A mixed methods study exploring weight related bias in undergraduate

and qualified nurses

Elisabeth Jane Goad

Submitted for the Degree of

Doctor of Psychology(Clinical Psychology)

School of PsychologyFaculty of Health and Medical Sciences

University of SurreyGuildford, SurreyUnited KingdomSeptember 2017

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Statement of Originality

This thesis and the work to which it refers are the results of my own efforts. Any ideas, data, images, or text resulting from the work of others (whether published or unpublished) are fully identified as such within the work and attributed to their originator in the text. This thesis has not been submitted in whole or in part for any other academic degree or professional qualification.

Name: Elisabeth Jane Goad

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Portfolio Overview

There is substantial evidence suggesting that nurses’ do hold weight bias

towards patients with obesity. The evidence is also suggestive of a range of

psychological and physical health implications for patients experiencing

such bias. Despite this, weight bias research in nurses is not only limited but

also contradictory. This thesis aimed to determine how a range of factors

might relate to weight bias in nurses. Part one of this portfolio presents a

literature review of several factors associated with weight bias in nurses.

The findings of the review suggested that due to limitations in the amount

and quality of the literature surrounding weight bias in nurses, a consensus

about factors relating to weight bias could not be reached. Part two presents

an empirical paper that investigated the relationships between nurses’ self-

esteem, BMI, qualification status, stress and burnout; and their associations

with weight bias in nurses. The quantitative findings suggested that there

were no clear relationships between these variables and weight bias.

However, the qualitative analysis helped to interpret the quantitative

findings with more clarity, suggesting that social identities may influence

weight bias in addition to the conceptual frameworks nurses use to make

sense of obesity. Part three of this portfolio consists of a brief description of

all five placements and a summary of the opportunities and experiences I

had for each one. Finally, part four outlines each academic assessment

completed throughout my three years of training.

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Contents Page

Acknowledgements………………………………………………..………..1

Part 1: MRP Literature Review.………………………………………2-64

Abstract……………………………………………………………………...3

Introduction…………………………………………………………….....4-9

Methods………………………………………………………………...10-17

Results………………………………………………………………….17-29

Discussion……………………………………………………………...29-36

References……………………………………………………………...37-50

Appendix 1……………………………………………………………..51-52

Appendix 2……………………...……………………………………...61-64

Part 2: MRP Empirical paper……………..……………………….65-219

Abstract………………………………………………………………...66-67

Introduction…………………………………………………………….68-75

Methods……………………………...…………………………………75-84

Results………………………………………………………………...84-100

Discussion…………………………………………………………...100-115

References……………………………………………………….......116-134

List of appendices……………………………………………………..…135

Appendices…………………………………………………………..136-219

Part 3: Summary of clinical experience……...….………………….220-222

Part 4: Table of assessment………………………………………….….223

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Acknowledgements

As with anything worthwhile, this research was not completed in

isolation. Firstly, a big thank-you to all of the research participants, and

countless ward managers who gave their time to either completing the

research or supporting the recruitment process. I know how busy they were

and thus their support was much appreciated. Without their input this

research would not have been possible. The support I have received from

my friends and family throughout the process has given me the strength to

keep going through the difficult moments and for which I am eternally

grateful. A heartfelt thank-you to my fellow trainee clinical psychologist

colleagues whose knowledge, advice and friendship continue to prove

invaluable. Finally, a very special thank-you to my two research

supervisors, Dr Kate Gleeson and Dr Sue Jackson, whose passion and

mountainous knowledge has been truly inspiration. Their endless patience,

sensitivity and willingness to guide me to a place of understanding ‘what it

really means to know something’ has without doubt changed my research

and my clinical practice for the better.

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Research part 1

Literature Review

Personal factors associated with the

attitudes of UK nurses toward

patients with obesity: A literature

review

Word Count: 7642

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Abstract

Weight bias towards patients with obesity is prevalent within

healthcare settings and may compromise care quality causing negative

consequences for the patient; both psychologically and physically. Yet

relatively little is known about factors that influence weight bias in

healthcare staff and particularly in nurses who spend the most time caring

for patients directly.

This literature review focuses on the association between BMI,

qualification status, self-esteem, levels of stress and burnout in nurses,

alongside their attitudes towards patients with obesity. These variables have

been found to be relevant to weight bias, or with prejudice more generally,

but findings are inconclusive. Searches were conducted on five databases

using terms relating to ‘attitudes’ ‘healthcare staff or nurses’ and ‘obesity’.

Ten studies met the inclusion criteria and were tabulated and critiqued .

The literature reviewed focused on the association between BMI and

weight bias, qualification status, self-esteem, stress and burnout. The

literature covered a time span of over 30 years, the type and quality of study

methodologies varied. Research was particularly limited within a UK

population and was rarely underpinned by theory. Given these shortfalls; no

consensus was reached in drawing together the findings.

In conclusion, further research should focus on developing the

literature for each of these variables in a UK nursing population in relation

to weight bias. This should be undertaken using an appropriate theoretical

underpinning in order to make sense of the research that has begun further

a field.

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Obesity is a global challenge affecting developed and developing

countries across the world (WHO, 2000). In 2014, 39% of people over 18

years old were classified as overweight (BMI>25) and 13% were classified

as obese (BMI>30) globally (WHO, 2015). In the United Kingdom (UK)

63.4% of people are overweight and 28.1% are obese (WHO, 2015). The

ramifications of this on the systems in which the individual resides are

significant, with the cost of obesity to the NHS estimated to be around £6.1

billion a year, and around £27 billion to the wider economy (Department of

Health, 2011). Indeed, by 2050, the Department of Health suggest that the

costs of obesity may rise to almost £50 billion (Department of Health,

2011).

However, on an individual level, obesity itself increases mortality

rates (Duncan, Griffith, Rutter & Goldacre, 2010) with co-morbid

conditions such as cardiovascular disease, diabetes and some cancers,

causing complications at best, and fatality at worst (Haslam & James, 2005).

The Department of Health, (2011) suggests that obese men are two and a

half times more likely to have high blood pressure than non obese men, and

five times more likely to develop type two diabetes. Obese woman are three

times more likely to have a heart attack and 13 times more likely to develop

type two diabetes than non obese woman (Department of Health, 2011).

In acknowledgement of the impact obesity has on society as a whole

and on the person individually, a ‘whole systems’ effort by the UK

government and the NHS has been undertaken in order to tackle this

widespread issue (BPS, 2011). However, whether a ‘whole systems’

approach includes tackling the pervasive negative attitudes that people with

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obesity often face is debatable. Despite research suggesting that weight bias

may exceed the stigma notoriously projected towards other stereotyped

groups, (Latner, O’Brien, Durso, Brinkman & MacDonald, 2008) such as

race and gender (Andreyeva, Puhl, & Brownell 2008), weight bias is often

seen as the last acceptable form of prejudice within modern society (Puhl &

Heuer, 2009). The British Psychological Society’s publication examining

obesity from a psychological perspective (BPS, 2011), although mentioning

the existence of stigma and prejudice in some specific settings, does not

elaborate on how widespread the issue is and the phenomenal impact of it

on the person themselves, whether physically (Brown, 2006) or

psychologically (Kolotkin, Meter & Williams, 2001). However, exploring

the impact of and reasons for weight bias may be a key component of

understanding obesity in a truly psychosocial way.

Weight bias is pervasive across all settings, including education, (Puhl

& Brownell, 2001), employment (Puhl, Henderson & Brownell, 2005) and

worryingly in healthcare (Budd, Mariotti, Graff & Falkenstein, 2011).

Within health services weight bias has been reported across professional

groups, including those specializing in obesity (Schwartz, Chambliss,

Brownell, Blair & Billington, 2003).

The importance of recognizing weight bias within healthcare lies in

the impact it has on patients, whether that is the impact on their care or the

physical and psychological effect on the individual concerned. Widespread

attitudes relate to beliefs about patients who are obese being lazy, lacking

willpower, being undisciplined (Zhu, Norman & While, 2011), unintelligent

(Puhl & Heuer, 2010) and noncompliant with treatment (Brown, 2006).

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Some research suggests that healthcare providers may show less respect

towards obese patients (Puhl & Heuer, 2009; Hebl & Xu, 2001), spend less

time with them and provide fewer treatment options; including preventative

treatments (Swift, Hanlon, El-redy, Puhl, & Glazebrook, 2013). The

suggestion that negative attitudes of some healthcare staff may translate into

poor clinical care is extremely concerning.

Research exploring the perspective of patients with obesity suggests

that they are well aware of such attitudes directed towards them, reporting

feeling disrespected, receiving unhelpful advice, and finding that they were

discriminated against by not being provided with equipment to

accommodate their size (Amy, Aalborg, Lyons, Keranen, 2006).

Psychologically, being on the receiving end of weight bias has a range of

serious adverse consequences which include an increased vulnerability to

depression, low esteem, anxiety and suicide (Puhl & Heuer, 2009).

In addition to the psychological implications of weight bias, patients

with obesity are likely to experience adverse physical health consequences

as well. Research has indicated that patients who have experienced weight

bias within healthcare are less likely to engage in weight management

(Mold & Forbes, 2011), may increase unhealthy eating behaviours (Schvey,

Puhl & Brownell, 2012) and tend to experience poorer outcomes on weight

loss programmes (Carels et al., 2009). Understandably, patients

experiencing weight bias are also more likely to avoid using healthcare

services despite the co-morbidities associated with obesity (Hebl & Xu,

2003). The implications of poorer care from healthcare staff, additional co-

morbid health conditions as well as possible increases in behaviours that

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may exacerbate physical health problems mean that the potential to identify

and treat serious co-morbid conditions quickly may be missed. As such,

weight bias amongst healthcare staff has the potential to exacerbate obesity

and its associated health problems, the consequences of which are for the

individual and for healthcare services, catastrophic.

Overall, the research focusing on weight bias in healthcare is rising

(e.g. Berryman, Dubale, Manchester & Mittelstaedt, 2006; Forhan & Salas,

2013; Poon & Tarrant, 2009) but has mostly focused on the presence of

weight bias (Crandall, 1994; Bacon, Scheltema & Robinson, 2001), the

experience of weight bias and stigma from the perspective of the person

with obesity (Puhl, Moss-Racusin, Schwartz & Brownell, 2009) and

exploring the efficacy of weight bias reduction interventions (Hoppe &

Ogden, 1997; O’Brien, Puhl, Latner, Mir & Hunter, 2010).

The research exploring factors that may be associated with weight bias

is considerably more sparse and has focused on demographic variables such

as age, level of experience, gender or BMI (Brown, Stride, Psarou, Brewins

& Thompson, 2007; Swift, Hanlon, El-Redy, Puhl & Glazebrok, 2013;

Harvey, Summerbell, Kirk & Hills, 2002) and qualification status (Poon &

Tarrant, 2009). However, overall there remains little consensus on the

relationship between these variables and weight bias in healthcare.

Interestingly, despite the fact that in the literature focusing on

attitudes, self-esteem has long been considered a contributor to prejudiced

attitudes towards others (Duckitt, 1992; Fein & Spencer, 1997; Cheng,

Robins, & Trzesniewski, 2009, Tajfel & Turner, 1986), it does not appear to

have been extensively explored within weight bias research. The research

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suggests that prejudice towards stereotyped groups often occurs when the

group identity of the perpetrator is threatened in some way (Fein & Spencer,

1997). Thus in the context of prejudice occurring between a member of one

social group (nurses) towards members of another (patients with obesity) it

is reasonable to question how the impact of a group member’s own self-

esteem may relate to that.

Overall, the research in this field has largely been conducted in the

USA (e.g. Puhl & Heuer, 2009; Puhl & Brownell, 2001) rather than the UK.

Developing an understanding of the factors that are associated with weight

bias in the context of a UK population is particularly important given its

unique healthcare system, the National Health Service (NHS). The NHS

faces challenging times with particular stressors including staff shortages

and high patient demand, pay restraints and constant organizational change

(Cox, Randall & Griffiths, 2002), all the while with the expectation to

continue improving the quality and safety of its care (NHS Employers,

2009). As such, UK nurses are particularly vulnerable to the effects of stress

(NHS Employers, 2009) and burnout (Heinen et al., 2013) but the impact of

this on nurses’ attitudes towards patients with obesity is unknown.

Weight bias literature often refers to ‘healthcare professionals’, which

is a broad term encompassing groups of individuals who hold different skill

sets, and have differing priorities and pressures. The level, length and type

of training is very different between healthcare professionals and thus it

cannot therefore be assumed that the factors that may affect the attitudes

they hold towards stereotyped groups such as those who are obese, will be

unanimous. Nurses play an important role in providing care and support to

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patients who are obese (National Audit Office, 2001) and generally provide

the majority of one to one care (American Nurses Association, 1996). In

order to develop a more integrated understanding of the influences on

weight bias in nurses, an area that is currently under represented within

weight bias research, this literature review focuses on collating the current

research by examining current key variables and their relationship with

weight bias in nurses globally. The variables were chosen based on those

most frequently explored within current literature for example BMI and

qualification status combined with the variables most relevant to intergroup

theories of prejudice such as self-esteem. Finally, the variables stress and

burnout were chosen in light of the evidence of their commonality in UK

nurses and thus the importance of this social context on the attitudes of

nurses towards patients with obesity.

Research questions:

1) Are nurses BMI associated with the attitudes they hold towards

patients who are obese?

2) Is there a difference between the attitudes held towards patients who

are obese by student and qualified nurses?

3) Is the self-esteem of healthcare staff associated with the attitudes

they hold towards obese patients?

4) Is stress in healthcare staff associated with the attitudes they hold

towards patients who are obese?

5) Is burnout in healthcare staff associated with the attitudes they hold

towards patients who are obese?

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MethodSearch strategies

The electronic databases Psychology Cross search (Medline,

PsychINFO, PsychARTICLES & Psychology & Behavioural Sciences

Collection) Pubmed, Web of Science, Proquest Allied Health Professionals

and Google Scholar were searched by one researcher (EG) between January

1st and February 28th 2016. Search terms were used within each database as

shown in table 1:

Table 1:

Search terms

Search Category Search Terms Used Health care staff AND psych* OR nurs* OR phsyi (phys*)OR

doctor* OR clinician* OR counsellor* OR therap* OR occupational therap* OR profess* OR employ* OR staff* OR qualif* OR unqualified OR student* OR trainee* OR healthcare* 

Stigma and discrimination  AND

Stigma OR discriminat* OR anti-fat* OR bias* OR prejudice* OR attitude*

Obesity Obes* OR fat OR overweight OR BMI or body mass index OR Obesity Or Obesity bariatric* OR weight*

Each category of words were linked together with ‘AND’ to produce

results containing at least one word from each category. Preliminary

searches suggested that there would be limited literature exploring the

variables self-esteem, stress and burnout within the nursing population. As

such, terms relating to healthcare professionals more broadly, in addition to

nurses, were used in order to capture the wider literature on these variables.

No date limitations were applied during the search in order to collate

all prior research and allow for the development of the whole picture. The

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Psychology Cross Search N=422Pubmed N= 186Web of Science N=477Proquest N=765Google Scholar N=1Total N= 1851

Exclusion of duplicates N= 991

Potentially eligible recordsN= 860

Remaining eligible recordsN= 98

Exclusion of articles using criteria two N=89

Exclusion of articles using criteria one N= 762

Remaining eligible records N=9

References hand searched N=4

Remaining eligible records N=13

Two hand searched references not found

Remaining eligible records N=10

full search strategy is presented in figure 1.

Figure 1: Prisma flow diagram

Criteria one = exclusion based on title and abstractCriteria two = exclusion based on examination of the whole study

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The searches were also rerun to include the terms ‘self-esteem’ ‘body

image’ ‘self confidence and ‘self efficacy’ as well as ‘stress’ ‘burnout’

‘depersonali*’ ‘cynicism’ ‘fatigue’ and ‘exhaustion’ but this did not return

any additional results.

The quantity of research for each area differed significantly, which led

to the stipulation of slightly different inclusion criteria for each variable. For

example, literature was searched more widely when exploring self-esteem,

stress and burnout in order to contextualise them within the wider research

given their limited representation within this specific field. The inclusion

and exclusion criteria utilised for this literature review are illustrated in

Table 2 and table 3 below.

Table 2:

Inclusion & exclusion criteria for papers examining the relationship

between nurses BMI, qualification status & attitudes towards patients with

obesity.

Exclusion criteria Inclusion criteria

Studies not looking specifically at BMI or body weight in relation to weight biasWeight bias by any population other than nurses Weight related bias not directed towards patients Weight related bias directed towards childrenAttitudes towards weight management rather than attitudes towards the person with obesity more generally

Studies exploring nurses attitudes towards obese adult patients AND The relationship with nurses own BMI or body weight and weight related biasStudent nursesStudies from any country Studies from any time period

Table 3:

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Exclusion criteria Inclusion criteriaStudies not looking specifically at self esteem, stress, burnout or any aspect of these in relation to weight related biasWeight bias not directed towards patients Weight bias directed towards childrenWeight bias in participants who are not healthcare staff

Studies exploring healthcare professionals attitudes towards obese adult patients AND The relationship with the healthcare professionals own self esteem, stress, burnout or any aspect of these and weight related biasStudents within healthcare professionsStudies from any country Studies from any time period

Inclusion and exclusion criteria for papers examining the relationship

between nurses’ own self esteem, burnout or stress towards patients who

were overweight/obese.

Definition of termsIn the wider literature there is some variation between the definitions

of terminology used depending on the theoretical framework they are

situated within. The majority of research located for this literature review

focused on ‘attitudes;’ traditionally situated within a social psychology

framework. The definitions chosen for this literature review reflect this.

Attitude

As early as 1935, attitudes were described within social psychology

as, ‘a mental or neural state of readiness, organised through experience,

exerting a directive and/or dynamic influence upon the individual’s

responses to all objects and situations (Allport, 1935, p1). However, social

psychologists have more recently been criticised for their individualistic

approach towards attitude formation and for neglecting the social context in

which they arise (Hogg & Smith, 2007). As such, for this review, the term

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attitude will be defined as ‘an individual’s evaluation of any part of their

social world’ (Olson & Maio, 2003). This may be stable or dynamic

dependent on the context in which it has arisen (Schwarz & Bohner, 2001).

Weight bias

A variety of terminology has been used to describe negative affective

responses (e.g. prejudice), negative cognitive responses (e.g. negative bias,

negative stereotype) and differential behaviour (e.g. discrimination) directed

towards individuals or groups of people. Within this review, the

terminology ‘bias’ will be used to describe a non-neutral cognitive state

directed towards members of a particular social group. The direction of the

bias will be denoted in the text where appropriate. Deviation from this

language will be clarified when required.

Self-esteem

The term self-esteem is commonly defined as ‘self evaluations about

ones own worth or abilities’ (Oxford Dictionaries, 2016). However, self-

esteem has long been located at the centre of prejudice towards others

(Tajfel & Turner, 1986). In the context of attitudes research self-esteem is

integrally linked with interpersonal dynamics (Fein & Spencer, 1997) with

an inherently social nature. Indeed, key theorists (Tajfel & Turner, 1986)

suggest that negative attitudes are expressed in order to positively

distinguish collective self-esteem from those individuals belonging to other

group memberships. Thus the term self-esteem does not assume an

individualistic focus. However, to collate the research on self-esteem in

weight bias, more inclusive terms such as ‘body image’ have been included

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in recognition that body image is often represented as one component of

self-esteem across the wider literature.

Stress

Definitions of stress are often poorly defined within the literature with

no single definition in existence (Pines & Keinan, 2005). Most commonly it

is defined as a psychological response to situations or events that are

appraised to be threatening or otherwise demanding and the person has

insufficient resources available to cope (Lazurus, 1977). However, this

focuses more on momentary appraisals of stressful situations rather than

stress as an ongoing and chronic response to stressors that this review

considers. This review focuses on chronic work-related stress. For example

stress in the context of healthcare, which has been associated with increased

workload, time pressures, coping with the emotional needs of the patients

and shift work (McVicar, 2003). This type of stress has been related to the

development of emotional exhaustion and ultimately burnout in nurses

(Bakker, Blanc & Schaufeli, 2005; Lederer, Kinzl, Traweger, Dosch &

Sumann, 2008).

Burnout

Maslach, Jackson & Leiter define burnout as ‘a syndrome of

emotional exhaustion, depersonalisation and reduced personal

accomplishment that can occur among individuals who do “people work” of

some kind’ (p1, 1996). The term depersonalisation has previously been

construed as meaning alienation from self within a psychiatric model

(Scaufeli, & Salanova, 2014). However, in this context it is referred to as an

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impersonal and dehumanized perception of recipients rather than an

impersonal view of self (Maslach, Jackson & Leiter, 1996).

Nurse

For the purpose of this review, student and qualified nurses were

included and were defined as individuals who have completed or are

completing a formally recognised programme of nursing education that is

authorised by the appropriate governing nursing body within their country

(ICN, 2015).

Obesity and overweight

The World Health Organization defines being overweight as a body

mass index greater than or equal to 25; and defines obese as having a body

mass index of greater than or equal to 30 (WHO, 2015). Although these

definitions will loosely aid understanding of the terms obesity and

overweight in this review, it is participants perceptions of those overweight

or obese that are of interest and thus their judgement on what it means to be

overweight or obese will likely vary. Participants identifying their attitudes

of both overweight and obese patients will be included within this review.

Findings

Thirteen suitable studies met the inclusion criteria including one

systematic review, four dissertations and eight quantitative studies. Two of

the dissertations were unpublished (Carson and Carson, 1987 & Clevenger,

1983) and despite contacting the authors and universities where they were

written, these were not located and thus were removed from the final

selection. The literature review (Brown, 2006) identified only two studies

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that met the criteria for the current review but these two studies had already

been located and included in the final selection (Culbertson & Smolen,

1995; Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989) and therefore

the Brown, (2006) literature review was not included. As such, in total, 10

studies were analysed within this literature review.

The variables explored within this literature review were generally

only included as one aspect of a wider research question in the studies

reviewed. As such, only the elements of each study directly relating to the

research questions developed within the current literature review were

critiqued. The Critical Appraisal Skills Programme Checklists (Critical

Appraisal Skills Programme, 2013) were used to appraise the systemic

review and the STROBE checklist (Strobe statement, 2009) was used as a

guideline to review the quantitative design studies.

Results

Is a nurses BMI associated with weight bias? As nurse BMI increases level of weight bias decreases

Four studies were identified that suggested that nurses with a higher

body mass index (BMI) demonstrated more positive attitudes towards

patients with obesity than nurses with lower BMI’s (Brown, Stride, Psarou,

Brewins & Thompson, 2007; Garcia, 2012; Geckle, 2001; Lilliot, 2000).

The studies were all cross sectional survey designs spanning a time period

of 12 years (2000-2012). All four studies were from western countries such

as the USA (Garcia, 2012; Geckle, 2001 & Lilliot, 2000) or the UK (Brown,

Stride, Psarou, Brewins, & Thompson, 2007) and thus the cultural narratives

surrounding what it means to be obese were construed as reasonably similar.

