The relationship between gender attitudes and children’s feelings of shame in

response to imagined failure.

By

Indigo Davis

Submitted in partial fulfilment of the degree of Doctor of Psychology (Clinical

Psychology)

School of Psychology

Faculty of Health and Medical Sciences

University of Surrey

September 2019

© Indigo Davis 2019

1

Abstract

Objective: Shame is a secondary self-conscious distressing emotion that can be

evoked following experiences of failure. Research indicates potential gender

differences in shame responses following failure however findings have been mixed.

The current study examined whether gender-stereotypicality of a task was related to

anticipated shame following task failure, and whether gender attitudes in mothers

and children were related to anticipated shame.

Design: Mothers and their children completed measures assessing gender

stereotyped attitudes. Children were then asked to read six short stories about failing

a task (2 male-stereotyped, 2 female-stereotyped, 2 non-stereotyped). Following each

story, children were asked to rate how much shame they would experience in the

situation.

Participants: Participants were 28 mother-child dyads recruited from schools in

London.

Results/Findings: ANOVA and correlational analysis were used to explore

relationships between mother and child gender attitudes, and feelings of anticipated

shame in response to gender-stereotyped and non-gender stereotyped failure. Results

suggested a main effect of task, however associations between parent and child

gender attitudes were inconsistent.

Conclusions/Implications: Mostly, the study hypotheses were not supported.

Conceptual and methodological critiques are considered, such as validity of the

concept of gender stereotyped tasks, task salience and measurement issues. Further

research is needed to explore parent-child gender attitudes and the implications of

these for the development of self-conscious emotions such as shame.

2

Acknowledgements

I wish to extend my sincere gratitude to the entire course team at the University of

Surrey for their expertise, dedication and support throughout clinical training. The

last three years have been undoubtedly some of the hardest, but also most enriching

and rewarding of my career to date.

I would like to first thank my Clinical Tutor, Dr Nan Holmes, whose unwavering

support, encouragement and attention to detail over the last three years helped me to

develop both personally and professionally in ways that allowed me to complete

clinical training to the best of my ability. I will be forever grateful for your kindness

and compassion.

My appreciation and admiration go to Dr Laura Simonds. Your sense of humor,

desire to help others and seemingly endless patience were invaluable to me and

without you this research would not have been possible. Your integrity and the

passion you have for your work is inspiring. Thank you also to Dr Harriet

Tenenbaum for all your support and guidance throughout the research process.

Acknowledgements also go to my various placement supervisors who all showed

such dedication to the profession and helped bridge the gap between theory and

practice.

Most of all I would like to thank my patients, their families and carers for placing

their trust in me and allowing me into their private worlds. It is a privilege I am most

grateful for.

Finally, I would like to thank my husband, Tom, for believing in me when I didn’t

and supporting me unconditionally through the highs and lows of doctoral training.

3

Contents List

Part I: MRP Empirical Paper p5MRP Appendices p56

Part II: MRP Literature Review p103MRP Literature Review Appendices p171

Part III: Summary of Clinical Experience p186Part IV: Summary of Assessments p189

4

Part I: MRP Empirical Paper

The relationship between gender attitudes and children’s feelings of shame in

response to imagined failure.

5

Abstract

Objective: Shame is a secondary self-conscious distressing emotion that can be

evoked following experiences of failure. Research indicates potential gender

differences in shame responses following failure however findings have been mixed.

The current study examined whether gender-stereotypicality of a task was related to

anticipated shame following task failure, and whether gender attitudes in mothers

and children were related to anticipated shame.

Design: Mothers and their children completed measures assessing gender

stereotyped attitudes. Children were then asked to read six short stories about failing

a task (2 male-stereotyped, 2 female-stereotyped, 2 non-stereotyped). Following each

story, children were asked to rate how much shame they would experience in the

situation.

Participants: Participants were 28 mother-child dyads recruited from schools in

London.

Results/Findings: ANOVA and correlational analysis were used to explore

relationships between mother and child gender attitudes, and feelings of anticipated

shame in response to gender-stereotyped and non-gender stereotyped failure. Results

suggested a main effect of task, however associations between parent and child

gender attitudes were inconsistent.

Conclusions/Implications: Mostly, the study hypotheses were not supported.

Conceptual and methodological critiques are considered, such as validity of the

concept of gender stereotyped tasks, task salience and measurement issues. Further

research is needed to explore parent-child gender attitudes and the implications of

these for the development of self-conscious emotions such as shame.

6

Introduction

Shame is considered a secondary emotion, often evoked following

experiences of failure (Bidjerano, 2010). It is also classified as a ‘self-conscious’

emotion in that it arises in the context of actual or anticipated judgement from others.

Shame develops gradually over childhood and facilitates children’s skills in

negotiating social interactions and interpersonal relationships. However, if shame is

not well regulated its potential to be adaptive is compromised (Muris & Meesters,

2014), whereupon it is associated with feelings of powerlessness, worthlessness,

inferiority and a sense of the whole self as a failure, stupid or bad (Andrews, Qian &

Valentine, 2002). Shame is associated with a range of psychological difficulties

including low self-esteem, depression, anxiety, eating disorders, and self-harm

(Andrews et al., 2002; Assor, Roth & Deci, 2004; Gilbert et al., 2010; de Hooge,

Zeelenberg & Breugelmans, 2010; Kelly & Carter, 2013; Swan & Andrews, 2003;

Vizin, Urban & Unoka, 2016) as well as behavioural problems including withdrawal

and avoidance (Assor et al., 2004; Frijda, Kuipers & Ter Schure, 1989; Gilbert,

2000; Grabhorn, Stenner, Stangier & Kaufhold, 2006; Scherer & Wallbott, 1994;

Tangney, Wagner, Hill-Barlow, Marschall, & Gramzow, 1996; Wicker, Payne &

Morgan, 1983).

Self-conscious emotions emerge around the second year of life following

cognitive developments such as the capacity for self-awareness and the formation of

stable self-representations (Muris & Meesters, 2014). Moreover, children develop a

growing appreciation of social rules and standards of conduct and also theory of

mind ability that allows them to apprehend that others have expectations for their

behaviour (Muris & Meesters, 2014). These developments enable a child to evaluate

their own behaviour and consider this against his/her own standards or the standards

7

he/she anticipates others expect, to consider success and failure in relation to these

standards, and to generate attributions about the self, based on these outcomes

(Lewis, 1992) such as that failure was due to a stable personal characteristic (more

liable to evoke shame) as opposed to a situational reason (more liable to evoke guilt).

On the basis of a meta-analysis of gender differences in self-conscious

emotions, Else-Quest, Higgins, Allison and Morton (2012) concluded that the

stereotypical assumption of greater emotionality in females was not warranted. A

gender difference was observed in some domains (e.g. eating and body-related

shame) but not others. Research specifically on gender differences in general shame

responses following failure has provided mixed findings. Whilst some studies have

shown girls to exhibit higher levels of shame than boys in response to failure (Ruble,

Eisenberg & Higgins, 1994; Barrett, Zahn-Waxler, & Cole, 1993; Lewis, 1992,

Lewis, Sullivan, Stanger, & Weiss, 1989; Bafunno & Camodeca, 2013), this effect

has not been consistently replicated. One possible explanation is that children only

feel shame when they do not succeed at tasks typical of their gender because such

tasks are part of their self-conception (Martin, Ruble, & Szkrybalo, 2002). It is

possible therefore that gender differences in shame following failure are moderated

by the gender stereotypicality of the task and this explains why a gender difference is

not consistently found between studies.

Gender schema theory argues that children develop a gendered lens or a

gender schema through which they understand attributes such as behaviours,

interests and personality traits (Weisgram, 2016). The relationship between sex-

typed beliefs and behaviour in children is widely documented in gender research

(Arthur, Bigler, Liben, Gelman, & Ruble, 2008; Martin, 2000; Martin & Halverson,

1981; Martin, Ruble, & Szkrybalo, 2002; Tobin et al., 2010) and studies have

8

demonstrated strong support for congruence between these constructs, for example,

in Martin and Dinella’s (2012) study girls were ten times more likely to endorse

own-sex stereotyped activities than other-sex stereotyped activities. According to

such theories, children’s gender schematicity will influence the filter through which

they view the world (Wilansky-Traynor & Lobel, 2008). Germane to the current

research, the degree to which children see the world through gender may influence

the degree to which they experience shame in relation to the gender-stereotyped

nature of a task. In line with predictions, findings indicate that higher gender

schematicity is shown to be a predictor of gender stereotype endorsement and

decision-making using gender schemas (Weisgram, 2016).

These theories allocate considerable attention to the role of children’s

experiences with important others, such as parents, in shaping the development of

stereotyped attitudes and beliefs about gender (Aboud, 2005; Liben & Bigler, 2002;

Bigler & Liben, 2007; Martin & Dinella, 2012; Martin et al., 2002; Weisgram 2016).

Through everyday conversations, mothers implicitly teach children about the beliefs

of their parents. This may partially explain why parents’ own gender schemas are

associated with children’s gender schemas (Tenenbaum & Leaper, 2002).

Given that children tend to conform their behaviour with gender stereotypes

(Bigler & Liben, 2007), it would make sense for negative self-evaluations of gender-

appropriate behaviour (e.g., a boy failing at a competitive sport) to elicit experiences

of shame. Due to the societal salience of gender, children may place high value on

meeting personal standards, or perceived standards of others linked to gendered

behaviour, and experience negative global evaluations of the self if such standards

are not met. In addition, the literature cited above suggests that parents’ gendered

9

expectations about children’s performance may further amplify the self-evaluative

consequences of failure.

The current study aimed to explore these questions in a sample of children

aged 7-9 years. This is based on findings by Mills, Arbeau, Lall, and de Jaeger

(2010) who found that shame-related gender differences were observable in children

of this age, with girls showing more shame than boys in response to failure. Task

failure was operationalised using hypothetical failure situations in the form of

vignettes. This is in part motivated by the ethical considerations of using real failure

experiences with children, however, it is also a commonly used strategy in shame

related research. For example, the Test of Self-Conscious Affect (Tangney, Wagner

& Gramzow, 1989) and various subsequent iterations of this measure is the most

widely used measure of shame in children and comprises hypothetical scenarios of

shame. Further, evidence shows this methodology is a reliable predictor of shame

responding in children (de Hooge et al., 2010), with children reporting statistically

significantly higher levels of shame in hypothetical failure conditions than control

conditions using vignettes. Finally, the study focused on recruiting mothers as

opposed to parents as this is a more accessible population in child research.

Researching shame in the context of failure develops the existing body of

literature but also provides an accessible context in which to intervene, as situations

involving failure are common. Similar initiatives already exist, such as programmes

encouraging gender neutral treatment of children in classrooms, which aim to

counteract the negative effects of gender stereotyping (Jones, Howe & Rua, 2000).

The present study investigated anticipated shame following task failure in

children, exploring whether this was related to the gender-stereotyped nature of the

task or associated with parent and child beliefs about gender. The study focused on

10

contexts which elicit experiences of failure, as this is known to be a reliable predictor

of shame (Elliot & Thrash, 2004).

Based on existing literature, the following hypotheses were tested;

1. Anticipated shame will be higher in relation to failure of gender-stereotyped

vs non. gender-stereotyped tasks

2. Gender-stereotyped attitudes in children will correlate positively with

anticipated shame in relation to failure of gender stereotyped tasks

3. Gender-stereotyped attitudes in mothers will correlate positively with

anticipated shame responses in children in relation to failing gender-

stereotyped tasks

11

Method

Participants

The target sample for the study was children aged 7 to 9 years and their

mothers. Participants were recruited from schools and after-school clubs in London

through convenience sampling. It was not possible for more than one child from the

same family to participate. No incentives were used to gain participation. Children

and their mothers were informed that the research aim was to explore how parents

and children understand everyday successes and failures. Participants were not

informed of the objective to explore gender effects so as to avoid response bias.

Materials

The Children’s Occupation, Activity, and Trait Scales– Short Form (COAT-

SF) (Liben & Bigler, 2002). Children’s gender-stereotyped attitudes were assessed

using the COAT Short Form scales. These scales assess sex-typed attitudes towards

others (Attitude Measure: COAT-AM) (Appendix M), and sex-typing of the self

(Personal Measure: COAT-PM) (Appendix L). Each of these two measures consists

of three subscales assessing gender-stereotyped attitudes in relation to occupations,

activities, traits. Each subscale comprises 25 items (10 masculine-stereotyped, 10

feminine-stereotyped, 5 neutral). Items for the COAT scales were selected on the

basis of previous research on gender and sex-typing in children. To test validity of

items, Liben and Bigler (2002) conducted a study with college students who were

asked to rate each item as (1) for males only, (2) much more likely for males, (3)

somewhat more likely for males, (4) equally likely for males and females, (5)

somewhat more likely for females, (6) much more likely for females, (7) for females

only. Mean scores for individual items of 3.4 or below were categorized as

masculine, 4.6 or above were categorized as feminine, and items between this range

12

as neutral. Items were examined for equivalence in regard to their stereotypicality

and no significant differences were found in ratings of masculine or feminine items,

nor were there any significant differences in ratings according to rater gender.

To assess gender attitudes towards others, the COAT-AM asks children to

rate each item as applicable only to males (“only men” = 1), females (“only women”

= 2) or both (“both men and women” = 3). The COAT-AM measures sex

stereotyping of others using three scales that ask respondents to indicate whether

men and women “should” perform various jobs or activities, or have various

personality characteristics. The wording, “should” is used instead of “does”, as the

latter taps into knowledge of, rather than attitudes towards, gender stereotypes

(Liben & Bigler, 2002; see Signorella, Bigler, & Liben, 1993). Following Liben and

Bigler (2002), the proportion of stereotypic responses is obtained by totalling the

number of times children assign the feminine-stereotyped items to “only women”

and the number of masculine-stereotyped items assigned to “only men” and dividing

this by the total number of stereotypic items on the scale (i.e. 20) to give a maximum

score of 1 for each subscale. A score of 1 would indicate 100% stereotyped

responses. Liben and Bigler (2002) indicate there is no need to create separate

attitude scores for masculine-stereotyped and feminine-stereotyped items because

they are highly correlated. Given the inter-correlations between the three subscales,

Liben and Bigler (2002) indicate that a mean of the three subscale scores may be

calculated to give a total maximum score of 1. A higher score indicates stronger

gender stereotyped attitudes.

The COAT-PM (gender self-typing) has the same number of items as the

COAT-AM (10 masculine, 10 feminine, 5 neutral) and the same three subscales but

for this children are asked to rate the applicability of each item in relation to

13

themselves. Liben and Bigler (2002) note that it is important to create separate

masculine-stereotyped and feminine-stereotyped scores because they are not

correlated. Children rate their interest in certain jobs, the extent to which they

participate in certain activities, and the degree to which they believe a trait describes

them on a 4-point Likert scale that differs depending on emphasis of the subscale.

For example, trait scale items are rated from 1 (‘not at all like me’) to 4 (‘very much

like me’). Masculine and feminine gender self-typing scores are calculated by

computing the mean rating for masculine and feminine items separately. This gives a

maximum score of 4 for each of the three subscales. A mean is created across the

three subscales by totalling the subscales and dividing by 3. These means are created

separately for the masculine and feminine gender self-typing scores with higher

scores indicating stronger gender self-typing.

All scoring of the COAT followed the suggested procedure (Liben & Bigler,

2002). The COAT measures take approximately 25 minutes to complete and can be

administered to children aged 7 and above. Initial validation (Liben & Bigler, 2002)

indicated internal consistency of subscales (COAT-AM, a = .81 to .87; COAT-PM, a

= .67 to .83) with good test-retest reliability of (a = .73 to .79) and (a = .71 to .82) for

COAT-AM and PM respectively.

Vignettes

Imagined failure was operationalized using six vignettes that described

failure scenarios children would be likely to encounter. To explore the effect of

gender, failure scenarios were gender stereotyped. Based on existing literature on

gender bias in educational settings (Herbert & Stipek, 2005), female failure scenarios

focused on reading and creative art tasks (Appendix N, O), and male failure

scenarios on maths and sports tasks (Appendix P, Q). The remaining two scenarios

14

were non-gender stereotyped and involved failure on games that do not require

gender-specific stereotyped skills (“Guess Who” and “Pass the Parcel”) (Appendix

R, S). An additional seventh vignette was presented at the end which described a

positive story of achievement, success and social acceptance (Appendix T). This

vignette was included so that children did not leave the study in a state of imagined

failure.

Anticipated Shame Items (Appendix U)

Questions assessing anticipated shame were designed specifically for the

present study due to unsuitability of existing measures. Requirements included a

need for items to measure “state” rather than “trait” shame, to be directly linked to

gender stereotyped and non-gender stereotyped tasks included in the vignettes, and

to be age and context appropriate based on the child sample recruited. Four items

were devised to assessed anticipated feelings of shame in children following

presentation of each vignette. These were based on key dimensions of shame

identified in the literature (Tangney & Dearing, 2002; Simonds et al., 2015). The

items were (1) negative global self-evaluation (“I would feel stupid”), (3) desire to

escape, hide or disappear (“I would not want my parents to know”), (5) negative self-

evaluation by others (“Other people would think I’m stupid”), (8) value placed on

others’ appraisal of the self (“I would care if my friends knew”). A further four items

were formulated to mask the specific focus on shame. These items were (2) “I would

forget about it pretty quickly afterwards”, (4) “I wouldn’t care too much because it

isn’t important to me” (6) “I would worry that it might happen again in the future”

and (7) “I would feel angry”. Data from these latter four items were not part of the

hypothesis-testing. Children were given instructions to imagine they were the person

in the vignette, and answer items based on how they think they would feel in that

15

situation. Children were asked to indicate how much they agreed with each item on a

3-point scale where “No I don’t agree” = 0, “Maybe/ Not Sure” = 0 and “Yes, I

Agree” = 1. The total possible anticipated shame score for each scenario was 4 with

higher scores indicating greater anticipated shame. A mean shame item score was

calculated for male, female and non-stereotyped tasks (i.e. the mean of the 4 items

from each of the two relevant scenarios) for use in the analysis.

The Occupation, Attitude and Trait Scales - Short Version (OAT-SF) (Liben

& Bigler, 2002). Mothers’ attitudes towards gender were measured using the OAT

scales. These are parallel forms of the COAT scales designed for use with adults.

They have the same format as the COAT scales but different content due to items

being selected on the basis of gender-related work on sex-typing in adults rather than

children (Liben & Bigler, 2002). They also have different rating scales. These

measures quantify the strength of beliefs in gender roles and measure beliefs about

both gendered activities and personality constructs. Similarly to COAT scales, the

OAT measures distinguish between gender attitudes towards others (OAT-AM)

(Appendix I) and sex-typing of the self (OAT-PM) (Appendix H). Each scale

consists of 25-items consisting of separate occupation, activity and traits subscales.

