364. https://doi.org/10.1037/0882-7974.14.3.355
Zarit, S. H., Reever, K. E., & Bach-Peterson, J. (1980). Relatives of the Impaired Elderly: Correlates of Feelings of Burden. The Gerontologist, 20(6), 649–655. https://doi.org/10.1093/geront/20.6.649
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Appendix A: Aims and Scope of Social Sciences & MedicineFrom: https://www.journals.elsevier.com/social-science-and-medicine, retrieved on
14/01/18.
“Social Science & Medicine provides an international and interdisciplinary forum for the dissemination of social science research on health. We publish original research articles (both empirical and theoretical), reviews, position papers and commentaries on health issues, to inform current research, policy and practice in all areas of common interest to social scientists, health practitioners, and policy makers. The journal publishes material relevant to any aspect of health from a wide range of social science disciplines (anthropology, economics, epidemiology, geography, policy, psychology, and sociology), and material relevant to the social sciences from any of the professions concerned with physical and mental health, health care, clinical practice, and health policy and organization. We encourage material which is of general interest to an international readership.
The journal publishes the following types of contribution:
1) Peer-reviewed original research articles and critical or analytical reviews in any area of social science research relevant to health. These papers may be up to 8,000 words including abstract, tables, and references as well as the main text. Papers below this limit are preferred.
2) Peer-reviewed short reports of research findings on topical issues or published articles of between 2000 and 4000 words.
3) Submitted or invited commentaries and responses debating, and published alongside, selected articles.
4) Special Issues bringing together collections of papers on a particular theme, and usually guest edited.”
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Clinical ExperienceYear 1 – Working Age Adults
I spent a year in a community mental health service for working age adults with
severe and enduring mental health difficulties. I worked with individuals who were
challenged by problems such as psychosis, health anxiety, OCD, and depression. I
did this in the form of consultation, one to one therapy, and group facilitation. I
offered training to staff within the team (how to use CBT worksheets) and to carers
(using ACT to support self-care). I also completed some neuropsychological
assessments including the use of psychometric testing. Whilst on placement I worked
with a range of other health and social care professionals, met clients and carers
outside of my clinical work, visited other local services and became involved in
some reflective team meetings which used a systemic framework. Main therapeutic
models used on this placement were ACT, CBT, systemic, neuropsychological, and I
had the opportunity to have some psychodynamic conversations with the art
therapist.
Year 2 – Learning Disabilities
I spent 6 months in a Learning Disabilities (LD) service for adults. During this time I
offered 1:1 therapy, family work, consultation and cognitive assessment. I worked
with individuals who were affected by a LD with difficulties such as being
vulnerable to sexual assault, distress that was difficult for their care team to manage
(challenging behaviour), memory difficulties, partner’s decline of dementia, and
satisfaction with relationships. I worked with families, carers, and individuals
affected by LD in the clinic, and in residential settings. I also worked with a range of
different health conditions (such as visual impairment, Downs syndrome and
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encephalopathy) and across the spectrum of ability within this client group (including
work with a non-verbal individual). I completed cognitive assessments including
assessment of LD in the context of autism and dementia assessment in the context of
a LD. I also offered training to local social services staff about mental health
difficulties in Learning disabilities, and dementia training to staff at a residential
home. The main therapeutic models used during this placement were Behaviour
analysis, neuropsychological and systemic.
Year 2 – Child and Adolescent Mental Health
I spent 6 months in a Child and Adolescent Mental Health Service (CAMHS)
working with children from the age of 5 to the age of 18 and their families. I worked
with a range of presenting difficulties including anxiety over exams, OCD,
depression, tics and hearing voices. Main therapeutic approaches included CBT,
habit reversal training, neuropsychological and systemic. I offered training to staff
regarding the use of outcome measures and also contributed to service development
with regards to implementation of outcome measures. I also completed some
neuropsychological assessment with children regarding possible learning disability,
and developing understanding of behaviours at school. I spent time in local services,
meeting children and young people outside of the context of clinical work. I was also
involved in a reflecting team in a systemic intervention for a family affected by
PTSD, ADHD, and anger.
Year 3 – Neurorehabilitation in-patient (specialist placement)
I spent 6 months in a neurorehabilitation ward working with individuals with head
injury, stroke, MS and other neurological difficulties. I worked with individuals to
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understand their cognitive difficulties and support them to maximise on their
cognitive strengths to aid recovery. I also worked with individuals to understand and
talk through their experiences and support and monitor their emotional wellbeing.
Predominantly I used neuropsychological models for this placement however
behavioural models, ACT, systemic working and a biopsychosocial approach were
also utilised. I contributed to a business proposal to start up a singing group on the
ward by putting together a literature review on the influence of music and singing on
emotional wellbeing. I worked with a range of professionals to ensure a shared
understanding of patient’s experiences. I provided training to stroke survivors, their
carers and professionals on cognitive impairments following stroke.
Year 3 – Older Adult Community Mental Health Service
I spent 6 months in an older adult community mental health service. This involved
memory assessments, support with mental health difficulties, and behavioural work
within a care home. Interventions were 1:1, with families, in services, and within the
multidisciplinary team. I provided training to professionals within the rehabilitation
service about psychological approaches to fear of falling. I took part in reflecting
teams for systemic interventions with families affected by bipolar disorder and
psychosis. I was involved in reinstating dementia information packs for individuals
who were newly diagnosed and planned an audit on the use of the ACE III. I
attended local services to meet older adults outside of the clinical context. I worked
with people experiencing difficulties with anxiety, memory, mood, perfectionism,
hoarding, relationship stress, and bipolar disorder.
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PSYCHD CLINICAL PROGRAMME
Table of assessments completed during trainingYear I Assessments
Assessment Title
WAIS WAIS interpretation (online assessment)
Practice report of clinical activity A Cognitive Behavioural Therapy (CBT) assessment and formulation with a female in her 40s who had a diagnosis of Obsessive Compulsive Disorder.
Audio recording of clinical activity with critical appraisal
A critical appraisal of a Cognitive Behavioural Therapy (CBT) intervention session with a British woman in her 40s with a diagnosis of Obsessive Compulsive Disorder (OCD).
Report of clinical activity N=1 A CBT assessment, formulation and intervention with a female in her 50s who was facing challenges relating to anxiety and depression.
Major research project literature survey A literature survey to examine what makes peer support effective for carers of “adult experiencers of serious mental illness” in the UK
Major research project proposal An investigation into the role of leisure activities in the wellbeing of female carers who spend 20 or more hours a week caring
Service-Related Project Evaluation of the use of goals for admission, crisis plans, and duration of admission with people with personality disorders who have been admitted to adult acute psychiatric inpatient wards.
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Year II Assessments
Assessment Title
Report of clinical activity – Formal assessment
A dementia assessment with a white-British female in
her mid-thirties with diagnoses of Learning Disability and Downs Syndrome.
PPLD Process Account Reflections from a Trainee Clinical Psychologist on
the use and impact of a Personal and Professional Development Group on personal and professional development
Presentation of clinical activity Team Resistance building a weapon against the OCD bully: Working with a ten year old boy and his family using a narrative and CBT approach
Year III Assessments
Assessment Title
Major research project literature review Leisure influences on wellbeing among those who spend a significant amount of time caring for others: A systematic review
Major research project empirical paper The relationship between leisure and mental wellbeing in middle-aged women who care for more than 20 hours per week: A secondary analysis using data from a national survey
Final reflective account A reflective account of my personal and professional development during training as I approach qualification.
Report of clinical activity A cognitive neurorehabilitation intervention with a White British male in his mid-50s following an anterior communicating artery aneurysm rupture.
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