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Each of the four studies concluded that higher BMI or higher

perceived weight was associated with more positive attitudes in nurses

although there were significant differences between the studies requiring

consideration. Three studies (Brown, Stride, Psarou, Brewins & Thompson,

2007; Garcia, 2012 & Lilliot, 2000) utilised the measurement tool BMI

requiring participants to report their estimated weight and height. On the

other hand, Geckle (2001) used self-categorization (underweight,

appropriate weight or overweight), representing a different underlying

mechanism required for participants to respond. For example, weight and

height measurements can be recalled relatively objectively by the individual

and do not assume the necessity of a socially relational comparison in order

to do so. However, categories such as ‘underweight’ or ‘overweight’ are

entirely socially constructed. To use such categories the individual must

organize themselves in to specific group memberships by making

comparisons with others in each group of reference; and then establish

where they best fit. Although a direct numerical measurement of weight

(such as kg or pounds) may have social meaning attached to it, it remains an

objective measure that does not require social comparisons to be made in

order to report it. Thus the different underlying mechanisms highlighted in

measurement technique between the studies may query whether each of the

studies are measuring the same constructs; or indeed the constructs in which

they had intended to measure.

Interestingly, the three studies that used BMI as a measurement tool

(Brown, Stride, Psarou, Brewin & Thompson, 2007; Garcia, 2012 & Lilliot,

2000) reported statistically significant correlations between BMI and weight

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bias although the magnitude of the correlations for these three studies were

weak. The study requesting participants to self-categorize (Geckle, 2001)

demonstrated a significant difference between weight categories although

did not provide an effect size. None of the studies explored both BMI and

self-categorization of weight thus it is unclear whether the weaker

correlations detected in the three studies using BMI were actually indirectly

identifying a relationship between weight bias and how nurses perceived

their weight rather than what they objectively weighed.

Each of the four studies (Brown, Stride, Psarou, Brewin & Thompson,

2007; Garcia, 2012; Geckle, 2001; Lilliot, 2000) utilised questionnaires

designed to measure various attitudes towards patients with obesity.

However, it is noteworthy that each questionnaire measured slightly

different aspects of attitudes towards patients with obesity as summarized in

table 4. As such, although a broad spectrum of attitudes were assessed

across these studies, it may also make comparisons between findings

difficult and thus if a more detailed understanding of specific attitudes is

required then the generalizability of the findings should be treated

cautiously.

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Table 4:

The different attitudes towards patients with obesity measured by each

questionnaire

Study Questionnaire Attitudes measured Brown,Stride, Psarou,-Brewins

& Thompson (2007)

Developed by the researchers

Personal effectiveness in caring for an obese patientBeliefs that obesity is an important health service development issueExternal causes of obesity

Garcia (2012) NATOOPS Nurse response to obese patients Attitudes towards the characteristics of of the obese patient Attitudes towards controllability f factors in obesity Stereotypic characteristics of patients with with obesity ……. Supportive roles in caring for obese patients

Geckle (2001) ANTOAP Attitudes towards nursing management of obese patientsLifestyle characteristics of obese patients

Lilliot, (2000) BATOS Negative views towards obese patientsOrganizational support in caring for obese patientsObesity causationPerceived characteristics towards patients with obesity

The reliability estimates for each of the studies were between

‘adequate’ and ‘good’1 for the range of questionnaires used to measure

participant attitudes towards patients with obesity. However, the ‘negative

views’ subscale in Brown, Stride, Psarou, Brewin & Thompson’s (2007)

study had a Cronbach alpha at .69, falling just short of adequate reliability.

Equally, although Garcia (2012) suggests an overall Cronbach alpha of .81,

a number of subscales did fall below the cut off of .7 (Kline, 1999), which 1 The reliability estimate cut off criteria used was that of Kline (1999) which suggests .7 or above is adequate reliability.

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may impact, on the reliability of some items. The majority of the

questionnaires were validated within nursing populations, however, the

BATOS, utilised by Lilliot (2000) was not. As the general population may

have a different relationship with the meaning of obesity than nurses do due

to nurses health education and training as well as the impact obesity may

have on their ability to nurse effectively, the validity of this questionnaire

amongst a nursing population may be questionable.

As nurse BMI increases their level of weight bias increases In contrast to the previous studies discussed, only one study suggested

that as nurse BMI increased, negative attitudes towards patients with obesity

also increased. This was a study of cross sectional survey design in a USA

nursing population (Torrey, 2013). The results suggested that nurses within

higher BMI categories tended to have more negative attitudes than those in

lower BMI categories, reporting medium to large effects. Although the

NATOOPS (Watson, Oberle & Deutscher, 2008) was the same

questionnaire as the Garcia, (2012) study used to measure nurses attitudes

towards patients with obesity, in this instance, the reliability estimates

calculated were at best adequate and for some subscales were poor; with

Cronbach alphas ranging from .45-.78. Details of which subscales were of

poor reliability were not reported, making interpreting subscale results

reliably difficult.

In considering the validity of the study, higher BMI categories also

appeared to correlate with higher levels of body image guilt and shame.

However, neither guilt or shame were controlled for when exploring the

other which made it difficult to interpret how they related to the nurses

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attitudes and how they related to each other. However, it is one of the few

studies that captured both BMI and the subjective experience of how

participants felt about their body image and its appropriate method draws on

a large sample size and adequate power to its credit.

There is no relationship between level of weight bias and nurse BMI

Finally, three studies (Culbertson & Smolen, 1995; Poon & Tarrant,

2009; Young, 1985) found no association between nurse BMI and their

attitudes towards patients with obesity. The publication dates of these

studies spanned a time period of over 20 years. This is relevant because the

relationship the world has with obesity has changed over time. Since the

1980’s worldwide obesity has nearly doubled (WHO, 2015) which clearly

has a significant impact on healthcare, the economy and the individual. Thus

the attitudes of nurses in the earlier Young (1985) study are likely situated

within the context of a very different culture than those in the later Poon and

Tarrant study (2009). Equally, cross culturally, studies situated in western

cultures are more likely to perceive obesity as a one-dimensional visible

flaw (Puhl & Brownell, 2003) as the values of western culture continue to

shift towards an emphasis on thinness which will likely impact on attitudes.

Culturally, the Chinese based Poon and Tarrant (2009) study may also be

subject to differing cultural bias. For example, China has historically been

considered to have one of the leanest populations worldwide (WHO, 1989).

Although its population is fast catching up with the west in terms of the

proportion of its population with obesity (Wu, 2006), it has not been

perceived as a long standing drain on the economy as it perhaps has in

22

western cultures. As such, the historical context may be important in

interpreting the findings of these studies in the present day.

There was also variation within how obesity was measured within

these studies as well. More recent studies have tended to use either self-

categorization of weight or BMI (e.g. Garcia, 2012 or Poon & Tarrant,

2009) the problems of which have been discussed. However, Young (1985)

used an older measurement system, the ‘Metropolitan Life Tables’

(Metropolitan Life Insurance Company, 1959), which are not comparable

with the other measurement systems used in this review. The Metropolitan

Life Tables were developed using populations of insured people and given

that the literature suggests that those with health insurance are much more

likely to be ‘healthy’ than those without (Hadley, 2003), this is likely

reflected in average weight differences between these two populations. As

such, the population used to develop this system of measurement were very

unlikely to be representative of the general population at the time; let alone

over 30 years later.

In examining each of the nine studies in consideration of the question

‘are nurses own BMI associated with the attitudes they hold towards

patients with obesity?’ the results were inclusive. Methodological

weaknesses were found across studies but particularly in the older studies

(e.g. Young, 1985) where the operationalization of variables was

questionable, reliability of measures inadequate and where there was poor

detail regarding the methodology. Combining these issues with the

historical and cultural differences between studies means interpretation of

the results in a meaningful and helpful way is difficult.

23

Are there differences between weight bias in undergraduate or post-

graduate nurses?

One study was identified within this review that reported differences

in weight bias between undergraduate and post-qualified nurses (Poon and

Tarrant, 2009). The results indicated that qualified nurses held more bias

towards patients with obesity than undergraduate nurses did. The study was

adequately powered with an appropriate sample size. The F scale, the

questionnaire used to measure attitudes, was reported to be reliable in other

studies (e.g. Bacon, Scheltema & Robinson, 2001), although the study was

conducted in the USA with a non-nurse sample and reliability estimates for

the current study were not provided. In examining the results undergraduate

nurses were reported to be significantly younger than qualified nurses were

which was not controlled for within the results. As such, it is unclear

whether the result is attributable to age (with older nurses having more bias)

or professional status. In considering the wider literature, older nurses have

been associated with more negative attitudes (Bagley, Conklin, Isherwood,

Pechiulis, Watson, 1989), although research has also found no association

between these variables (Bocquier et al., 2005; Brown, Stride, Psarou,

Brewins & Thompson, 2007; Miller et al., 2013). In contradiction, other

studies have suggested that older nurses have also shown more positive

attitudes than younger nurses (e.g. Culbertson & Smolen, 1999; Puhl,

Latner, King & Luedicke, 2013; Wise, Harris & Olver, 2014) even when

other demographic variables were controlled for (e.g. Schwartz, Chambliss,

Brownell, Blair & Billington, 2003). The significant relationships between

24

age and qualification status make it difficult to differentiate between which

variable actually relates to weight bias. The wider literature on age and

weight bias is also contradictory and thus does not clarify this picture.

Are negative attitudes towards patients with obesity linked to nurse’s own

self-esteem?

The initial results yielded few studies exploring the relationship

between nurses’ self-esteem and their attitudes towards obesity and thus the

review was expanded to contain studies including participants of all types of

healthcare professional. Three studies were included within this review all

of which were published in the USA but spanned 20 years (Bagley, Conklin,

Isherwood, Pechiulis & Watson, 1989 & Puhl, Luedicke & Grilo, 2013;

Torrey, 2013). Puhl, Leudicke & Grilo (2013) suggested that nurses self-

esteem or weight concerns were not associated with negative attitudes

towards patients with obesity although it did indicate that those with

increased weight concerns were more likely to perceive weight bias in

others around them. The psychometric properties for the questionnaires used

in thus study were reliable. However, there was little detail on the

methodology in general; including whether adequate power and sample size

was reached. Social desirability bias may have also have been a factor as

participants appeared able to report bias in others but not in relationship to

themselves. This may represent participants who with weight or shape

concerns of their own feel more sensitive to bias recognized in others, but

equally may highlight a discrepancy between nurses actual attitudes and

what they feel able to report in terms of their own prejudice towards those

with obesity.

25

The second two studies were conducted on nursing populations

(Bagley, 1989; Torrey, 2013) and focused on body dissatisfaction rather

than self-esteem more generally. Both studies suggested that nurses

dissatisfied with their own body weight held more negative attitudes

towards patients with obesity than those who were more satisfied. However,

the Bagley (1989a) study, although a validation study for a weight bias

measure within a nursing population was only four paragraphs long. As

such, it contained very little detail about the measure itself, its psychometric

properties, its sample, and indeed its results which were all significant

limitations. Other authors appear to have had similar difficulties locating the

full length article (Brown, 2006) despite being cited frequently throughout

the literature (e.g. Maroney & Golub, 1992; Culbertson & Smolen, 1989).

There was not enough detail produced to assess how robust the

methodology was or the reliability of its findings within this review.

However, the measurement scale has since been reproduced in other studies

who report reliable psychometric properties (e.g. Yuker at al., 1995) and

who have published the items in full highlighting the range of attitudes the

questionnaire covers.

The second study conducted on a nursing population explored the

relationship between body image guilt and shame in relation to negative

attitudes in nurses towards patients with obesity (Torrey, 2013). The results

suggested that nurses in the overweight and obese categories had

significantly higher levels of body image guilt and shame comparatively to

average weight nurses with a medium to large effect. Those with higher

body image guilt and shame in the overweight group had more negative

26

attitudes towards patients with obesity than those with less body image guilt

and shame in the average weight group. However, clearly as BMI increased

so did body image guilt and shame thus both correlating with increased

negative attitudes in nurses towards patients with obesity. As such, again the

question is raised as to whether it is BMI itself, or whether it is the nurses’

perception of their own body size and the associated emotional impact of

that; which relates to their attitudes towards patients who are obese.

The wider literature on self-esteem and prejudice

Given the limited literature on self-esteem in nurses or healthcare staff

and their relationship with weight bias towards patients with obesity, an

overview of the wider literature is summarized here. Within social

psychology, self-esteem is considered a contributor to prejudiced attitudes

towards others (see Duckitt, 1992; Hogg & Smith, 2007) Studies in this area

have suggested that prejudice against a range of stereotyped groups (for

example race or sexuality) is common after threats to self-image/esteem and

serve to protect the perpetrator from feeling bad about themselves (Fein &

Spencer, 1997). Social Identity Theory (Tajfel & Turner, 1986) encapsulates

this concept within their self-esteem hypothesis which suggests that

negative attitudes may serve to protect against or maintain social self-

esteem. Thus prejudice is directed towards members of other social groups

in order to manage the identity of their own social group positively and thus

their own self-esteem. There is a small amount of research conducted in the

field of weight bias which suggests that students with lower self body image

have higher levels of implicit and explicit weight bias; in part mediated by

the tendency to make physical appearance comparisons (O’Brien, Hunter,

27

Halberstadt & Anderson, 2007). That is, people may compare themselves

favourably against people with obesity in order to make themselves feel

better and thus this is associated with greater weight bias. These findings

have not yet been replicated in a healthcare professional population.

However, this body of literature does corroborate with the literature

explored within this review which suggests that those with high body

dissatisfaction are more likely to express negative attitudes towards people

with obesity.

The wider literature on stress and burnout

No studies were identified within this review examining the impact of

stress and or burnout in nurses or healthcare professionals and their attitudes

towards patients with obesity. This is despite the vast body of literature

suggesting that burnout is a particular problem within the ‘caring

profession’ (Maslach, 2003). Indeed, burnout is rife in nurses around the

globe (McFeely, 2007) but particularly within the UK which has the highest

reported rate of burnout at 42% compared to the 28% average across the rest

of Europe (Heinen et al., 2013). The evidence suggests that nurses who are

burnt out tend to have poorer attitudes towards their jobs and have less

concern for patients (Abushaikha & Saca-Hazbun, 2009). Indeed, by

definition, burnout includes cynicism, a negative or callous detached

response to aspects of the job (Maslach, Schaufeli & Leiter, 2001). In

addition, 30% of NHS staff sickness relates to stress in England, a

significant contributor to burnout itself (Maslach, 2006) which not only puts

a financial strain on the system itself but also negatively impacts on patient

experience and quality of care (NHS, employers 2009). Yet despite this

28

evidence the impact of stress or burnout on nurses’ attitudes towards

particular social groups, such as patients who are obese, remains unknown.

Discussion

There is global recognition that obesity is a public health concern

(Brown, 2006) with the associated negative social attitudes of healthcare

professionals towards patients with obesity documented for over three

decades (e.g. King, Latner, Puhl & Luedicke, 2013;Young, 1987). Yet

despite this body of research, the factors relating to weight bias in healthcare

staff remains unclear. This may in part relate to the varying focus,

methodological issues and contradictory results of previous research. This

literature review focused specifically on studies which examined the

relationship between BMI, qualification status, self-esteem, stress and

burnout in nursing populations and their attitudes towards patients with

obesity in order to draw together previous research and draw on current

theory to help develop the picture in this field. Overall, the results were in

some areas limited and often contradictory. As such, no meaningful

conclusions in relation to how specific factors may influence weight bias in

nurses were drawn.

The range of methodological issues identified when examining the

relationship between BMI and weight bias may have contributed to the

conflicting results. Given the variability across studies in relation to their

adequate power, sample size (Culbertson & Smolen, 1999), reliability,

method of measurement (Brown, Stride, Psarou, Brewin & Thompson,

2007), and ability to control for confounding variables (Poon & Tarrant,

2009), drawing conclusions was difficult. Additionally, there were

29

differences in how weight was operationalized across the studies (e.g.

Geckle, 2001 versus Garcia, 2012). However, one might argue that even the

studies that did use BMI to categorise participants weight in to socially

constructed categories may not have been able to do so accurately. For

example, BMI cannot distinguish between body fat and muscle (Centre for

Disease Control and Prevention, 2009) and thus may not be the most

appropriate determinant of obesity, especially when taken alone. Finally, in

some studies the methodologies were so poorly documented that it was

difficult to interpret the findings at all (e.g. Culbertson & Smolen, 1999).

These difficulties were not unique to studies examining the impact of weight

on nurses attitudes towards obesity. The literature on self-esteem and body

image also had methodological difficulties (e.g. Bagley, 1989) which

limited how able this review was in interpreting these findings.

The lack of research exploring the relationship between nurses stress

and burnout and their relationship with weight bias is interesting given that

both stress and burnout is extremely common in UK nurses (Heinen, 2013).

This high level of stress may relate to the NHS’ current financial difficulties

(NHS Employers, 2009) including the reality of privatization (Health and

Social Act, 2012) and associated problems with workload and low staff

morale (Kings Fund, 2015). Intergroup theories of prejudice such as

Relative Deprivation Theory (Stouffer, Suckman, DeVinney, Star &

Williams, 1949) suggest that at times of social change, group members may

strive to re-evaluate the position of the group (Moghaddam, 2002). If social

changes are deemed unfair in relation to the social group the person situates

themselves within then they may act out frustration or anger towards the

30

‘other’ (Smith, Pettigrew, Pippin & Bialosiewiczi, 2011). In a climate where

resources are scarce, the impact of this on nurses is clear in relation to the

highlighted levels of stress and burnout. It is possible that displaying such

frustration in the form of negative attitudes towards more vulnerable ‘out’

groups such as patients with obesity is likely. The research clearly states that

many nurses are stressed and burnt out and that they often hold negative

attitudes towards obese patients, yet currently, there is no clarity about the

relationship between the two.

Reviewing the research on self-esteem in healthcare professionals and

weight bias also did not clarify the relationship between them. This may in

part relate to the limited research found but may also in part relate to the

more individual approach taken to understanding self-esteem which may not

have captured self-esteem in the social context it is generally seen within

attitudes research. For example, in considering how an individual may feel

about him or herself, the definition must invariably be situated within a

social context. To acknowledge a person as ‘average’ or ‘over’ weight, a

comparison to what is considered ‘normal’ or ‘over’ weight, thus to the

normative reference group of which that weight category represents, must

be made. In other words, an individual can only be average, under or over

weight in relation to another. Indeed, from a Social Identity Theory

perspective (Tajfel & Turner, 1986), the social comparisons that are made

between the individual and those from other group memberships help

develop and maintain a sense of identity (Brewer, 1979) by positively

differentiating characteristics of their own social group from the

characteristics of the ‘outside’ comparison group which are generally

31

devalued (Tajfel & Turner, 1986). Thus there is a strong element of de-

valuing attitudes towards others serving a function for the benefit of the

individual’s own self-esteem which cannot be ignored.

However, individuals often operate within numerous social groups at

one time and thus have numerous social identities and group memberships

(Hogg & Abrams, 1988). The social group the individual is interacting

within provides the context for the person’s social identity at that time

(Torrey, 2013). However, this is problematic when two social identities

oppose each other. For example, nurses belong to an elite group of

healthcare professionals (Torrey, 2013) symbolized as role models to their

patients and are often expected to meet the social norm for their own body

weight (Brown, Stride, Psarou, Brewins & Thompson, 2007). To be part of

such a respected group representing good health yet also to be overweight or

obese, a group generally personifying poor health (Torrey, 2013) represents

a significant conflict in identity. Social Identity Theory (Tajfel & Turner,

1986) argues that individuals gravitate towards the most well thought of part

of their identity, thus suggesting that nursing identity is likely to be more

salient than a weight related identity one, potentially giving rise to nurses

treating patients with obesity as the ‘out-group’. However, other research

suggests that people are likely to continue to identify with their in-group and

increase their commitment to its cause even if it is relatively low status

(Ellemers, Spears & Doosje, 1997). Thus, despite self-esteem being central

to theories of prejudice for some time (e.g. Tajfel & Turner, 1986), there

remains many arguments about exactly how it actually fits within these

theories along with debates about the evidence for such assertions (Abram

32

& Hogg, 1988; Brown, 2005; Rubin & Hewstone, 1999). Although current

understandings of the relationship between self-esteem and prejudice are

more comprehensive (Hogg & Smith, 2007), the evolving history is likely

reflected in the limited and inconclusive results of these study.

In considering the impact of group identity on prejudice, the cultural

narrative surrounding nurse identity should also be considered. It is visible

from the results of this review that even in studies suggesting that nurses

that did show weight bias towards patients with obesity, the effect sizes

were often relatively weak and the overall reported attitudes were actually

neutral or slightly positive (Geckle, 2001; Garcia, 2012). In the context of

Social Identity (Tajfel & Turner, 1986), nurses discriminating against

certain groups do not fit with their ascribed identity, for example, as the face

of compassion to patients and their families (Peplau, 1991). Thus, a nurse

openly ‘owning’ negative attitudes towards patients with obesity would

create a conflict between these identities and threaten their own assured

identity as a nurse. As such, weak or non significant relationships between

weight bias measures and the variables explored may represent the social

desirability bias required to protect their identity as a nurse rather than a true

representation of weight related attitudes. Further research may consider the

use of implicit as well as explicit measures of weight bias to produce more

consistent and accurate results.

However, changing the methodology to hone consistency assumes that

consistency is the benchmark to achieve, a benchmark that critical social

psychologists would likely disagree with (e.g. Potter & Wetherell, 1987).

For example, more discursive approaches suggest that inconsistent results

33

are to be expected and are a normal part of the variation that occurs within

language depending on its function (Potter & Wetherell, 1987). As such, it

is not unreasonable to suggest that inconsistencies will occur between

individuals as well as within them and indeed the ability to accept

variability as an expected part of language allows for a richer analysis of

human experience. In relation to the cross sectional methodologies typically

used within the weight bias literature, critical social psychologists argue that

they restrict variability in an attempt to locate consistent attitudes but that in

doing so they may misinterpret what is real, in favour of what is the same

(Potter & Wetherell, 1987). Therefore, in this context, the inconsistent

results found in this review, may arguably suggest that answering the

questions posed in the studies reviewed may have different functions

dependent on the differing context in which individuals were responding

from within. Given the wide range of cultures, countries, healthcare systems

and time periods of studies, this review located, it is possible that the

inconsistent results do indeed relate to this.

Various theoretical frameworks have been used within the attitudes

literature generally and in some cases, more specifically within the weight

bias literature. Although the literature within attitudes research has tended to

ground its research within, both traditional and more recently critical social

psychological approaches, the weight bias literature that is grounded in

theory, has tended to remain within the more traditional or experimental

social psychology paradigms. However, in examining the research within

this review, although some of the more recent studies were underpinned

with relevant theory (e.g. Torrey, 2013), often they were not. This meant

34

that it was difficult to situate the research that was reviewed within current

theory. The limited literature located for each variable was problematic as it

meant that in order to conduct a comprehensive review, literature was

reviewed of varying quality. This made it difficult to interpret the findings

accurately and compare studies systematically. As such, contextualizing the

literature reviews findings within the wider research was difficult.