Liben and Bigler (2002) developed the OAT measures in the same way as COAT

measures. However, items were chosen based on previous research pertaining to

gender and sex-typing in adults (Helmreich & Spence, 1978)

Regarding assessment of gender-stereotyped attitudes, all OAT-AM

subscales are rated on a 5-point likert scale where the respondent is asked to rate

occupations, activities and traits as appropriate for “only men” (1), “mostly men,

some women” (2), “both men and women” (3), “mostly women, some men” (4) or

“only women” (5). The short versions of the OAT measures were used, where each

16

subscale is made up of the 25 best-performing items from the longer scales (10

masculine-stereotyped, 10 feminine-stereotyped, 5 neutral). On the OAT-AM traits

subscale, which asks respondents, “Who Should Be This Way?”, a sixth response

option, “Neither Men Nor Women” (N) is provided. The proportion of stereotypic

responses is scored by totalling the total number of feminine-stereotyped items rated

as “only women”, plus the total number of masculine-stereotyped items rated as

“only men” and dividing this by the total number of stereotypic items on the scale

(i.e., 20 items on the short version of the COAT-AM) to give a maximum score of 1.

The score obtained for each subscale is then summed, to give a maximum score on

the OAT-AM, with a total maximum score of 3. As with the COAT-AM, the inter-

correlation between subscales allows for them to be combined and divided by three

to give a total maximum score of 1 with higher scores indicating stronger gender

stereotyped attitudes.

Regarding assessment of gender self-typing in respondents (OAT-PM), three

respective subscales ask respondents to rate their interest in certain jobs, the extent to

which they participate in certain activities, and the degree to which they believe a

trait describes them. Items on all OAT-PM scales are rated on a 4-point likert scale.

The wording of each scale differs depending on emphasis of the subscale, e.g.

Occupational (“How much would you want to be an…?”), Activity (“How often do

you …?”) and Trait (“Is this like you?” e.g. not at all like me (1), not much like me

(2), somewhat like me (3), and very much like me (4)). For the OAT-PM subscales,

masculine and feminine gender self-typing attitudes are calculated separately to give

a total masculine and total feminine score. This is achieved by summing the number

of points scored, separately, for masculine and feminine items, and dividing this by

the total number of items of each type (10), giving a maximum score of 4 for each

17

subscale. A mean of the overall masculine and feminine score of each subscale

(occupations, activities, and traits) is then created to give a maximum score of 4 with

higher scores indicating stronger gender self-typing. All scoring of the OAT

followed the suggested procedure (Liben & Bigler, 2002).

The OAT measures take approximately 20 minutes to complete. Liben and

Bigler (2002) reported initial measure validation indicated internal consistency of

subscales (OAT-AM, a = .75 to .91; OAT-PM, a = .65 to .81) and test-retest

reliability (OAT-AM, a = .72 to .75; OAT-PM, a = .72 to .88).

Ethical Considerations

Favourable ethical approval was obtained from the Faculty of Health and

Medical Sciences Ethics Committee at the University of Surrey (Appendix V).

Written consent from mothers and written assent from children was obtained before

children were permitted to participate in the study. The testing protocol with children

(Appendix J-U) took place either at the child’s school with a teacher present but not

visible, or in the child’s home with their mother present but not visible during

testing. The researcher was mindful of children’s reactions throughout the testing

procedure and attentive to any signs children could get upset. For the imagined

failure task, a vignette was presented at the end which described a positive story of

achievement, success and social acceptance to ensure children did not leave the

study in a state of imagined failure. No child became upset or presented as a concern.

Procedure

Administrators for state and public schools were contacted and provided with

information about the design and rationale of the study. Interested mothers notified

school administrators and completed consent forms and OAT measures using an

online program which took approximately 20 minutes (Qualtrics). Mothers

18

completed OAT-PM measures prior to OAT-AM measures “to avoid making

individuals’ gender-related beliefs highly salient prior to their self-ratings” (Liben &

Bigler, 2002, p. 134).The testing protocol lasted approximately 45 minutes and was

administered with children individually either at school or in their homes. Details of

the study were provided to children through written and verbal explanation, after

which written assent was obtained. As with mothers, children completed COAT-PM

then COAT-AM measures. Each questionnaire was read aloud by the researcher.

After completing the questionnaires, each vignette, followed by shame questions was

read aloud. Once the testing protocol was finished, children were debriefed and

given opportunity to ask any questions about the study. To protect anonymity,

response materials were coded by assigning a numerical ID to each participant.

Data-Analytic Strategy

Data analysis was a multi-step process. First, data for mothers and children

was anonymised, scored, and entered into a SPSS database (Version 25). Initial

screening of the dataset indicated no missing values. The reliability of the COAT,

OAT and anticipated shame measures was assessed using Cronbach’s alpha and

mean inter-item correlations. Next, sample demographic data were summarised and

descriptive statistics were derived for child gender attitudes, child anticipated shame,

and maternal gender attitudes. Preliminary analysis included testing all variables for

normality. The first hypothesis was tested using a mixed analysis of variance

(ANOVA) with a between participants independent variable of gender (2 levels) and

a within participants independent variable of imagined failure task (3 levels - female-

gendered, male-gendered, and non-gendered) with total anticipated shame as the

dependent variable. Post-hoc pairwise comparisons were conducted with Bonferroni

19

correction to avoid inflation of Type I error. The final step in the analytic strategy

was to explore hypotheses 2, 3 and 4 using correlation analysis.

A priori sample size calculation was based on detecting the ANOVA

interaction term (Hypothesis 1) with at least 80% power (alpha = .05) and a medium

effect size (f=.25). This indicated a total sample size of 28 children could detect an

effect of at least this size with 82% power.

Results

Participants

As schools contacted parents directly, the exact number of participants

approached is unknown. A total of 40 children were given parental consent to

participate. However, 12 of these children were excluded on the basis of being

related to another child participant. Therefore, the final sample consisted of 28

mother-child dyads. Sixteen children completed measures at home, and twelve

completed measures at school. Sample characteristics are summarised in Table 1.

There seem to be clear ethnic group differences between boys and girls.

Table 1. Demographic Characteristics of Overall SampleChildren Mothers

Boys (n = 14) Girls (n = 14) (n = 28)

Age (M, SD) 8.0 (.80) 8.0 (.73) 40.32 (5.23)Ethnicity n (%) Middle Eastern 5 (35.7) - - Asian 3 (21.4) 3 (21.7) 4 (28.5) White European 1 (7.1) 9 (64.3) 10 (71.5) Mixed Ethnicity 5 (35.6) 2 (14.2) -M = Mean, SD = Standard Deviation, Standard deviations are reported in parentheses.

Measures

Reliability information for study measures is presented in Table 2.

Cronbach’s alpha for measures of gender attitudes in children was acceptable for

COAT-AM and COAT-PM scales. For measures of gender attitudes in mothers,

20

Cronbach’s alpha for OAT-PM scales was good however values for the OAT-AM

were less acceptable. Exploration of item-total correlations indicated removal of

items would make minimal improvements to internal consistency, therefore all

original items were retained and findings are considered with caution on the basis

this measure did not meet accepted standards of reliability in the current sample.

With regards to the Anticipated Shame items, Briggs and Cheek (1986) recommend

that for scales of less than 10 items, it is appropriate to report the mean inter-item

correlation (with an optimal range of .2 to .4) instead of Cronbach’s alpha. The mean

inter-item correlation for the measure of anticipated shame in the present study

was .31.

Table 2. Cronbach’s alpha for COAT and OAT scalesGender Attitudes Towards Others (AM) (a)

Sex-typing of self (PM) (a)

Children (COAT)

.95 .88

Mothers (OAT) .67 .83

COAT Children’s Occupation, Activities, and Traits Measure; OAT Occupation, Activities, Traits Measure; AM Attitude Measure; PM Personal Measure, a Cronbach’s alpha

Descriptive Statistics

Tables 3 presents descriptive data for children. Results indicated boys and

girls scored similarly on measures of gender attitudes towards others (COAT-AM),

reporting low levels of gender stereotyped attitudes towards others.

21

Table 3. Means and Standard Deviations for Gender Attitudes in ChildrenGender Attitudes towards

Others (COAT-AM)Sex-typing of self (COAT-PM)

Masculine Feminine

Boys (n = 14) .27 (.18) 2.36 (.30) 1.97 (.32)

Girls (n = 14) .27 (.23) 2.32 (.25) 2.54 (.19)

COAT-AM Children’s Occupation, Trait and Activity Scale-Attitude Measure, COAT-PM Personal MeasureM = Mean, SD = Standard DeviationStandard deviations are reported in parentheses.

Mothers reported low levels of gender stereotyped attitudes towards others.

As expected, sex-typing of the self was higher for feminine traits than masculine

traits (Table 4).

Table 4. Means and Standard Deviations for Gender Attitudes in MothersGender Attitudes towards

Others (OAT-AM)Sex-typing of self (OAT-PM)

Masculine Feminine

Mothers (n = 28) .04 (.07) 2.23 (.32) 2.65 (.31)

OAT-AM - Occupation, Trait and Activity Scale-Attitude Measure (Adult Version), OAT-PM - Personal Measure, M - Mean, SD - Standard Deviation. Standard deviations are reported in parentheses.

Hypothesis 1 - Anticipated shame will be higher in relation to failure of gender-

stereotyped vs non gender-stereotyped tasks

Preliminary analyses were performed to explore boys’ and girls’ scores on

shame questions (Table 5). Shapiro-Wilk’s test of normality (Thode, 2002) showed

the assumption of normality was upheld for all group combinations of child gender

and task type, with the exception of girls’ scores on the feminine and non-gender

stereotyped failure scenarios (Appendix W). Girls’ scores on anticipated shame

questions following imagined failure of feminine stereotyped tasks showed a

skewness of .76 (SE = .60) and kurtosis of -.88 (SE = 1.15), however visual

inspection of the histogram showed no marked skew which was in line with

expectation. In the non-gender stereotyped condition, scores showed a skewness of

22

1.82 (SE = .60) and kurtosis 4.72 (SE = 1.15). Visual inspection of the histogram

showed positive skewness supporting the prediction that children would report less

shame in a non-gender stereotyped failure scenario. Table 5 shows the means for

anticipated shame in relation to each task by child gender.

Table 5. Children’s anticipated shame scores Shame Response (M, SD)

Masculine Tasks Feminine Tasks Neutral TasksBoys (n = 14) 1.32 (1.08) 1.00 (.71) .50 (.62)Girls (n = 14) .79 (1.13)* 1.0 (1.07) .36 (.70)*M = Mean, SD = Standard Deviation, Standard deviations are reported in parentheses.*Variables not normally distributed

A mixed 2 (girl, boy) x 3 (feminine-stereotyped, masculine stereotyped,

neutral) ANOVA was conducted to assess whether there was an interaction between

child gender and task type The interaction term was not statistically significant F(2,

25) = 1.68, p = .20, ηp2 = .06) (Fig.1)

23

Figure 1. Mean anticipated shame ratings by child gender and imagined failure task type.

There was a significant main effect of Task, F(2, 25) = 10.46, p < .001, ηp2 =

.29. Descriptive statistics and Bonferroni corrected post-hoc tests showed that

overall, children reported significantly higher levels of anticipated shame on

masculine (M = 1.05, SD = 1.12) and feminine stereotyped (M = 1.00, SD = .89)

compared to non-gender stereotyped tasks (M = .43, SD = .65). Paired samples t-

tests were used to assess if shame ratings differed between masculine and feminine

stereotyped tasks. No significant difference in boys’ anticipated shame scores

between tasks was found, t(13) = -1.19, p = .26. The magnitude of the differences in

the means (mean difference = - .32, 95% CI: -.91 to .26) was very small (eta squared

= .05). Similarly, the paired samples t-test showed no significant difference in girls’

scores between tasks t(13) = 1.25, p = .23. The magnitude of the differences in the

24

means (mean difference = .21, CI: -.16 to .58) was also very small (eta squared

= .01).

The main effect of child gender was not significant, F(1,26) = .58, p = .45,

ηp2 = .02, suggesting boys and girls reported similar levels of anticipated shame

across all tasks combined.

Hypothesis 2 - Gender-stereotyped attitudes in children will correlate positively with

anticipated shame in relation to failure of gender stereotyped tasks

Pearson’s product-moment correlations were run to assess the relationship

between child gender attitudes (COAT-AM and COAT-PM) and anticipated shame.

Preliminary analyses showed relationships to be linear and assumptions of normality

to be supported in all variables with the exception of COAT-AM (Appendix X).

Given that the Pearson correlation is somewhat robust to deviations from normality

(Havlicek & Peterson, 1976), the decision was made to proceed with a parametric

test. Non-parametric equivalents of tests were also performed to ensure results were

not significantly distorted by this decision. Results of these showed minimal

differences between the two statistical procedures (Appendix Z).

As indicated in Table 6 there was little evidence that gender attitudes were

correlated with anticipated shame in boys or girls.

Table 6. Pearson Product-moment Correlations between Measures of Gender Attitudes and Anticipated Shame in Children

Boys (n=14) Girls (n=14)

COAT-AM (r)

COAT-PM (r) COAT-AM (r)

COAT-PM (r)

Masculine

Feminine Masculine

Feminine

Anticipated Shame Feminine Task

.28 (.33) .15 (.61) .14 (.63) .04 (.90) -.05 (.86) -.05 (.86)

Anticipated Shame Masculine Task

.17 (.56) -.12 (.69) -.09 (.76) -.05 (.86) -.08 (.80) -.06 (.85)

25

COAT-AM Children’s Occupation, Trait and Activity Scale-Attitude Measure, COAT-PM Personal MeasureSig. (2-tailed) values are provided in parentheses

26

Hypothesis 3 - Gender-stereotyped attitudes in mothers will correlate positively with

anticipated shame responses in children in relation to failing gender-stereotyped

tasks

Preliminary analyses indicated mothers’ responses on OAT-AM scales

violated assumptions of normality, with a skewness of 1.91 (SE = .44) and kurtosis

2.83 (SE = .86). A histogram showed that mothers reported low gender stereotyped

attitudes towards others. Mothers’ data were normally distributed for OAT-PM

Feminine and Masculine scores (Appendix Y). As with Hypothesis 2, the decision

was made to proceed with a Pearson correlation due to the relative robustness of this

test to deviations from normality (Havlicek & Peterson, 1976).

There was evidence that mothers’ gender attitudes towards others was

positively correlated with girls’ anticipated shame in response to female-stereotyped

and non-gender stereotyped imagined failure scenarios. There was little evidence

that mothers’ self sex-typing was related to anticipated shame in girls.

There was limited evidence of relationships between mothers’ gender

attitudes and boys’ anticipated shame related to task failure.

27

Table 7. Pearson Product-moment Correlations between Mother gender attitudes and Children’s anticipated shame.

Anticipated Shame

Boys (n=14) Girls (n=14)

Feminine

Masculine Neutral Feminine Masculine Neutral

Mother Gender Attitudes (n=28)

OAT-AM -.08 (.78)

-.19 (.52) .18 (.53) .52 (.06) .42 (.13) .54 (.05)*

OAT-PM Masculine

.15 (.60) .21 (47) -.06 (.85) .05 (.85) .08 (.79) -.34 (.23)

OAT-PM Feminine

.46 (.10) -.05 (.87) .21 (.47) -.25 (.38) -.33 (.25) -.11 (.71)

OAT-AM Occupation, Activity and Trait Scale – Attitude Measure (Adult Version); OAT-PM Occupation, Activity and Trait Scale – Personal Measure Masculine Total; OAT-PM Occupation, Activity and Trait Scale – Personal Measure Feminine Total ScoreSig. (2-tailed) values are provided in parentheses

28

Discussion

There was little evidence to support the first study hypothesis that anticipated

shame would be higher in relation to failure of gender-stereotyped vs non gender-

stereotyped tasks in a sample of children aged 7 to 9 years using hypothetical failure

scenarios. As predicted, boys reported higher levels of anticipated shame following

imagined failure of a masculine stereotyped task, and girls reported higher levels of

anticipated shame following imagined failure of a feminine stereotyped task however

the interaction between gender and task was not statistically significant. The main

effect of task was statistically significant. Follow-up analysis indicated that

significantly higher levels of anticipated shame were reported following imagined

failure of gender stereotyped compared to non-gender stereotyped tasks in this

sample. However, there was no difference in anticipated shame following failure of

masculine vs. feminine stereotyped tasks.

The finding that children reported higher levels of anticipated shame

following failure of gender stereotyped vs non-gender stereotyped tasks is consistent

with evidence demonstrating the psychological salience of gender-relevant material

(Athur et al., 2008; Hilliard & Liben, 2010). In the present study, children may have

anticipated less shame following failure of neutral tasks such as the games in the

non-gender stereotyped condition as these might be considered more trivial in nature

compared to the gendered tasks associated with sex-typing or sex-roles. These might

conceivably be construed as more salient and relevant to one’s sense of self as they

require a higher level of intellectual ability and skill.

The finding that girls and boys reported similar levels of anticipated shame

on gender stereotyped tasks contradicts predictions based on gender schema theory

29

and raises questions about whether tasks in this study could be reliably categorised

as masculine- and feminine-stereotyped. For many decades, researchers have

documented gender differences in children’s perceived competence for tasks

traditionally viewed as either masculine or feminine-stereotyped. Studies have

documented girls reporting higher ability self-perceptions in educational settings for

languages and arts subjects, with lower ability self-perceptions for subjects such as

maths when compared to boys, particularly when negative gender stereotypes are

activated (Fredricks & Eccles, 2002; Jacobs, Lanza, Osgood, Eccles & Wigfield,

2002; Tomasetto, Alparone, & Cadinu, 2011). However, women are increasingly

represented in traditionally male-dominated areas such as maths (Hyde, Lindberg,

Linn, Ellis & Williams, 2008; Halpern, 2007) with many developments being made

to encourage female participation in activities such as sport, especially in schools

(Wellard, 2007). If societal developments in the form of improved gender

representation in traditionally sex-typed domains have influenced children’s

perceptions of occupations and activities, children’s conceptualisations of gender-

typed activities may have changed. It is possible, given children’s low scores on

measures of gender stereotyped attitudes towards occupations, activities and

personality traits in this study, that the tasks included in the gender stereotyped

scenarios were not strongly perceived by children as masculine or feminine. One

way to explore this paradigm would be to repeat Liben & Bigler’s (2002) study

which explored the content validity of items to be included in the COAT measures

by asking students to rate activities and occupations as being more likely to be

performed by males, females or both.

It is important to note the potential implications of cultural differences in the

present sample of children, given the ethnic composition of boys was more diverse

30

than that of girls. Research indicates a mediating role of ethnicity and culture on

various types of gender attitudes such as gender roles (Brown, 2017; Cuddy et al.,

2015; Durik et al., 2006; Ghavami & Mistry, 2019; Gushue & Whitson, 2006; Kane,

2000). The possibility should therefore be considered that results could have been

influenced by variations in cultural factors that were not measured in the current

investigation. The majority of boys in the present sample identified as Middle

Eastern or Mixed Ethnicity, whereas girls were predominantly White European. Due

to the cultured nature of gendered stereotypes (Weisgram, 2016), it is possible that

endorsement of sex-typed attitudes varied according to ethnicity, rather than gender

alone, which may have influenced children’s perceptions of tasks and subsequent

anticipation of shame.

Child gender attitudes and anticipated shame

The hypothesis that gender-stereotyped attitudes in children would correlate

positively with anticipated shame in relation to failure of gender stereotyped tasks

was not supported by the data. Several reasons for these findings can be considered.