Conclusion

In conclusion, this review aimed to examine the research focusing on

the relationship between nurses’ own BMI, qualification status, self-esteem

and stress with weight bias towards patients with obesity. The results found

that within some areas, such as when examining BMI, the results were

contradictory. In other areas, such as with qualification status, self-esteem,

stress and burnout, there was limited research conducted within nursing

populations and thus the wider literature was included in order to make

sense of findings. As such, the disjointed nature of both the historic and

current research in this area has been highlighted. This may relate to the fact

that studies are often not grounded within the theoretical frameworks

commonly used within the wider literature on attitudes which means making

sense of them in the context of prior or wider research difficult. This is

despite attempts to highlight theoretical frameworks and their evidence base

within the weight bias literature (e.g. Puhl & Brownell, 2007). Although

there are criticisms of traditional social psychological approaches to

attitudes, within the wider weight bias literature, these approaches have

been more commonly used. As such, before considering the appropriateness

of alternative approaches to understanding attitudes, drawing together the

35

research using a traditional social psychological framework may be helpful

prior to considering where the focus of future research should lie and the

most useful theories to underpin this within.

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50

Appendix 1 – Quality Appraisal Tools

Strobe Checklist

51

Appendix 1 (Continued)

52

Appendix 2 – Study quality analysis summary tables Authors (year)

Aim Location

Design Sampling Response rate

Instruments Reliability Comments

Bagley, Conklin, Isherwood, Pechiulis & Watson (1989)

To develop a scale to measure nurses attitudes about obese patients

USA Cross validation study

107 RN graduate nurses Convenience sample.

N/A Measure of dissatisfaction of own body image isn’t specified Questionnaire not named, but subscales include 15 item Nursing Management Scale and 13 item Personality and Lifestyle Scale,

Psychometricproperties not provided.

Nurses who were dissatisfied with their own body weight were linked to negative attitudes towards obese patients (r= -.26) hospital effect was found (p<.05) independent of age and education.

Brown, Stride, Psarou, Brewin & Thompson, 2007)

Does BMI relate to negative attitudes towards obese patients in nurses?

UK Cross sectional survey design

564 nurses across four Primary Care Trusts. Convenience sample

72.3% Questionnaire developed by researchers.

a= .69 Weak positive correlation r= 0.12 (higher BMI less negative attitudes)

Culbertson & Smolen (1995)

Exploring the effects of RN students demographic variables on their attitudes toward obesity

USA Cross sectional survey design

73 nurse students Convenience sample.

N/A Self reported whether they thought needed to loose 10IB or not BMI! NATOAP (Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989b). Internal reliability.92

a= .92 No statistical significant difference in attitudes between those needing/not needing to loose 10Ib.

61

62

Appendix 2 – Quality analysis summary tables (Continue)

Authors (year) Aim Location Design Sampling Response rate

Instruments Reliability Comments

Garcia (2012) Assessing weight bias in nursing staff

USA Cross sectional survey design

113 nurses Convenience sample across three hospitals.

42.9% BMI calculated from self reported weight and heightNATOOPS (Watson, Oberle & Deutscher, 2008).

a = .97Individual subscales between .83 & .97

Weak positive correlation between BMI and weight bias p= -.121 (higher BMI less negative attitudes). One controllability factor statistically significant with underweight nurses having more bias p<.05

Geckle (2001) Assessing the relationship between nurses perception of their weight & attitudes towards patients with obesity

USA Cross sectional survey design

300 nurses

Convenience sample

44.7%. ANTOAP (Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989a) questionnaire. Chronbach alpha 0.97, individual subscales between .83 and .97Weight categorised by weight category groups

a = .97Individual subscales a = .83 & .97

Significant difference between appropriate weight & overweight group and their attitudes p<.05 (overweight more positive) No effect size reported.

Lilliot (2000) Is there a relationship between nurse BMI and attitudes towards obese patients?

USA Cross sectional survey design

143 nurses Convenience sample across three sites.

29%. BATOS (Bray, 1972) a= 0.74 in previous studies

Weak positive correlation r=.17 (higher BMI less negative attitudes)

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Appendix 2 - Quality analysis summary tables (Continued)

Authors (year)

Aim Location

Design Sampling Response rate Instruments Reliability

Comments

Poon & Tarrant (2009)

To examine the attitudes of registered and undergraduate nurses towards obesity

China Cross sectional survey design

352 undergraduate nurses199 registered nurses

88% recruited over two years due to recruitment issues

ATOAP (Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989a) reliability .79 and Fat Phobia Scale (Bacon, Scheltema, Robinson, 2001).

a = .79

a= .82

The data for BMI is not shown but overall there were no significant differences on ATOAP p=0.29 or FPS p=0.08 and BMI, sample to detect small effect. Registered nurses showed more weight bias but were also older, not controlled for.

Puhl, Leudicke & Grilo (2013)

To examine weight bias among trainee health students in relationship to characteristics such weight, shape and self esteem

USA Cross sectional survey design

107 postgraduate healthcare students, range of professions, recruited at university,

91% EDE-Q, (body image concerns)Rosenberg Self-esteem scale (Rosenberg, 1965), UMB-FAT (Latner, O’Brien & Durso 2008),

a =.94 a =.88,

a =.87

Self-esteem was not correlated with attitudes questionnaire. It was correlated with four outcome variables, including perceived weight bias but none significant. EDE-Q was significantly associated with perceptions of weight bias in HC setting.

64

Appendix 2– Quality analysis summary tables (Continue)

Authors (year)

Aim Location

Design Sampling Response rate Instruments Reliability

Comments

Torrey (2013)

Assessing weight bias in nursing staff

USA Cross sectional survey design

114 nurses, systematic sampling, sent questionnaire through post.

31% NATOOPS (Watson, Oberle & Deutscher, 2008).

a = .45- .78

Higher BMI associated with more bias.As body image guilt and shame increased so did negative attitudesBMI, guilt and shame not controlled for

Young (1985)

Differences in attitudes toward obesity between obese and non obese nurses

USA Cross sectional survey design

59 female nurses recruited from one federal hospital Convenience sampling

N/A The Obesity QuestionnaireMetropolitan Life Insurance Company’s desired weight standards (1959)

Overall reliability reported as r=.58

Mann-Whitney U test suggested no stat sig difference between obese and non obese participants (mean 31.31/29.43, no effect sizes reported

65

Part 2

MRP Empirical paper

A mixed methods study exploring

weight related bias in

undergraduate and qualified nurses

Word Count: 9998

Abstract

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There is good evidence to suggest that nurses’ bias towards patients

with obesity has adverse psychological and physical health implications for

patients in terms of poorer care from healthcare staff and the avoidance of

healthcare. Despite important clinical implications the literature yields no

consensus about specific factors relating to weight bias and no consistently

used theoretical framework to interpret findings. Therefore this study aimed

to draw on intergroup theories of weight bias to explore the relationship

between weight bias in nurses and their self-esteem, BMI, qualification

status, stress and burnout.

The study used a cross sectional mixed method design, involving an online

survey using standardized weight bias, self-esteem, stress and burnout

measures and an open ended question about bias. Participants were 218

undergraduate and postgraduate nurses practicing within the United

Kingdom.

There was no evidence of weight bias and hence limited correlations

detected between weight bias and self-esteem, BMI, qualification status,

stress and burnout. Analysis of the open-ended responses suggests that

social identity may influence weight bias, and the conceptual frameworks

that nurses use to make sense of obesity.

The used of standardised measures to explore factors relating to

weight bias did not add clarity to the literature. However, qualitative data

in this study enabled a better understanding of the complexity of attitudes

towards obesity. Attitudes are portrayed in the context of a hierarchy of

complex social identities situated within a broader social context. The

qualitative analysis revealed that both these issues may make it difficult for

nurses to ‘own’ more negative attitudes, which may explain the inability of

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more restrictive survey design methodologies to reveal the complexity of

attitudes within a social context. Future research that uses methodologies

that enable exploration of the complexity around the nursing role may

further enhance our understanding of weight bias in nurses.

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Historically, prejudice towards marginalized social groups has been

explicitly expressed (Sears, 2007). Brownell and Fairburn (1995) suggest

that more recently overt prejudice and discrimination have become subtler

and less acceptable. However, prejudice towards people with obesity has

remained explicit, suggested to be the last acceptable form of prejudice (e.g.

Puhl & Heuer, 2009) even exceeding that of other marginalized groups

including race and gender (Andreyeva, Puhl & Brownell, 2008).

Prejudice towards people with obesity is well evidenced across a

range of social contexts, including education (Puhl & Brownell, 2001),

employment (Puhl, Henderson & Brownell, 2005), and the media (Yoo,

2013). Equally, within healthcare, weight bias is pervasive across a range of

professional groups (see Phelan, Dovidio, Puhl, Burgess, Nelson, Yeazel,

Hadreman, Perry & van Ryn, 2013; Bleich, Bandara, Bennett, Cooper &

Gudzune, 2014). Of particular concern is the convincing evidence that

nurses hold negative attitudes towards patients with obesity, viewing them

as overindulgent and lazy (Brown, 2006), and feeling hostile and angry

when caring for them (Crandall et al, 2001). As frontline professionals

spending the most time directly caring for patients of all healthcare

professionals (National Audit Office 2001), there is a real concern that such

attitudes may translate into poor clinical care and patient experience.

The evidence suggests that healthcare staff who display weight bias

demonstrate less respect for patients with obesity (Puhl & Heuer, 2009),

spend less time caring for them (Swift, Hanlon, El-redy, Puhl &

Glazebrook, 2013), less time discussing treatment options with them and are

less likely to provide intervention (Forhan, 2013). They also provide

preventative health screening less often comparatively to those of an

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average weight (Bertakis & Azari, 2005). They do not provide appropriate

resources to help accommodate patients’ size as often or as willingly (Amy,

Aalborg, Lyons, Keranen, 2006).

In addition to the psychological implications of such bias on the

patient with obesity, which include lower self-esteem, poorer mental health

and an increased risk factor in the likelihood of suicide (Puhl & Heuer,

2009), there are also significant physiological clinical implications. Obese

men are five times, and woman thirteen times, more likely to develop type

two diabetes than non-obese men and woman (Department of Health, 2011).

There are increased risks for cardiovascular disease (de Koning, Merchant,

Pogue & Anand, 2007), asthma (Beuther & Sutherland, 2007) and various

cancers (e.g. Renehan, Tyson, Egger, Heller & Zwahlen, 2008; Larsson,

2007). The physical co-morbidities (Department of Health, 2011) associated

with obesity are significant in relation to weight bias because patients

experiencing such bias are less likely to engage with health services (Hebl

& Xu, 2003) and increase unhealthy eating behaviours (Schvey, Puhl, &

Brownell, 2012). As such, presenting co-morbid conditions are more

advanced and difficult to treat by the time the person accesses services

(Phelan, Burgess, Yeazel, Hellerstedt, Griffin & van Tyn (2015). Moreover,

when the patient does access services they may be less adherent to

prescribed treatment and self care (Cohen, Steele & Ross, 1999), further

reducing treatment success. Thus, the combination of poorer care from

healthcare professionals and the avoidance of healthcare from the patient

risks serious complications (Haslam & James, 2005).

Despite the clarity surrounding the clinical implications of weight bias

in healthcare and in nurses, a recent comprehensive review suggests that the

70

research is surprisingly fragmented (Goad, 2016). The focus of research is

variable and has identified no specific factors that unanimously relate to

weight bias. In fact, the results of these studies have often contradicted each

other, for example when exploring the relationship between weight bias and

nurses BMI (e.g. Garcia, 2012 & Torrey, 2013).

The variability in research and contradictions in findings may relate to

the lack of a coherent body of theory that interprets of findings. A variety of

theoretical frameworks have been utilized to underpin weight bias (see Puhl

& Brownall, 2003 for a review). For example, Attribution Theory (Crandall,

2001) and Social Identity Theory (Tajfel & Turner, 1986) but these have not

been used consistently to conceptualize studies in relation to earlier research

making the bigger picture harder to understand.

Any exploration of the attitudes of nurses towards patients with

obesity involves exploring the attitudes of one social group towards

members of another; thus a theoretical framework that incorporates

intergroup theories of prejudice would seem logical. One theory with

explanatory potential is Social Identity Theory (Tajfel & Turner, 1986)

which posits that discrimination may occur due to group processes (Rubin &

Hewstone, 1998). One of Social Identity Theories key hypotheses suggests

that group members protect or enhance their own self-esteem through

positive identification with the in-group; often achieved through

discrimination against the out-group (Martiny & Rubin, 2016).

Yet, despite self-esteem being indicated at the heart of prejudice and

discrimination (Tajfel &Turner, 1986) the only study explicitly exploring

self-esteem in healthcare professional trainees found no association with

weight bias (Puhl, Leudicke, & Grilo (2013). However, tentative

71

relationships have been found between weight bias and other factors relating

to self-esteem such as lower levels of body dissatisfaction (e.g. Bagley,

1989) or body guilt and shame (Torrey, 2013). Research outside of

healthcare also suggests that students with lower self body image have

higher levels of implicit, and explicit weight bias mediated by downward

social comparison (O’Brien, Hunter, Halberstadt & Anderson, 2007). Thus,

although people may compare themselves favorably against patients with

obesity in order to improve their own view of themselves, the impact of

self-esteem itself on weight bias remains unclear.

An individual’s physical appearance has been linked to self-esteem

(Crocker, Luhtanen, Copper & Bouvrette, 2003), for example with much

more research exploring weight bias and nurses own weight (e.g. Garcia,

2012; Geckle, 2001; Poon & Tarrant, 2009), although the rationales do not

generally relate to the self-esteem hypothesis (Tajfel & Turner, 1986).

However, one study (Torrey, 2013) exploring the relationship between BMI

did so, highlighting the conflict between the ‘in-group’ membership of a

nurse, often held in high esteem as a health promoter, and the characteristics

of those who are also overweight or obese which would simultaneously

place them in the out-group (Torrey, 2013). The salience of group

membership as well as group identification is key in determining how

attitudes are expressed towards the ‘out-group’ (Hogg & Smith, 2007). Thus

the salience and identification of a nursing identity versus a weight related

identity may determine the expression of the nurses attitudes towards

patients with obesity. However, the complex interplay of these identities and

their expression is often unclear, perhaps explaining why previous studies

have been contradictory with some suggesting that as nurse BMI increases

72

weight bias decreases (Brown, Stride, Psarou, Brewin & Thompson, 2007;

Garcia, 2012; Geckle, 2001; Lilliot, 2000), as nurse BMI increases, weight

bias increases (Torrey, 2013) and some indicating no relationship at all (e.g.

Culbertson & Smolen, 1995; Poon & Tarrant, 2009; Young, 1985). The lack

of theoretical underpinning in many studies makes deciphering these mixed

findings difficult.

If, alongside group salience, group identification partially predicts

how attitudes are expressed towards out-groups (Hogg & Smith, 2007), then

exploring the strength of identification with nursing membership in relation

to weight bias is imperative. Although not situated within intergroup

relations theory, one study did explore the differences between qualified and

student nurses and weight bias (Poon and Tarrant, 2009). Debatably,

qualified nurses may be expected to identify with their nursing identity more

strongly than those in training and thus more weight bias may be expected.

This study did indicate that qualified nurses held more weight bias than

nurses in training thus aligning with this hypothesis. However, the

undergraduate nurses were also significantly younger than qualified nurses,

and thus the interplay with age should be considered, particularly as the

literature on weight bias and age in healthcare staff is also contradictory

(e.g. Bagley, Conklin, Isherwood, Pechiulis, Watson, 1989; Wise, Harris &

Olver, 2014; Miller et al., 2013).

Finally, traditional attitudes research has been heavily criticised for its

lack of focus on the wider social context, instead favouring attitudes as

internal cognitive representations (Hogg & Smith, 2007). The reality is that

the changes in modern society are numerous and rapid (Rogers, 2003) and

do of course influence attitudes held within groups (Prislin & Wood, 2005).

73

This is particularly true in the context of the NHS, where the organization is

constantly facing restructuring and monetary cuts (Warner & O’Sullivan,

2014) translating to high staff turnover, increased workloads and staff

shortages (Van Bogaert et al., 2009). With 30% of staff sickness within the

NHS related to stress (NHS Employers, 2009); nurses are likely struggling

with those pressures. Burnout is also increasingly common, for nurses

globally (McFeely, 2007). In the UK the rate of reported burnout in nurses

is 14% higher than the European average (Heinen et al., 2013).

In times of monumental change within the NHS, Relative Deprivation

Theory (RDT; Stouffer, Suckman, DeVinney, Star & Williams, 1949),

recently seen within the realm of intergroup theories of prejudice, suggests

that in times of social change, group members are continually re-evaluating

the position of their group (Moghaddam, 2002). If re-evaluation deems the

impact of social change as a) disadvantageous and b) unfair, then members

are likely feel increased frustration to which they may respond (Smith,

Pettigrew, Pippin & Bialosiewicz, 2011). If group members experience the

impact of this personally (Walker & Smith, 2002); they are likely to feel

more stressed on an individual level, but if it threatens their group identity

they are more likely to exhibit prejudice towards other groups (Walker &

Smith, 2002). Theories preceding Relative Deprivation Theory (e.g.

Dollard, Doob, Miller, Mowrer, & Sears, 1939) have suggested that such

frustration is rarely expressed towards the actual perpetrator of the

perceived deprivation but is often displaced on to more vulnerable groups

(Brown, 1995). In the context of nurses, it may be patients with obesity who

are targeted because they are more easily accessible for blame than the

wider political system and they may represent an increased workload, which

74

is then used to justify the negative attitudes directed towards them. Research

unequivocally suggests that many nurses are highly stressed (NHS

Employers, 2009) and burnt out (Heinen et al., 2013). It also indicates that

they may hold negative attitudes towards patients with obesity (Brown,

2006). Yet despite grave concerns about the impact on clinical care, no

research has explored the relationship between stress and burnout in relation

to weight bias in nurses.

Research rationale

Negative attitudes towards patients with obesity are well evidenced

(e.g. Brown, 2006) alongside the serious clinical repercussions of that bias

when exhibited by nurses (Haslam & James, 2005). Yet despite this, there

appears to be no clear pattern that explains or predicts this bias. This may in

part relate to the lack of consistent theoretical frameworks underpinning

weight bias research conducted so far. However, attitudes research has often

historically been situated within intergroup theories of prejudice (e.g.

Stouffer, Suckman, DeVinney, Star & Williams, 1949; Tajfel & Turner,

1987). As such, this study draws on intergroup theory to explore the

relationship between weight bias and self-esteem, BMI, qualification status,

stress and burnout using a mixed method design.

Research questions

1) Is nurse self-esteem associated with weight bias?

2) Is nurse BMI associated with weight bias?

3) Are there differences between undergraduate and qualified nurses and

weight bias?

4) Is nurse stress associated with weight bias?

5) Is nurse burnout associated with weight bias?

75

Method

Design

A cross-sectional mixed method design was employed comprising an

online survey using standardized questionnaires plus a demographic

questionnaire with one open-ended question enabling participants to provide

unconstrained responses.

Participants

Undergraduate and qualified adult nurses were contacted through one

local NHS Foundation Trust, undergraduate and postgraduate nursing

programmes at two UK universities, and through nursing groups on the

social network sites Twitter and Facebook.

Eligibility criteria

English speaking adults enrolled on adult nursing programmes within

the UK or qualified adult nurses currently practicing in the UK were eligible

to participate.

Sample Size

Statistical power calculations using G* Power 3.1.7 (Faul, Erdfelder,

Buchner & Lang, 2009) were conducted in order to establish the sample size

needed to detect a medium effect size as detected in prior studies (e.g.

Brown, Stride, Psarou, Brewins & Thompson, 2007) when using the

relevant statistical analysis. The power analysis calculated that a sample size

of 109 participants per group (student and qualified nurses) were required

for analyses comparing groups in order to achieve a power of 80% and

detect a medium effect between variables at the 5% level using a two-sided

test. For correlation analyses the power analysis suggested that a sample

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size of 82 participants overall would detect a medium effect at the 5% level

using a two-sided test (see appendix 1).

Participant demographic information (appendix 2)

In total, 218 nurses completed the questionnaires of which 113 were

undergraduate nurses and 105 were qualified nurses. Seventeen were male

(7 undergraduate and 10 qualified nurses) and 201 were female (106

undergraduate and 95 qualified). The mean age across all 218 participants

was 32.02 (±11.36) with a mean of 26.8 (±9.1) for undergraduates and 37.66

(±10.99) for qualified nurses. The majority of the participants were white

British (84 undergraduate and 78 qualified nurses) although a small number

of other ethnicities were represented. The mean BMI for the 218

participants was 25.63 (±4.73), for undergraduate nurses was 24.7 (±4.5)

and for qualified nurses was 26.7 (±17.4).

Of 218 data sets, 197 were complete and 21 were incomplete with

the demographic and Anti Fat Attitudes (AFA) questionnaires completed

but missing data amongst all of the other questionnaires (see appendix 3).

However, as the AFA questionnaire was the only questionnaire required in

comparison of undergraduate and qualified nursing groups, this did not

reduce the power of the study.

Ethical Considerations

Ethical approval was granted by The Faculty of Health and Medical

Science at the University of Surrey, the University of the West of England

(appendix 4) and through the local NHS Research and Development

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approval process (appendix 5). The study was conducted in accordance with

the Code of Human Research Ethics (British Psychological Society, 2010).

Procedure

Data was collected between December 2015 and May 2016.

Participants were recruited from two universities through emails containing

the study link, online learning portals, poster advertising and lecture

attendance by the researcher for adult undergraduate and postgraduate

nurses (appendix 6). Participants were also recruited from one local hospital

site through email distribution and poster advertisements as well as

circulated on nursing group social networks including Facebook and

Twitter. Advertising emails were re-circulated monthly to improve response

rates. Participants could opt in to the online survey by clicking on the link to

the survey included with the advertisements. The study was configured to

ensure that the information sheet (appendix 7) was presented first, followed

by the consent form (appendix 8). Participants were required to confirm

consent online prior to being able to access the survey. Participants were

offered the opportunity to provide their email address in order to receive a

summary of the results or to be entered in to a prize draw for one of five £20

Amazon vouchers. On completion links to organizations able to provide

emotional support were provided in the event of any emotional distress

caused (see appendix 9).

Measures

The survey was developed to include a set of self-administered

questionnaires aimed at capturing information on participant demographic

information, attitudes about obesity, self-esteem, perceived stress and level

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of burnout. Measures were chosen based on the strength of their

psychometric properties as described in current and relevant literature; as

well as their suitability for use with a nursing population accessing them

online. A participant demographic questionnaire was developed by the

researcher to gather the basic information required for the analysis

(appendix 10). An unrestricted character text box was provided to facilitate

the participant’s responses to the question, ‘what are your views on why

nurses might hold negative attitudes towards patients with obesity?’ The

standardized questionnaires (appendix 11) are described below in the order

they were presented to the participants.

Anti Fat Attitudes (AFA) questionnaire (Crandall, 1994)

This 13-item assessment of anti-fat attitudes, has three subscales,

‘Dislike,’ ‘Fear of Fat,’ and ‘Willpower.’ Participants were required to

indicate their level of agreement on a scale of 0 (very strongly disagree) to 9

(very strongly agree). The AFA has shown good internal reliability on all

three subscales with coefficient alphas of .88, .88 & .72, respectively

(Robinson, Ball & Leveritt, 2014).

Attitudes towards Obese Persons (ATOP) (Allison, Basile & Yuker,

1991)

This 20-item questionnaire is a general measure of attitudes towards

people who are obese including attitudes towards their quality of life,

personality and self-esteem. Participants indicate their agreement to each

statement on a scale of -3 (strongly disagree) to +3 (strongly agree).

Coefficient alphas ranging from .8 to .84 across populations indicate its

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reliability (e.g. Puhl & Brownell, 2006; Brewis & Wutich, 2012). It has

good construct validity, correlating positively with the Beliefs about Obese

Persons Scale (BAOP) (r=.4, p<.05 ) (Allison, Basile, & Yuker, 1990).

Rosenberg’s Self-Esteem scale (RSE) (Rosenberg, 1965)

This widely used measure (Donnellan, Trzesniewski, & Robins, 2011)

is a 10 item scale with item responds represented on a four point Likert

scale. Substantial evidence supports the predictive validity and internal

reliability of the scale both historically (i.e. Byrne, 1983 & Kaplan, 1980)

and recently (Sinclair, Blais, Gansler, Sandberg, Bistis & LoCicero, 2010).

More recent studies cite coefficient alphas of .88 and good construct validity

with the RSE positively correlating with optiminism (r=.44, p <.5) and

negatively with shyness (r= -.26, p<.28) (Robins, Hendin & Trzezniewski,

2001). The scale is validated in nursing (Takase, Yamamoto, Sato, Nittani &

Uemura, 2015) and UK populations (Bagley & Mallick, 2012).

Perceived Stress Scale (PSS) (Cohen, Kamarck, & Mermelstein, 1983)

This 14-item scale measures how participants perceive their own

stress through item responses on a five point Likert scale from 0 (never) to 4

(very often). Its internal consistency using Cronbach alpha is 0.75 and it

shows good construct validity e.g. correlating positively with depressive

symptomology r=.65 and .76, p<0.05 (Cohen, Kamarck, & Mermelstein,

1983).

Maslach’s Burnout inventory (MBI) (Maslach & Jackson, 1981)

This 22-item measure of burnout includes three subscales, emotional

exhaustion, depersonalization and lack of personal accomplishment with

item responses represented using how frequently, from ‘never’ to ‘every

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day’, they related to each item. Reliability coefficients for the emotional

exhaustion subscale were .9, for the depersonalization subscale, .79 and for

the personal accomplishment subscale .71. Each dimension correlated

highly with ratings given by peers who knew the individual well, for

example, the item ‘higher emotional exhaustion’ was positively correlated

with the MBI, (r=. 56, p< .001) (frequency) and (r= .57, p< .001) (intensity;

Maslach & Jackson, 1981) suggesting good convergent validity.

The normative data for each questionnaire, as established by the

respective authors is shown in table 1.

Table 1.

Normative questionnaire data

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Reliability estimates

Table 2 indicates that the majority of the questionnaires and associated

subscales had Cronbach alphas of above .7, deemed within the acceptable

range (Kline, 1999). The Cronbach alphas for the ‘willpower’ subscale of

the AFA and the ‘depersonalization’ subscale on the MBI were slightly

lower than this cut off but may be accounted for by each subscale having a

smaller number of items than their counterparts, a factor known to reduce

reliability estimates (Cortina, 1993).

Table 2.

Reliability estimates. Questionnaire Subscale Cronbach alphaAFA Dislike .888

Fear of Fat .839Willpower .685

Questionnaire Normative questionnaire data AFA dislike Scale based on averages, average score = 5AFA fear Scale based on averages, average score = 5AFA willpower Scale based on averages, average score = 5ATOP total High numbers= more positive attitudes. Score of 60

is average (0-120) RSE Total Higher scores from 0-40 = higher self esteem PSS Total Scores of around 13 are average, scores of 20 are

considered ‘high stress levels’ MBI DP 13 and over = High

7-12 = Moderate0-6 = Low

MBI PA 39 and over = High32 to 38 = Moderate0 to 31 = Low

MBI EE 27 and over = High17 to 26 = Moderate0 to 16 = Low

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ATOP N/A .735RSE N/A .874PSE N/A .837MBI Depersonalization .618

Personal Accomplishment .815Emotional Exhaustion .866

Quantitative analysis

Descriptive statistics were conducted prior to full analysis. An

independent t-test was used to test whether there was a difference in the

AFA weight bias measure between undergraduate and qualified nurses.

Correlational analyses examined the relationships between the two weight

bias measures (AFA and ATOP), the measure of self-esteem (RSE),

perceived stress (PSS) and burnout (MBI).

Qualitative analysis

A qualitative methodology was chosen to complement the quantitative

methodology due to a longstanding critique of quantitative methodologies in

attitudes literature which holds reservation about both experimental and

survey designs in representing ‘attitudes’ (see Potter & Wetherell, 1987).

Qualitative methodologies allow for a deeper level of analysis in relation to

understanding human experience (Harper & Thompson, 2012) and do not

seek to restrict data in the way that traditional quantitative methodologies do

(Rogers, Stenner, Gleeson & Rogers, 1995) allowing participants to share

their views of nurses attitudes towards patients with obesity in their own

language (see appendix 12 for a summary critique of the attitudes literature).

A range of qualitative analyses were considered (appendix 13) but a

thematic analysis was chosen given the exploratory nature of the study.

Thematic analysis is not attached to any specific theoretical framework

(Braun & Clarke, 2006), allowing it to be used more flexibly as long as its

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chosen theoretical position is made clear. Given the limited theoretical

underpinning of weight bias literature (Zhu, Norman & While, 2011), an

inductive approach was employed to enable a ‘bottom up’ analysis (Frith &

Gleeson, 2004) with the development of themes strongly linked to data

(Patton, 1990). The guidelines established by Braun & Clarke (2006) for

completing a thematic analysis were followed (appendix 14).

Predominantly, themes were detected at a semantic level in the

context of how nurses made sense of negative attitudes towards patients

with obesity. Although thematic analysis primarily focuses on either

semantic or latent themes, latent themes were also detected and were

important in interpreting the data in the context of the research question, and

thus were included and demarcated as such.

Epistemological position

A theoretical position of social constructionism was assumed in

conducting the analysis, seeking to interpret data within the sociocultural

context in which it resides (Braun & Clarke, 2006). It is based on the

assumption that meaning is socially produced rather than the product of the

individual (Burr, 1995).

Researcher position and reflexivity

The social constructionist position assumed also aligns with my own

stance as a researcher and a trainee clinical psychologist. My reflections in

relation to this can be found in appendix 15.

Credibility

This study was conducted in line with Yardley’s four characteristics

indicative of credible qualitative research (Yardley, 2000). The integration

of these principles in the context of this research can be found in appendix

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16. Appendices 17, 18 and 19 also provide examples of the coding themes

alongside the development of each thematic map to aid transparency.

Results

Data screening

A thorough data screening process was undertaken, the full analysis of

which can be located in appendix 202.

Table 3 illustrates the mean scores for each questionnaire/subscale

total for all 218 participants.

Table 3.Mean scores for each questionnaire and subscales.

Questionnaire N Mean (S.D.)AFA dislike average 218 7.5 (1.8)AFA fear average 218 3.8 (2.7)AFA willpower 218 4.3 (2.2)ATOP total 196 70.6 (14.4)RSE Total 198 21.1 (6.1)PSS Total 195 19.4 (4.8)MBI DP 170 4.5 (3.8)MBI PA 185 31.1 (6.3)MBI EE 184 25.8 (8.7)

Table 1 in the methods section illustrate the comparative norms for

each questionnaire. The mean scores in table 3 above suggest that nurses’

attitudes towards patients who are obese were neither negative nor positive

overall. On both the AFA subscales and the ATOP, nurses attitudes fell

close to average (as ‘slightly positive’ or ‘slightly negative’). Nurse’s self-

esteem measured by the RSE was also average. Nurse’s overall perceived

stress was within the ‘high range’ on the PSS. In the measure of burnout

(MBI), low levels of depersonalization were detected in nurses, but

2 The data screening analysis was initially illustrated in the main body of this thesis but can now be located in appendix 20. As such, appendices 21-25 are referenced from within appendix 20 rather than in the main text.

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moderate levels of emotional exhaustion and low levels of personal

accomplishment.

Table 4.

Mean scores for the AFA and the ATOP split by qualification status.

Questionnaire (subscale)

Qualifications status N Mean (S.D.)

AFA (dislike) Undergraduate 112 7.3 (2.0)Qualified 106 7.7 (1.5)

AFA (fear of fat) Undergraduate 112 3.6 (2.9)Qualified 106 4.0 (2.5)

AFA (willpower) Undergraduate 112 4.5 (2.2)Qualified 106 4.1 (2.1)

For research question three, participants were grouped by qualification

status to explore differences in their responses on the AFA. As such, the

means for the qualified and undergraduate nurses separately are illustrated

in table 4. The means between qualification groups combined were very

similar to the means when undergraduate and qualified nurses were

separated.

The Spearman’s correlation coefficient was used for correlation

analyses involving the AFA as the data did not meet the assumptions of

normality required for parametric testing. The second weight bias

questionnaire (ATOP) was analysed using the parametric Pearson’s

correlation as it did meet the parametric assumptions required.

Table 5.

Spearman’s rho for the AFA questionnaire and Pearson’s correlation for

the ATOP when correlated with BMI, RSE, PSS and MBI.

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AFA dislike

AFA fear

AFA willpower

ATOP

BMI Correlation Coefficient

.092 -.004 -.015 .056

Sig. (2 tailed) .174 .955 .828 .435N 218 218 218 196

RSE Correlation Coefficient

-.134 -.189** .091 -.104

Sig. (2 tailed) .060 .008 .202 .146N 198 198 198 198

PSS Correlation Coefficient

-.156* -.142* .040 -.066

Sig. (2 tailed) .029 .048 .575 .358N 195 195 195 195

MBI DP Correlation Coefficient

-.322** -.163* -.098 -.319**

Sig. (2 tailed) .000 .033 .206 .000N 170 170 170 169

MBI PA Correlation Coefficient

.075 -.013 .104 .178*

Sig. (2 tailed) .308 .865 .158 .016N 185 185 185 183

MBI EE Correlation Coefficient

-.067** -.023 .049 -.093

Sig. (2 tailed) .005 . .004 .213N 184 184 184 182

* Correlation significant at the .05 level (2- tailed) **Correlation significant at the .01 level (2- tailed)

Of note, the direction of the ATOP questionnaire is opposite to that of the

AFA, with higher scores meaning more positive attitudes on the ATOP but

equalling more negative attitudes on the AFA. The meaning of the direction

of scores for each questionnaire are represented in table 6 below.

Table 6.

The direction of scores meaning for each questionnaire

Standardized questionnaire Direction of scoring

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AFA (all subscales) Increasing AFA scores across subscales mean higher levels of weight bias.

ATOP Increasing ATOP scores mean lower levels of weight bias

RSE Increased RSE scores mean higher self-esteem

PSS Increased PSS scores mean higher perceived stress

MBI - DP - EE - PA

Increased scores on the MBI subscales mean higher levels of DP, EE and PA.

Research question one: Is nurses own self-esteem associated with their

attitudes towards patients with obesity?

A significant negative correlation was detected between the RSE and

the AFA fear subscale (p <.01), such that as nurses own self-esteem

increased, their ‘fear of fat’ decreased (table 5). However, the correlation

coefficient suggested that the relationship was of a weak to moderate effect3

and the scatter plot representing this correlation (appendix 26) does not

depict a clear relationship between the two variables suggesting that the

magnitude of this result may be small. No relationship was detected

between the RSE and second two AFA subscales, dislike and willpower

(p>.05). The Pearson’s correlation conducted on the RSE and the ATOP

was non-significant (table 5), which suggests that there was no relationship

between nurses self-esteem and their overall attitudes towards patients who

are obese (p>.05).

Research question two: Is nurses own BMI associated with the attitudes

they hold towards patients with obesity?

Questionnaire Qualification status

N Mann-Whitney U

Z Asymp. Sig (2- tailed)

3 The correlation coefficient is considered to be a standardised measure of the observed effect and thus may be used as an effect size. A small effect is represented to be <.1 or <-1, a medium effect is represented by .1 to .3 or -.1 to -.3 and a large effect .3-.5 or -.3 to -.5.

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AFA (dislike) Undergraduate 112 5091.5 -1.8 .07Qualified 106

AFA (fear of fat)

Undergraduate 112 5264.5 -1.4 .1

Qualified 106AFA (willpower)

Undergraduate 112 5310.5 -1.3 .2

Qualified 106ATOP Undergraduate 112 4110.00 -1.5 .1

Qualified 84Table five shows no significant relationship was detected between

nurses own BMI and each of the three subscales on the AFA (p>.05). The

Pearson’s correlation replicated this result suggesting no relationship

between nurses own BMI and the ATOP (p>.05).

Research question three: Is there a difference between undergraduate

and qualified nurses in their attitudes towards patients with obesity?

No significant difference was detected between the ATOP or each of

the three AFA subscales and qualification status, p > .05, suggesting that

attitudes towards patients who are obese do not differ between

undergraduate and qualified nurses (table 7).

Table 7.

Mann-Whitney U Test - differences between qualified and undergraduate

nurses attitudes towards patients with obesity.

Research question four: Is there an association between nurses

perceived levels of stress and their attitudes towards patients with

obesity?

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The Spearman’s correlation (table 5) indicated that there was a

significant negative correlation between the PSS and the AFA dislike

subscale (r = -.156, p <.05) and also between the PSS and the AFA fear of

fat subscale (r = -.142, p <.05). This indicated that as dislike and fear of fat

attitudes increased, perceived stress decreased. However, the correlation

coefficients suggested a weak to moderate effect and the scatter plot

representing each correlation (appendix 26) did not depict clear

relationships between each of the two variables. No significant relationship

was detected between the PSS and the AFA willpower subscale (p>.05).

The Pearson’s correlation conducted (table 5) between the PSS and the

ATOP was non-significant indicating that there was no relationship between

nurse’s overall attitudes towards obese patients and their perceived level of

stress (p>.05).

Research question five: Is there an association between nurse’s level of

burnout and their attitudes towards obese patients?

The Spearman’s correlation indicated (table 5) that there was a

significant weak to moderate correlation between the AFA dislike subscale

and the MBI DP subscale (r = -.322, p < .01) such that as depersonalization

decreased, dislike towards the person increased. There was a weak

correlation between the AFA fear and the MBI DP subscale (r = -.163, p

<.05) such that as ‘fear of fat’ increased, level of depersonalization

decreased. No significant relationships between the AFA willpower

subscale and the MBI DP subscale (p >.05) or any of the AFA subscales and

the MBI PA and EE subscales (p >.05) were detected.

The Pearson’s correlation between the MBI and the ATOP indicated a

significant weak to moderate negative correlation between the MBI

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depersonalization subscale and the ATOP (r = -.319, p < .01) such that as

level of depersonalization reduced, ATOP attitudes became more positive

(higher scores equal more positive attitudes). There was also a significant

weak positive correlation between the MBI PA, and the ATOP (r = .178,

p>.05) such that as feelings of personal accomplishment increase nurses

attitudes towards patients who are obese become more positive.

The results between the two weight bias measures were contradictory

when correlated with the MBI questionnaire. As such outliers previously left

in were removed and the data re-analyzed but this did not significantly alter

the results (appendix 24).

Thematic analysis

The thematic analysis was conducted on the responses from the

optional opened ended question, ‘what are your views on why nurses might

hold negative attitudes towards patients with obesity?’ This question was

completed by 196 of the 218 participants with responses ranging from 7 to

217 words giving an average of 44.9 words per response. The analysis

revealed six key themes as shown in the thematic map in figure 1 overleaf.

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Wider society

Media

NHS moral discourses

Cultural context

Pragmatics of caring

Lack of resourcesComplicationsIn caring

Acknowledging wider factors Blame

Deservingness

Preventability

Responsibility

Identity

Identity management strategies

De-Identification

Denying impact of attitudes on careStake Inoculation

Weight related Identity

Personal Identity

Nursing Identity

Figure 1.

Thematic map

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The identity theme related to the three identities nurses appeared to

speak from including nursing, personal or weight related identities. Three

themes related to how nurses made sense of their own attitudes, the first

through acknowledging the wider factors that influence obesity and the

second, ‘pragmatics of caring’ theme, related to the nurses experience of the

complexities in caring for someone with obesity. The third was a theme of

‘blame’, particularly relating to beliefs about responsibility, preventing

obesity and the person’s deservingness of healthcare. More broadly, nurses

referred to the narratives held about obesity in the NHS, the media or wider

society; captured in a theme of cultural context. Finally, further analysis

focusing more on latent patterns than on explicitly stated semantic content,

appeared to demonstrate a range of identity management strategies employed

in order to manage the negative attitudes that were expressed.

1) Identity The participants expressed their opinions through three visible

identities; as a nurse, a person, and in relation to their own weight.

a) Nursing identity: The participant’s perception of what it meant to be

a nurse appeared to inform their attitudes towards patients with obesity.

‘I did not become a nurse to judge someone I became a nurse to help them’.

‘As a nurse it is my job to learn their story…’

The participants drew on specific characteristics associated with their

nursing identity such as providing ‘help and support regardless of

appearance’ and of treating all patients ‘the same despite their size.’ They

clearly articulated their view that in their role ‘as a health care professional

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there shouldn’t be negative attitudes’. The nurses’ characterized their

identity as non-judgmental and understanding. However, expressed ideas

about nurses as health promoters with the ‘duty of healthcare staff to gently

highlight or educate the benefits of not being overweight,’ illustrated

instances where judgments were made about the impact of being

overweight.

b) Identity as a person: In addition to drawing on their nursing identities to

inform their attitudes towards patients with obesity, they also drew on their

values as a human being.

‘As humans, we should not judge/discriminate others when we do not know

anything about them’

Here, similar values were cited as those associated with their nursing

identity, for example, treating others ‘equally and with respect.’ However,

these values were explicitly placed in the context of being a human rather

than specifically a nurse, tending to extrapolate out to ‘any people’ rather

than only in the context of their attitudes towards patients:

‘I believe in equal and fair treatment, regardless of race, religion and

certainly appearance i.e. weight.’

Thus of note, both the characteristics associated with the identity as a

nurse and as a person were portrayed positively alongside the associated

attitudes towards obesity.

c) Weight related identity: Nurses identified with their own weight which

impacted on their attitudes towards patients with obesity in different ways.

For example, sometimes more negatively:

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‘I was obese and lost 5.5 stone in 1 year. I get frustrated when people don't

try to lose weight’.

Yet others voicing their own weight struggles having ‘nothing but

empathy’ and thus impacting on their attitudes more positively:

‘It's much easier to understand and be empathetic if you have experienced

it yourself’.

Thus the experience of weight difficulties in itself did not appear to

influence attitudes per se, rather the nurses experience of their own

difficulties did.

2) Acknowledgement of wider factors

Some participants appeared to draw on their knowledge of the

development and maintenance of obesity as more complex and multifaceted

than perhaps the dominant narrative surrounding them might suggest:

‘That some patients may have other more complex reasons for being

obese, other than the assumed self inflicted, lifestyle choice that some

staff may adopt’.

Participants acknowledged a range of factors including ‘medical

conditions’, ‘social circumstances’ and ‘financial difficulties;’ their

acceptance of these alternative explanations appeared protective against

negative attitudes.

‘I do not have a negative attitude towards obese patients as there is

always more to it than people know’

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3) The pragmatics of caring Alternatively, participants often appeared to relate their attitudes

towards patients with obesity to their view of the pragmatic difficulties in

caring for them.

a) Complications of caring: The complexity of caring for a person with

obesity related to both the impact on staff, for example with ‘moving and

handling being more challenging’ as well as ‘turning, washing and wound

dressing’, and also the level of complexity in providing effective care:

‘HCP’s may feel that obese patients, can present a more complex

treatment course than necessary e.g. co-morbidities, heightened risks

or difficult ventilation when in the theatre...’

b) Lack of resources: The lack of a range of resources available to care

adequately for patients with obesity including time, staff, equipment and

funding were often raised:

‘I feel that the need for extra staff in some cases puts strain o nurses

and healthcare professionals and clouds their objectiveness…’

‘Obese patients can add a lot of extra effort onto an already busy

workload’

The complicated nature of caring, the lack of adequate resources to

care and the impact of this on staff were represented through participants

tending to illustrate more negative attitudes within this context.

4) Blame A clear framework of blame permeated the analysis through the

analysis, attributing blame either for the obesity itself or by ‘blaming the

patients for the state of their health’ suggesting that, ‘obesity is a long-term

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condition that is self-inflicted over a period of time’. Three distinct

subthemes, responsibility, preventability and deservingness were each used

in the context of justifying their position of blame.

b) Responsibility: Nurses often attributed blame when they indicated that the

patient with obesity was responsible for their own weight and the associated

health problems.

‘I feel they are not taking responsibility for their own health care such

as people with diabetes shortness of breath or cardiac problems.’

Beliefs about responsibility also extend to ‘abdicated responsibility’

where patients may believe nurses to be responsible for their health rather

than themselves:

‘Some patients do expect us as health care professionals to have all

the answers and solve their problems. They may not always want to do

the hard work themselves.’

c) Preventability: Participants voiced their belief that obesity and its health

consequences were preventable:

‘They may feel that they've made themselves unwell by living an

unhealthy lifestyle and that they could have prevented their illness’

Commonly, the language used indicates that participants could not

only have prevented their health problems if they had adopted a healthier

lifestyle, but that they have actively ‘made themselves unwell’ which may

have then justify taking a position of blame.

d) Deservingness: Beliefs about the extent to which patients with obesity

deserved services were infiltrated through the text, visible through a

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consistent choice of language. For example, ‘using up’ resources, being a

‘waste of resources’ or ‘burdening’ services.

‘Obesity also costs our NHS huge amounts of money each year. Since

nurses are having to campaign and fight for even a 1% pay rise, this

could be seen by many as an unfair spending of money - why spend

millions on treating fat people who hurt themselves when it could be

spent increasing the wages of nurses...’

The beliefs about deservingness often appear to be relational, that is

patients with obesity are less deserving of funding than nurses doing ‘the

hardest job in the world’. Thus deservingness for funding is seen as a direct

competition between groups of patients with obesity and nursing groups.

5) Cultural Context

Participants often directly acknowledged that cultural narratives

influenced their attitudes towards patients with obesity, whether through

moral discourses about the NHS, the media and within wider society.

a) Moral discourse about the NHS: A discourse about the NHS in ‘crisis’

was illustrated throughout the analysis and the discourse itself was directly

acknowledged in relation to obesity:

‘…currently seems to be an acceptable prejudice towards the obese in

the media, where the state of the NHS crisis is blamed on the obese

epidemic’.

At times, narratives about the pressures on the NHS appeared to lead

nurses towards the belief that patients with obesity ‘are slightly resented for

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putting extra pressure on an already stretched workload using up resources

and staff time’.

b) Media: Societal messages about obesity are often delivered through the

media with participants frequently citing ‘a lot of stereotyping by the

media…’

‘…I believe that there are negative messages in the media…who

attributes many health issues with being obese….with the sub text of if

you are not slim/fit you are not trying hard enough…’

Participants indicated that these messages were predominately

negative in relation to identity with common themes around being ‘thin is

beautiful and fat is ugly’ with examples of ‘celebrities who are idolized in

newspapers, magazines etc tend to be slim’. Messages that had

‘conditioned’ them in to believing obesity was ‘wrong’.

c) Wider Society: In addition to the negative messages communicated

through the media, participants were also aware that they were also held in

wider society suggesting that, ‘widespread societal weight bias…affects

most people’. Unsurprisingly these messages were similar to those portrayed

through the media:

‘Thin privilege is a very real and unfortunate thing in our society.’