Similarly to the first hypothesis, a lack of support for a relationship between child

gender attitudes and anticipated shame may also be explained by whether or not

gender stereotyped tasks in the present investigation could be reliably categorised as

masculine and feminine-stereotyped. An alternative explanation comes from gender

schema theory. Weisgram (2016) initially found that gender differences did not

account for variations in congruence between gender-typed attitudes and children’s

interest in novel items. However, when results were stratified according to gender

schematicity, children with more gender-stereotyped views were more likely to

indicate novel items as only for boys or only for girls. Due to small sample size in

this study, relationships between gender-stereotyped attitudes and anticipated shame

31

responses in the present study were analysed according to child gender, however,

evidence supporting constructionist theories would suggest that examining individual

differences in gender schematicity may be important in determining which children

are most affected by gender-typing and therefore, could be more likely to experience

shame in the context failure or gender-stereotyped tasks.

A second consideration is that gender attitude measures such as the COAT

may no longer accurately capture key markers of stereotypical attitudes relating to

gender in today’s society. Two of the three subscales focus on activities and

occupations, areas which have seen significant social change regarding gender

representation in recent decades (Fawcett Society, 2018). Advancements in policy

and legislation listing sex as a protected characteristic such as The Equality Act

(Legilsation.gov.uk, 2010) have considerably impacted UK industry in ways which

are increasingly reflected in public and private sectors (Equality and Human Rights

Commission, 2011). These societal shifts in attitudes, beliefs and behaviour in

relation to gender will have undoubtedly influenced the environmental context in

which children aged 7-9 have been exposed, particularly given the educational and

occupational characteristics of mothers in the present study. Where an indicator of

stereotypical gender attitudes in previous decades might have been a lack of female

representation in industry, a more reliable indicator now might be parity of pay or

number of women in positions of power. As a result, measures such as the COAT

may no longer be relevant or valid for many children is today’s society as they lack

the sensitivity to capture different ways gendered stereotypical beliefs might

manifest in current social climates through, for example, perceptions of competence

as opposed to opportunity.

32

Attitude theories may also help to interpret such findings. The Meta-

Cognitive Model (MCM; Petty & Brinol, 2006; Petty, Brinol & DeMarree, 2007) is

a framework of attitude structure which discusses the role of a “denied evaluation”.

When encountering an attitude object, an individual may hold a past attitude or

association that was never endorsed but may be salient e.g. due to the person’s

culture. Stereotypical gender beliefs in children may be an example of an automatic

association based on internalised familial, cultural or societal values that are

consciously recognized as unfounded through experiences such as being in

coeducational environments where boys and girls are increasingly encouraged to

partake in activities previously associated with one gender, such as football.

According to the MCM, “implicit ambivalence” (Brinol & Petty, 2009) can result in

situations where one evaluation is accepted but another is denied (e.g. “girls can’t

play football”). In such instances the person may not report any conscious

ambivalence, but both current and previous evaluations emerge spontaneously in the

presence of the attitude object, to the extent that the rejected evaluation might still

influence affective or behavioural responses (Baumeister & Finkel, 2010). In this

context, a discrepancy between explicit responses on attitudinal measures and

reported feelings of shame could be interpreted as an example of implicit

ambivalence, where children anticipate shame when imagining failure of a gender

stereotyped task even if they do not consciously endorse the stereotype. Support for

this idea is discussed elsewhere in attitude literature, in research showing attitudes

can be conditioned through exposure without conscious awareness (Cacioppo et al.,

1992; Murphy, Monahan, & Zajonc, 1995).

Mothers’ gender attitudes and anticipated shame in children

33

The hypothesis that gender-stereotyped attitudes in mothers would correlate

positively with anticipated shame responses in children in relation to failing gender-

stereotyped tasks received mixed support. Overall, there was little evidence of a

relationship in mother-son dyads. Moreover, as regards mother-daughter dyads, a

relationship was only evident for mothers’ gendered attitudes towards others and not

their self sex-typing.

Mothers’ gender attitudes towards others were positively associated with

girls’ shame in both gendered and non-gendered tasks. This was unexpected given

predictions of a difference between gender-stereotyped and non-gender stereotyped

tasks. One question here is whether these results could reflect the additional

influence of factors such as attitudes towards failure and achievement. Gender

differences in domains such as academic expectations are frequently documented in

achievement literature, and research indicates that boys and girls may be

differentially affected by parental attitudes and expectations. Further, studies have

shown that parental effects of academic expectations may be greater for mothers and

daughters than fathers and sons (Flouri & Hawkes, 2008). Although research on this

topic is mixed, it raises the question whether the positive correlation between

mothers’ gender attitudes and girls’ anticipated shame following imagined failure in

the present study could be affected by the influence of parental attitudes towards

success and failure on the mother-daughter relationship.

Feminine self sex-typing in mothers was negatively correlated with

anticipated shame in girls following imagined failure of both gender and non-gender

stereotyped tasks. Conversely, masculine self sex-typing in mothers showed a

positive, albeit weak correlation with anticipated shame in girls in gender

stereotyped conditions. Drawing on Wigfield and Eccles’ (2002) expectancy-value

34

model, self sex-typing in mothers might communicate implicit values about the

importance of feminine versus masculine tasks. Given that mothers in the present

sample exhibited similar levels of masculine and feminine self sex-typing, girls

might perceive mothers to place high value on stereotypically masculine as well as

feminine traits but perceive themselves to be less competent at masculine-

stereotyped tasks. This could lead to higher anticipated shame in masculine

compared to feminine tasks due to perceived negative maternal evaluation because

these tasks are associated with lower self-efficacy.

For boys, mothers’ gender attitudes towards others showed no statistically

significant relationships with reports of anticipated shame. There was strong

evidence that mothers’ feminine self sex-typing was positively correlated with boys’

reports of anticipated shame following failure of female-stereotyped tasks. This

might also be considered consistent with the previous interpretation that mothers’

self sex-typing might communicate implicit attitudes about the value and worth of

stereotypically gendered traits and activities, where boys experience shame at not

succeeding on tasks they perceive their mothers to consider important.

Finally, it is possible that mixed findings relating to the second hypothesis

were affected by low reliability of the OAT-AM measure in the present study

affecting correlations between mother gender attitudes and child anticipated shame.

As the measure was originally validated based on a sample of 167 undergraduate

students (Liben & Bigler, 2002), its applicability to more diverse populations could

be questioned. The same could be said for the COAT measure, which was developed

based on a sample of 154 children aged 11-12 which was 98% white and

predominantly middle-class in social background. On average mothers’ scores on the

OAT-AM were low. It is possible that mothers in this study either represented a

35

sample holding low levels of gender stereotyped beliefs, or as suggested earlier, the

measure lacked sensitivity to accurately capture attitudes of this kind. If the former

were true, this could help account for the mixed findings in the present study, as

children’s anticipated shame may have been influenced by maternal gendered beliefs

not captured by the measures used. A third hypothesis is that the mechanisms by

which children develop gender attitudes are more complex than simple modelling

processes, and that other mediating variables not studied in this investigation, such as

peer relationships (Harris, 1998) or parent gender (Bornstein, 2013), influence

children’s gender beliefs as has been suggested elsewhere in the literature.

Clinical Implications

Investigating the correlates of shame in children has important clinical

implications given the long-term consequences of chronic shame and the need to

understand ways to ameliorate the experience of problematic shame. Shame is

considered a powerful, psychologically damaging emotion that can be overwhelming

and affect an individual’s global sense of self (deMarrais & Tisdale, 2002; Andrews

et al., 2002). Emerging in childhood (Lewis, 2003) it is associated with an array of

mental health conditions in both children and adults. Therefore, research which

contributes to knowledge of shame risk factors is central not only to understanding

the underlying cognitive and emotional processes of this emotion but related

psychopathology. Women are consistently reported to experience higher rates of

mood disorders including depression, GAD and low-self-esteem (Astbury, 2001).

Research into the development and mechanisms of maladaptive shame, and the

relationship between shame and gender, will add to the knowledge base and could

aid the consideration of interventions to manage psychological disorders where

shame is implicated.

36

The present study adds to the existing literature base suggesting a

relationship between experiences of failure (real or perceived) and anticipated

feelings of shame in children. Consideration of failure experiences as a trigger for

feelings of shame has important implications in both clinical and non-clinical

populations. For example, interventions for psychological disorders in which shame

may have an exacerbating or mediating role, such as depression and anxiety, might

include cognitive strategies aimed specifically at challenging unhelpful thoughts

associated with failure, or focusing on the development of coping strategies to

manage experiences of failure. In non-clinical environments such as schools where

experiences of failure such as those included in this study’s vignettes are

commonplace, further research could support a better understanding of factors

mediating the relationship between failure experiences and shame. This could

support the development of programmes aimed at identifying and helping children

who may be particularly at risk of emotional distress, such as teacher training

programmes or peer support initiatives.

Results of this investigation link to findings from other developmental

research which reports that gendered expectations about performance can amplify

the self-evaluative consequences of failure in children aged 7-9 (Mills, Arbeau, Lall

& de Jaeger, 2010). Whilst the hypotheses of the present investigation have a

theoretical basis, empirical support was inconsistent and therefore future research is

needed to clarify links between individual differences such as gender and shame

responses in children.

Strengths and Limitations of the present investigation

Shame is implicated in a range of psychological difficulties and represents an

area critical to emotional development. Findings discussed here raise interesting

37

questions about the role of task in psychological research. Evidence was found to

support the suggestion that the gendered nature of tasks may influence children’s

experience of shame following failure, however questions remain about how tasks

can be stereotyped as masculine and feminine. Although there has been a vast

amount of research into the impact of gender on psychological constructs such as

shame, the role of gender in tasks is not routinely identified as a variable of

importance in the same way as other factors might be, for example, task difficulty

(Lewis, Alessandri & Sullivan, 1992).

As previously noted shame is an area of psychological research in which

further study is needed however ethical considerations rightly limit the nature in

which such emotions are manipulated. The present study provides further support for

the use of imagined failure scenarios which offer a safe, inexpensive and time-

efficient research methodology allowing for continued research with people across

the lifespan in both clinical and nonclinical populations that can be adapted to

different cultures and languages. As well as furthering scientific knowledge,

researching shame within this context provides an accessible setting in which to

intervene, as situations involving failure are commonly experienced.

Results of the study indicated several strong positive correlations which

warrant further investigation, most notably between mothers’ gender attitudes

towards others and girls’ anticipated shame following imagined failure, particularly

of neutral and feminine tasks. Similarly, there was evidence of a relationship

between mothers’ masculine self sex-typing and sons’ anticipated shame following

failure of feminine tasks. However, reasons why positive correlations were not found

in several instances should be considered. Firstly, whether or not gender stereotyped

38

tasks could be reliably categorised as masculine and feminine may have had a

significant impact on children’s anticipated shame responses.

Secondly, issues pertaining to construct validity and reliability of measures in

the present sample. The vignettes and anticipated shame items used in the present

study were designed specifically for the current investigation, therefore conclusions

based on such measures are tentative given that reliability and validity of such tools

was not explored. Further, tools such as the OAT and COAT scales which measure

explicit attitudes towards gender are subject to criticism for their vulnerability to

conscious processes such as social desirability bias which distort participants’

responses. Given substantial mass media coverage opposing gender discrimination in

recent years, mothers’ may have underreported stereotyped attitudes towards gender

due to concerns about self-presentation. As such, validated assessments of gender

attitudes are needed given their sensitivity to social and cultural changes over time.

Future research could also consider the use of alternative implicit measures of gender

attitudes such as the Implicit Association Test (IAT; Greenwald, McGhee &

Schwartz, 1998) which has been used to successfully identify biases in gendered

attitudes (Nosek, Bananji & Greenwald, 2002) which may be more robust to

contextual influences.

Another consideration is Bussey & Bandura’s (1999) critique of

psychological theories for conceptualising gender development as a phenomenon of

childhood. According to the authors, gender roles exist within a sociocultural context

and vary across the lifespan, shifting according to social and civic changes

(technological, political, economic, familial and academic). Support for this idea is

found in research identifying child age as a significant moderator in parent-child

gender beliefs (Tenenbaum & Leaper, 2002). Therefore, using such measures at a

39

single point in child development might be insufficient to encapsulate the complexity

of parent-child gender attitudes.

Related to this critique is a worthwhile consideration of a key conceptual

issue; are gender differences between men and women important, or even real?

Many sociologists and psychologists have rejected a dichotomous categorisation of

gender, proposing that any differences in cognition and behaviour are far exceeded

by similarities (Hyde, 2005, Hyde et al., 2008; Spelke, 2005). Bussey and Bandura

(1999) argued decades earlier that homogenous typing of gender is an approach

which is fundamentally flawed as it ignores the vast individual differences within

each category influenced by demographic characteristic including socioeconomic

status, disability, education, culture, occupation and ethnicity. Support for such ideas

has grown in recent years and a growing body of research is now focusing on non-

binary conceptualisations of gender (Davidson, 2007; Kuper, Nussbaum &

Mustanski, 2012; Nestle, Howell & Wilchins, 2002; Valentine, 2007)

Several factors relating to sample characteristics warrant further discussion.

Parent gender was not explored in the present study however research shows it may

be an important mediator in parent-child gender attitudes (Tenenbaum & Leaper,

2002). Fathers may have added an important dimension, as is observed in

psychological research of other constructs such as perfectionism where there is

suggestion that parent-child gender pairs contribute differently to developing

perfectionistic traits. Other demographic characteristics of the sample including age,

education and occupation should also be considered. For example; mothers in the

present study, predominantly well-educated and employed, could be more likely to

possess liberal, non-traditional gender attitudes that are less representative of the

wider population. Most notably, this study did not recruit from clinical populations

40

whose responses to shame inducing stimuli might be quantitatively different to that

in community samples. It is possible that correspondence between parent-child

gender beliefs may also be different in these samples. As such, findings of the study

are limited in their generalizability to clinical groups who might arguably be more

likely to benefit from such research.

Small sample sizes present several challenges to analysis, interpretation and

generalisation of findings (Hackshaw, 2008). Examples of this in the present study

include instances where suggestions of effect missed statistical significance, in

addition to insufficient power as indicated in post-hoc power analysis. In the current

study, a priori power analysis was calculated based on a medium effect size (f=.25),

however in order to avoid Type II error, a post-hoc power analysis was conducted.

This indicated ability to detect a small to moderate effect (f=.18), suggesting a larger

sample may have been required to detect smaller effect sizes. Analysis was affected

in that it was not possible to explore the statistical significance of differences

between correlation coefficients for boys and girls on measures of gender attitudes

and anticipated shame in more detail, but this would be interesting to explore in

future studies.

Finally, two notable weaknesses of the study included use of correlational

design and cross-sectional convenience sampling methods. At present, it remains

unclear which factors contribute to the development of children’s gender attitudes

however, evidence from investigations such as which highlight a relationship

between parent gender beliefs and children’s emotional responses suggest it would

be reasonable to conclude that parental attitudes, both implicit and explicit, are

implicated in some way. To elucidate the underlying mechanisms of this

relationship, future research utilising both experimental and longitudinal research

41

designs are needed so as to map progression over time as well as substantiate causal

inference.

Suggestions for Future Research

Several areas are identified for future research. In addition to alternative

research designs, studies are needed which utilize a variety of methodologies, for

example, measures of implicit attitudes, or observational techniques. Future studies

should also attempt to address sampling issues that weaken the existing evidence

base. Diverse sampling methods, larger sample sizes and recruitment from clinical as

well as community populations would advance the knowledge base and support

clarification of the relationship between parent-child gender attitudes and self-

conscious emotions such as shame.

Conclusion

The present study provides several important findings suggesting evidence of

a relationship between anticipated shame and failure of gender stereotyped vs non-

gender stereotyped tasks. A relationship between parent gender beliefs and

anticipated shame in children was also supported in some analyses. An association

suggested in gender development literature between parent-child gender beliefs was

difficult to interpret in this study as results were inconsistent. This may be linked to

methodological limitations such as measurement bias, solutions for which are

discussed.

42

References

Aboud, F.E. (2005). The development of prejudice in childhood and adolescence. In

J.F. Dovidio, P. Glick, & L.A. Rudman (Eds.), On the nature of prejudice:

Fifty years after Allport (pp.310–326). New York: Blackwell.

https://doi.org/10.1002/9780470773963.ch19

Andrews, B., Qian, M., & Valentine, J. D. (2002). Predicting depressive symptoms

with a new measure of shame: The Experience of Shame Scale. British Journal

of Clinical Psychology, 41(1), 29-42.

https://doi.org/10.1348/014466502163778

Andrews, B., Qian, M., & Valentine, J. D. (2002). Predicting depressive symptoms

with a new measure of shame: The Experience of Shame Scale. British Journal

of Clinical Psychology, 41(1), 29-42.

https://doi.org/10.1348/014466502163778

Arthur, A. E., Bigler, R. S., Liben, L. S., Gelman, S. A., & Ruble, D. N. (2008).

Gender stereotyping and prejudice in young children. In Levy, S. R., & Killen,

M (Eds.), Intergroup attitudes and relations in childhood through adulthood

(pp. 66-86). New York: Oxford University Press.

Assor, A., Roth, G., & Deci, E. L. (2004). The Emotional Costs of Parents'

Conditional Regard: A Self-Determination Theory Analysis. Journal of

Personality, 72(1), 47-88.

https://doi.org/10.1111/j.0022-3506.2004.00256.x

Astbury, J. (2001). Gender disparities in mental health. In: Mental health. Ministerial

Round Tables 2001, 54th World Health Assembly. Geneva, World Health

Organisation.

43

Bafunno, D., & Camodeca, M. (2013). Shame and guilt development in preschoolers:

The role of context, audience and individual characteristics. European Journal

of Developmental Psychology, 10(2), 128-143.

https://doi.org/10.1080/17405629.2013.765796

Barrett, K. Zahn-Waxler, C., & Cole, P. M. (1993). Avoiders vs. Amenders:

Implications for the investigation of guilt and shame during Toddlerhood?

Cognition and Emotion, 7(6), 481-505.

https://doi.org/10.1080/02699939308409201

Baumeister, R. F., & Finkel, E. J. (Eds.). (2010). Advanced social psychology: The

state of the science. New York, NY, US: Oxford University Press.

Bidjerano, T. (2010). Self-conscious emotions in response to perceived failure: A

structural equation model. The Journal of Experimental Education, 78(3), 318-

342. https://doi.org/10.1080/00220970903548079

Bigler, R. S., & Liben, L. S. (2007). Developmental intergroup theory: Explaining and

reducing children's social stereotyping and prejudice. Current Directions in

Psychological Science, 16(3), 162-166. https://doi.org/10.1111/j.1467-

8721.2007.00496.x

Bornstein, M. H. (2013). Parenting× gender× culture× time. In Wilcox, B. W., &

Kline, K. K. (Eds.), Gender and parenthood (pp. 91-119). New York:

Columbia University Press.

Briggs, S. R., & Cheek, J. M. (1986). The role of factor analysis in the development

and evaluation of personality scales. Journal of Personality, 54(1), 106-148.

https://doi.org/10.1111/j.1467-6494.1986.tb00391.x

44

Brinol, P., & Petty, R. E. (2009). Persuasion: Insights from the self-validation

hypothesis. In Zanna, M. P., (Eds.), Advances in experimental social

psychology, 41, 69-118. DOI: DOI: 10.1016/S0065-2601(08)00402-4

Brown, C. S. (2017). Discrimination in childhood and adolescence: Patterns across

social groups. London, UK: Psychology Press/Taylor & Francis.

https://doi.org/10.4324/9781315208381

Bussey, K., & Bandura, A. (1999). Social Cognitive Theory of Gender Development

and Differentiation. Psychological Review, 106(4), 676-713.

https://doi.org/10.1037/0033-295X.106.4.676

Cacioppo, J. T., Marshall-Goodell, B. S., Tassinary, L. G., & Petty, R. E. (1992).

Rudimentary determinants of attitudes: Classical conditioning is more effective

when prior knowledge about the attitude stimulus is low than high. Journal of

experimental social psychology, 28(3), 207-233. https://doi.org/10.1016/0022-

1031(92)90053-M

Cuddy, A. J., Wolf, E. B., Glick, P., Crotty, S., Chong, J., & Norton, M. I. (2015).

Men as cultural ideals: Cultural values moderate gender stereotype content.

Journal of Personality and Social Psychology, 109(4), 622.

https://doi.org/10.1037/pspi0000027

Davidson, M. (2007). Seeking refuge under the umbrella: Inclusion, exclusion, and

organizing within the category transgender. Sexuality Research & Social

Policy, 4(4), 60. https://doi.org/10.1525/srsp.2007.4.4.60

Durik, A. M., Hyde, J. S., Marks, A. C., Roy, A. L., Anaya, D., & Schultz, G. (2006).

Ethnicity and gender stereotypes of emotion. Sex Roles, 54(7-8), 429-445.

https://doi.org/10.1007/s11199-006-9020-4

45

Elliot, T., & Thrash, T. M. (2004). The Intergenerational Transmission of Fear of

Failure. Personality and Social Psychology Bulletin, 30(8), 957-971.

https://doi.org/10.1177/0146167203262024

Else-Quest, N. M., Higgins, A., Allison, C., & Morton, L. C. (2012). Gender

differences in self-conscious emotional experience: A meta-analysis.

Psychological bulletin, 138(5), 947. https://doi.org/10.1037/a0027930

Equality and Human Rights Commission. (2011). The essential guide to the public

sector equality duty. Manchester: Equality and Human Rights Commission.

Retrieved from:

https://www.equalityhumanrights.com/sites/default/files/psed_essential_guide_

-_guidance_for_english_public_bodies.pdf

Erdfelder, E., Faul, F., & Buchner, A. (1996). GPOWER: A general power analysis

program. Behavior research methods, instruments, & computers, 28(1), 1-11.

https://doi.org/10.3758/BF03203630

Fawcett Society. (2018). Sex and Power 2018. Retrieved from:

https://www.fawcettsociety.org.uk/Handlers/Download.ashx?

IDMF=ea2cb329-e6e0-4e0f-8a0b-5022f99bc915

Flouri, E., & Hawkes, D. (2008). Ambitious mothers–successful daughters: Mothers'

early expectations for children's education and children's earnings and sense of

control in adult life. British Journal of Educational Psychology, 78(3), 411-

433. https://doi.org/10.1348/000709907X251280

Frijda, N. H., Kuipers, P. & Ter Schure, E. (1989). Relations among emotion,

appraisal, and emotional action readiness. Journal of Personality and Social

Psychology, 57(2), 212-228. https://doi.org/10.1037/0022-3514.57.2.212

46

Fredricks, J. A., & Eccles, J. S. (2002). Children's competence and value beliefs from

childhood through adolescence: Growth trajectories in two male-sex-typed

domains. Developmental psychology, 38(4), 519. https://doi.org/10.1037/0012-

1649.38.4.519

Gelman, S. A., Taylor, M. G., & Nguyen, S. P. (2004). Mother-child conversations

about gender: Understanding the acquisition of essentialist beliefs:

Abstract. Monographs of the Society for Research in Child Development,

69(1), vii, 116-127.

http://dx.doi.org/10.1111/j.1540-5834.2004.06901001.x

Ghavami, N., & Mistry, R. S. (2019). Urban ethnically diverse adolescents’

perceptions of social class at the intersection of race, gender, and sexual

orientation. Developmental psychology, 55(3), 457.

https://doi.org/10.1037/dev0000572

Gilbert, P. (2000). The relationship of shame, social anxiety and depression: The role

of the evaluation of social rank. Clinical Psychology & Psychotherapy: An

International Journal of Theory & Practice, 7(3), 174-189.

https://doi.org/10.1002/1099-0879(200007)7:3<174::AID-CPP236>3.0.CO;2-

U

Gilbert, P., McEwan, K., Irons, C., Bhundia, R., Christie, R., Broomhead, C., &

Rockliff, H. (2010). Self-harm in a mixed clinical population: The roles of

self-criticism, shame, and social rank. British Journal of Clinical Psychology,

49(4), 563-576. https://doi.org/10.1348/014466509X479771

Grabhorn R., Stenner, H., Stangier, U., & Kaufhold, J. (2006). Social Anxiety in

Anorexia and Bulimia Nervosa: The Mediating Role of Shame. Clinical

Psychology and Psychotherapy, 13(1), 12-19. https://doi.org/10.1002/cpp.463

47

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual

differences in implicit cognition: the implicit association test. Journal of

personality and social psychology, 74(6), 1464. https://doi.org/10.1037/0022-

3514.74.6.1464

Gushue, G. V., & Whitson, M. L. (2006). The relationship of ethnic identity and

gender role attitudes to the development of career choice goals among black

and Latina girls. Journal of counseling psychology, 53(3), 379.

https://doi.org/10.1037/0022-0167.53.3.379

Hackshaw, A. (2008). Small studies: strengths and limitations. European respiratory

journal, 32(5), 1141-1143. https://doi.org/10.1183/09031936.00136408

Halpern, D. F., Benbow, C. P., Geary, D. C., Gur, R. C., Hyde, J. S., & Gernsbacher,

M. A. (2007). The science of sex differences in science and mathematics.

Psychological science in the public interest, 8(1), 1-51.

https://doi.org/10.1111/j.1529-1006.2007.00032.x

Harris, J. R. (1998). The nurture assumption: Why children turn out the way they do.

New York: Free Press.

Havlicek, L. L., & Peterson, N. L. (1976). Robustness of the Pearson Correlation

against violations of assumptions. Perceptual and Motor Skills, 43(3), 1319-

1334. https://doi.org/10.2466/pms.1976.43.3f.1319

Helmreich, R. L., & Spence, J. T. (1978). The Work and Family Orientation

Questionnaire: An objective instrument to assess components of achievement

motivation and attitudes toward family and career. JSAS Catalog of Selected

Documents in Psychology, 8, 35.

48

Hilliard, L. J., & Liben, L. S. (2010). Differing levels of gender salience in preschool

classrooms: Effects on children’s gender attitudes and intergroup bias. Child

development, 81(6), 1787-1798. https://doi.org/10.1111/j.1467-

8624.2010.01510.x

de Hooge, I. E., Zeelenberg, M., & Breugelmans, S. (2010). Restore and protect

motivations following shame. Cognition & Emotion, 24(1), 111-127.

https://doi.org/10.1080/02699930802584466

Hyde, J. S. (2005). The gender similarities hypothesis. American psychologist, 60(6),

581-592. https://doi.org/10.1037/0003-066X.60.6.581

Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008).

Gender similarities characterize math performance. Science, 321(5888), 494-

495. https://doi.org/10.1126/science.1160364

IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk,

NY: IBM Corp.

Jacobs, J. E., Lanza, S., Osgood, D. W., Eccles, J. S., & Wigfield, A. (2002). Changes

in children’s self‐competence and values: Gender and domain differences

across grades one through twelve. Child development, 73(2), 509-527.

https://doi.org/10.1111/1467-8624.00421

Jones, G. M., Howe, A., & Rua, M. J. (2000). Gender Differences in Students’

Experiences, Interests, and Attitudes toward Science and Scientists. Science

Education, 84(2), 180-192. https://doi.org/10.1002/(SICI)1098-

237X(200003)84:2<180::AID-SCE3>3.0.CO;2-X

Kane, E. W. (2000). Racial and ethnic variations in gender-related attitudes. Annual

Review of Sociology, 26(1), 419-439.

https://doi.org/10.1146/annurev.soc.26.1.419

49

Kelly, A. C., & Carter, J. C. (2013). Why self‐critical patients present with more

severe eating disorder pathology: The mediating role of shame. British Journal

of Clinical Psychology, 52(2), 148-161. https://doi.org/10.1111/bjc.12006

Kuper, L. E., Nussbaum, R., & Mustanski, B. (2012). Exploring the diversity of

gender and sexual orientation identities in an online sample of transgender

individuals. Journal of sex research, 49(2-3), 244-254.

https://doi.org/10.1080/00224499.2011.596954

Legislation.gov.uk. (2010). Equality Act 2010. [online] Available at:

http://www.legislation.gov.uk/ukpga/2010/15/contents

Lewis, M. (1992). Shame: The exposed self. New York: Free Press.

Lewis, M. (2003). The role of the self in shame. Social Research, 70(4), 1181-1204.

Retrieved from https://search.proquest.com/docview/209669129?

accountid=17256

Lewis, M., Alessandri, S. M., & Sullivan, M. W. (1992). Differences in Shame and

Pride as a Function of Children’s Gender and Task Difficulty. Child

Development, 63(3), 630-638. https://doi.org/10.2307/1131351

Lewis, M., Sullivan, M. W., Stanger, C., & Weiss, M. (1989). Self development and

self-conscious emotions. Child development, 60(1), 146-156.

https://doi.org/10.2307/1131080

Liben, L., Bigler, R., Ruble, D., Martin, C., & Powlishta, K. (2002). The

Developmental Course of Gender Differentiation: Conceptualizing, Measuring,

and Evaluating Constructs and Pathways. Monographs of the Society for

Research in Child Development, 67(2), I-183. Retrieved from

http://www.jstor.org/stable/3181530

50

deMarrais, K., & Tisdale, K. (2002). What happens when researchers inquire into

difficult emotions? Reflections on studying women’s anger through qualitative

interviews. Educational Psychologist, 37(2), 115–123.

https://doi.org/10.1207/S15326985EP3702_6

Martin, C. (2000). Cognitive theories of gender development. In T. Eckes & H. M.

Trautner (Eds.), The developmental social psychology of gender (pp. 91–121).

Mahwah: Lawrence Erlbaum Associates Publishers.

Martin, C. L., & Dinella, L. M. (2012). Congruence between gender stereotypes and

activity preference in self-identified tomboys and non-tomboys. Archives of

Sexual Behavior, 41(3), 599-610. https://doi.org/10.1007/s10508-011-9786-5

Martin, C. L., & Halverson Jr, C. F. (1981). A schematic processing model of sex

typing and stereotyping in children. Child development 52(4), 1119-1134.

https://doi.org/10.2307/1129498

Martin, C. L., Ruble, D. N., & Szkrybalo, J. (2002). Cognitive theories of early gender

development. Psychological bulletin, 128(6), 903.

https://doi.org/10.1037/0033-2909.128.6.903

McKown, C., & Weinstein, R. S. (2003). The development and consequences of

stereotype consciousness in middle childhood. Child Development, 74(2), 498-

515. https://doi.org/10.1111/1467-8624.7402012

Mills, R. S. L., Arbeau, K. A., Lall, D. I. K., & de Jaeger, A. E. (2010). Parenting and

Child Characteristics in the Prediction of Shame in Early and Middle

Childhood. Merrill-Palmer Quarterly, 56(4), 500-528.

https://doi.org/10.1353/mpq.2010.0001

51

Murphy, S. T., Monahan, J. L., & Zajonc, R. B. (1995). Additivity of nonconscious

affect: combined effects of priming and exposure. Journal of personality and

social psychology, 69(4), 589. https://doi.org/10.1037/0022-3514.69.4.589

Muris, P., & Meesters, C. (2014). Small or big in the eyes of the other: On the

developmental psychopathology of self-conscious emotions as shame, guilt,

and pride. Clinical child and family psychology review, 17(1), 19-40.

https://doi.org/10.1007/s10567-013-0137-z

Nestle, J., Howell, C., & Wilchins, R. (Eds.). (2002). Genderqueer: Voices from

beyond the sexual binary. Los Angeles: Alyson.

Nosek, B. A., Banaji, M. R., & Greenwald, A. G. (2002). Math= male, me= female,

therefore math≠ me. Journal of personality and social psychology, 83(1), 44.

https://doi.org/10.1037/0022-3514.83.1.44

Petty, R. E., & Brinol, P. (2006). A metacognitive approach to" implicit" and"

explicit" evaluations: Comment on Gawronski and Bodenhausen (2006).

Psychological Bulletin, 132(5), 740-744. https://doi.org/10.1037/0033-

2909.132.5.740

Petty, R. E., Brinol, P., & DeMarree, K. G. (2007). The Meta–Cognitive Model

(MCM) of attitudes: Implications for attitude measurement, change, and

strength. Social Cognition, 25(5), 657-686.

https://doi.org/10.1521/soco.2007.25.5.657

Qualtrics, (2017), Provo, UT, USA. Accessed via http://www.qualtrics.com.

Ruble, D. N., Eisenberg, R., & Higgins, T. (1994). Developmental Changes in

Achievement Evaluation: Motivational Implications of Self-Other Differences.

Child Development, 65(4), 1095-1110. https://doi.org/10.2307/1131307

52

Scherer, K. R., & Wallbott, H. G. (1994). Evidence for Universality and Cultural

Variation of Differential Emotion Response Patterning. Journal of Personality

and Social Psychology, 66(2), 310-328. https://doi.org/10.1037/0022-

3514.66.2.310

Signorella, M. L., Bigler, R. S., & Liben, L. S. (1993). Developmental differences in

children′ s gender schemata about others: A meta-analytic review.

Developmental review, 13(2), 147-183. https://doi.org/10.1006/drev.1993.1007

Simonds, L. M., John, M., Fife-Shaw, C., Willis, S., Taylor, H., Hand, H., Rahim, M.,

Winstanley, H., & Winton, H. (2015). Development and Validation of the

Adolescent Shame-Proneness Scale. Psychological Assessment, 28(5), 549-

562. https://doi.org/10.1037/pas0000206

Spelke, E. S. (2005). Sex differences in intrinsic aptitude for mathematics and

science?: a critical review. American Psychologist, 60(9), 950.

https://doi.org/10.1037/0003-066X.60.9.950

Swan, S. & Andrews, B. (2003). The relationship between shame, eating disorders and

disclosure in treatment. The British Journal of Clinical Psychology, 42(4),

367-78. https://doi.org/10.1348/014466503322528919

Tangney, J. P., Wagner, P. E., Hill-Barlow, D., Marschall, D. E., & Gramzow, R.

(1996). Relation of shame and guilt to constructive versus destructive

responses to anger across the lifespan. Journal of personality and social

psychology, 70(4), 797. https://doi.org/10.1037/0022-3514.70.4.797

Tangney J. P., & Dearing, R. L. (2002). Shame and Guilt. New York: Guildford Press.

Tangey, J. P., Wagner, P. E., & Gramzow, R. (1989) The Test of Self-Conscious

Affect. George Mason University: Fairfax, VA.

53

Tenenbaum, H. R., & Leaper, C. (2002). Are Parents’ Gender Schemas Related to

Their Children’s Gender-Related Cognitions? A Meta-Analysis.

Developmental Psychology, 38(4), 615-630. https://doi.org/10.1037/0012-

1649.38.4.615

Thode, H. (2002). Testing For Normality. Boca Raton: CRC Press.

https://doi.org/10.1201/9780203910894

Tobin, D. D., Menon, M., Menon, M., Spatta, B. C., Hodges, E. V., & Perry, D. G.

(2010). The intrapsychics of gender: A model of self-socialization.

Psychological Review, 117(2), 601. https://doi.org/10.1037/a0018936

Tomasetto, C., Alparone, F. R., & Cadinu, M. (2011). Girls' math performance under

stereotype threat: The moderating role of mothers' gender stereotypes.

Developmental psychology, 47(4), 943. https://doi.org/10.1037/a0024047

Valentine, D. (2007). Imagining transgender: An ethnography of a category. Durham,

NC: Duke University Press.

Vizin, G., Urban R. & Unoka, Z. (2016). Shame, trauma, temperament and

psychopathology: Construct validity of the Experience of Shame Scale.

Psychiatry Research, 246, 62-69.

https://doi.org/10.1016/j.psychres.2016.09.017

Wicker, F. W., Payne, G. C., & Morgan, R. D. (1983). Participant descriptions of guilt

and shame. Motivation and Emotion, 7(1), 25-39.

https://doi.org/10.1007/BF00992963

Weisgram, E. S. (2016). The cognitive construction of gender stereotypes: Evidence

for the dual pathways model of gender differentiation. Sex Roles, 75(7-8), 301-

313. https://doi.org/10.1007/s11199-016-0624-z

54

Wellard, I. (Ed.). (2007). Rethinking gender and youth sport. England: Routledge.

https://doi.org/10.4324/9780203933619

Wigfield, A., & Eccles, J. S. (2002). The development of competence beliefs,

expectancies for success, and achievement values from childhood through

adolescence. In A. Wigfield & J. S. Eccles (Eds.), A Vol. in the educational

psychology series. Development of achievement motivation (pp. 91-120). San

Diego, CA, US: Academic Press. http://dx.doi.org/10.1016/B978-012750053-

9/50006-1

Wilansky-Traynor, P., & Lobel, T. E. (2008). Differential effects of an adult

observer’s presence on sex-typed play behavior: A comparison between

gender-schematic and gender-aschematic preschool children. Archives of

sexual behavior, 37(4), 548-557. https://doi.org/10.1007/s10508-008-9342-0

55

Appendix

A. Parent Information LetterB. Parent/Guardian Consent FormC. Child Information SheetD. Child Assent Form E. Recruitment Letter for SchoolsF. Parent Demographic QuestionsG. Occupation, Activity and Trait Scale-Personal Measure, Short Version

(OAT-PM) (Liben & Bigler, 2002)H. Occupation, Activity and Trait Scale-Attitude Measure, Short Version

(OAT-AM) (Liben & Bigler, 2002)I. Child Test Protocol IntroductionJ. Child Demographic QuestionsK. Children’s Occupation, Activity and Trait Scale – Personal Measure, Short

Version (COAT-PM) (Liben & Bigler, 2002)L. Children’s Occupation, Activity and Trait Scale – Attitude Measure, Short

Version (COAT-AM) (Liben & Bigler, 2002)M. Vignette 1 (Feminine Stereotyped Imagined Failure Scenario)N. Vignette 2 (Feminine Stereotyped Imagined Failure Scenario)O. Vignette 3 (Masculine Stereotyped Imagined Failure Scenario)P. Vignette 4 (Masculine Stereotyped Imagined Failure Scenario)Q. Vignette 5 (Non-Gender Stereotyped Imagined Failure Scenario)R. Vignette 6 (Non-Gender Stereotyped Imagined Failure Scenario)S. Vignette 7 (Positive Story of Achievement)T. Anticipated Shame QuestionsU. Favourable ethical approval from the Faculty of Health and Medical

Sciences Ethics Committee at the University of SurreyV. Hypothesis 1: Histogram for mean anticipated shame scores by child gender

and task type.W. Hypothesis 2: Histogram for mean scores on gender attitude measures by

child genderX. Hypothesis 3: Histogram for mothers’ mean scores on gender attitude

measuresY. Comparison of Pearson product-moment and Spearman’s rank-order

correlations

56

Appendix A: Parent Information Letter

57

58

59

Appendix B: Parent/Guardian Consent Form

60

Appendix C: Child Information Sheet

61

Appendix D: Child Assent Form

62

Appendix E: Recruitment Letter for Schools

63

Appendix F: Parent Demographic Questions

64

65

Appendix G: Occupation, Activity and Trait Scale-Personal Measure, Short Version (OAT-PM) (Liben & Bigler, 2002)

Name of measure not reproduced here due to copyright.