The participants directly linked the impact of these messages on their

own attitudes towards patients with obesity for example, as they are ‘carried

into the workplace’.

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6) Identity management strategies

Through repeated engagement with the data, another layer of

interpretation emerged that provided an insight into the tolerant and liberal

stance expected of a nurse by acknowledging the negative biases towards

obesity in a context where bias is normalized by cultural discourses. Themes

emerged that appeared to describe strategies used to manage the difference

between the positive identities that nurses had often portrayed alongside the

negative attitudes that they were aware were available to them. Three

separate strategies, stake inoculation, de-identifying, and by justifying

attitudes through denying the impact on care were identified.

a) Stake inoculation: There appeared to be a vested interest in reporting

negative attitudes, but not directly. Often it appeared that negative attitudes

towards patients with obesity where reported in ‘other staff’ rather than the

participants owning the attitudes themselves:

‘Food is an addiction and patients need support with that. However I

feel other staff members do take a more negative approach…’

This, ‘I don’t but others do’ approach was often used as a pre-requisite

to expressing a negative attitude in the form of someone else’s opinion:

‘I personally don't hold any negativity towards obese people, however,

I have heard that some people see obese people as a strain and lazy.’

Participants often then appeared to add their own judgment to this

‘other’ opinion, for example by suggesting that this, ‘of course this is the

wrong way of thinking and highly unprofessional’.

100

b) De-identification: Other ways of managing negative attitudes towards

patients with obesity in relation to their own identity was to directly de-

identify with their nursing identity slightly:

‘We all have our own hang ups, we're only human’.

‘I think it's just human to have certain thoughts go through your mind

and nurses aren't immune to this.’

In de-identifying with their nursing identities the participants actively

appeared to bring forth their identities as people. The pretext of ‘nurses are

humans too’ being that unlike nurses, humans are imperfect and it is perhaps

more acceptable to hold negative attitudes as a human than as a nurse.

c) Denying the impact of attitudes on care: Finally, where participants

acknowledged their own negative attitudes towards patients with obesity it

was often done in the context of being explicit about such attitudes not

impacting on patient care:

‘…these brief thought have never caused me or any colleague I know

to compromise the care of an obese person...’

This perhaps seems to indicate that ‘brief’ negative attitudes towards

patients with obesity are more acceptable as long as they do not impact on

care.

DiscussionThis study aimed to explore weight bias towards patients with obesity

in UK nurses. As there appeared to be no clear pattern in the literature that

explained or predicted this bias, this study explored the relationship between

weight bias and nurses’ qualification status, BMI, self-esteem, stress and

burnout in the context of intergroup relation theories. The analysis of

101

quantitative data failed to identify a simple relationship between a single

factor and weight bias. The qualitative results tentatively suggest that bias

may be understood in terms of a complex hierarchy of interacting social

identities that this discussion will seek to explain.

The findings give a mixed message about the relationship between

obesity and weight bias, with some of the quantitative measures utilized to

help develop a better understanding of this relationship, unable to clarify

this picture. The quantitative analysis indicated that attitudes towards

patients with obesity were reported as neutral on both the AFA and the

ATOP. This is a finding that has been replicated in previous studies (Poon &

Tarrant, 2009) although not consistently (e.g. in Brown, 2006). There were

no significant relationships detected between the AFA and the ATOP with

nurses’ own BMI or qualification status. There was one significant

relationship between the RSE measure of self-esteem and the ‘fear of fat’

subscale on the AFA such that as self-esteem increased, ‘fear of fat’

decreased. There was no relationship between the second two AFA subscale

or the ATOP. The PSS, measure of perceived stress and the AFA ‘dislike’

and ‘fear of fat’ scales suggested that as dislike and fear of fat attitudes

increased, perceived stress decreased. There was no detected relationship

between the third subscale on the AFA or on the ATOP. Finally, there were

contradictions between the AFA and ATOP in relation to the MBI

depersonalization subscale with the AFA ‘dislike’ and ‘fear of fat’ subscales

increasing as the MBI depersonalisation reduced yet on the ATOP weight

102

bias increased as MBI depersonalisation decreased. The significant

relationships that were detected were all of weak to moderate effect.

The suggestion that nurses’ attitudes towards patients with obesity are

neutral is interesting given that there is no dispute in the literature about the

fact that patients with obesity do experience prejudice in healthcare settings

(e.g. Friedman, Ashmore & Applegate, 2008; Merrill & Grassley; 2008;

Puhl & Brownell, 2006). Thus, this anomaly may relate to the complexity of

nursing identity. Nursing has historically struggled with its professional

image (McAllister, Downer & Opresou, 2014) being characterized

differently by the media, politics and within the profession itself (Andrews,

Ferguson, Wilkie, & Simpson, 2009; Santry, 2010). Yet perhaps owing to

the legacy of iconic characters such as Florence Nightingale (McAllister,

Downer & Opresou, 2014), one consistency has been the portrayal of nurses

as self-sacrificing and altruistic (Gordon & Nelson, 2005). With such a

strong historical view on the meaning of nursing still permeating modern

society, nurses may be more vulnerable to social desirability bias in order to

protect themselves from the incongruence weight bias would have with this

ascribed identity. The ramifications for this research are that reported neutral

attitudes do not necessarily indicate that negative attitudes do not exist;

rather that social desirability bias may limit their expression reliably.

However, the idea that the RSE self-esteem scores increased as the

AFA ‘fear of fat’ scores decreased is interesting. Social Identity Theory

(Tajfel & Turner, 1986) suggests that self-esteem is central to prejudice,

originally postulating within the second corollary of its self-esteem

103

hypothesis that ‘threatened self-esteem motivates discrimination’ (Martiny

& Rubin, 2016 p.3). Thus higher self-esteem may reduce the likelihood that

obesity threatens identity, rendering nurses’ comparisons with this perceived

subordinate group unnecessary. Indeed, although limited, previous research

suggests that nurses who feel better themselves in someway (e.g. with

higher body satisfaction; Bagley, 1989, or with lower body image guilt and

shame; Torrey, 2013) are less likely to hold weight bias.

However, the relationship between the AFA ‘fear of fat’ and the RSE

measure of self-esteem was weak. This may relate to the limitations of data

potentially influenced by social desirability bias, but perhaps also to how

self-esteem is constructed within Social Identity Theory (Tajfel & Turner,

1987). In this context, attitudes expressed are to positively distinguish

collective self-image from the alternative group in order to manage social

self-esteem (Rubin & Hewstone, 2004). However, the RSE (Rosenberg,

1965) is a measure of personal self-esteem and may not be sensitive to

testing hypotheses conceptualizing self-esteem socially (Rubin & Hewstone,

2004). There is though a distinct lack of adequate social self-esteem

measures available as many do focus on global, personal self esteem (see

Rubin & Hewstone, 1998) which makes choosing an appropriate measure

difficult.

Moreover, how self-esteem relates to prejudice has long been debated

(Abrams & Hogg, 1988; Brown, 2005; Hogg & Abrams 1990). Since its

inception, their has been limited evidence found for discrimination that is

motivated by the need for self-esteem (see Rubin & Hewstone, 1998) which

104

further confuses the picture as to whether self-esteem relates to weight bias.

More recently, reformulations of this hypothesis may though better capture

its complexity (see Martiny and Rubin, 2016). For example, social norms

play a part in determining the impact of self-esteem in motivating prejudice

(Scheepers, Spears, Manstead & Dooske, 2009), often interwoven with the

individuals personal norms (Hogg & Smith, 2007). The nuanced and

dynamic nature of group norms, subtly fitting with the cultural contexts of

the moment (Hogg & Smith, 2007), indicate that if norms of nurse identity

centre around compassion and altruism; negative attitudes may actually

reduce rather than increase self-esteem as such attitudes represent a

deviation from that particular groups norm.

Overall, the complexity surrounding nursing identity may influence

how openly nurses express their attitudes towards patients with obesity in a

quantitative methodology where they were asked to directly state attitudes

which may force them to confront a conflict in their identity which is

uncomfortable and more easily reconciled through changing the expression

of attitude, rather than changing identity. However, the contradictions

between the AFA and ATOP with elements of the measure of perceived

stress (PSS) and burnout (MBI) are more difficult to explain in the context

of quantitative analysis. However, the qualitative analysis may also help to

provide a tentative interpretation of this complexity.

Thematic analysis

Although the AFA and the ATOP standardized weight bias measures

indicated that nurses attitudes were neutral, the thematic analysis suggests

105

quite a complex picture where negative attitudes were clearly visible but

were also variable both across and within participant responses. A complex

hierarchy of interacting social identities were revealed; with the conflicts

between them being actively managed by nurses in a range of ways. This

framework of understanding and the relationships between themes are

presented in figure 2.

Before elaborating on the diagram presented, it is important to draw

attention to the fact that while the qualitative data provides good evidence

for some of the links produced in figure 2, some links are less strongly

evidenced and drawn more from current theory in order to realize the

potential explanatory power of the diagram. The relationship of each link

and its evidence depicted in the text is illustrated using the width of line.

106

Wider society

Media

NHS moral discourses

Cultural Context

Pragmatics of caring

Lack of resourcesComplicationsIn caring

Acknowledging wider factors Blame

Deservingness

Preventability

Responsibility

Identity

Identity management strategies

De-Identification

Denying impact of attitudes on careStake Inoculation

Weight related Identity

Personal Identity

Nursing Identity

Figure 2.

Theme relationships.

Conceptual frameworks

107

Figure 2 represents how the range of identities expressed may interact with

the wider cultural context around them to inform which one of three

competing frameworks the individual may use to make sense of their

attitudes towards patients with obesity. However, given that these

frameworks were not always associated with positive attitudes, nurses

appear to operationalize a range of identity management strategies in order

to manage the conflict that their attitudes portray between the framework

they choose to understand obesity within and their most salient identity.

Identity

The assumption that people belong to multiple social memberships

(Gergen, 1971) is evidenced within the theme of ‘identity’ where a range of

perspectives relating to nursing identities, identities as people or weight

related identities were apparent. The social context may determine which

identity is most salient at one given time, which in turn is associated with

attitude expression (Hogg & Smith, 2007). Although primarily an automatic

process, which identity is presented can also be used strategically to create a

positive representation of the self (Hogg, 2009), which may explain why

each of the three represented identities were often positively portrayed.

However, there were also multiple components to each identity evidenced

which appeared to shape attitudes in different ways. For example, within the

nursing identity subtheme sometimes nurses portrayed themselves as ‘health

promoting’, which given the health complications associated with obesity

may associate with more negative attitudes than those who portrayed their

nursing identity as non judgmental. Equally, weight related identity relating

predominantly to nurses experience of their own weight difficulties, are not

likely to predict attitudes in and of itself but how nurses make sense of their

own experiences of weight difficulties may do. For example, those viewing

their own successful weight loss as within their control are more likely to

hold negative attitudes than nurses acknowledging their own weight

struggles, who exhibit more empathy. This variability may explain the

quantitative findings where no relationship was detected between BMI and

the two weight bias measures, the AFA and ATOP, as well as the mixed

results produced by previous research in this area (e.g. Garcia, 2012; Poon

& Tarrant, 2009; Torrey, 2013). Thus, the identities presented are complex

and multi-faceted with the salience of each identity influencing attitudes in

different ways.

Attitudes in the context of three conceptual frameworks

There were also three themes that appeared to represent conceptual

frameworks that may be used to understand nurses’ attitudes towards

patients with obesity. Interestingly, despite the identity themes portrayed

depicting mainly positive characteristics, the conceptual frameworks used to

understand obesity that were not wholly positive representing somewhat of

a-conflict.

Research suggests that the causes of obesity are a complex

combination of biopsychosocial and environmental factors, (BPS, 2011).

The ‘acknowledgement of wider factors’ theme captured this complex

understanding of obesity. Those acknowledging the medical, social and

psychological factors relating to obesity tended to demonstrate more

accepting attitudes towards patients with obesity overall which was

congruous with the theme illustrating positively expressed identities.

109

However, the ‘pragmatics of caring’ theme demonstrated the nurses

awareness of the difficulties involved in caring for a patient with obesity for

example, the complexity involved in caring and the lack of adequate

resources required for caring properly. This theme appeared to be more

associated with a more negative outlook on obesity.

The third framework used to conceptualize nurses’ attitudes was one

of blame. Where attitudes appeared to be justified through ideas about

obesity being preventability, the person taking responsibility for their own

health and also their judgment of how deserving the obese person was of

receiving support from NHS services. Perhaps unsurprisingly, these ideas

also appeared to be associated with overtly negative attitudes from nurses

towards patients with obesity.

The framework used to inform nurses understanding of obesity

appears to relate to the types of attitudes expressed, Yet this is not always

congruent with other themes within the analysis, primarily that of positively

presented identity. This suggests that the expression of attitudes is

dependent on more than just the salience and identification of a particular

constructed identity in that it is also influenced by a much wider social

context such as social norms and normalized discourses.

Cultural context

Despite the acknowledgement that attitudes research cannot be

conducted within a socio-cultural vacuum (Taijfel, 1981), the importance of

the wider social context has arguably been traditionally under represented

(e.g. Allport, 1935; Hogg & Vaughan, 2002). Yet the organizational,

institutional and historical cultures that permeate attitudes are paramount

110

(Howarth, 2006). Firstly, the UK is part of western society where obesity is

viewed as a preventable, controllable (Crandall et al, 2001), visible flaw

(Puhl & Brownell, 2003). This view of individualism and accountability,

coupled with the westernized aspiration towards thinness (Budd, Mariotti,

Gradd & Falkenstein, 2009) will likely develop a more blaming culture than

where obesity is seen as a sign of happiness, health and prosperity (Budd,

Mariotti, Gradd & Falkenstein, 2009). Nurses were certainly explicit about

the direct influence of such views communicated culturally on their attitudes

towards the patient with obesity.

Secondly, narratives relating to ‘care and cash crises threatening to

debilitate the wider public sector and economy’ are shared within the NHS

but also within wider society (Warner & O’Sullivan, 2014, p8). However,

there are also culturally available narratives about shared values with the

NHS being seen as the ‘nearest thing this country has to a religion’ (Warner

& O’Sullivan, 2014, p7) suggesting a certain protectiveness and pride in the

NHS. The moral discourses theme recognized the nurses’ acknowledgement

of the difficulties facing the NHS. Their alignment with its plight is perhaps

more likely to draw them towards either attributing blame for obesity or to

one acknowledging the pragmatic difficulties of caring for a person with

obesity within the current climate.

Conflict management strategies

The qualitative analysis suggests that how a given identity is

constructed and its associated salience; alongside the influence of narratives

held within the wider culture help to make sense of the attitudes that nurses

held towards patients with obesity within this study. However, people

111

generally endeavour to create an overall integrated sense of self where

identity and attitudes do not clash (Bannister, 1998) which may account for

why the final theme appeared to illustrate a range of ‘identity management

strategies’ which nurses appeared to use to manage conflict. For example,

nurses often ‘de-identified’ or, played down, one identity over another

(Hogg & Smith, 2015). These are not behaviours that they acknowledged

and described as their own but were observed in the kinds of explanations

they gave and the ‘disclaimers’ they used in presenting their opinions. Those

exhibiting negative attitudes also tended to justify them by reaffirming their

minimal impact on clinical care. Most commonly though, there was a theme

of stake inoculation whereby nurses displaced their own attitudes on to that

of others (‘I don’t but others do’) which appeared to allow them to express

negative attitudes in a way that did not jeopardize their own identity.

Overall, the analysis of quantitative data depicted a confusing picture

that failed to identify a simple relationship between a single factor and

weight bias. However, the qualitative analysis helps to interpret these

findings by suggesting that nurses attitudes may be influenced by a complex

hierarchy of interacting social identities and that when those identities

conflict with their attitudes towards patients with obesity, they may be

employing identity management strategies to aid reconciliation. The

qualitative analysis was more sensitive to this level of complexity due to the

analysis on freely expressed data than the more restrictive nature of the

quantitative data allowed for.

Historically research has suggested that subtle variations in the

wording of questionnaires can create large differences in responses (Marsh,

112

1982) and that contradictions are not uncommon (Kinder & Sears, 1985).

By using both the AFA and the ATOP weight bias measures in order to gain

a range of beliefs about obesity, the variability in responses that

standardized questionnaires usually restrict (Potter & Wetherell, 1987)

became visible but were difficult to interpret in isolation. The qualitative

analysis supports this hypothesis, as variability across themes were clearly

observable and the theme of ‘identity management’ suggested that nurses

may find negative attitudes difficult to own outright, precisely what the

objective measures asked them to do. Thus a more complex

conceptualization was required than the interpretation of the standardized

questionnaire results could provide alone.

Limitations

Previous authors have suggested that survey designs tend to create

social environments of their own and do not allow for naturally occurring

variability due to their restrictive nature (Rogers, Stenner, Gleeson &

Rogers, 1995). They often favour what is consistent over what is real;

problematic in understanding attitudes which are often dynamic, conflicting

and changing (Potter & Wetherell, 1987). Within the quantitative analysis it

is possible that the small effect sizes found may be the result of a by-product

of the large sample size deployed for this research rather than true effects

meaning that these results may be negligible. Secondly, the AFA and the

ATOP measured different constructs which may partly relate to the

difference in results between them. Additionally, the AFA weight bias

measure did not meet parametric assumptions and thus non parametric tests

were used for tests involving this measure, whilst the parametric equivalents

113

were used for the ATOP as part of testing the same hypotheses. The

difference in the ability of each test to detect power may also in part account

for the variability in the two measures within each hypothesis.

The study was situated within the context of intergroup theories of

prejudice, primarily Social Identity Theory (Tajfel & Turner, 1987) given

that the use of theoretical frameworks to understand weight bias has

previously been limited (Zhu, Norman & While, 2011). Other theories can

be used to underpin weight bias research, for example, the emerging themes

in both the ‘pragmatics of caring’ and the ‘moral discourses about the NHS’

could be explained using Realistic Conflict Theory (Stouffer, Suckman,

DeVinney, Star & Williams, 1949) although this does not appear to be used

widely the literature. Attribution Theories of prejudice are more strongly

evidenced (Crandall, 1994, Puhl & Brownell, 2006) and may account for the

theme of blame, but neither theory was able to account for the complexity of

weight bias and its interaction with the social environment in the way that

Social Identity Theory is able to.

Nevertheless, alongside traditional attitudes research, Social Identity

Theory has received its fair share of criticism, with many authors suggesting

it should be better able to consider attitudes in relation to the wider social

environment of group memberships, norms, identities and intergroup

relations (See Prislin & Wood, 2005) as it has previously focused on

attitudes as cognitive representations within the individual and perhaps

neglected the wider social context (Hogg & Smith, 2007). However, since

its origins (e.g. Tajfel, 1972) it has developed in to a comprehensive and

114

integrated theory of self-concept and intergroup behaviour (Hogg & Smith,

2007) and it is within this context that this study presumes.

Conclusion

In conclusion, this study explored the relationship between weight

bias and nurses qualification status, BMI, self-esteem, stress and burnout in

the context of intergroup relation theories such as Social Identity Theory

(Tajfel & Turner, 1987). Although the analysis of quantitative data failed to

identify a simple relationship between a single factor and weight bias, the

qualitative analysis illustrates that a complex hierarchy of conflicting social

identities may influence nurses’ weight bias. The identity management

strategies employed to manage this suggest that ‘owning’ these attitudes

may be difficult, accounting for why they are not visible within the

quantitative analysis. Overall, exploring individual factors in relation to

weight bias may not yield success; the complexity illustrated may partially

explain why the results of previous literature are also contradictory.

Further research should first and foremost be situated within a

theoretical framework of weight bias to aid the further development of

knowledge in the context of previous research. Future studies should

consider using qualitative methodologies to enable the complexity of

attitudes, particularly in populations who might find their attitudes difficult

to ‘own’, to be expressed fully. However, where quantitative survey

methodologies are utilized, implicit rather than explicit measures may

enable the process of automatic versus strategic social identity processes to

be further understood (Hogg & Smith, 2007). The model presented in the

discussion represents a range of evidenced and less well evidenced concepts

115

which provide the basis for further research. Priorities based on this might

consider how manipulating the salience of the various social identities

impact on attitudes as well as exploring the impact of wider cultural

discourses on attitudes. Clinically, working across multiple levels to

challenge weight bias may be helpful. For example, weight bias training

could be integrated across nurse training and supervision. On a broader

level, working within the context of the media may help to shift attitudes

towards obesity more generally given that nurses raised the media as an

influencing factor on their own attitudes within this research. However,

replication studies should be considered prior to deciding how best to

influence weight bias in nurses given that this study represents the first

study to explore weight bias using a mixed methods design. However, what

can be drawn from this research with more certainty is knowing that there is

a place for psychologists to change perceptions of obesity, replication

studies in this area would help to determine how best to do this. Only

through developing a better understanding of these issues may their impact

on clinical care be understood and thus challenged.

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List of appendices

Appendix 1 Power calculations…………………………………...............136Appendix 2 Participant demographic information…………………...137-138Appendix 3 Missing data summary tables…………………………...139-144Appendix 4 Ethical approval documentation………………………...145-146Appendix 5 NHS Research and Development approval………………….147Appendix 6 Advertisement email template……………………………….148Appendix 7 Participant information sheet…………………………...149-150Appendix 8 Participant consent form………………………………….….151Appendix 9 Emotional support information page…………………….…..150Appendix 10 Demographic information questionnaire……………….…..153Appendix 11 Standardized questionnaires…………………………...154-159

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Appendix 12 A summary critique surrounding attitudes literature….160-161Appendix 13 Choice of qualitative analysis………………………….…..162Appendix 14 Phases of thematic analysis………………………………...163Appendix 15 Researcher reflexivity…………………………………164-165Appendix 16 Yardley’s principles of credibility…………………….166-167Appendix 17 Thematic map examples and discussion………………168-170Appendix 18 Examples data and coding……………………………..173-175Appendix 19 Final coding categories……………………………......176-177Appendix 20 Full data screening analysis…………………………...178-183Appendix 21 Chi Squared analysis- missing data and demographic___________variables……………………………………………….184-193 Appendix 22 Chi Squared analysis- demographic factors & qualification ___________status…………………………………………………..194-195Appendix 23 Normality distribution histograms…………………….196-203Appendix 24 Correlation analysis with AFA & MBI outlier…………….204Appendix 25 Normality tests post transformations………………….205-209Appendix 26 Scatterplots for correlation analyses…………………..210-219

Appendix 1 – Power calculations (G Power 3.1: Faul, Erdfelder, lang, Buchner, 2007)

All power calculations were completed a priori using G* Power 3.1.7 (Faul, Erdfelder, Lang & Buchner, 2007). In order to complete this calculation, effect size was estimated through examination of previous literature that had identified a medium effect size when examining the relationship between weight related bias and other variables in nurses (e.g. Brown, Stride, Psarou, Brewins & Thompson, 2007). As such, in calculating sample size for correlation analysis, a power of 0.8 was assumed, to detect a medium effect (r=0.3), with a 2 tailed

136

hypothesis and an alpha of 0.05 using a point biserial model. This a priori calculation suggested a sample of 82 participants should be obtained. Power calculations were also completed for a multiple regression analysis. Assuming power of 0.8 to detect a translated medium effect (r=0.15), using a 2 tailed hypothesis and an alpha of 0.05 for a linear multiple regression, fixed model, R2, deviation from zero, a sample size of 109 participants was suggested. Finally, power calculations were also completed for an independent samples t test. Assuming power of 0.8 in order to detect a medium effect (d=0.5), using a 2 tailed hypothesis and an alpha of 0.05 using a Means: difference between two independent means (two groups) test, a sample size of 64 participants per group was suggested. In order to have a large enough sample size to complete correlation and regression analysis on each group separately, the largest sample size calculated was be used. As such, a sample size of 109 participants per group was obtained, a total sample size of 218 participants.

Appendix 2- Participant demographic information

Gender Undergrad Qualified Both

MaleFemale

7105

1095

17201

AgeUndergraduat Qualified Both

137

e18-21 49 4 5322-30 30 32 6231-40 22 27 4941-50 9 22 3151-60 2 20 22>60 0 1 1Mean (S.D) Age 26.8 (9.1) 37.66 (10.9) 32.02 (11.36)

EthnicityUndergraduate Qualified Both

White British 84 78 162White Irish 9 9White Other 6 5 11White and Black Caribbean

1 0 1

White and Black African

1 0 1

White and Asian 1 2 3Mixed other 3 0 3Indian 2 2 4Pakistani 2 1 3Asian other 4 2 6Black or black British Caribbean

1 0 1

Black or black British African

4 5 9

Black or black British other

1 0 1

Chinese 1 0 1Other 2 1 3

Appendix 2- Participant demographic information

BMIUndergraduate Qualified Both

<18.5 5 2 718.5-24.9 62 42 10425-29.9 32 40 72>30 13 20 33Mean (S.D) 24.7 (4.5) 26.7 25.63 (4.73)Range 23.10 (16-39.1) 27.6 (17.4-45) 29.8 (16-45.2)

138

Body appearance satisfaction Undergraduate Qualified Both

Dissatisfied 27 20 47Somewhat Dissatisfied

34 37 73

Not dissatisfied or satisfied

14 9 23

Somewhat Satisfied 18 26 44Satisfied 19 12 31Mean 2.71 (1.43) 2.73 (1.33) 2.72 (1.38)

Demographic details (data collected for qualified only)

Do you currently work in the NHS? Response Number of participants Yes 79No 17No response

How long have you worked in the NHS for?

Number of years Numbers of participants 0-10 5411-20 1921-30 1131-40 841-50 0Missing 13Mean (S.D) 11.17

Appendix 3 - Missing data summary tables

Anti fat Attitudes Questionnaire (AFA)AFA item number Number missing

(from total)Percentage missing %

1 0 (218) 0%2 0 (218) 0%3 0 (218) 0%4 0 (218) 0%5 0 (218) 0%6 0 (218) 0%7 0 (218) 0%8 0 (218) 0%

139

9 0 (218) 0%10 0 (218) 0%

Attitudes Towards Obese Persons (ATOP) ATOP item number Number missing

(from total)Percentage missing %

1 1 (218) 0.52 1 (218) 0.53 1 (218) 0.54 1 (218) 0.55 1 (218) 0.56 1 (218) 0.57 6 (218) 2.88 6 (218) 2.89 6 (218) 2.810 6 (218) 2.811 1 (218) 0.512 7 (218) 3.213 8 (218) 3.714 1 (218) 0.515 7 (218) 3.216 8 (218) 3.817 7 (218) 3.218 1 (218) 0.519 7 (218) 3.220 20 (218) 9.2

140

Appendix 3 - Missing data summary tables (continued)

Rosenberg Self Esteem Scale (RSES)RSES item number Number missing

(from total)Percentage missing %

1 20 (218) 9.22 20 (218) 9.23 20 (218) 9.24 20 (218) 9.25 20 (218) 9.26 20 (218) 9.27 20 (218) 9.28 20 (218) 9.29 20 (218) 9.210 20 (218) 9.2

Perceived Stress Scale (PSS)PSS item number Number missing

(from total)Percentage missing %

1 20 (218) 9.22 20 (218) 9.23 20 (218) 9.24 20 (218) 9.25 20 (218) 9.26 20 (218) 9.27 20 (218) 9.28 20 (218) 9.29 20 (218) 9.210 22 (218) 10.1

141

Appendix 3 - Missing data summary tables (continued)

Maslach Burnout Inventory (MBI)MBI item number Number missing

(from total)Percentage missing %

1 22 (218) 10.12 23 (218) 10.63 22 (218) 10.14 22 (218) 10.15 22 (218) 10.16 22 (218) 10.17 22 (218) 10.18 22 (218) 10.19 22 (218) 10.110 22 (218) 10.111 22 (218) 10.112 22 (218) 10.113 22 (218) 10.114 22 (218) 10.115 22 (218) 10.116 22 (218) 10.117 22 (218) 10.118 22 (218) 10.119 22 (218) 10.120 22 (218) 10.121 22 (218) 10.122 39 (218) 17.9

Appendix 3 - Missing data summary tables (continued)

142

Missing data analysis split by professional group (undergraduate or qualified nurse)

Anti Fat Attitudes (AFA) QuestionnaireUndergraduate nurses Qualified nurses

AFA item number

Number missing

(from total)

Percentage missing %

Number missing

(from total)

Percentage missing %

1 0 (112) 0 0 (106) 0 2 0 (112) 0 0 (106) 03 0 (112) 0 0 (106) 04 0 (112) 0 0 (106) 05 0 (112) 0 0 (106) 06 0 (112) 0 0 (106) 07 0 (112) 0 0 (106) 08 0 (112) 0 0 (106) 09 0 (112) 0 0 (106) 010 0 (112) 0 0 (106) 0

Appendix 3 - Missing data summary tables (continued)

143

Attitudes Towards Obese Persons (ATOP)Undergraduate nurses Qualified nurses

Atop item number

Number missing

(from total)

Percentage missing %

Number missing

(from total)

Percentage missing %

1 0 (112) 0 1 (106) 0.92 0 (112) 0 1 (106) 0.93 0 (112) 0 1 (106) 0.94 0 (112) 0 1 (106) 0.95 0 (112) 0 1 (106) 0.96 0 (112) 0 1 (106) 0.97 0 (112) 0 6 (106) 5.78 0 (112) 0 6 (106) 5.79 0 (112) 0 6 (106) 5.710 0 (112) 0 6 (106) 5.711 0 (112) 0 1 (106) 0.912 0 (112) 0 7 (106) 6.613 0( 112) 0 8 (106) 7.514 0 (112) 0 1 (106) 0.915 0 (112) 0 7 (106) 6.616 0 (112) 0 8 (106) 7.517 0 (112) 0 7 (106) 6.618 0 (112) 0 1 (106) 0.919 0 (112) 0 7 (106) 6.620 0 (112) 0 20 (206) 18.9

Rosenberg self esteem Scale (RSES)

Undergraduate nurses Qualified nursesRSES item

number

Number missing

(from total)

Percentage missing

%

Number missing (from

total)

Percentage missing %

1 0 (112) 0 20 (106) 18.92 0 (112) 0 20 (106) 18.93 0 (112) 0 20 (106) 18.94 0 (112) 0 20 (106) 18.95 0 (112) 0 20 (106) 18.96 0 (112) 0 20 (106) 18.97 0 (112) 0 20 (106) 18.98 0 (112) 0 20 (106) 18.99 0 (112) 0 20 (106) 18.910 0 (112) 0 20 (106) 18.9

Appendix 3 - Missing data summary tables (continued)

144

Perceived Stress Scale (PSS) Undergraduate nurses Qualified nurses

PSS item number

Number missing

(from total)

Percentage missing %

Number missing

(from total)

Percentage missing %

1 0 (112) 0 20 (106) 18.92 0 (112) 0 20 (106) 18.93 0 (112) 0 20 (106) 18.94 0 (112) 0 20 (106) 18.95 0 (112) 0 20 (106) 18.96 0 (112) 0 20 (106) 18.97 0 (112) 0 20 (106) 18.98 0 (112) 0 20 (106) 18.99 0 (112) 0 20 (106) 18.910 0 (112) 0 22 (106) 20.8

Maslach Burnout Inventory (MBI)

Undergraduate nurses Qualified nursesMBI item number

Number missing (from

total)

Percentage missing %

Number missing

(from total)

Percentage missing %

1 0 (112) 0 22 (106) 20.82 0 (112) 0 23 (106) 21.73 0 (112) 0 22 (106) 20.84 0 (112) 0 22 (106) 20.85 0 (112) 0 22 (106) 20.86 0 (112) 0 22 (106) 20.87 0 (112) 0 22 (106) 20.88 0 (112) 0 22 (106) 20.89 0 (112) 0 22 (106) 20.810 0 (112) 0 22 (106) 20.811 0 (112) 0 22 (106) 20.812 0 (112) 0 22 (106) 20.813 0 (112) 0 22 (106) 20.814 0 (112) 0 22 (106) 20.815 0 (112) 0 22 (106) 20.816 0 (112) 0 22 (106) 20.817 0 (112) 0 22 (106) 20.818 0 (112) 0 22 (106) 20.819 0 (112) 0 22 (106) 20.820 0 (112) 0 22 (106) 20.821 0 (112) 0 22 (106) 20.822 0 (112) 0 39 (106) 36.8

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Appendix 4 – Ethical approval documentationPSYCHD CLINICAL PSYCHOLOGY

Review of MRP Proposal for RGC

Trainee Name/URN: 6338210 Date: 22 July 2015

Comments

RGC Decision

Please tick one:

Proceed Proceed with considerations Resubmit proposal

Comments from the committee:

It might be the case that you recruit more students than qualified nurses so you might have an issue with applicability and, if the levels of stress and burnout are low, then this might limit the size of correlation with attitudes to obesity. You might need to take this into consideration in your write up should you have such difficulties.

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Appendix 4 – Ethical approval documentation (continued)

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Appendix 5 – NHS Research and Development approval

Note: This letter has been cropped to exclude the names and addresses of the organization it represents.

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Appendix 6 – Advertising email template

As a qualified or undergraduate nurse can you help us understand nurses attitudes towards obesity?

Your chance to be entered in to a prize draw to win a £20 Amazon Voucher!

Please click on the link below to take part in a short survey.

www.link provided here

or contact the researcher at e.goad@surrey.ac.uk for the link or more information

Your views matter, we want to hear from you.Thank you!

This study has received a favourable opinion from the University of Surrey Ethics Committee

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Appendix 7 – Participant information sheetStudy title: Exploring attitudes and beliefs about obesity in healthcare

professionals

Information sheet

My name is Elisabeth Goad, a Trainee Clinical Psychologist studying at the University of Surrey. I would like you to take part in a research project details of which are given below.

The current literature suggests that there is obesity related bias in the general population but also in healthcare staff as well. Such bias may result in negative consequences such as an increase in unhealthy eating behaviours and reduced engagement with healthcare. This study examines the beliefs of healthcare staff about obesity and considers factors that might influence these attitudes.

Participation is completely voluntary and if you do decide to take part you have the right to withdraw your participation at any stage and your data until data is analysed (31st July 2016) without giving reason.

If you decide to take part in the study after reading this information sheet you can proceed to a consent form before continuing on to complete a series of short questionnaires which should take no longer than 30 minutes to complete. The unique participant identifier on the consent form will enable us link your consent form to your questionnaire if required without using your name and thus maintaining anonymity. If you wish to withdraw your data from the study at a later date, we will need your participant identifier to do so. All the information you provide will be kept confidentially and made anonymous prior to being entered into a database for analysis. Anonymised data will be kept by the University for 10 years. Group data may be published in an academic journal, but no details which could be used to identify individual participants will be published. There is one optional open ended question within the questionnaire, the anonymised responses of which will be seen by the researcher, two research supervisors and also examiners assessing the research.

Your participation will help us understand how best nurses can be supported in working with patients with obesity. Completing the questionnaires might evoke difficult feelings so a list of contact details for organisations that you can talk to is included at the end of the questionnaire pack.

All participants are eligible for entry in to a prize draw to win one of four £20 Amazon vouchers as a small token of our appreciation. The prize draw will take place at the end of data collection on 30th May 2016 and the winners will be notified by email.

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Thank you for taking the time to read this information sheet. If you would like more information please contact us. For any complaints or concerns please contact the principle researcher in the first instance or another member of the research team. Study Contact details Elisabeth Goad (Principle researcher)Trainee Clinical Psychologist PsychD Doctoral Training Programme University of Surrey e.goad@surrey.ac.uk

Dr Sue Jackson Teaching Fellow (Research & Development)PsychD Doctorate Training ProgrammeSchool of PsychologyUniversity of Surreys.jackson@surrey.ac.uk

Appendix 8 – Participant consent form

Dr Kate Gleeson (supervisor)Research Director PsychD Doctoral Training Programme School of PsychologyUniversity of Surrey k.gleeson@surrey.ac.uk

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Study title: Exploring attitudes and beliefs about obesity in healthcare professionals (in training and post-qualified)

I have read and understood the information sheet provided (Version 1, 08.09.15). I have been given a full explanation by the researchers of the nature, purpose and duration of the study and what I will be expected to do.

I have been advised about any disadvantages of taking part in the study

I have been given time to consider taking part in this research

I agree for my anonymised data to be used for this study and any future research that will have received all relevant legal, professional and ethical approvals.

I understand that all research data will be held for at least 10 years in accordance with University policy and that my personal data is held and processed in the strictest confidence, and in accordance with the UK Data Protection Act (1998).

I understand that the group data may be published in an academic journal, but the information I provide will be kept confidential and made anonymous. I understand open ended question responses will be seen by the researcher, and anonymised versions seen by the research supervisors and the examiners assessing the research.

I understand that I can withdraw my participation from the study at any time without needing to justify my decision and without my legal rights being affected.

I understand that I can withdraw my data from the study until July 31 st 2016 when data analysis has been completed.

I have had the opportunity to ask questions about the study and all questions have been answered to my satisfaction.

I agree to provide my email address for receipt of a results summary

Signed:_________________________ (participant)

Date:___________________________

To generate your unique participant number, please provide the following information:

First 3 letters of your mother’s maiden name: ___ ___ ___First 2 digits of your date of birth: ___ ___My email address for the results summary is:……………………………

Appendix 9 – Emotional support page

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Helpline numbersIf, after completing this questionnaire, you need to talk to someone confidentially about how you are feeling, information about some support services and organisations is provided below. Careline is a confidential national telephone counselling service. ‘Our highly trained counsellors are experienced in supporting you through issues that include living with critical illness, emotional heartbreak and sexuality.’Tel: 0845 122 8622 Monday to Friday 10am - 1pm & 7pm to 10pm Website www.carelineuk.org NHS Direct provide information and advice about health, illness and health services, to enable patients to make decisions about their healthcare and that of their families. Helpline (24 hour): 0845 4647. Calls charged at local rate. Website www.nhsdirect.nhs.uk Samaritans provide confidential emotional support for people who are experiencing feelings of distress or despair.’ We are here for you if you're worried about something, feel upset or confused, or just want to talk to someone.’Helpline (24 hour): 08457 90 90 90. Calls charged at local rate. Website: www.samaritans.org SANE provides practical information, crisis care and emotional support for anybody experiencing mental health problems and their families and carers. This could include anxiety or depression, distress following treatment, concern over side-effects of drugs. SANEline: 08457 678 000 open from1pm – 11pm each day. Calls charged at local rates. Website: www.sane.org.uk

Appendix 10- Demographic information questionnaire

Male ___ Female ___

Age: ____ years

Are you currently working for the NHS? Yes ___ No ___

If yes, what do you do? _______________________________________________

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If yes, are you full-time ___ part-time ___ or other (e.g. maternity leave)? ___

How many years have you worked in the NHS for?____ What band is your job role? _____

If a student, what qualifications are you studying for? ________________________

If a student, which institution to you study at?_____________________________ How many hours per week do you spend in direct contact with patients?_________

What is your height? _________

What is your weight? _________

Appendix 11 – Standardized questionnaires

Anti Fat Attitudes Questionnaire4 (AFA) Crandall, 1994) For each item below, please circle the number that best represents your answer to each statement:1. I really don’t like fat people much

Very strongly 0 1 2 3 4 5 6 7 8 9 Very strongly

4 This is the Anti Fat Attitudes Questionnaire, given with kind permission of the author Christian Crandall. Published by the American Psychological Association. Copyright 1994 by the American Psychological Association, Inc. Permission given only for the use of this questionnaire in this research. 

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disagree agree

2. I don’t have many friends that are fatVery strongly

disagree0 1 2 3 4 5 6 7 8 9 Very strongly

agree

3. I tend to think that people who are overweight are a little untrustworthy

Very strongly disagree

0 1 2 3 4 5 6 7 8 9 Very strongly agree

4. Although some fat people are surely smart, in general, I think they tend not to be quite as bright as normal weight people

Very strongly disagree

0 1 2 3 4 5 6 7 8 9 Very strongly agree

5. I have a hard time taking fat people too seriouslyVery strongly

disagree0 1 2 3 4 5 6 7 8 9 Very strongly

agree

6. Fat people make me somewhat uncomfortableVery strongly

disagree0 1 2 3 4 5 6 7 8 9 Very strongly

agree

7. If I were an employer looking to hire, I might avoid hiring a fat person

Very strongly disagree

0 1 2 3 4 5 6 7 8 9 Very strongly agree

8. I feel disgusted with myself when I gain weightVery strongly

disagree0 1 2 3 4 5 6 7 8 9 Very strongly

agree

9. One of the worst things that could happen to me would be if I gained 25 pounds

Very strongly disagree

0 1 2 3 4 5 6 7 8 9 Very strongly agree

10. I worry about becoming fatVery strongly

disagree0 1 2 3 4 5 6 7 8 9 Very strongly

agree

11. People who weigh too much could lose at least some part of their weight through a little exercise

Very strongly disagree

0 1 2 3 4 5 6 7 8 9 Very strongly agree

12. Some people are fat because they have no willpowerVery strongly

disagree0 1 2 3 4 5 6 7 8 9 Very strongly

agree

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13. Fat people tend to be fat pretty much through their own faultVery strongly

disagree0 1 2 3 4 5 6 7 8 9 Very strongly

agree

Appendix 11 – Standardized questionnaires (continued)

Attitudes Towards Obese Persons Scale (ATOP)5 (Allison, Basile & Yuker, 1991)Please mark each statement below in the left margin, according to how much you agree or disagree with it. Please do not leave any blank. Use the numbers on the following scale to indicate your response.

5 This is the Attitudes To Obese Persons Scale, author Dr D.B Allison, taken from Allison, D.B., Basile, V.C. & Harold, Y.E. (1991). The measurement of attitudes toward and beliefs about obese persons. International Journal of Eating Disorders, 10, 5,  (599-607). Published by John Wiley & Sons.  © 1991 by John Wiley & Sons, Inc. Permission kindly given to use the ATOP for this research only. 

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Be sure to place a minus or plus sign ( - or +) beside the number that you choose to show whether you agree or disagree.

-3 -2 -1 +1 +2 +3

I strongly disagree

I moderately

disagree

I slightly disagree

I slightly agree

I moderately

agree

I strongly

agree

1. Obese people are as happy as non obese people.2. Most obese people feel that they are not as good as other people.3. Most obese people are more self-conscious than other people.4. Obese workers cannot be as successful as other workers.5. Most non obese people would not want to marry anyone who is obese.6. Severely obese people are usually untidy.7. Obese people are usually sociable.8. Most obese people are not dissatisfied with themselves.9. Obese people are just as self-confident as other people.10. Most people feel uncomfortable when they associate with obese people.11. Obese people are often less aggressive than non obese people.12. Most obese people have different personalities than non obese people.13. Very few obese people are ashamed of their weight.14. Most obese people resent normal weight people.15. Obese people are more emotional than non obese people.16. Obese people should not expect to lead normal lives.17. Obese people are just as healthy as non obese people.18. Obese people are just as sexually attractive as non obese people.19. Obese people tend to have family problems.20. One of the worst things that could happen to a person would be for him

to become obese.

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Appendix 11 – Standardized questionnaires (continued)

Rosenberg Self Esteem Scale (RSES)6 (Rosenberg, 1965)

The scale is a ten item Likert scale with items answered on a four point scale - from strongly agree to strongly disagree. Instructions: Below is a list of statements dealing with your general feelings about yourself. If you strongly agree, circle SA. If you agree with the statement, circle A. If you disagree, circle D. If you strongly disagree, circle SD.

E1 On the whole, I am satisfied with myself. SA A D

SD

E2 At times, I think I am no good at all. SA A D

SD

E3 I feel that I have a number of good qualities. SA A D

SD

E4 I am able to do things as well as most other people. SA A D

SD

E5 I feel I do not have much to be proud of. SA A D

SD

E6 I certainly feel useless at times. SA A D

SD

E7 I feel that I’m a person of worth, at least on an equal plane with others.

SA A D

SD

E8 I wish I could have more respect for myself. SA A D

SD

E9 All in all, I am inclined to feel that I am a failure. SA A D

SD

E10 I take a positive attitude toward myself. SA A D

SD

Appendix 11 – Standardized questionnaires (continued)

Perceived Stress Scale (PSS)7 (Cohen, Kamarck & Mermelstein, 1983)

6 This is the Rosenberg Self Esteem Scale taken from the Measures in Health Psychology Portfolio, permission for The University of Surrey to use for the purpose of this research. With thanks to the author, M Rosenberg. 7 This is the Perceived Stress Scale taken from Measures in Health Psychology Portfolio, permission for The University of Surrey to use for the purpose of this research. With thanks

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The questions in this scale ask you about your feelings and thoughts during the last month. In each case, you will be asked to indicate by circling how often you felt or thought a certain way. Name ____________________________________________________________ Date _________ Age ________ Gender (Circle): M F Other_____________0 = Never 1 = Almost Never 2 = Sometimes 3 = Fairly Often 4 = Very Often

1. In the last month, how often have you been upset because of something that happened unexpectedly?

2. In the last month, how often have you felt that you were unableto control the important things in your life?

3. In the last month, how often have you felt nervous and “stressed”? 4. In the last month, how often have you felt confident about your ability to handle

your personal problems? 5. In the last month, how often have you felt that things were going your way?6. In the last month, how often have you found that you could not cope

with all the things that you had to do?7. In the last month, how often have you been able to control irritations in your life?8. In the last month, how often have you felt that you were on top of things? 9. In the last month, how often have you been angered because of things that were

outside of your control? 10. In the last month, how often have you felt difficulties were piling up so high that

you could not overcome them?

Appendix 11 – Standardized questionnaires (continued)

Maslach Burnout Inventory (MBI)8 (Maslach & Jackson, 1981)Health Survey Form9

The purpose of this survey is to assess how staff members view their job and their reactions to their work.Instructions: On the following pages are 16 statements of job-related feelings. Please read each statement carefully and decide if you ever feel this way about your job. 

to the author Sheldon Cohen.8  MBI-Human Services Survey: Copyright ©1981 Christina Maslach & Susan E. Jackson. Published by Mind Garden. Permission kindly given for the use of the MBI-Human Services Survey only. Copyright did not extend to include the entire questionnaire within the appendices.