66

Appendix H: Occupation, Activity and Trait Scale-Attitude Measure, Short Version (OAT-AM) (Liben & Bigler, 2002)

Name of measure not reproduced here due to copyright.

67

Appendix I: Child Test Protocol Introduction

68

Appendix J: Child Demographic Questions

69

Appendix K: Children’s Occupation, Activity and Trait Scale – Personal Measure, Short Version (COAT-PM) (Liben & Bigler, 2002)

Name of measure not reproduced here due to copyright.

70

Appendix L: Children’s Occupation, Activity and Trait Scale – Attitude Measure, Short Version (COAT-AM) (Liben & Bigler, 2002)

Name of measure not reproduced here due to copyright.

71

Appendix M: Vignette 1 (Feminine Stereotyped Imagined Failure Scenario)

72

Appendix N: Vignette 2 (Feminine Stereotyped Imagined Failure Scenario)

73

Appendix O: Vignette 3 (Masculine Stereotyped Imagined Failure Scenario)

74

Appendix P: Vignette 4 (Masculine Stereotyped Imagined Failure Scenario)

75

Appendix Q: Vignette 5 (Non-Gender Stereotyped Imagined Failure Scenario)

76

Appendix R: Vignette 6 (Non-Gender Stereotyped Imagined Failure Scenario)

77

Appendix S: Vignette 7 (Positive Story of Achievement)

78

Appendix T: Anticipated Shame Questions

79

Appendix U: Favourable ethical approval from the Faculty of Health and Medical Sciences Ethics Committee at the University of Surrey

80

Appendix V: Hypothesis 1; Histogram for mean anticipated shame scores by child gender and task type.

81

82

83

Appendix W: Hypothesis 2; Histogram for mean scores on gender attitude measures by child gender

84

85

86

Appendix X: Hypothesis 3: Histogram for mothers’ mean scores on gender attitude measures

87

88

Appendix Y: Comparison of Pearson product-moment and Spearman’s rank-order correlations to assess the relationship between child gender attitudes (COAT-AM and COAT-PM) (Liben & Bigler, 2002) and Anticipated Shame.

Pearson product-moment correlations:Boys (n=14) Girls (n=14)

COAT-AM (r)

COAT-PM (r) COAT-AM (r)

COAT-PM (r)

Masculine

Feminine Masculine

Feminine

Anticipated Shame Feminine Task

.28 (.33) .15 (.61) .14 (.63) .04 (.90) -.05 (.86) -.05 (.86)

Anticipated Shame Masculine Task

.17 (.56) -.12 (.69) -.09 (.76) -.05 (.86) -.08 (.80) -.06 (.85)

Spearman’s rank order correlations:Boys (n=14) Girls (n=14)

COAT-AM (r)

COAT-PM (r) COAT-AM (r)

COAT-PM (r)

Masculine

Feminine Masculine

Feminine

Anticipated Shame Feminine Task

.19 (.51) .18 (.55) .21 (.46) .08 (.79) -.27 (.35) -.18 (.55)

Anticipated Shame Masculine Task

.10 (.74) -.12 (.68) -.08 (.79) -.17 (.57) -.23 (.43) -.12 (.68)

89

Part II: Literature Review

Parent-Child Perfectionism: A Systematic Literature Review

90

Abstract

Objective: Perfectionism is a personality trait linked to various psychopathologies

that can impede positive treatment outcomes and increase risk of psychiatric

conditions. Dysfunctional perfectionism can emerge in childhood and become more

pervasive with age. Research into developmental factors indicates a potential

association between parent and child perfectionism. The current review summarises

existing literature on the relationship between parent-child perfectionism whilst also

considering diversity in the conceptualisation and measurement of perfectionism.

Methods: A systematic search of Child Development and Adolescent Studies, ERIC,

PsycARTICLES, PsycINFO, PsycTESTS, and Psychology and Behavioural

Sciences Collection databases was performed using key search terms; Child*

perfectionis* AND Parent* perfectionis*. Eligible articles identified from database

searches that met inclusion criteria were supplemented with other eligible papers

identified from reference list screening and using database “cited by” function. A

total of 11 papers published between 1999 and 2019 were identified that assessed the

relationship between parent and child perfectionism.

Results: All studies included in the review were correlational in design, with a

variety of measures used and participant samples recruited. Associations between

parent and child perfectionism were inconsistent, with studies failing to replicate

significant findings.

Conclusion: Whilst there is evidence of significant correlations between parent and

child perfectionism, issues relating to methodology and statistical analysis in the

existing literature limit the formulation of meaningful conclusions. Limitations of the

review are considered with suggestions made for future research.

91

Introduction

Perfectionism is broadly defined as a personality disposition characterized by

a combination of extreme high standards and a tendency towards self-critical

evaluation (Flett & Hewitt, 2002; Frost et al., 1990; Hewitt & Flett, 1991b; Hill &

Curran, 2016; Slaney et al., 2001; Stoeber, 2018). Since the 1980’s research into

perfectionism has increased exponentially (Ganske & Ashby, 2007) but in spite of

expanding understanding, longstanding debate pertaining to definition and

dimensionality persists (Lo & Abbot, 2013). Although many different models of

perfectionism exist (Flett & Hewitt, 2002), the most widely accepted approach

conceptualises perfectionism as multidimensional, with both intrapersonal and

interpersonal constructs underlying the manifestation of perfectionistic traits in

relation to the self and others (Dunkley, Zuroff, & Blankstein, 2003; Frost et al.,

1991; Hewitt & Flett, 1991a; Hill et al., 2004; Johnson & Slaney, 1996; Rheaume et

al., 1995; Slaney, et al., 2001).

It is suggested that dimensions of perfectionism have distinct characteristics

(Hill & Curran, 2016); however, views on the content and significance of these

differ. Early work by Hewitt and Flett (1991b) for example, led to the development

of a Multidimensional Perfectionism Scale (MPS-HF) which includes two subscales

focusing on interpersonal dimensions of perfectionism - Other Oriented

Perfectionism (OOP) and Socially Prescribed Perfectionism (SPP) - and one on

intrapersonal dimensions - Self-Oriented Perfectionism (SOP). Around the same

time, Frost and colleagues (1991) developed a different multidimensional scale, the

Frost Multidimensional Perfectionism Scale (FMPS). This placed greater emphasis

on intrapersonal dimensions, as measured by four subscales: Personal Standards,

Doubts About Actions, Concern Over Mistakes, and Organisation, with only two

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subscales focusing on interpersonal aspects expressed specifically within the parent-

child relational context: Parental Expectations and Parental Criticism.

As well as self-other dimensions, theorists have argued for perfectionism to

be conceptualised on an adaptive continuum (Rice, Ashby & Slaney, 2007; Slaney,

Ashby & Trippi, 1995; Slaney et al., 2001). The idea that perfectionism is an entirely

negative trait (Burns, 1980; Hollender, 1965; Ganske & Ashby, 2007)) has lost

support on the basis it is inadequate for fully understanding perfectionistic behaviour

(Flett & Hewitt, 2002; Ganske & Ashby, 2007). Hamacheck (1978) initially

differentiated what he termed “normal” from “neurotic” perfectionism. Since then,

conceptions of this dimension have evolved and adaptive perfectionism (also

referred to as ‘perfectionist striving’) is largely considered as striving for high

standards with a sense of accomplishment and satisfaction when these are met.

Maladaptive perfectionism (or ‘perfectionist concerns’), on the other hand, involves

the setting of unrealistically high standards and excessive self-criticism (Lo &

Abbott, 2013).

The evolution of various models and conceptualisations of perfectionism has

led to an expansive body of literature in which dimensions and sub-dimensions of

the trait are explored. Accordingly, numerous theoretically informed measures now

exist which aim to tap into distinct components of perfectionism, however evidence

indicates considerable overlap exists between these (Hill, 2004). Whilst this

represents an exciting area of research, a clear understanding of the current

conceptual and methodological issues would be valuable to researchers hoping to

further understanding and advance research methodology in this area.

Whilst further clarification of existing conceptual and methodological issues

is important from a theoretical perspective, its significance may best be framed

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within the context of its applications to clinical psychology. An example of this

would be the adaptive-maladaptive continuum model which distinguishes between

adaptive and maladaptive perfectionism. The importance of these distinctions is best

understood when considered within the context of psychopathology. Perfectionism is

linked to psychological distress in clinical and nonclinical populations (Flett &

Hewitt, 2002; O’Connor & Sheehy, 2001; O’Connor et al., 2009; Shafran &

Mansell, 2001; Stoeber & Otto, 2006). Maladaptive perfectionism is implicated in

mental and physical health disorders including affective disorders, anxiety disorders,

suicide attempts, personality disorder, eating disorders, somatic disorders and fatigue

in both adults and children (Boone et al., 2012; DiBartolo & Varner, 2012; Dittner,

Rimes & Thorpe, 2011; Flett, Panico & Hewitt, 2011; Fry & Debats, 2009; Molnar

et al., 2012; Roxborough et al,, 2012; Shafran & Mansell, 2001). High levels of

maladaptive perfectionism also compromise psychotherapeutic treatment outcomes

for a range of conditions (Egan, Wade & Shafran, 2011). Conversely, adaptive

perfectionism has been deemed as normal, healthy and positive (Cook & Kearney,

2014; Shafran & Mansell, 2001) and is associated with positive affect,

conscientiousness, academic achievement, organisation, and life satisfaction (Hill,

Huelsman & Araujo, 2010).

Gaining insight into the nature and evolution of perfectionism is of great

importance and developmental approaches offer valuable opportunities to explore

the origins of this construct. Several studies have replicated findings indicating

maladaptive perfectionism emerges in childhood (Cox & Enns, 2003; Herman et a.,

2013; Nilsson, et al., 2008; O’Connor et al., 2009; Rice & Aldea, 2006) and remains

relatively stable over time, with maladaptive perfectionistic cognitions and

behaviours observed in children as young as 7 years old (Flett et al., 2000). Risk

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factors for this younger age of onset include temperament, genetics, and family

environment (Cook & Kearney., 2014; Flett et al., 2002; Soenens et al., 2005a),

specifically, parent factors.

Parent psychopathology and parenting style have been identified as potential

methods of transmission of perfectionism through modelling, reinforcement, and

information transfer (Fisak & Grills-Taquechel, 2007; Hutchinson & Yates, 2008;

McArdle & Duda, 2008; Rice, Tucker & Desmond, 2008). Parents with high levels

of perfectionism may embody values centred on achievement, flawless performance,

impressing others, and organisation (Flett et al., 2002). Flett and Hewitt (2002)

proposed that social expectations held by parents with high levels of perfectionism

may lead to anxious parenting practices and children’s internalization of perceived

standards and expectations. If so, learning may become more ingrained over time

leading to higher levels of perfectionism as children age, an idea which appears

supported by longitudinal research (Stoeber, Otto & Dalbert, 2009).

Alternatively, researchers have suggested other factors, such as parental

anxiety or psychological control (Flett et al., 2002; Flett, Sherry & Hewitt, 2001;

Pettit et al., 2001; Soenens et al., 2005a; Soenens et al., 2005b) may better predict

perfectionism in children. For example, anxious parents may be overprotective and

fearful of their children making mistakes. As a consequence, parents may exaggerate

responses to suboptimal performance, or frequently remind children of the

importance of how one is perceived by others. By this logic, anxious parents may

inadvertently reinforce perfectionist tendencies without actually being perfectionists

themselves.

Although current theory would suggest that the extent of perfectionism in

children is correlated with parent perfectionism, a review of this literature has not

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been undertaken. The aim of this review was to assess evidence that parent and child

perfectionism is correlated and to highlight methodological and conceptual issues.

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Method

Search Strategy

The PRISMA Guidelines (Moher et al., 2009) were used to select studies for

the current review. The search terms were: Child* perfectionis* AND Parent*

perfectionis* and the following databases were searched: Child Development and

Adolescent Studies, ERIC, PsycARTICLES, PsycINFO, PsycTESTS, and

Psychology and Behavioural Sciences Collection. Databases were searched in

September 2018 with no time limits. Results were limited to peer reviewed journal

articles, published in English. Age limits were not applied since ‘child’ in the present

review refers to offspring of any age.

Criteria for Inclusion/Exclusion

Studies were eligible for inclusion if they reported primary data on the

relationship between perfectionism in parents and children using validated measures

of perfectionism. Studies based on participants diagnosed with intellectual

disabilities or severe mental illness (e.g. psychosis, schizophrenia, bipolar disorder,

major depressive disorder, eating disorder, post-traumatic stress disorder, panic

disorder) were not eligible for inclusion due to the distinct clinical profiles of such

conditions.

Study Selection

Study identification and selection involved a three phase strategy to ensure as

many studies fulfilling inclusion criteria were identified. In phase one, the database

search identified 56 potentially eligible research studies. Following the removal of

duplicates (N=23), titles and abstracts were screened, and potentially eligible studies

(N=13) were referred for full text analysis. In phase two a reference list search of the

(N=13) studies identified through phase one was performed. From this, further

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studies were identified (N=4) and referred for full text analysis. In phase three, each

database record of the 13 studies identified in phase one was accessed and the ‘cited

by’ function was used, where it was available, to identify further potentially eligible

studies. Through title and abstract screening, further (N=5) studies were allocated for

full text review. All potentially eligible articles identified during the three phases

(N=22) was assessed individually using the inclusion and exclusion criteria, resulting

in a final eligible sample of articles (N=11) for the review. See Figure 1 for a

summary of study selection and exclusion.

Data Extraction

The following data were extracted from each study: study details (authors,

publication year and country), objective/aim, study design, sampling method, sample

size, participant demographic information such as age and ethnicity, sample

characteristics (e.g. mother-child dyads), measures of perfectionism used, main

findings and statistical information.

Quality Assessment of Studies

Methodological quality was assessed using a tool developed specifically for

this review (Appendix B) as no single alternative could be found that was

appropriate for the non-intervention correlational designs of the studies of interest.

Items were adapted from the Checklist for Measuring Quality (Downs & Black,

1998) and the Standard Quality Assessment Criteria for Evaluating Primary

Research Papers from a Variety of Fields (Kmet, Lee & Cook, 2004) through

discussion with the research team. These tools were chosen based on the relevance of

their quality criteria to the studies reviewed and the scoring framework. The authors’

definition for items taken from each tool was adhered to, so as not to compromise the

operationalization of criteria. The scoring criteria was also adopted from existing

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measures, so the tool used in the present review consisted of 9 items scored with 0

(absent) or 1 (present), giving a maximum score of 9. Areas of quality assessed by

existing tools was considered through discussion, and those relevant to studies in the

present review were included so that quality was assessed according to: reporting (4

items), external validity (2 items), internal validity (2 items), power (1 item). The

systematic scoring system allowed studies to be evaluated relative to each other even

though they were heterogeneous in objective and methodology. Studies were not

excluded on the basis of quality so that methodological strengths and limitations in

this area could be identified in order to inform future research. Overall quality scores

can be found in Table 3. Although a range of quality criteria were assessed, it was

not possible to cover all possible biases influencing psychological research. It is

therefore possible that studies suffered from limitations that were outside the range

of the quality assessment items, such as data collection and measurement bias.

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Records identified through database searching

(n = 56)

Scr

een

ing

Incl

ude

d

Elig

ibi

lity

Ide

ntifi

cati

on

Additional records identified through other sources including reference

search and “cited by” functions(n = 1052)

Records after duplicates removed(n = 1085)

Records screened (n = 1085)

Records excluded at Title

(n = 992)Records excluded at

Abstract (n = 71)

Full-text articles excluded (n = 11).

Reasons: Failure to report

primary data Failure to

provide correlation coefficient for parent-child perfectionism

Failure to use validated measure of perfectionism

Study not peer reviewed

Studies included in review

(n = 11)

Figure 1. PRISMA flow diagram of study selection and exclusion (Moher, 2009)

Full-text articles assessed for eligibility

(n = 22)

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Results

Whilst both forms of perfectionism have far reaching clinical implications,

one could argue the most useful research is that which is able to distinguish

underlying mechanisms of adaptive from maladaptive perfectionism. For this reason,

researchers have typically mapped the different dimensions of measures onto either

adaptive or maladaptive perfectionism. The following section will consider the

different ways perfectionism was measured by studies identified in this review,

summarising findings regarding the correlation between parent and child

perfectionism. Key features of measures and how these can be understood within the

context of the adaptive-maladaptive dimension of perfectionism is discussed. Key

information from the studies is presented in Table 1.

Participants

The total number of participants was 5,632. Seven studies included mothers

and fathers, three studies recruited mothers only, and one study (Smith et al., 2017a)

included just fathers. Nine studies recruited sons and daughters, and two studies

recruited only daughters (Smith et al., 2017a; Smith et al., 2017b). In six studies,

child age was reported but not parent age, three studies reported both parent and

child age data, and two studies did not report specific age data for participants (Azizi

& Besharat, 2011; Smith et al., 2019). Six studies reported ethnicity information for

either parents or children, however five studies reported no ethnicity information. All

but one study (Azizi & Besharat, 2011) were conducted in North America and the

UK.

Settings

Studies were conducted across a variety of settings. Four recruited high

school age adolescents from schools or community organisations such as activity

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centres (Azizi & Besharat., 2011; Clark & Coker., 2009; Cook & Kearney., 2009;

Cook & Kearney., 2014). Four studies recruited college age students from

universities (Smith et al., 2017a; Smith et al., 2019; Smith et al., 2017b; Vieth &

Trull., 1999). The remaining three studies recruited specific participant groups from

community settings; two of these included participants with chronic illnesses

(Randall et al., 2018; Rice, Tucker & Desmond., 2008) and one was based on a

sample of elite adolescent athletes (Appleton, Hall & Hill., 2010).

Designs

All studies included in the review were cross-sectional and correlational in

design.

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Table 1 – Study CharacteristicsStudy Total

Sample (N)

Parent Sample Child sample Demographic Characteristics of Participants(e.g. Mean age, Ethnicity)

Setting

Appleton, Hall & Hill (2010)UK

1122 Fathers=259Mothers=302

Sons=324 (173 in Mother Group)Daughters=237 (129 in Mother Group)

Mother Group: Sons (M=14.76, SD = 1.70), Daughters (M=14.55, SD = 2.14)Father Group: Sons (M=14.87, SD = 1.68), Daughters (M=14.52, SD = 2.00)

Sport

Azizi & Besharat (2011)Iran

1106 Fathers=342Mothers=364

Sons=187Daughters=213

High school age children from schools in Tehran, Iran.

Education (School)

Clark & Coker (2009)UK

220 Mothers=110 Sons=50Daughters=60

Sons/Daughters (M=13.2, SD= .98).Mothers (M=44.0, SD= 4.29).

Education (School)

Cook & Kearney (2009)USA

239 Fathers=63Mothers=87

Sons=39Daughters=48

Sons/Daughters 11-17 years (M = 14.3, SD = 2.0).Family members; European-American (75.9%), Hispanic (9.2%), Asian-American (6.0%), multiracial (4.0%), African-American (3.2%), or other (1.6%).

Community

Cook & Kearney (2014)USA

358 Fathers=86Mothers=112

Sons=67Daughters=93

Sons/Daughters 8-17 years; European American (63.7%), Hispanic American (12.5%), Multiracial (11.9%), Other (11.9%).Mothers/Fathers; European American (69.2%), Hispanic American (12.1%), Other (18.7%).

Community

Randall et al. (2018)USA

N=478 239 Parent-Child pairs.Fathers=Approx. 19Mothers=Approx. 220

Sons=Approx.43Daughters= Approx.196

Sons/Daughters 8-17 years (M=13.99, SD = 2.38).

Participants were mostly White (95.3%).

Chronic Pain Outpatient

Rice, Tucker &

184 Mothers=90 Sons=35Daughters=59

Sons (11), Daughters (28)

Chronic Condition

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Desmond (2008)USA

African AmericanSons (24), Daughters (31) White.African American (M=13.38 years, SD=1.57), White (M=13.86 years, SD=1.30).Mothers (35) = African American (M = 44.00years, SD = 9.53), Mothers (55) = White (M=41.39years, SD = 7.43).

Outpatient

Smith et al. (2017a)Canada

318 F=159 D=159 Daughters (M=19.9 years, SD = 3.0), 91.8% CaucasianFathers (M=52.3 years, SD = 6.8), 92.5% Caucasian

Education (University)

Smith et al. (2019)Canada

577 Fathers=102 Mothers=168

Sons=Approx. 93Daughters=Approx. 214

NR Education (University)

Smith et al. (2017b)Canada

436 Mothers=218 Daughters=218 Daughters (M=20years, SD=NR); Caucasian (89.9%).Mothers (91.7% Caucasian).

Education (University)

Vieth & Trull (1999)USA

594 Fathers=194Mothers=212

Sons=60Daughters=128

Sons (M=19.03years, SD = 0.84).Daughters (M=18.91years, SD = 2.32).

Education (University)“Intact” families (children reared by both biological parents until 18)

NR=Not Reported.

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Measurement of Perfectionism

The majority of studies used multidimensional measures of perfectionism,

with one using the Effortless Perfectionism Scale, a unidimensional measure (EPS;

Travers et al., 2015). The use of different measures means the specific dimensions of

perfectionism assessed varied. Measures used in the literature have considerable

overlap, with no single measure covering the full range of fundamental constructs

(Hill et al., 2004). Issues pertaining to the definition, dimensionality and

maintenance of perfectionism remain highly debated with disagreement surrounding

which cognitive, affective and behavioural factors ought to be considered significant

(Lo & Abbott, 2013). However, as noted, a common distinction is that of adaptive

and maladaptive perfectionism (Stöber & Otto, 2006). Whilst widely used measures

such as the Hewitt and Flett Multidimensional Perfectionism Scale (MPS-HF;

Hewitt & Flett, 1991) and the Frost Multidimensional Perfectionism Scale (FMPS;

Frost et al., 1991) do not explicitly measure these two types of perfectionism (Cox,

Enns, Sareen & Freeman, 2001) researchers often select subscales based on their

association with either dimension. Other researchers have developed measures to

explicitly explore the adaptive-maladaptive components of perfectionism

(Hamacheck, 1978; Slaney, Ashby & Trippi, 1995; Slaney et al., 2001) using tools

such as the Almost Perfect Scale-Revised (APS-R; Slaney & Johnson, 1992) and

Perfectionism Inventory (Hill et al., 2004).

Seven of the included studies in this review used the same measure for both

parent and child participant groups (Appleton, Hall & Hill., 2010; Azizi & Besharat.,

2011; Clark & Coker., 2009; Rice, Tucker & Desmond., 2008; Smith et al., 2019;

Smith et al., 2017b; Vieth & Trull., 1999) whereas four studies used different

measures for parents and children (Cook & Kearney., 2009; Cook & Kearney., 2014;

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Randall et al., 2018; Smith et al., 2017a). Several studies used measures in their full

version (Appleton, Hall & Hill., 2010; Azizi & Besharat, 2011; Clark & Coker.,

2009; Cook & Kearney., 2009; Cook & Kearney., 2014; Randall et al., 2018; Vieth

& Trull., 1999) however some focused on specific subscales (Rice, Tucker &

Desmond., 2008; Smith et al., 2017a; Smith et al., 2019; Smith et al., 2017b).

Hewitt and Flett’s (1991) Multidimensional Perfectionism Scale (MPS-HF)

The MPS-HF assesses perfectionism as a three-dimensional construct using

45 items. A shorter 15-item version (MPS-HF-SF; Hewitt et al., 2008) has shown to

correlate well with the original version (Stoeber, 2018). The three dimensions are:

Self-Oriented (SOP) which reflects the setting of unrealistically high standards and a

hypersensitivity to flaws or failures in one’s performance; Other-Oriented (OOP)

which reflects exaggerated expectations, and subsequent critical evaluation, of

others; and, Socially Prescribed Perfectionism (SPP) which reflects the pursuit of

standards and expectations perceived to be set by significant others. The MPS is one

of the most widely used measures in perfectionism research and has robust

psychometric properties in clinical and non-clinical samples (Cox, Enns & Clara,

2002). Factor analytic studies that aim to assess support for a two-factor adaptive-

maladaptive structure of perfectionism suggest self-oriented perfectionism loads with

other scales that measure adaptive perfectionism whilst socially-prescribed

perfectionism loads with those measuring maladaptive perfectionism (Cox, Enns,

Sareen & Freeman, 2001).

Frost Multidimensional Perfectionism Scale (FMPS; Frost et al., 1991)

Concurrent to the development of the MPS-HF, Frost et al. (1991)

independently developed the 35-item FMPS comprising six subscales. Concern Over

Mistakes (CM) represents negative reactions to mistakes, a tendency to interpret

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mistakes as failures and the belief that failure ultimately results in a loss of respect

from others. Personal Standards (PS) reflects high standards of performance and

evaluation of oneself in relation to these. Parental Expectations (PE) and Parental

Criticism (PC) reflect the extent to which parents are perceived as having high

expectations and being overly critical. Doubts About Actions (DA) reflects a

preoccupation with doing things right, repeating work and getting behind.

Organisation (OR) reflects neatness and organisation. Research shows the CM and

DA subscales load onto the same factor and provide a measure of “dysfunctional

perfectionism” (DP; Bieling, Israeli & Antony, 2004; Soenens et al., 2005a; Soenens

et al., 2005b; Stöber, 1998). Enns et al. (2001) found Personal Standards loaded with

the MPS-HF self-oriented perfectionism scale to form an adaptive perfectionism

factor (or ‘perfectionist striving’).

, the MPS-HF and FMPS are increasingly critiqued for being dated and

failing to encompass the full range of theorised perfectionism dimensions. As a

result, researchers increasingly combine subscales of both measures, or develop new

measures that better reflect newer conceptualisations of perfectionism (Besharat &

Atari, 2017).

Child Adolescent Perfectionism Scale (CAPS)

The CAPS (Flett et al., 1997) is a 22-item measure based on the MPS-HF

(Hewitt & Flett, 1991) designed specifically for use with children and adolescents

aged 6 to 18 (O’Connor, Dixon & Rasmussen, 2009). Similar to the MPS-HF, the

CAPS self-orientated and socially-prescribed subscales are associated respectively

with adaptive and maladaptive dimensions of perfectionism (Flett et al., 2016). An

important difference is the use of a two rather than three factor model. Other-

oriented perfectionism was not included due to a lack of understanding surrounding

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the developmental age at which young people develop perfectionistic expectations of

others (Flett et al., 2016). In a similar vein to critiques of other MPS scales, rapid

growth in child perfectionism research has meant additional dimensions of

perfectionism have since been proposed. For example Perfectionistic Self-

Presentation (PSP) has been suggested to denote a need to appear perfect to others

(Hewitt et al., 2011). Findings suggesting this interpersonal perfectionistic striving

may be evident in children and adolescents (Hewitt et al., 2011; Peterson, 2003) have

prompted development of newer scales such as the Perfectionistic Self-Presentation-

Scale-Junior Form (PSPS-Jr; Hewitt et al., 2011) which aim to assess these

dimensions not included in the CAPS.

Almost Perfect Scale – Revised (APS-R)

The APS-R (Slaney et al., 2001) is a 23-item self-report measure of three

dimensions of perfectionism. Discrepancy refers to the perceived difference between

a person’s performance expectations and subsequent performance self-evaluations.

Higher scores on this subscale are associated with psychological distress and

maladjustment. High Standards refers to levels of performance expectations. Order

refers to a preference for neatness and structure. Higher scores on Discrepancy and

High Standards indicate higher levels of perfectionism. Although various studies

support the association between high scores on Discrepancy and psychological

distress (Elion, Wang, Slaney, & French, 2012; Gilman, Adams, & Nounopoulos,

2011; Rice et al., 2012; Rice & Stuart, 2010; Sherry et al., 2012; Sironic & Reeve,

2012), the link between High Standards and adaptive perfectionism is inconsistent

(Rice, Richardson & Tueller, 2014), and some researchers have advocated the

removal of the Order subscale altogether (Stoeber & Otto, 2006). Faults found with

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the APS-R have led to the development of alternatives such as Short Form of the

Almost Perfect Scale (SAPS; Rice, Richardson & Tueller, 2014).

Perfectionism Inventory (PI)

The PI (Hill et al., 2004) combines core dimensions of the MPS-HF and

FMPS, offering researchers a method for capturing fundamental dimensions of

perfectionism without having to use multiple measures (Hill et al., 2004). The

measure comprises 59 items distributed across eight subscales: Concerns Over

Mistakes, Need for Approval, Organisation, Striving for Excellence, High Standards

for Others, and Perceived Parental Pressure. Two additional subscales, Planfulness

and Rumination, were also developed. The PI demonstrates good convergent validity

with other measures of perfectionism (Hill et al., 2004). The adaptive-maladaptive

classification of perfectionism is represented in the PI as Conscientious (adaptive)

perfectionism (order, striving, and planning) and Self-Evaluative (maladaptive)

perfectionism (concern about mistakes, need for approval, and rumination). Whilst

the PI reports strong psychometric properties, the measure has not been as widely

used as other measures and interpretations may be limited by the narrow range in

age, race and educational level of the samples upon which it was created (Hill et al.,

2004).

Effortless Perfectionism Scale (EPS; Travers et al., 2015)

The EPS is a 10-item unidimensional measure assessing effortless

perfectionism; the need to appear perfect without seeming to exert effort (Yee,

2003). Theoretically underpinned by Hewitt and Flett’s (2008) model of the

interpersonal expressions of perfectionism, effortless Perfectionism (EP) is a distinct

maladaptive form of perfectionismwhereby particular emphasis is placed not just on

the projection of an image of perfectionism, but one that is accomplished with ease

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(Travers et al., 2015). Results indicate the EPS correlates well with other measures

of maladaptive perfectionism whilst also tapping into a construct not captured by

other scales (Travers et al., 2015), however a notable limitation of the measure is its

restricted scope.

Measures of perfectionism used by the studies are presented in Table 2

alongside corresponding reliability information which is discussed in further detail in

the quality appraisal section.

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Table 2Measures of PerfectionismStudy*(indicates child sample > 18years)

Parent Measure of Perfectionism(Cronbach’s alpha coefficient)

Child Measure of Perfectionism(Cronbach’s alpha coefficient)

Appleton, Hall & Hill (2010)

MPS-HF (Overall sample)SOP (α= .87)

SPP (α = .75 to .69)OOP (α = .67 to .72)

Azizi & Besharat (2011)

MPS-HF (Overall sample)SOP (α = .90)OOP (α = .91)SPP (α = .81)

Clark & Coker (2009) FMPSDP (α = .89)

FMPSDP

S (α = .83)D (α = .85)

Cook & Kearney (2009)

MPSSOP/SPP

Calculated across all adult measures in study♦Mothers: (a = .77)Fathers: (a = .72)

CAPSSOP/SPP

Calculated across all child measures in study♦(a = .78)

Cook & Kearney (2014)

MPS-HF (α = .70)SOP/SPP/OOP

CAPS (α = .58)SOP (α = .74)SPP (α = .66)

Randall et al. (2018) MPS-HFSOP (α = .87)OOP (α = .71)SPP (α = .83)

CAPSSOP (α = .87)SPP (α = .88)

EPS (α = .81)

Rice, Tucker & Desmond (2008)

APS-RDI (α = .86 to .96)HS (α = .67 to .84)

Smith et al. (2017a)* MPS-HF-SFOOP (α = .87)

MPS-HFOOP (α = .86)

PIHS (α = .90)

MPS-HF-SFSPP (α = .84)SOP (α = .87)

FMPSCM (α = .84)DA (α = .80)PS (α = .89)

Smith et al. (2019)* MPS-HFOOP

M (α = .78)F (α = .79)

MPS-HFSPP (α = .79)

Smith et al. (2017b)* MPS-HFOOP (α = .92)

MPS-HF-SFSPP (α = .84)SOP (α = .88)

Vieth & Trull (1999)* MPS-HFSOP (α = .88 to .91)SPP (α = .86 to .88)OOP (α= .76 to .81)

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Key: M = Mothers, F = Fathers, S = Sons, D = Daughters, NR = Not Reported, MPS-HF = Multidimensional Perfectionism Scale (Hewitt & Flett, 1991b), MPS-HF-SF = Multidimensional Perfectionism Scale – Short Form (Hewitt et al., 2008), SOP = Self Oriented Perfectionism, SPP = Socially Prescribed Perfectionism, OOP = Other Oriented Perfectionism, TMPS = Tehran Multidimensional Perfectionism Scale (Besharat, 2007), FMPS = Frost Multidimensional Perfectionism Scale (Frost et al., 1991), DP = Dysfunctional Perfectionism, CM = Concern Over Mistakes, DA = Doubts About Actions, PS = Personal Standards, CAPS = Child Adolescent Perfectionism Scale (Flett et al., 1997), EPS = Effortless Perfectionism Scale (Travers et al., 2015), APS-R = Almost Perfect Scale – Revised (Slaney et al., 2001), DI = Discrepancy, HS = High standards, PI = Perfectionism Inventory (Hill et al., 2004).♦ Cronbachs alpha provided for whole scale rather than individual subscales >> Parent and Child measures of perfectionism were the same unless otherwise stated.

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Quality Ratings of the Studies

Percentage quality scores (Table 3) were derived by dividing the total score

achieved by the total possible score of 9. Studies varied in quality with overall

quality ratings ranging from 78% - 89% with most achieving 8 out of 9 due to no

studies reporting power analysis.

A clear limitation identified through quality appraisal was power. As none of

the studies reported sample size calculations or power analysis, it is important to

question whether studies included in the present review were sufficiently powered to

detect statistically significant relationships between parent and child self-reported

perfectionism. Although some studies had larger sample sizes (ranging from N=184

to N=1122) (Appleton, Hall & Hill, 2010; Rice, Tucker & Desmond, 2008), if

underpowered, studies might not detect smaller effect sizes typically observed in

psychological research.

A second limitation was outcome measures. Four of the studies used

measures developed for adult populations with adolescent samples (Appleton, Hall

& Hill, 2010; Azizi & Besharat, 2011; Clark & Coker, 2009; Rice, Tucker &

Desmond, 2008). However, all studies included in the review utilised validated

measures of perfectionism and demonstrated evidence of reliability by providing

internal consistency data for their sample in the form of Cronbachs alpha.

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Table 3Quality appraisal ratings of studies using criteria adapted from Checklist for Measuring Quality (Downs & Black, 1998) and Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields (Kmet, Lee & Cook, 2004).Study Hypoth

esis/ Objective

Appropriate research design

Main outcome description

Subject selection method

Sample demographic information

Main findings

Statistical analysis

Outcome measures

Power

Total Score

Appleton, Hall & Hill (2010)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Azizi & Besharat (2011)

1 1 1 1 0 1 1 1 0 7/9 (78%)

Clark & Coker (2009)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Cook & Kearney (2009)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Cook & Kearney (2014)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Randall et al. (2018)

1 1 1 1 0 1 1 1 0 7/9 (78%)

Rice, Tucker & Desmond (2008)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Smith et al. (2017a)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Smith et al. (2019)

1 1 1 1 0 1 1 1 0 7/9 (78%)

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Smith et al. (2017b)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Vieth & Trull (1999)

1 1 1 1 1 1 1 1 0 8/9 (89%)

Key: 1= Yes; 0= No

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Relationship between Parent and Child Perfectionism

Findings pertaining to the relationship between parent and child

perfectionism are presented below and have been organised according to the

adaptive-maladaptive dimension in relation to child perfectionism. Firstly, effect

sizes of studies using measures of perfectionism in children aligning with the

adaptive dimension are considered. Next, findings based on measures aligning with

maladaptive perfectionism are presented.

Effect Sizes

To aid interpretation of effect sizes, Cohen’s (1988) benchmark

categorisations for correlation effect size (r) were used: small (0.1–0.29), medium

(0.3-0.49) and large (0.5+). Effect sizes are shown separately for bivariate

correlations in which the child perfectionism dimension has been found in studies to

load onto adaptive perfectionism, such as self- and other-oriented perfectionism, and

high standards (Table 4), and in which the child perfectionism dimension has been

found to load onto maladaptive perfectionism, such as socially-prescribed

perfectionism, concern over mistakes, doubts about actions, discrepancy, effortless

perfectionism (Table 5).

Parent Perfectionism and Child Adaptive Perfectionism

At least one statistically significant relationship was observed in all but one study

(Cook & Kearney, 2009). This study had notably small sample sizes which may have

led to underpowered analyses. However, it was not possible to determine if this was

the case as authors did not comment on power. Studies differed in their approach to

data collection and analysis. Five studies grouped sons and daughters and two

studies reported results for parents as a single group. One study recruited data for

fathers and daughters, one study recruited mothers and daughters, and one recruited

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mothers and children of both genders (reporting results for children as a single

group).

Effect sizes for the relationship between parent perfectionism (adaptive or

maladaptive) and child adaptive perfectionism varied (Table 4). Correlations are

reported according to parent gender, except for one study in which perfectionism

scores of mothers and fathers were combined to produce an index of parent

perfectionism (Randall et al., 2018).

Father and child adaptive perfectionism

There was little consistency between studies in the correlation between father

adaptive perfectionism and child adaptive perfectionism. Effect sizes ranged from r

= -.01 to r = .46. For example, using the MPS-HF, none of the correlations reported

by Appleton et al. (2010) were significant. In contrast, using the same measure,

Vieth and Trull (1999) reported a moderate to large significant positive correlation

between father and son adaptive perfectionism. Variation between these two studies

may be due to Vieth and Trull (1999) stratifying analysis by child gender whereas

Appleton et al. (2010) did not. A general conclusion regarding the correlations

involving father-child dyads is that there is no consistent relationship within or

between studies.