9

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If you have never had this feeling, select the button under the Never column. If you have had this feeling, indicate how often you feel it by selecting the phrase that best describes how frequently you feel that way. The phrases describing the frequency are:How Often:-Never -A few times a year or less -Once a month or less -A few times a month -Once a week -A few times a week -Every day 

Example questions 1. I feel emotionally drained from my work.2. In my opinion, I am good at my job.3. I doubt the significance of my work.

Appendix 12 – A summary critique surrounding attitudes literature

The ‘attitudes’ literature has traditionally been situated within experimental or ‘traditional’ social psychology and has been a subject of interest since the discipline itself began (Rogers, 2003). However, 21st

century social psychology is a divided discipline, often seen with two opposing sides, experimental or traditional social psychology and critical social psychology (Rogers, 2003). Experimental social psychology has primarily taken a positivist approach to attitudes, assuming a cause and effect model (Rogers, Stenner, Gleeson & Rogers, 1995) typical of experimental methodologies. Yet a ‘cause and effect’ model of attitudes has not proven fruitful (discussed below) and critical approaches to attitudes research have heavily condemned the survey and experimental methodologies typically used in line with this

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cause and effect model of thinking. For example, discourse analysts suggest that experimental designs control variables so much that they lose sight of what is real, or would be considered in discourse terms as normal variability in the construction of language rather than a problem to be controlled (Potter & Wetherall, 1987). Equally survey designs also seek to reduce natural variability, seeing it as problematic and indeed produce responses in line with the designers own predetermined conceptualisation rather than a representation of the participant’s social world (Harre, 1979). A knowledge of these critiques are important, given that the majority of contemporary knowledge about attitudes has been conducted within experimental research methods. In addition to a heavy critique of the methodologies employed by experimental social psychologists, another considerable criticism has been locating attitudes historically within the mind of the individual (Hogg & Smith, 2007). This widely held view of attitudes is not extinct; it is still widely accepted that attitudes are ‘a psychological tendency that are expressed by evaluating a particular entity’ (Eagly & Chaiken, 1993, p.1). Yet given attitudes are studied within ‘social’ psychology, the absence of the ‘social’ has not gone unnoticed. Traditional social psychologists themselves have attempted to redress the balance, suggesting that the social context of attitudes have not been denied, but have not perhaps been the primary focus (Prislin & Christensen, 2005). Many theories have been redeveloped to draw back in the social nature of attitudes, for example Social Identity Theory (Tajfel & Turner, 1986; see Hogg & Smith, 2007) but critical social psychologists suggest that the concept of an ‘attitude’ itself cannot incorporate the ‘social’ in an adequate way (Howarth, 2006). One example of this, social representations theory (Farr & Moscovivi, 1984) focuses primarily on the dynamic and interactive relationship between social practices and identity (Howarth, Foster & Dorrer, 2004) For example, Puddifoot, (1997) suggests that the environment is not something that is responded to via an individuals ‘attitudes,’ rather people actually co-produce the realities that constitute that environment. As such, social representations are a far more encompassing concept than the attitude itself could ever be. Indeed discourse analysts also argue against the notion of the “individual” attitude. Potter & Wetherall (1987) highlight the difficulty traditional social psychology has had in evidencing the link between attitudes and behaviour. The social psychology crisis of the 70’s drew attention to the fact that there was actually weak evidence for the link between attitudes and their impact on behaviour, whereby the development of a large range of modifiers has enabled significant flexibility in responses to be explained (Potter & Wetherell, 1987), the argument remains that if so many modifying factors are needed to explain the ‘attitudes’ relationship to behaviour then it may no longer be helpful to preserve the notion of an underlying attitude at all (Potter & Wetherell, 1987). Yet despite the critiques that now surround attitudes research, the majority of research is still experimental and based on the concept of the attitude and much of our current understandings in to attitudes is based on this although this of course needs to be understood within the social context in which it resides. And attitude is a term that clearly has a place in the social world and is used and understand as part of everyday language.

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However, despite, the longevity of this dominant field of research in to attitudes, in relation to weight bias it remains fragmented and disjointed. Drawing together the research as it currently stands, and using a survey methodology within the current study in order to do this, made it possible to relate to existing research but to do so critically.

Appendix 13 - Choice of qualitative analysis

A thematic analysis was chosen as the analysis of choice for this research due the considerable advantage of its flexibility. It can be used within both constructionist and essentialist paradigms (Braun & Clarke, 2006), is compatible to use alongside positivist paradigms (Hayes, 2000), such as in the quantitative aspect of this research, and can be theory lead or data driven (Braun & Clarke, 2006). Its flexibility also allows one to identify themes on a semantic and/or an interpretive level and enables analysis of a range of data types. Finally, in recognition of my novice status as a qualitative researcher, it is an accessible form of analysis that does not necessarily require the detailed theoretical knowledge of its approach making it suitable for those early in qualitative research careers (Braun & Clarke, 2006). Content analysis

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The initial plan for data analysis of the open-ended responses in the free text box was to use content analysis. As there was only one optional opened ended question per participant, a content analysis was initially deemed sufficient to support the interpretation of the quantitative data collected, and would have enabled further analysis using descriptive and potentially inferential statistics. However, during the early stage of analysis which involved familiarization with the data, the depth, richness and subtly of the data became apparent, thus making a reductionist approach inappropriate to capture the experience of the participants well enough. My reflections on changing from content analysis to thematic analysis can be located in appendix 15. Grounded theory A grounded theory analysis would have required an opportunity to engage in theoretically guided sampling to build theory, and the use of constant comparison in the analysis until saturation is reached. This was not an option given the survey design, and the limited focus of the open-ended response material. Additionally, would typically be conducted on unstructured interviews of participant observation data (Hayes, 2000) and is used to develop new models of thinking. Its iterative process makes it time consuming and given the time constraints of this research project it was not deemed possible to complete a grounded theory analysis thoroughly enough within the available time.Interpretative Phenomenological Analysis (IPA)IPA was not selected due to the large number of participant responses analyzed with a view of exploring themes across participants. IPA intends to infiltrate deeply in the world of each participant in great detail to enable a complete understanding of the phenomenon in question (Hayes, 2000). Thus given the type of data collected, penetrating the world of each participant deeply enough for this analysis to be suitable was not possible.

Appendix 14 – Phases of the thematic analysis

Phases of a thematic analysis (Braun & Clarke, 2006)

Description of how each phase was operationalized for this study

1) Familiarization with the data

Data was removed from each participants survey and collated in one document, double spaced and line numbered by sentence where possible, before reading and re-reading the whole data set from the beginning.

2) Generating codes Initial codes or protothemes were written alongside each sentence giving equal attention to each extract.

3) Searching for themes Themes were developed by cutting out each

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separate code and organizing them to ‘theme piles’ which were then represented in visual mind maps.

4) Reviewing the themes Step 3 was fine tuned and repeated alongside a second researcher removing themes with little data to support them, condensing overlapping themes or sub-themes that did not add to the research questions, and expanding themes with sub-themes that were relevant to the research questions, until the majority of data was accounted for and there was agreement between researchers about thematic categories.

5) Defining and naming the themes

Step 4 and 5 were repeated with the researchers reviewing and amending themes until definitions were distinct.

6) Producing the report The thematic analysis was reported as part of the mixed methods design of this study.

Appendix 15 – Researcher reflexivity

Reflective conversations were undertaken within the supervisory relationship and documented within my supervision notes in order to explore how my own position, attitudes and assumptions have influenced the design, data collection and analysis in this study. Three particularly important reflections are summarized below in order to provide examples of these conversations to aid the transparency of the research process. 1) The context of the NHS Early supervision conversations lead to debate as to whether my recruitment strategy should target ‘NHS’ nurses or whether I should recruit for UK nurses generally. This highlighted to me immediately that I had specific assumptions about NHS nurses that for me, made them ‘different’ to nurses within private or third sector services. On reflection, these assumptions were based on my own knowledge of the discourses that surround the current NHS. Discourses that suggest it is a source of national

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pride (I recall watching the opening ceremony of the London 2012 Olympics with my own pride) but also discourses expressing great threat, of underfunding, overworked staff and the associated uncompromising positions frontline staff may be put in that compromise care. Nurses are often at the forefront of such narratives with long working hours, patient contact time and the amount of nursing staff needed to care for patients effectively. I recognized that these narratives were all ones that I, to one degree or another, had been influenced by as a member of British society, as a trainee clinical psychologist, and as a person. I found myself in a position where, although not a nurse, I do empathize with their plight. Yet equally, I experience my own growing concern about the impact of such organizational pressures on patient care, for whom advocacy is a role I hold dear within my own professional context. As such, I have needed to hold awareness of and be transparent about the fact that I am also situated within the same cultural context even though my role might be different. I have needed to be aware of this possible bias in both interpreting the data by assuming similarity between the participants and myself but also in assuming difference. The input of two additional researchers both of whom have accessed the data and one of whom who has provided a second perspective allowing for debate and critique about the thematic development has enabled me to be aware of and manage my own position within the research as well as possible. Additionally, these reflections influenced my recruitment process as I made the decision to include all UK nurses, rather than just NHS ones to ensure my own bias about what it might mean to be an NHS nurse did not bias the results through exclusion of those working in other organizations. Finally, acknowledging my own assumptions in this way meant that when initially familiarizing myself with the data, cross checking responses with whether the individual did indeed work within the NHS context before making assumptions about what statements such as being ‘overworked’ might mean was an important part of interpretation.

2) The change from content to thematic analysis My inclusion of one open ended question with an unlimited character free text box was to enable the collection of data that was less constrained than that collected by the likert scale survey design characteristic of the quantitative element of this study. My choice of content analysis reflected my belief that the exploration of themes identified through these means would support the interpretation of the quantitative data with the frequency of themes being synonymous with their importance. However, my own journey within the context of this research has lead me to move from a research position that prioritizes quantitative, objective, measurable and reliable data to one that realizes that real life information can not and should not always be reduced to numbers. To do so by way of the gross categorization typical of content analysis would be to loose the subtly, the complexity and richness of language as well as the potential, where necessary, to understand its function. My realization of this materialized from familiarizing myself with the data and recognizing the complexity of the language, breadth and detailed information provided by participants. Discussing this with my supervisors and challenging my assumptions about

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what it means to ‘know’ something (discussed below) lead me to switch to using a more flexible thematic analysis.3) My own research orientation As I have insinuated above, my own research orientation has shifted not only during, but also because of, my commitment to immersion with this research. I have certainly had to acknowledge my own personal preference for phenomena to be reduced in complexity to a level that I can make sense of it, thus perhaps my own preference for quantitative research approaches. My research in to the critical social psychology perspective has opened my eyes to what it really means to ‘know’ something and has raised questions to me in this regard that my original position has struggled to answer. In holding in mind critical approaches to my understanding of attitudes within this research I have learned to embrace the uncertainty that not having one concrete answer inevitably brings. This development in my position as a researcher has shifted in part through my engagement with my own research data (as described above) but it also comes from my clinical practice. Working with clients over the last few years has lead me to appreciate more post structural forms of therapy (such as narrative approaches) as I begin to understand that as a clinician, the expert position often taken (although not always acknowledged) within modernist therapies, can limit us and our clients in accessing different types of knowledge and actively co-constructing knowledge, in a way that may not be helpful. These developments in my own work did influence the decision to move from a content analysis to a thematic analysis and are likely to influence the type of research methodologies I may indeed use within attitudes research in the future. In the context of this research, these reflections allowed me the flexibility in my own mind to consider something ‘bigger’ than an attitude. It allowed me to engage with critical approaches to attitudes wholly and genuinely in way that I may not have been able to do so before. As such, I have been able to integrate the perspectives of traditional and critical social psychology in to my work, an important stepping-stone in moving forward within a field that has typically been dichotomous.

Appendix 16 – Yardley’s principles of credibility

Establishing guidelines to assess the quality of qualitative research has notably been more difficult than in the traditions of quantitative research (Yardley, 2000). However, there is still a need to show that qualitative research is of good quality and credibility and thus in the context of this research, Yardley’s (2000) four characteristics of good qualitative research were drawn upon to illustrate this as discussed below.

1) Sensitivity to context This research explored weight bias in nurses and as such prior to the study commencing immersion with prior research relevant to this field was paramount. In order to fully understand the context in which previous literature on weight bias in nurses had been developed a range of research areas were drawn upon. This was largely due to the many fields that have

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influenced the development of the weight bias literature. These included broadly reviewing ‘attitudes literature’ generally along with the associated critique, the literature on prejudice and discrimination, as well as the literature exploring weight bias exhibited to and by different populations. Exploring the context in this way also lead to the exploration of a range of different methodologies employed to ‘measure’ attitudes and a range of underpinning theories used to understand weight bias but also attitudes more generally. Contextualizing the current research project within wider research and theory was important but given the predominantly inductive approach undertaken here, staying sensitive to the data in order to allow data driven themes to emerge was also necessary and achieved through supervision. A summary of attitudes research and its wider critique can be found in appendix 12. Additionally, the socio-cultural context of the current study was also considered. Although the study recruited all UK nurses, thus incorporating those in NHS, private and third sectors, the majority of participants were nurses working within the context of the NHS. The NHS is a often a forum within there are many competing viewpoints and discourses surrounding it all fighting for ascendency which are likely to influence the participants of this study. Although I am not a nurse, I am employed by the NHS and thus my awareness of the influences that has on my interpretation of the data was considered. My reflections on these contextual components can be found in appendix 15.

2) Commitment and rigor Commitment to process was adhered to through the immersion of the researcher within the data. Data was read and re-read regularly and over a period of several months. Data was referred back to regularly throughout the analysis and theme development. Researcher competence in the chosen analysis was developed through supervision, post-doctoral teaching, analysis of prior research using thematic analysis and reflective practice. Given the large participant sample size, saturation within the data was easily reached.

3) Transparency and coherence Transparency about the research process was achieved through the use of regular supervision and open conversations amongst researchers. Appendices 17, 18, & 19 document the process of theme development alongside reflections of how the researchers own position may impact on interpretation. Examples of each theme are provided within the results section to aid transparency. The fit between the qualitative method chosen (thematic analysis) and its function within the wider research are coherent as it enabled a richer perspective of the participants than the quantitative analysis could illustrate alone.

4) Impact and importance The importance of this research is addressed in the introduction and the discussion sections. Primarily, the importance of understanding weight related bias lies within the clinical and psychological implications it may have for the person who experiences that bias. Given the fragmented literature within this field, this is an important part of not only understanding weight bias but also changing the discourses associated with it in western cultures that are not helpful to the person concerned.

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Appendix 17 – Thematic map examples and discussion

Initial thematic map

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Appendix 17 – Thematic map examples and discussion (continued)

Developed thematic map

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Appendix 17 – Thematic map examples and discussion (continued)

Final thematic map

171

Appendix 17 – Thematic map examples and discussion (continued)

Key changes during the development of the thematic maps discussion

Initial thematic map Initially every code that appeared in the text more than once was included in this map to ensure no potential themes were eliminated too quickly. There were some themes that appeared to overlap (for example the ‘NHS context’ theme within the pragmatics of caring theme and the ‘moral discourses’ in the culture theme). However, these were left separate at this stage until further evidence for each subtheme could be examined and reworked if appropriate. Themes were developed largely semantically but themes did emerge on an interpretative level as well. These appeared strongly evidenced within the text, and thus were also included in the analysis.

Developed thematic map This map was developed through re-reading the data and matching each code with each theme and sub theme. Where there was not sufficient evidence to support a theme or sub theme, it was removed. On re-reading the data and matching data with themes it was noted between researchers that there were several subthemes within the map that were well evidenced but did not fit well within their current category. Through drawing these out of the map, these sub themes appeared to serve a common purpose, that of ‘protecting’ the nurses identity in some way. For example, de-identifying with their nursing identity and aligning with their identity as a person when they voiced negative attitudes, distancing themselves from the obese patient, commenting on attitudes within others but not themselves or denying their negative attitudes impacted on the level of care the person received. As such, these were re grouped in to a theme of ‘identity management’.

Final thematic map This map was the final version and a product of comparing definitions between themes and subthemes to look for distinctiveness. At this stage, several subthemes were integrated either where by definition they were too similar or within the data they were used frequently within the context of each other (for example responsibility and choice/control). In addition to this, subthemes were also integrated depending on whether they added anything to the theme in the context of the overall research. For example, knowing that nurses who acknowledge a wide range of factors in their appraisal of what it means to be obese appear to hold more positive attitudes seemed equally as useful as differentiating between what each of those factors might be. The terms of themes were also examined in the context of the data that supported them and where needed, themes were re-defined to be more inclusive. For example, ‘culture’ was renamed ‘cultural context’ and attitudes

172

seen in others became stake inoculation to highlight the idea that nurses appeared to have a stake in these attitudes but could not own them themselves. Some themes were also renamed to be more specific; for example, identity management became identity management strategies.

173

Appendix 18- Example data and coding

174

Appendix 18- Example data and coding

175

Appendix 18- Example data and coding

176

Appendix 19– Final coding categories

Theme Sub theme Coding categories included

Identity

Nursing identity Nurses non-judgmental, understanding, equality, compassionate, listening & to educate

Personal identity As with nursing identity but in the context of ‘being a human’

Weight related identity

Positive attitudes -increases empathy, compassion and understanding.

Negative attitudes- increases frustration if have experienced own successful weight loss.

Acknowledgement of wider factors

Social factors, education, finance, medical conditions, adverse experiences, inequality

Pragmatics of caring

Complications in caring

Risk of injury to HCP, difficulty in manual handling and mobilizing, increased and more complex interventions, difficulty with personal care, increased medical risk, co-morbidities

Lack of resources Lack of time, resources, funding, staff and equipment needed to care effectively

BlameResponsibility For losing weight, for

managing health conditions or following advice

Preventability Preventing associated health conditions or obesity itself

Deservingness Deservingness of healthcare, services and funding

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Appendix 19– Final coding categories (continued)

Theme Sub theme Coding categories included

Culture

Media Media (TV, newspaper)Social media

Wider society Society generallyWestern populations

NHS moral discourse

Acknowledgement of NHS as ‘underfunded, resourced or staffed’ NHS in ‘crisis’, NHS staff overworked.

Identity management strategies

Stake inoculation Attitudes expressed through others (blame, characteristics, general opinions).

De-identification Identifying with identity as a person over a nurse

Denying impact of attitudes on care

Denying the impact of negative attitudes on empathy, compassion, practical care and equal treatment

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Appendix 20 – Full data screening analysis

Four of the questionnaires (ATOP, RSE, PSS and MBI) had more

than 5% missing data (see missing data summary table Appendix 2) and

thus Little’s MCAR test (Little, 1988) was undertaken. This resulted in a

statistically significant result (p < .05), indicating that the missing data from

each questionnaire was not missing at random (see table 1).

Table 1. Little’s MCAR Test Results

Little’s MCAR Test ResultsScale Chi Squared (X ²) Significance Value (p)ATOP 158.774 p < .01RSE .000 p < .01PSS 27.705 p < .01MBI 174.724 p < .01

The presentation order appeared to have an effect, with those

questionnaires presented later, being more likely to have missing data. As

such all 218 participants completed every item on the first scale presented,

the AFA, whilst the last presented scale, the MBI, had between 10-18%

responses missing for each item. Participants with declining responses were

initially removed from the analysis and Little’s MCAR Test (Little, 1988)

repeated; but this still resulted in a statistically significant result (p< .05)

suggesting that the missing data remained not missing at random (see table

2).

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Appendix 20 – Full data screening (continued)Table 2.

Little’s MCAR test for non ‘trail off data’

Little’s MCAR Test ResultsScale Chi Squared (X ²) Significance Value (p)ATOP 33.419 p < .05PSS 27.623 p < .01MBI 202.326 p < .01Note: RSE missing data analysis was not computed as once the ‘trail off’ data was removed there were no missing values.

In response to the Little’s MCAR test results, Chi Squared tests were

conducted on the missing and non-missing data in relation to qualification

status, age, BMI, gender and number of hours spent with patients in order to

assess whether the missing data within each questionnaire related to

particular demographic variables. Missing data was associated with the

largest age category (ages 22-30) for qualified nurses, (p<. 05); (see

appendix 21) which may relate to nursing managers’ comments during

recruitment about concerns that qualified nurses may not have time to

complete the survey.

Given that there was no missing data for the AFA, the scale required

for research question one which needed an equal number of undergraduate

and qualified nurses, missing data for the remaining scales was excluded

using the ‘exclude pairwise’ option to enable full sets of data to be used

where appropriate ant thus a large enough sample size for each remaining

questionnaire to reach statistical power.

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Appendix 20 – Full data screening (continued)

In relation to research question one a number of Chi Squared tests

were conducted to assess the pattern of responses between demographic

variables and qualification status for the AFA scores. No patterns were

detected between gender, BMI, and number of patient hours in

undergraduate or qualified nurses (p>.05). However, patterns were detected

between age and qualification status, X² (5, N=218) = 66.754, p< .01 with

undergraduate nurses being significantly younger than qualified nurses

(appendix 22).

A series of Mann Whitney U tests were conducted to assess for

significant differences in the results of each scale between the undergraduate

and the qualified nurses due to the proposed analysis of these groups

together for research question 2,3,4 and 5. There were no significant

differences between the overall scores on the ATOP (U=4110.000, p >.05)

or the RSE (U=4787.500, p >.05) but undergraduate nurses scores were

significantly higher than qualified nurses (U=3550.500, p>.05) on the PSS.

There was no significant difference on the MBI between the

depersonalization average scores for undergraduate and qualified nurses

(U=3264.000, p >.05) or for the emotional exhaustion subscale

(U=3967.000, p>.05). However, for the personal accomplishment subscale,

undergraduate nurses scored significantly higher than qualified nurses did

(3374.500, p< .05).

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Appendix 20 – Full data screening (continued)

Homogeneity of variance

A Levenes test of variance was conducted on the AFA scale, required

prior to the comparison of its two qualification groups which indicated equal

variances between both groups for the dislike subscale (F=1.645, p>.05), the

fear of fat subscale (F=2.779, p>.05) and the willpower subscale (F=1.400,

p>.238).

Tests of normality

The Kolmogorov Smirnov (K.S.) tests (table 3) of normality

conducted for the ATOP and the PSS were both non significant (p>.05)

suggesting that both questionnaires were normally distributed. The RSE

scale, the MBI subscales and the AFA subscales were all significant (p<.05)

suggesting non normal distributions (see appendix 23).

Table 3.

Tests of normality

Scale Subscale Skewness Kurtosis K.SSE SE p

AFA Dislike -2.122 .165 4.912 .328 .209 .000**Fear .400 .165 -876 .328 .094 .000**Willpower .199 .165 -.757 .328 .071 .010*

ATOP -.090 .174 -.621 .346 .058 .200RSE .221 .173 -.523 .344 .067 .032*PSS .142 .174 .173 .346 .053 .200MBI DP 1.305 .182 1.920 .361 .164 .000**

PA -1.191 .174 2.303 .346 .121 .000**EE .078 .174 -.331 .346 .078 .006**

Note: DP = depersonalization, PA = personal accomplishment, EE=emotional exhaustion * p < .05, ** p <.01

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Appendix 20 – Full data screening (continued)

In relation to research question one, K.S tests were also run for both

qualification groups separately for the AFA. The subscales ‘dislike’ and

‘fear’ remained non normally distributed (p<.01) although the third subscale

‘willpower’ became normally distributed for both groups (table 4).

Table 4.

Normality tests for the AFA split by undergraduate and qualified nursing

groups.

Subscale Q-S Skewness Kurtosis K.SSE SE p

Dislike U -2.093 .228 4.119 .453 .221 .000Q -1.973 .235 5.241 .465 .192 .000

Fear U .522 .228 -.931 .453 .129 .000Q .297 .235 -.715 .465 .118 .001

Willpower U .034 .228 -.793 .453 .061 .200*Q .380 .235 -.612 .465 .080 .091*

Note: Q-S=qualification status, U=undergraduate, Q= qualified

* = Significant at the 0.5 level

Outliers

Outliers were detected on the dislike scale of the AFA, the PSS and on the

depersonalization and personal accomplishment subscales of the MBI

(appendix 24). The raw data was checked for errors and the trimmed means

examined for each scale which remained close in proximity to the means

(table 5). The assumptions of normality were retested for each scale with

outliers removed but the scales remained non-normally distributed and as

the trimmed mean suggested they were not distorting the results of each

scale in deviating from the mean, the outliers remained.

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Appendix 20 – Full data screening (continued)

Table 5.

Mean (S.E.) and Trimmed means for scale scores.Scale Subscale Mean score (S.E.) Trimmed meanAFA Dislike

FearWillpower

7.4734 (.13976)3.7929 (.21257)4.3116 (.16402)

7.71333.71534.2885

ATOP 71.5385 (1.12065) 71.7268RSE 26.2012(.43825) 20.0270PSS 19.3373 (.38451) 19.2761MBI DP

PAEE

.9053 (.05909)3.9830 (0.5416)2.9034 (.07574)

2.8864

Transformations

In light of the non-normally distributed data, transformations were

conducted based on whether the scale was positively or negatively skewed.

However, the range of transformations performed did not aid the data in

meeting the assumptions required of parametric data (appendix 25). The

reliability estimates for the items of each scale were examined and the most

unreliable item from each scale removed. However, this also did not

improve the distribution of scores and equally did not reduce the overall

reliability of the scale so the items remained.

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Appendix 21 – Chi Squared analysis for missing data and demographic variables

Note: The Pearson’s Chi squared statistic is reported except in the 2x2 designs where the continuity correction was reported or where a test yielded a count of less than five when a Fisher’s Exact statistic was reported instead. Regardless the statistic is reported as ‘chi squared’ within each table.

Attitudes Toward Obese Persons Scale (ATOP)

Table 1: Chi Squared for ATOP missing data and qualified status

Table 2: Chi Squared for ATOP missing data and gender

p <.05 significant

Chi Squared for ATOP missing data and qualified statusQualification status

Missing data

S.R Non missing data

S.R Chi Squared

P value

Undergraduate 0 -3.1 112 .9 28.081 .000Qualified 18 3.2 86 -1Total 22 196

Chi Squared for ATOP missing data and genderGender Missing

data S.R Non missing

data S.R Chi

Squared P value

Male 1 -.5 16 .2 .412 .706Female 21 .2 180 -.1Total 22 196

185

Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Table 3: Chi Squared for ATOP missing data and BMI

Chi Squared for ATOP missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P value<18.5 0 -.8 7 .3

1.170 .74018.5-24.9 10 -.2 95 .125-29.9 7 -.1 65 .030 plus 5 .8 29 -.3Total 22 196

Table 4: Chi Squared for ATOP missing data and number of hours spend with patients

p <.05 significant

Chi Squared for ATOP missing data and number of hours spend with patientsNo of patient hrs

Missing data S.R. Non missing data S.R. Chi Squared P Value

0-20 7 -.7 84 .2

8.893 .08621-40 13 .1 111 .041-60 1 1.8 1 -.660 plus 1 2.8 0 -.9Total 22 196

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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Table 5: Chi Squared for ATOP missing data and age categories

Rosenburg Self Esteem Scale (RSE)

Table 6: Chi Squared for RSE missing data and qualified statusChi Squared for RSE missing data and qualified status

Qualification status Missing data S.R Non missing data S.R Chi Squared P value Undergraduate 0 -3.2 112 -1.0 21.057 .000Qualified 20 3.3 86 -1.0Total 20 198

p <.05 significant

Chi Squared for ATOP missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 1 -1.9 52 .6 9.781 .09122-30 11 1.9 51 -.631-40 4 -.4 45 .141-50 3 -.1 28 .051-60 3 .5 19 -.260 plus 0 -.3 1 .1Total 22 196

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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Table 7: Chi Squared for RSE missing data and gender

Table 8: Chi Squared for RSE missing data and BMI

Chi Squared for RSE missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P Value<18.5 0 .1 7 .3 .625

.929

.18.5-24.9 10 .1 95 .025-29.9 1 -.2 66 .130 plus 4 .5 30 -.2Total 20 198

p <.05 significant

Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Chi Squared for RSE missing data and genderGender Missing data S.R Non missing data S.R Chi Squared P value Male 1 -.4 16 .1 .003 .958Female 19 .1 182 .0Total 20 198

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Table 9: Chi Squared for RSE missing data and number of hours spend with patients

Table 10: Chi Squared for RSE missing data and age categories

p <.05 significant

Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Chi Squared for RSE missing data and number of hours spend with patientsNo of patient hrs

Missing data S.R. Non missing data S.R. Chi Squared P Value

0-20 6 -.8 85 .35.271 .21121-40 13 .5 111 -.2

41-60 1 1.9 1 -.660 plus 0 -.3 1 .1Total 20 198

Chi Squared for RSE missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 1 -1.8 52 .6

11.093 .04022-30 11 2.2 51 -.731-40 4 -.2 45 .141-50 1 -1.1 30 .351-60 3 .7 19 -.260 plus 0 -.3 1 .1Total 20 198

189

Perceived Stress Scale (PSS)

Table 11: Chi Squared for PSS missing data and qualified status

Chi Squared for PSS missing data and genderGender Missing data S.R Non missing data S.R Chi Squared P Value Male 2 .2 15 -.1 .000 1Female 21 .0 180 .0Total 23 195

Table 12: Chi Squared for PSS missing data and gender

p <.05 significant

Chi Squared for PSS missing data and qualified statusQualification status Missing data S.R Non missing data S.R Chi Squared P Value Undergraduate 0 -3.4 112 1.2 24.918 .000Qualified 23 3.5 83 -1.2Total 23 195

190

Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Table 13: Chi Squared for PSS missing data and BMI

Table 14: Chi Squared for PSS missing data and number of hours spend with patients

p <.05 significant

Chi Squared for PSS missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P Value<18.5 0 -.9 7 .3

2.009 .66818.5-24.9 10 -.3 95 .125-29.9 9 -.3 95 .130 plus 4 .5 63 -.2Total 23 195

Chi Squared for PSS missing data and number of hours spend with patientsNo of patient hrs Missing data S.R. Non missing data S.R. Chi Squared P Value 0-20 7 -.8 84 .3

4.935.20921-40 15 .5 109 -.2

41-60 1 1.7 1 -.660 plus 0 -.3 1 .1Total 23 195

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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Table 15: Chi Squared for PSS missing data and age categories

Table 16: Chi Squared for MBI missing data and qualified statusChi Squared for MBI missing data and qualified status

Qualification status Missing data S.R Non missing data S.R Chi Squared P Value Undergraduate 1 -4.3 111 2.0 44.481 .000Qualified 39 4.4 67 -2.1Total 40 178

p <.05 significant

Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)

Chi Squared for PSS missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 1 -1.9 52 .7

12.355 .022

22-30 12 2.1 50 -.731-40 6 .4 43 -.141-50 1 -1.3 30 .451-60 3 .4 19 -.260 plus 0 -.3 1 .1Total 23 195

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Table 17: Chi Squared for MBI missing data and gender

Table 18: Chi Squared for MBI missing data and BMI

Chi Squared for MBI missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P Value<18.5 0 -1.1 7 .5

1.898 .57818.5-24.9 18 -.3 87 .125-29.9 14 .2 58 -.130 plus 8 .7 26 -.3Total 40 178

p <.05 significant

Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)Table 19: Chi Squared for MBI missing data and number of hours spend with patients

Chi Squared for MBI missing data and genderGender Missing data S.R. Non missing data S.R. Chi Squared P Value Male 3 -.1 14 .0 .000 1.000Female 37 .0 164 .0Total 40 178

193

Table 20: Chi Squared for MBI missing data and age categories

p <.05 significant

Appendix 22 – Chi Squared analysis between demographic variables and qualification status

Chi Squared for MBI missing data and number of hours spend with patientsNo of patient hrs

Missing data S.R. Non missing data S.R. Chi Squared P Value

0-20 17 .1 74 .02.282

.53921-40 22 -.2 102 .1

41-60 1 1 1 -.560 plus 0 -.4 1 .2Total 40 178

Chi Squared for MBI missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 2 -2.5 51 1.2

17.547 .00222-30 14 .8 48 -.431-40 8 -.3 41 .241-50 7 .6 24 -.351-60 9 2.5 13 -1.260 plus 0 -.4 1 .2Total 40 178

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Note: The Pearson’s Chi squared statistic is reported except in the 2x2 designs where the continuity correction was reported or where a test yielded a count of less than five when a Fisher’s Exact statistic was reported instead. Regardless the statistic is reported as ‘chi squared’ within each table.

Table 1: Chi Squared for qualification status and gender AFA questionnaire

Table 2: Chi Squared for qualification status and age categories

Qualification status

Age category (number of participants) Chi Squared P Value18-21 22-30 31-40 41-50 51-60 60+

Undergraduate 49 30 22 9 2 0 66.754 .000Qualified 4 32 27 22 20 1

Table 3: Chi Squared for qualification status and BMI categories

Qualification status

BMI category (number of participants) Chi Squared P Value<18.5 18.5-24.9 25-29.9 30+

Undergraduate 5 62 32 13 7.335 .062Qualified 2 43 40 21

p <.05 significant

Qualification Status

Gender (number of) Chi Squared P ValueMale Female

Undergraduate 7 105 .389 .453Qualified 10 96

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Appendix 22 – Chi Squared analysis between demographic variables and qualification status (continued)

Table 4: Chi Squared test for qualification status and number of hours spent with patients per weekQualification status

Patient hours (number of participants) Chi Squared P Value0-20 21-40 41-60 60+

Undergraduate 51 60 1 1 2.468 .620Qualified 40 64 64 1

p <.05

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Appendix 23 – Normality distribution histograms

Figure 1: AFA Dislike Subscale

Figure 2: AFA Fear

197

Appendix 23 – Normality distribution histograms (continued)

Figure 3: AFA Willpower Subscale

AFA subscale histograms split by qualification status

Figure 4: AFA Dislike Subscale undergraduate nurses only

198

Appendix 23 – Normality distribution histograms (continued)

Figure 5: AFA Dislike Subscale qualified nurses only

Figure 6: AFA Fear Subscale undergraduate nurses only

199

Appendix 23 – Normality distribution histograms (continued)

Figure 7: AFA Fear Subscale qualified nurses only

Figure 8: AFA Willpower Subscale undergraduate nurses only

200

Appendix 23 – Normality distribution histograms (continued)

Figure 9: AFA Willpower Subscale qualified nurses only

Figure 10: ATOP

201

Appendix 23 – Normality distribution histograms (continued)

Figure 11: RSE

Figure 12: PSS

202

Appendix 23 – Normality distribution histograms (continued)

Figure 13: MBI Depersonalization Subscale

Figure 14: MBI Personal Accomplishment Subscale

203

Appendix 23 – Normality distribution histograms (continued)

Figure 15: MBI Willpower Subscale

204

Appendix 24 -Correlation analysis with AFA dislike and MBI Depersonalization outliers removed

** significant at the .01 level

AFA dislike MBI DPAFA dislike Spearman’s rho 1 -.292**

Sig. (2-tailed) .000N 208 166

MBI DP Spearman’s rho -.292** 1Sig. (2-tailed) .000N 166 170

205

Appendix 25 – Normality tests post transformations

Table 1: Anti-Fat Attitudes Scale (AFA) tests of normality on raw data and transformationsTest performed

AFA subscale

No transformation Log10-Reflect SQRT-Reflect Reciprocal= Reflectp p p p

K S Test (p) Dislike .209 .000 .125 .000 .153 .000 .088 .000Fear .094 .000 .169 .000 .142 .000 .279 .000Willpower .071 .010 .119 .000 .094 .000 .225 .000

Skewness Dislike -2.12 1.043 1.378 .302Fear .4 -1.100 -.829 2.387Willpower .199 -.909 -.625 2.528

Kurtosis Dislike 4.912 .683 1.788 -.847Fear -.8 .265 -.267 5.121Willpower -.757 .252 -.275 7.599

p <.05 significant

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Appendix 25 – Normality tests post transformations (continued)Table 2: AFA tests of normality on raw data and transformations split by qualification status Test performed

AFA subscale

Log10-Reflect SQRT-ReflectUndergraduate p Qualified p Undergraduate p Qualified p

Kolmogorov Smirnoff

Dislike .146 .000 .150 .000 .173 .000 .159 .000Fear .175 .000 .180 .000 .138 .000 .158 .000Willpower .102 .006 .146 .000 .083 .057 .119 .001

Skewness Dislike 1.136 -920 1.466 1.202Fear -1.137 -1.090 -.900 -.784Willpower -.786 -1.055 -.485 -.784

Kurtosis Dislike .886 .242 1.852 1.288Fear .173 .484 -.319 -.100Willpower .090 .528 -.396 -.040

Test performed

AFA subscale

Reciprocal ReflectUndergraduate p Qualified p

Kolmogorov Smirnoff

Dislike .073 .188 .104 .007Fear .301 .000 .277 .000Willpower .214 .000 .248 .000

Skewness Dislike .390 .171Fear 2.81 2.535Willpower 2.281 2.535

Kurtosis Dislike -.491 -1.117Fear 4.453 6.215Willpower 7.320 6.869

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Appendix 25 – Normality tests post transformations (continued)Table 3: Attitudes Toward Obese Persons Scale (ATOP) tests of normality on raw data and transformationsTest performed

No transformation p Log10-Reflect p SQRT-Reflect p Reciprocal= Reflect p

K S Test (p) .058 .200 .119 .000 .062 .062 .334 .000Skewness -.090 -1.657 -.511 10.471Kurtosis -.621 4.899 -.075 128.792Test performed

Log10 p SQRT p Reciprocal p

K S Test (p) .087 .001 .073 .012 .113 .000Skewness -.594 -.324 1.354Kurtosis .217 -.350 3.237

p <.05 significant

208

Appendix 25 – Normality tests post transformations (continued)

Table 4: Rosenberg Self Esteem Scale (RSE) tests of normality on raw data and transformations

Test performed

No transformation

p Log10 p SQRT p Reciprocal p

K S Test (p) .067 0.32 0.87 .001 .060 .082 .136 .000Skewness .221 -.397 -.082 1.050Kurtosis -523 -.355 -.550 .729

Table 5: Perceived Stress Scale (PSS) tests of normality on raw data and transformations

Test performed

No transformation p Log10 p SQRT p Reciprocal p

K S Test (p) 0.60 2.00 0.92 .000 0.68 .030 .147 .000Skewness .142 -.653 -.243 1.634Kurtosis .173 -.761 -.208 .4.259

p <.05 significant

209

Appendix 25 – Normality tests post transformations (continued)

Table 6: MBI tests of normality on raw data and transformationsTest performed Subscale10 No transformation Log10-Reflect SQRT-Reflect Reciprocal= ReflectK S Test (p) DP

PAEE

.164 .000 .089 .001 .181 .000 .136 .000

.121 .000 .089 .001 .100 .000 .060 .083

.078 .006 .196 .000 0.85 .002 .231 .000Skewness DP

PAEE

1.305 -.648 -1.675 1.436-1.191 .460 .804 .198.078 -2.269 -.350 4.139

Kurtosis DPPAEE

1.920 .358 3.974 3.6502.303 .242 .954 .319-.331 7.831 -.182 27.836

Test performed Log10 SQRT ReciprocalK S Test (p) DP

PAEE

.086 .002 .126 .000 .124 .000

.168 .000 .144 .000 .252 .000

.088 .001 .064 .051 .136 .000Skewness DP

PAEE

.346 .789 .356-3.101 -1.909 6.742-1.009 -.350 3.703

Kurtosis DPPAEE

-.583 .240 -.92416.041 6.542 55.4372.966 .415 23.215

10 Note: DP=depersonalization, PA= Personal Accomplishment, EE=Emotional Accomplishment

210

Appendix 26 – Scatterplots for correlation analyses

Figure 1: Scatter plot for the correlation between the AFA dislike subscale and BMI

Figure 2: Scatter plot for the correlation between the AFA fear of fat subscale and

BMI

211

Appendix 26 – Scatterplots for correlation analyses (continued)

Figure 3: Scatter plot for the correlation between the AFA willpower subscale and BMI

Figure 4: Scatter plot for the correlation between the AFA dislike subscale and the RSE

212

Appendix 26 – Scatterplots for correlation analyses (continued)Figure 5: Scatter plot for the correlation between the AFA fear of fat subscale and the RSE

Figure 6: Scatter plot for the correlation between the AFA fear of fat subscale and the RSE

213

Appendix 26 – Scatterplots for correlation analyses (continued)Figure 7: Scatter plot for the correlation between the ATOP and RSE

Figure 8: Scatter plot for the correlation between the AFA dislike subscale and the PSS

214

Appendix 26 – Scatterplots for correlation analyses (continued)

Figure 9: Scatter plot for the correlation between the AFA fear of fat subscale and the PSS

Figure 10: Scatter plot for the correlation between the AFA willpower subscale and the PSS

215

Appendix 26 – Scatterplots for correlation analyses (continued)

Figure 11: Scatter plot for the correlation between the ATOP and the PSS

Figure 12: Scatter plot for the correlation between the AFA dislike subscale and the MBI DP subscale

216

Appendix 26 – Scatterplots for correlation analyses (continued)

Figure 13: Scatter plot for the correlation between the AFA dislike subscale and the MBI PA subscale

Figure 14: Scatter plot for the correlation between the AFA dislike subscale and the MBI EE subscale

217

Appendix 26 – Scatterplots for correlation analyses (continued)

Figure 15: Scatter plot for the correlation between the AFA fear of fat subscale and the MBI DP subscale

Figure 16: Scatter plot for the correlation between the AFA fear of fat subscale and the MBI PA subscale

Appendix 26 – Scatterplots for correlation analyses (continued)

Figure 17: Scatter plot for the correlation between the AFA fear of fat subscale and the MBI EE subscale

218

Figure 18: Scatter plot for the correlation between the AFA willpower subscale and the MBI DP subscale

219

Appendix 26 – Scatterplots for correlation analyses (continued)

Figure 19: Scatter plot for the correlation between the AFA willpower subscale and the MBI PA subscale

Figure 20: Scatter plot for the correlation between the AFA willpower subscale and the MBI EE subscale

220

Part 3: Summary of clinical experience

Over the course of three years on the PsychD Clinical Psychology programme I

have completed five clinical placements across the lifespan and within a variety of

specialties. This section of the portfolio outlines a description of each placement

alongside the experiences and opportunities I gained from each.

In year one I completed a 10 month placement in a community adult mental

health recovery and support service. I worked across both adult community and

inpatient settings providing comprehensive psychological assessment, formulation,

intervention and consultation. My main therapeutic model was CBT although the

majority of my work was also informed by attachment and systemic theory. I co-

facilitated a psychoeducation group for managing bipolar disorder and a cognitive

based mindfulness therapy group for people with complex depression and anxiety. I

held responsibilities for risk assessment and clinical governance for my clients

alongside the wider MDT and enjoyed engaging with teaching opportunities with the

team to help develop psychological thinking.

In year two, my first six-month placement was in a community learning

disability service. Adapting evidence based therapies in flexible ways enabled me to

make psychological therapy accessible for people with learning disabilities and

mental health difficulties. I worked on a consultancy basis with behaviours that

challenge from a Positive Behavioural Support standpoint, infiltrating systemic and

attachment ideas. I conducted a range of assessments including eligibility, sexual

knowledge, dementia and autism. I also taught on the learning disabilities module of a

clinical psychology masters programme. This placement enabled me to hone my

verbal and written communication skills to meet the needs of this client group.

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The second six-month placement in my second year was in a child and

adolescent mental health team. I was part of the reflecting team within the systemic

family therapy service for young people with eating disorders and was lead therapist

for one family. I worked with young people using either CBT or narrative practice,

although again being informed by attachment and systemic theory. I worked within

the neurodevelopment pathway to conduct neuropsychological assessments for

children with possible autism and/or ADHD. I learned to work creatively and

adaptively according to the developmental stage of the clients.

In my first placement of my third year I worked within an older adult

community mental health team. Here I worked predominantly within a narrative

therapeutic framework whilst working with clients individually. I worked within a

Positive Behavioural Support framework to provide consultancy other services where

there were difficulties caring for clients diagnosed with dementia and the associated

behaviours that staff found challenging. I conducted a range of neuropsychological

investigations to aid the assessment of dementia.

My last six-month placement was my specialist option. I worked within the

personality disorder pathway within a community mental health team and also within

an Early Intervention Service for people with psychosis. I worked with people with a

diagnosis of personality disorder in a group context (STEPPS group) and individually

highlighting the impact of early attachment difficulties and trauma on the

development of severe mental health difficulties.

Through working within the Early Intervention Service for psychosis I have

worked within the CBT-P model for clients with psychosis, developing skills in

therapeutic engagement and developing collaborative understandings of the person’s

difficulties. I have conducted assessments and interventions using the Compassion

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Focused Therapy model and I have also co-facilitated a compassion focused resilience

group and an Acceptance and Commitment Group for this client group.

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Part 4PSYCHD CLINICAL PROGAMME

TABLE OF ASSESSMENTS COMPLETED DURING TRAINING

Year I AssessmentsASSESSMENT TITLE

WAIS WAIS Interpretation (online assessment)Practice Report of Clinical Activity

CBT assessment and formulation of Lucy, a female in her 40’s experiencing agoraphobia (without panic)

Audio Recording of Clinical Activity with Critical Appraisal

Audio recording of clinical activity and critical appraisal

Report of Clinical Activity N=1

Report of clinical activity, N=1 analysis. Mary a female in her 30’s with a diagnosis of bipolar disorder

Major Research Project Literature Survey

A literature survey investigating the factors associated with weight related bias in healthcare professionals towards obese patients

Major Research Project Proposal

A research proposal exploring the variables associated with weight related bias in healthcare professionals towards obese patients

Service-Related Project Evaluating a service user and carer based initiative at one UK Clinical Psychology Doctorate Training Course

Year II AssessmentsASSESSMENT TITLE

Report of Clinical Activity Formal Assessment

A learning disability assessment for Mel, a female in her late teenage years.

PPLD Process Account PPLDG Process Account

Year III Assessments ASSESSMENT TITLE

Presentation of Clinical Activity

A 9 year old girl experiencing intrusive thoughts and anxiety; who loves cats and playing teachers

Major Research Project Literature Review

Personal factors associated with the attitudes of UK nurses toward patients with obesity: A literature review

Major Research Project Empirical Paper

A mixed methods study exploring weight related bias in undergraduate and qualified nurses

Report of Clinical Activity

A story of a woman in her late 60’s and her experiences of distress: A Narrative informed approach.

Final Reflective Account

On becoming a clinical psychologist: A retrospective, developmental, reflective account of the experience of training

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