Mother and child adaptive perfectionism

Only one study (Rice, Tucker & Desmond, 2009) explored cultural

differences in perfectionism, reporting a small to moderate significant negative

association between adaptive perfectionism in mothers and children in an African-

American sample but not a White American sample where the correlation was

positive and non-significant. One other study reported a significant negative

correlation between mother and child adaptive perfectionism (Vieth & Trull, 1999)

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although this effect was only observed for mother-son dyads with the correlation

between mother-daughter dyads being significant and positive. Whilst there appeared

more consistency in findings within and between studies in mother-child correlations

than father-child dyads, there was still variability between studies. Possible

contributing factors to observed variation are the use of different measures,

insufficiently powered studies, use of measures with less evidence of validity with

culturally diverse samples, variation in whether studies stratified analyses by child

gender, and in the age group of the child samples.

Father maladaptive perfectionism and child adaptive perfectionism

Little consistency was found in the relationship between father maladaptive

perfectionism and child adaptive perfectionism. Azizi and Besharat (2011) reported a

small positive correlation but, overall, there was little evidence of a relationship

across the studies.

Mother maladaptive perfectionism and child adaptive perfectionism

There appeared to be a little more consistency in the correlation within

mother-child dyads with three studies demonstrating evidence of this association.

However, studies reporting a positive correlation indicated small effect sizes.

Whilst Randall et al. (2018) reported a positive correlation with a moderate

effect size between parent maladaptive perfectionism and child adaptive

perfectionism, their method of combining mother and father data is questionable in

light of evidence from other studies in this review. Given observed differences in

correlations involving mothers versus fathers, aggregating data for both parents may

have masked differences in correlations based on parent gender. It is not clear, for

example, whether the data from mothers is driving the overall significant effect.

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Table 4Effect Sizes – Parent Perfectionism Vs. Child Adaptive Perfectionism stratified by measures usedAuthors Participants (N)

& MeasuresMother/Child Dimensions

r Father/Child Dimensions

r

Measures: MPS-HF, MPS-HF-SF, TMPS, FMPSAppleton et al. (2010)

Mothers (302) Fathers (259)Sons (324) Daughters (237)Sons and daughters were grouped together.

MPS-HF

Self-oriented both .20** Self-oriented both -.01

Socially-prescribed/Self-

oriented

.09 Socially-prescribed/Self-oriented

.07

Other-oriented/Self-oriented

.14 Other-oriented/Self-oriented

-.01

Other-oriented both .26** Other-oriented both .23

Self-oriented/Other-oriented

.18* Self-oriented/Other-oriented

.05

Socially-prescribed/Other-

oriented

.20* Socially prescribed/Other-

oriented

-.01

Azizi & Besharat (2011)

Mothers (364) Fathers (342)Sons (187) Daughters (213)

TMPS

Self-oriented both .12* Self-oriented both .12*

Socially-prescribed/Self-

oriented

.11* Socially-prescribed/Self-oriented

.08

Other-oriented/Self-oriented

.08 Other-oriented/Self-oriented

.02

Other-oriented both .12* Other-oriented both .20**

Self-oriented/Other-oriented

.12* Self-oriented/Other-oriented

.09

Socially-prescribed/Other-

oriented

.14** Socially prescribed/Other-

oriented

.22**

Smith et al. (2017a) §

Fathers (159) Daughters (159)

MPS-HFMPS-HF-SFFMPS

-

MPS-HF-SF & FMPS-SF

Other-oriented/Self-oriented

.06

MPS-HF & MPS-HF-SF

Other-oriented/Self-oriented

.08

MPS-HF-SF & FMPSOther-oriented/

Personal standards

.06

MPS-HF & FMPSOther-oriented/

Personal standards

.19*

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Smith et al. (2017b) §

Mothers (218) Daughters (218)MPS-HF MothersMPS-HF-SF Children

Other-oriented/Self-oriented

.14* -

Vieth & Trull (1999) §

Fathers (194) Mothers (212)Sons (60) Daughters (128)MPS-HF

DaughtersSelf-oriented both

Other-oriented both.31**.14

DaughtersSelf-oriented both

Other-oriented both.00.03

SonsSelf-oriented both

Other-oriented both-.28*.06

SonsSelf-oriented both

Other-oriented both.46**.11

Authors Participants (N)& Measures

Mother/Child Dimensions

r Father/Child Dimensions

r

Measures: MPS-HF (Parents), CAPS (Children)

Cook & Kearney (2009)

Fathers (63) Mothers (87)Daughters (48), Sons (39)

Self-oriented both

Socially-prescribed/ Self-oriented

.15

-.02

Self-oriented both

Socially-prescribed/Self-oriented

.16

.01

Randall et al. (2018)

Fathers (19), Mothers (220)Sons (43), Daughters (196)

Mothers and fathers combined. Child self-oriented perfectionism vs

Parent self-oriented .16*Parent socially-prescribed .31**

Parent other-oriented .21**Measures: APS-R, EPS, & PI

Rice, Tucker & Desmond (2008)

Mothers (90)Sons (35)Daughters (59)Sons & Daughters were grouped together

APS-R

High standards bothAfrican-AmericanWhite American

-.37*.21 -

Discrepancy/ High standards

African-AmericanWhite American

-.12-.16

-

Smith et al. (2017a) §

Fathers (159)Daughters (159)

PI (HS)MPS-HF-SFFMPS-SF

-PI & MPS-HF-SF

Other oriented/ Self-oriented

.15

PI & FMPSOther oriented/

Personal Standards .20*

MPS-HF-SF & MPS-HF-SF

Other-oriented/ Self-oriented .06

MPS-HF-SF & FMPSOther-oriented/

Personal Standards .06

120

MPS & MPS-HF-SFOther-oriented/ Self-

oriented .08

MPS & FMPSOther-oriented/

Personal Standards .19*

§ = Child sample respondents aged 18 and over. MPS-HF = Multidimensional Perfectionism Scale (Hewitt & Flett); MPS-HF-SF = Multidimensional Perfectionism Scale – (Hewitt & Flett) Short Form; TMPS = Tehran Multidimensional Perfectionism Scale; FMPS = Frost Multidimensional Perfectionism Scale; CAPS = Child Adolescent Perfectionism Scale; KPS = Effortless Perfectionism Scale; APS-R = Almost Perfect Scale – Revised; PI = Perfectionism InventoryAdaptive dimensions of perfectionism indicated in italics.*Correlations significant at the p<.05 level**Correlations significant at the p<.01 level

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Parent Perfectionism and Child Maladaptive Perfectionism

Again, evidence for a correlation between parent perfectionism (adaptive or

maladaptive) and child maladaptive perfectionism varied within and between studies

(Table 5). At least one significant association between parent perfectionism and child

maladaptive perfectionism was demonstrated in all studies.

Father and child maladaptive perfectionism

Only one study (Azizi & Besharat, 2011) of three observed a significant

correlation between father and child maladaptive perfectionism. The correlation was

small and positive. However, this was the only study that used the TMPS. Two

studies using the MPS-HF (Appleton et al, 2010; Vieth & Trull, 1999) reported

similar results observing positive, small but non-significant correlations.

Mother and child maladaptive perfectionism

There was more consistent evidence for a relationship between mother

maladaptive perfectionism and child maladaptive perfectionism. Associations within

mother-child dyads were consistently larger than those for fathers and children,

except for those reported by Azizi and Besharat (2011), and more frequently

statistically significant, although effect sizes were generally small. Of note, and

potentially reflecting cultural factors, one study (Rice et al., 2008) reported a strong

positive correlation between mother and child dysfunctional perfectionism in a

White American sample but not an African American sample.

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Father adaptive perfectionism and child maladaptive perfectionism

Again, there were inconsistent findings within and between studies. For

example, using the MPS-HF, Appleton et al. (2010) reported a small significant

positive correlation between father other-oriented perfectionism and child socially-

prescribed perfectionism but not for father self-oriented perfectionism. Whilst Smith

et al (2017) also found significant positive correlations between father other-oriented

perfectionism and child maladaptive perfectionism this varied depending on the

measures of adult and child maladaptive perfectionism used. For example,

correlations were not significant when a short-form of the adult MPS-HF was used.

When using the Perfectionism Inventory to measure adaptive perfectionism in

fathers, these authors also reported no significant correlations with child maladaptive

perfectionism.

Mother adaptive perfectionism and child maladaptive perfectionism

Of four studies that assessed mother adaptive and child maladaptive

perfectionism, three reported a small significant positive correlation when assessing

mother other-oriented perfectionism (Azizi & Besharat, 2011; Smith et al., 2017b;

Smith et al., 2019). Appleton et al. (2010) did not find this although they used the

MPS-HF for both mothers and children whilst Azizi and Besharat (20110) used the

TMPS and Smith et al. (2017b) and Smith et al. (2019) used short forms of the MPS-

HF. In addition to this measurement variability, sampling differences are also

evident. One study recruited participants in Iran (Azizi & Besharat, 2011), and one

study recruited elite athletes (Appleton, Hall & Hill, 2010) whilst others recruited

high-school students. The two studies that assessed mother self-oriented

perfectionism did not observe significant correlations (Appleton et al., 2010; Azizi &

Besharat, 2011).

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Table 5Effect Sizes – Parent Perfectionism Vs. Child Maladaptive Perfectionism stratified by measures usedAuthors Participants

(N)& Measures

Mother/Child Dimensions

r Father/Child Dimensions r

Measures: MPS-HF, MPS-HF-SF, TMPS, FMPS

Appleton et al. (2010)

Mothers (302) Fathers (259)Sons (324) Daughters (237)MPS-HF

Socially prescribed both

.30*** Socially prescribed both .10

Self-oriented/ Socially prescribed

.07 Self-oriented/ Socially prescribed

.14

Other oriented/ Socially prescribed

.13 Other oriented/ Socially prescribed

.20*

Azizi & Besharat (2011)

Mothers (364) Fathers (342)Sons (187) Daughters (213)TMPS

Socially prescribed both

.16** Socially prescribed both .19**

Self-oriented/ Socially prescribed

.06 Self-oriented/ Socially prescribed

.13*

Other oriented/ Socially prescribed

.13** Other oriented/ Socially prescribed

.15**

Clark & Coker (2009)

Mothers (110) Sons (50)Daughters (60)FMPS

Dysfunctional perfectionism both

SonsDaughters

.20 ♦

-

Smith et al. (2017a) §

Fathers (159) Daughters (159)MPS-HFMPS-HF-SFFMPS-SF

-

MPS-HF-SF & MPS-HF-SF

Other-oriented/ Socially prescribed

.11

MPS-HF-SF & FMPS-SFOther-oriented/ Concerns

Over MistakesOther-oriented/ Doubts

About Actions

.15

.04

MPS-HF & MPS-HF-SFOther-oriented/ Socially

prescribed

.14

MPS-HF & FMPS-SFOther Oriented/ Concern

Over MistakesOther-oriented/ Doubts

About Actions

.17*

.18*

Smith et al. (2017b) §

Mothers (218) Daughters (218)MPS-HFMPS-HF-SF

Other oriented/ Socially prescribed

.22**

-

Smith et al. (2019) §

Fathers (102) Mothers (168)Sons (93) Daughters (214)MPS-HF-SF

Other oriented/ Socially prescribed

.25*** Other oriented/ Socially prescribed

-.09

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Vieth & Trull (1999) §

Fathers (194) Mothers (212)Sons (60) Daughters (128)MPS-HF

DaughtersSocially prescribed

both.23*

DaughtersSocially prescribed both .02

SonsSocially prescribed

both.20

SonsSocially prescribed both .16

Authors Participants (N)& Measures

Mother/Child Dimensions

r Father/Child Dimensions r

Measures: MPS-HF (Parents), CAPS (Children)

Randall et al. (2018)

Fathers (19), Mothers (220)Sons (43), Daughters (196)CAPS

Mothers and fathers combined. Child socially prescribed vsParent self-oriented .13

Parent other-oriented .11Parent socially-prescribed .24**

Authors Participants (N)& Measures

Mother/Child Dimensions

r Father/Child Dimensions r

Measures: APS-R, EPS, & PI

Randall et al. (2018)

Fathers (19), Mothers (220)Sons (43), Daughters (196)EPS

Mothers and fathers combined. Child effortless perfectionism vs.Parent self-oriented .15

Parent other oriented .13Parent socially prescribed .23**

Rice, Tucker & Desmond (2008)

Mothers (90)Sons (35)Daughters (59)

APS-R

Discrepancy bothAfrican-AmericanWhite American

-.08.47**

-

High standards/ Discrepancy

African-AmericanWhite American

-.11-.17

Smith et al. (2017a) §

Fathers (159)Daughters (159)

PI (HS)MPS-HF-SF

-PI & MPS-HF-SF

Other oriented/ Socially prescribed

.16

PI & FMPS-SFOther-oriented/ Concerns

Over MistakesOther-oriented/ Doubts

About Actions

.13

.03

§ = Child sample respondents aged 18 and over. MPS-HF = Multidimensional Perfectionism Scale (Hewitt & Flett); MPS-HF-SF = Multidimensional Perfectionism Scale – (Hewitt & Flett) Short Form; TMPS = Tehran Multidimensional Perfectionism Scale; FMPS = Frost Multidimensional Perfectionism Scale; CAPS = Child Adolescent Perfectionism Scale; KPS = Effortless Perfectionism Scale; APS-R = Almost Perfect Scale – Revised; PI = Perfectionism InventoryMaladaptive dimensions of perfectionism indicated in italics.*Correlations significant at the p<.05 level**Correlations significant at the p<.01 level

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***Correlations significant at the p<.001 level♦ Correlation not reported due to typographical error in original research article

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Discussion

Studies on the relationship between perfectionism in parents and children

were reviewed within the theoretical context of the adaptive-maladaptive continuum.

A total of eleven studies reporting primary data were included in the review. Effect

sizes for the relationship between parent perfectionism (adaptive or maladaptive) and

child adaptive perfectionism varied widely within and between studies. Generally, it

appeared there was no consistent relationship within father-child dyads when either

father adaptive or maladaptive perfectionism was investigated. Whilst there appeared

more consistency in findings within and between studies in mother-child

correlations, there was still variability between studies and effect sizes were

generally small.

Effect sizes for the relationship between parent perfectionism (adaptive or

maladaptive) and child maladaptive perfectionism also varied widely within and

between the studies reviewed. Similar to findings involving child adaptive

perfectionism, there was little consistent evidence of a relationship between

perfectionism in fathers and child maladaptive perfectionism. The most consistent

finding was that between fathers’ other oriented perfectionism and child maladaptive

perfectionism although this depended on the measures used. Again, the evidence

from mother-child dyads was a little more consistent. Regarding maladaptive

perfectionism, associations within mother-child dyads were consistently larger than

those for fathers and children and were more frequently statistically significant,

although effect sizes were generally small. Of note, and potentially reflecting

cultural factors, one study (Rice et al., 2008) reported a strong positive correlation

between mother and child dysfunctional perfectionism in a White American sample

but not an African American sample. There was some consistency in findings when

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assessing mother other-oriented perfectionism and child maladaptive perfectionism

and variability in measures used or samples recruited may explain some of the

inconsistency within these findings.

Whilst one study (Randall et al. 2018) reported a positive correlation with a

moderate effect size between parent maladaptive perfectionism and child adaptive

perfectionism, these findings should be treated with caution. Combining mother and

father data is questionable in light of the overall findings suggesting more

consistency and, at times, stronger relationships in mother-child dyads.

The variability observed in this review is consistent with much of the existing

literature which associates numerous variables with perfectionism, such as gender

(Hewitt & Flett, 1991), age (Flett et al., 2001), education (Parker, 2000), ethnicity

(Rice, Tucker & Desmond, 2008), and upbringing (Soenens et al., 2005), but offers

little clarity as to their relative impact on the development and maintenance of

perfectionism. Studies reporting non-significant relationships between parent-child

perfectionism appear to be in conflict with current theory and findings suggesting

otherwise (Cook, 2012; Cook & Kearney, 2008; Frost et al., 1991; Hutchinson &

Yates, 2008; McArdle & Duda, 2008; Rice, Tucker & Desmond, 2008; Soenens et

al., 2005), highlighting the need for more methodologically robust research.

Notwithstanding the evident variability in findings, it does appear that

relationships between mother and child perfectionism are more consistent in this

sample of studies than those observed between fathers and children. Overall, fewer

significant correlations were reported for father-child perfectionism than mother-

child perfectionism. Several hypotheses could be made here; firstly, it could be that

mothers contribute uniquely to perfectionism in children, for example, via increased

prevalence of anxiety disorders in women and norms for women to be primary

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caregivers. Literature on the relationship between anxiety and perfectionism in

mothers suggests maternal anxiety often involves specific cognitions characterised

by a preoccupation with being imperfect and making mistakes (Flett et al., 2002). As

women still take on the majority of child-caring roles and practices (Geary, 2010),

anxious mothers may be more instrumental in possessing and conveying

perfectionistic traits through behaviours such as excessive control and

catastrophizing (Van Gastel, Legerstee & Ferdinand, 2009).

A second interesting consideration would be to further investigate the

differential role parental figures have on child perfectionism. One question here is

whether fathers might serve as a protective factor against maladaptive perfectionism

in children. This idea is discussed elsewhere in developmental psychology literature.

For example, Bogels and Phares (2008) suggested that since fathers more frequently

have the role of stipulating boundaries and mothers of offering comfort,

dysfunctional behaviour on the part of either parent, for example, in the form of

mothers’ comforting role being compromised due to difficulties with dysfunctional

perfectionism, could present an increased risk for child anxiety. However, if fathers

compensated for this by extending their role as comforting caregiver, it may be they

represent a protective factor against child anxiety. The combination of parental

influences could be explored further by investigating whether the relationship, for

example, between mother and child perfectionism, is moderated by father

perfectionism (i.e. whether there is a positive correlation between mother and child

perfectionism when father perfectionism is high but not when it is low).

The decision to organise results according to the adaptive-maladaptive

perfectionism distinction, although reasonable based on developments in

perfectionism literature, should also be considered with caution. Several researchers

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(Gotwals, 2011; Hewitt & Flett, 2002; Hill, 2016) have raised concerns about this

categorical approach, questioning whether “healthy” perfectionists actually exist.

Labels such as “healthy”, “unhealthy”, “adaptive” and “maladaptive” have been

heavily criticised for failing to encapsulate the whole experience of people exhibiting

these traits and for being tautological (i.e. healthy perfectionists are those who

experience good health) (Gaudreau & Thompson, 2010). One suggestion is that such

labels should be discarded in favour of a focus on particular features of

perfectionism, such as “doubt-oriented” perfectionism (Hill, 2016). Findings of the

present review, for example that maladaptive perfectionism in parents appeared to be

associated with adaptive perfectionism in children, should be considered with such

conceptual criticisms in mind as distinctions between these dimensions are poorly

defined, in other words, when do adaptive high standards become maladaptive?

Although there are clear issues with the adaptive continuum model of perfectionism,

strengths of this framework are that it offers a helpful way of organising findings and

is a commonly used distinction in the literature, providing a common language in

which research can be disseminated.

Several issues merit comment regarding the quality of studies and

interpretation of results. These can be grouped according to sample characteristics,

methodological issues and statistical analysis.

Participant samples varied across key demographic markers including age,

ethnicity, gender, and cultural background. “Children” in seven of the studies were

of adolescent age while the remaining four recruited university students (Smith et al.,

2017a, 2017b, 2019; Vieth & Trull, 1999). Considering current literature suggests

differences in the development and manifestation of perfectionism in youth versus

adults (Flett et al., 2016) it is worth questioning whether results would have been the

130

same had “child” age been controlled for. This could be investigated in the future

using meta-analysis but the current small evidence based precludes this due to the

limited number of effect sizes. Further, although validation evidence was presented,

four studies in the review used adult measures with adolescent samples (Appleton,

Hall & Hill, 2010; Azizi & Besharat, 2011; Clark & Coker, 2009; Rice, Tucker &

Desmond, 2008). This review raises an important question about the interpretation of

data regarding the relationship between parent and child perfectionism based on

measures which may lack sufficient sensitivity to detect age-related differences

proposed in the literature.

Studies in the review demonstrated a lack of diversity in sample demographic

characteristics and several studies failed to report data on the ethnic composition of

their sample. Only one study focused on potential cultural or ethnic group

differences (Rice, Tucker & Desmond (2008) and observed different relationships

between mother and child perfectionism in an African American sample compared to

a white American participant sample. Moreover, only one study (Azizi and Besharat,

2011) focused on a Middle Eastern sample and reported different findings to studies

of similar methodology and sample size who recruited in the UK (e.g. Appleton, Hall

& Hill, 2010). This raises the possibility that some cultures may place more

emphasis on the adoption of expected standards of behaviour (i.e. parents convey

stronger expectations about adherence to high standards of conduct). For example, in

Chinese culture, Confucian philosophy promotes social norms which position the

family as more important than the individual (Yang, 1997). As children’s behaviour

can be perceived to represent the family as a whole, parents may emphasize a child’s

obligations to the family and the standards that are expected, employing parental

practices such as shaming in the event these are not met (Yeh & Hwang, 1999).

131

Through such practices, parenting behaviour may contribute to the socialization of

desired cultural attitudes and beliefs (Fung, Lieber & Leung, 2003). Markus and

Kitayama’s (2010) mutual constitution model suggests dominant cultural norms and

values shape the context in which institutions, both social and civic (e.g. academic,

familial, political, religious and economic), influence people’s beliefs and attitudes at

any one time. Investigations comparing different ethnic groups on measures of

perfectionism supports theories of cultural difference, showing for example, that

individuals of Asian descent consistently score significantly higher than Caucasian

Americans on the FMPS on subscales loading onto the maladaptive dimension of

perfectionism (Castro & Rice, 2003; Chang, 1998; Kawamura et al., 2002). Other

diversity characteristics such as education and socio-economic status were largely

unexplored limiting our understanding of the relationship these factors may have to

personality constructs such as perfectionism, as well as the generalisability of

findings to minority and underrepresented groups.

Another methodological weakness of studies included in the review was that

none included clinical populations. Given the probability that levels of distress

associated with perfectionism in clinical samples would likely be higher than in

community samples, it is possible that correspondence between parent-child

perfectionism here could also be quantifiably different. If levels of perfectionism are

low in community samples this would inevitably impact on the size of correlation

coefficients. As a result, the generalizability of findings from studies in the present

review would be restricted and arguably fail to extend to some groups most likely to

benefit in a clinically meaningful way from developments in this field.

Although all studies utilised validated measures of perfectionism, direct

comparison was hindered because of authors’ inclusion or exclusion of particular

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subscales (e.g. Smith et al., 2017a, 2017b) or analysis based on aggregate scores (e.g.

Clark & Coker, 2009). Comparison of studies was further hampered by variations in

the definition and operationalisation of perfectionism, use of multiple measures, and

use of adapted versions of measures. The inherent disadvantages of self-report

techniques, including fixed-choice format, social desirability bias, and acquiescence

also limits the interpretation of findings and highlights the need for studies to utilise

alternative forms of data collection such as observational methods.

Regarding statistical analysis, quality appraisal of studies identified several

weaknesses in the analyses performed, as well as instances where further analysis

would have been helpful. For example, analyses assessing whether the relationship

between parent and child perfectionism is moderated by both parent and child gender

would be valuable. However, it was not possible to explore this in any depth as the

majority of studies combined parent or child data, or both, masking any gender

differences. Other key limitation across studies was a failure to report a priori

sample size calculations.

Broadly speaking, probability sampling methods which facilitate recruitment

of diverse, heterogeneous samples representative of sociodemographic differences in

populations are the gold standard in developmental science. However, for various

reasons including availability and cost-effectiveness, non-probability convenience

samples remain the norm within psychological research despite their inherent

limitations in terms of generalizability. Use of convenience samples, however,

should not preclude the need to acknowledge and understand the influence that

sociodemographic differences have on human health and behaviour. As convenience

samples are likely to remain the standard, researchers such as Jager, Putnick and

Bornstein (2017) argue the focus should be on how to reduce limitations associated

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with these techniques rather than denigrate all convenience samples. To this end, the

authors emphasize the importance of homogenous as opposed to heterogeneous

convenience samples, which, when interpreted cumulatively maximise the likelihood

of gaining insight into actual population effects and sub-population differences.

Therefore, although in some ways it is a strength that studies in the present review

included heterogeneous samples, a weakness is that inconsistencies in findings

pertaining to parent-child perfectionism are harder to integrate, interpret and build

on. One way to disentangle the relative contribution of such observed differences in

studies including variability in samples, definition of “child”, collapsing mothers and

fathers in some studies into parents, different parent-child dyads explored across

studies, and use of different measures, would have been to undertake a meta-

analysis. However, the small number of eligible studies would fail to yield

meaningful moderator analyses, hence the decision to conduct a narrative review.

Lastly, all studies were cross-sectional and correlational in design meaning

the question of causality in parent-child perfectionism cannot be tested, despite

having intuitive appeal and some theoretical support. Moreover, such designs are

unable to capture the role of other potentially mediating variables suggested in

perfectionism literature, such as parental control or anxiety.

Strengths and Limitations of the present Literature Review

A strength of the current review is its application of a systematic method to

locate and assess evidence for the relationship between parent and child

perfectionism. Findings identify where future research is needed to fill gaps in the

literature that would enhance understanding of the fundamentals of this construct and

help apply findings to wider audiences. The review also provides an overview of

existing methodologies used in perfectionism research, considering how these relate

134

to one another, and their relationship to the adaptive continuum theory of

perfectionism. However, several limitations of the review should be noted.

The first limitation is that the conclusions of the present review are limited by

the forgoing of inclusivity for systematicity in several ways. Firstly, only studies that

met specified inclusion/exclusion criteria were reviewed. This means research which

could likely help illuminate the association between parent and child perfectionism,

such as grey literature in the form of dissertations or theses or unpublished studies

from prominent researchers, were not included. Secondly, the review focused on

studies of correlational design providing primary data for both parent and child

perfectionism. This is problematic due to such analyses being affected by

measurement error and inability to demonstrate causality.

A second limitation is the lack of inter-rater reliability regarding the quality

assessment of studies. The use of multiple raters in psychological research is widely

advocated as one way of reducing errors in the collection and interpretation of data

(McHugh, 2012). Future investigations would be enhanced by the addition of this

step as part of methodological procedure.

Due to multiple sources of heterogeneity in the review sample, it was not

possible to conduct a meta-analysis to search for common effects. This introduces a

third limitation, being that the scope of the present review is restricted to subjective

interpretation (Ellis, 2010). For this to be addressed, the present review proposes

several suggestions: 1) Use of alternative research designs including longitudinal,

interview, and observational. 2) Larger and more diverse samples for example using

cohort and cross-cultural research.

Clinical implications

135

The present review has important clinical implications in highlighting where

future research is needed. Maladaptive perfectionism is shown to impede treatment

for psychiatric disorders including anxiety, depression, suicidality, low self-esteem

and eating disorders and in children (Accordino et al., 2000; Chick, Whittal, &

O’Neill, 2008; Cox & Enns, 2003; Flett et al., 2002; Hewitt et al., 2008; McVey et

al., 2002; Shahar et al., 2004; Soenens et al., 2008). Dysfunctional perfectionism is

also implicated in adjustment problems in non-clinical populations and other

psychological phenomena, such as self-conscious emotions. Blatt et al. (1995)

suggested perfectionistic individuals are more vulnerable to depression due to a

distorted focus on self-worth and self-criticism; “they berate, criticize and attack

themselves, and experience intense feelings of shame, guilt, failure, and

worthlessness” (p.1012). Shame, often triggered by perceived failure (a core

component of perfectionism) can be a devastating emotion that is insidious and

difficult to control (deMarris & Tisdale, 2002). Thus, not only could further research

shed light onto risk factors for perfectionism but also related psychopathology, such

as depression and shame, by helping to uncover commonalities in aetiology and

latent structure of emotional disorders. Enhanced understanding of the relationship

between parent and child perfectionism could also aid clinical practice on a

procedural, as well as theoretical basis. If consistent evidence accumulates to support

a relationship between parent and child-perfectionism, the use of more systemic

approaches could be used to aid understanding and management of maladaptive

perfectionism. This could be at the level of access, where services encourage family

members as well individuals referred for support to engage with evidence-based

therapies for perfectionism such as Cognitive Behavioural Therapy (Lloyd, Schmidt,

Khondoker, & Tchanturia, 2015).

136

In conclusion, studies included in the present review appear to lend support

for theories suggesting an association between parent-child perfectionism, however,

results relating to the nature and strength of this relationship are inconsistent. Several

factors, both methodological and conceptual, may help to explain observed

variations however more research is needed to explore these further. Clarification of

mechanisms moderating perfectionism will have diverse clinical implications and is

key for the continued development of effective psychological interventions.

137

References

Ablard, K. E., & Parker, W. D. (1997). Parents' achievement goals and perfectionism

in their academically talented children. Journal of Youth and Adolescence,

26(6), 651-667. https://doi.org/10.1023/A:1022392524554

Accordino, D. B., Accordino, M. P., & Slaney, R. B. (2000). An investigation of

perfectionism, mental health, achievement, and achievement motivation in

adolescents. Psychology in the Schools, 37(6), 535-545.

https://doi.org/10.1002/1520-6807(200011)37:6<535::AID-PITS6>3.0.CO;2-

O

Antony, M. M., Purdon, C. L., Huta, V., & Swinson, R. P. (1998). Dimensions of

perfectionism across the anxiety disorders. Behaviour research and therapy,

36(12), 1143-1154. https://doi.org/10.1016/S0005-7967(98)00083-7

Appleton, P. R., Hall, H. K., & Hill, A. P. (2010). Family patterns of perfectionism:

An examination of elite junior athletes and their parents. Psychology of Sport

and Exercise, 11(5), 363-371.

https://doi.org/10.1016/j.psychsport.2010.04.005

Azizi, K., & Besharat, M. A. (2011). The relationship between parental

perfectionism and child perfectionism in a sample of Iranian families.

Procedia-Social and Behavioral Sciences, 15, 1287-1290.

https://doi.org/10.1016/j.sbspro.2011.03.279

Bieling, P. J., Israeli, A. L., & Antony, M. M. (2004). Is perfectionism good, bad, or

both? Examining models of the perfectionism construct. Personality and

individual differences, 36(6), 1373-1385. https://doi.org/10.1016/S0191-

8869(03)00235-6

Blatt, S. J., Quinlan, D. M., Pilkonis, P. A., & Shea, M. T. (1995). Impact of

perfectionism and need for approval on the brief treatment of depression:

138

Further analyses of the National Institute of Mental Health Treatment of

Depression Collaborative Research Program revisited. Journal of Consulting

& Clinical Psychology, 63(1), 125–132. https://doi.org/10.1037/0022-

006X.63.1.125

Besharat, M. A. (2005). Evaluating psychometric properties of Farsi version of the

Positive and Negative Perfectionism Scale. Psychological Reports, 97(1), 33-

42. https://doi.org/10.2466/pr0.97.1.33-42

Besharat, M. A. (2009). Reliability, validity and factorial analysis of a short form of

the Inventory of Interpersonal Problems in an Iranian Population.

Contemporary Psychology, 4(2), 25-36. [Farsi] Retrieved from:

http://bjcp.ir/files/site1/user_files_dbc6fd/drbesharat-A-10-32-9-323e40e.pdf

Besharat, M. A. (2011). Development and Validation of Tehran Multidimensional

Perfectionism Scale. Procedia-Social and Behavioural Sciences, 30, 79-83.

https://doi.org/10.1016/j.sbspro.2011.10.016

Besharat, M. A. & Atari, M. (2017). Psychometric evaluation of a Farsi translation

of the Big Three Perfectionism Scale. Personality and Individual Differences,

113, 5-12. https://doi.org/10.1016/j.paid.2017.02.067

Bögels, S., & Phares, V. (2008). Fathers' role in the etiology, prevention and

treatment of child anxiety: A review and new model. Clinical psychology

review, 28(4), 539-558. https://doi.org/10.1016/j.cpr.2007.07.011

Boone, L., Soenens, B., Vansteenkiste, M., & Braet, C. (2012). Is there a

perfectionist in each of us? An experimental study on perfectionism and

eating disorder symptoms. Appetite, 59(2), 531-540.

https://doi.org/10.1016/j.appet.2012.06.015

139

Bouchard, C., Rhéaume, J., & Ladouceur, R. (1999). Responsibility and

perfectionism in OCD: An experimental study. Behaviour Research and

Therapy, 37(3), 239-248. https://doi.org/10.1016/S0005-7967(98)00141-7

Castro, J. R., & Rice, K. G. (2003). Perfectionism and ethnicity: Implications for

depressive symptoms and self-reported academic achievement. Cultural

diversity and ethnic minority psychology, 9(1), 64.

https://doi.org/10.1037/1099-9809.9.1.64

Chang, E. C. (1998). Cultural differences, perfectionism, and suicidal risk in a

college population: Does social problem solving still matter?. Cognitive

therapy and research, 22(3), 237-254.

https://doi.org/10.1023/A:1018792709351

Chang, E. C., Watkins, A., & Banks, K. H. (2004). How Adaptive and Maladaptive

Perfectionism Relate to Positive and Negative Psychological Functioning:

Testing a Stress Mediation Model in Black and White Female College

Students. Journal of Counselling Psychology, 51(1), 93.

https://doi.org/10.1037/0022-0167.51.1.93

Chik, H., Whittal, M., L., & O’Neill, M. L. (2008). Perfectionism and treatment

outcome in obsessive-compulsive disorder. Cognitive Therapy and Research,

32(5), 676-688. https://doi.org/10.1007/s10608-007-9133-2

Clark, S., & Coker, S. (2009). Perfectionism, self-criticism and maternal criticism: A

study of mothers and their children. Personality and Individual Differences,

47(4), 321-325. https://doi.org/10.1016/j.paid.2009.03.020

Cook, L. C., & Kearney, C. A. (2009). Parent and youth perfectionism and

internalizing psychopathology. Personality and Individual Differences, 46(3),

325-330. https://doi.org/10.1016/j.paid.2008.10.029

140

Cook, L. C., & Kearney, C. A. (2014). Parent perfectionism and psychopathology

symptoms and child perfectionism. Personality and Individual Differences,

70, 1-6. https://doi.org/10.1016/j.paid.2014.06.020

Cox, B. J., & Enns, M. W. (2003). Relative stability of dimensions of perfectionism

in depression. Canadian Journal of Behavioural Science, 35(2), 124-132.

https://doi.org/10.1037/h0087194

Cox, B. J., Enns, M. W., & Clara, I. P. (2002). The Multidimensional Structure of

Perfectionism in Clinically Distressed and College Student Samples.

Psychological Assessment, 14(3), 365-373. https://doi.org/10.1037/1040-

3590.14.3.365

Curran, T., & Hill, A. P. (2017). Perfectionism is increasing over time: A meta-

analysis of birth cohort differences from 1989 to 2016. Psychological

Bulletin, 154(4), 1-21. http://dx.doi.org/10.1037/bul0000138

DeMarrais, K., & Tisdale, K. (2002). What happens when researchers inquire into

difficult emotions?: Reflections on studying women's anger through

qualitative interviews. Educational Psychologist, 37(2), 115-123.

https://doi.org/10.1207/S15326985EP3702_6

DiBartolo, P. M., & Varner, S. P. (2012). How children’s cognitive and affective

responses to a novel task relate to the dimensions of perfectionism. Journal

of Rational-Emotive & Cognitive-Behavior Therapy, 30(2), 62-76.

https://doi.org/10.1007/s10942-011-0130-8

Dittner, A. J., Rimes, K., & Thorpe, S. (2011). Negative perfectionism increases the

risk of fatigue following a period of stress. Psychology and Health, 26(3),

253-268. https://doi.org/10.1080/08870440903225892

141

Downs, S. H, & Black, N. (1998). The feasibility of creating a checklist for the

assessment of the methodological quality both of the randomised and non-

randomised studies of healthcare interventions. Journal of Epidemiology &

Community Health, 52(6), 377-384. https://doi.org/10.1136/jech.52.6.377

Dunkley, D. M., Zuroff, D. C., & Blankstein, K. R. (2003). Self-critical

perfectionism and daily affect: Dispositional and situational influences on

stress and coping. Journal of personality and social psychology, 84(1), 234.

https://doi.org/10.1037/0022-3514.84.1.234

Egan, S. J., Wade, T. D., & Shafran, R. (2011). Perfectionism as a transdiagnostic

process: A clinical review. Clinical psychology review, 31(2), 203-212.

https://doi.org/10.1016/j.cpr.2010.04.009

Elion, A. A., Wang, K. T., Slaney, R. B., & French, B. H. (2012). Perfectionism in

African American students: Relationship to racial identity, GPA, self-esteem

and depression. Cultural Diversity and Ethnic Minority Psychology, 18(2),

118-127. https://doi.org/10.1037/a0026491

Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-

analysis, and the interpretation of research results. England: Cambridge

University Press. https://doi.org/10.1017/CBO9780511761676

Enns, M. W., & Cox, B. J. (2002). The Nature and Assessment of Perfectionism: A

Critical Analysis. In G. L. Flett & P. L. Hewitt (Eds.), Perfectionism: Theory,

Research and Treatment (pp.33-62). Washington DC: American

Psychological Association. https://doi.org/10.1037/10458-002

Fisak, B., & Grills-Taquechel, A. E. (2007). Parental modelling, reinforcement, and

information transfer: Risk factors in the development of child anxiety.

142

Clinical Child and Family Psychology Review, 10, 213-231.

http://dx.doi.org/10.1007/s10567-007-0020-x.

Flett, G., & Hewitt, P. (2002). Perfectionism and Maladjustment: An overview of

theoretical, definitional and treatment issues. In G. L. Flett & P. L. Hewitt

(Eds.), Perfectionism: Theory, Research and Treatment (pp.5-29).

Washington DC: American Psychological Association.

https://doi.org/10.1037/10458-001

Flett, G., Hewitt, P., Boucher, D. J., Davidson, L. A., & Munro, Y. (1997). The Child

Adolescent Perfectionism Scale: Development, Validation and Association

with Adjustment. Unpublished Manuscript, York University, Toronto,

Ontario, Canada.

Flett, G., Hewitt, P., Oliver, J. M., & Macdonald, S. (2002). Perfectionism in

children and their parents: A developmental analysis. In G. L. Flett & P. L.

Hewitt (Eds.), Perfectionism: Theory, Research and Treatment (pp.89-132).

Washington DC: American Psychological Association.

https://doi.org/10.1037/10458-004

Flett, G. L., Hewitt, P. L., Besser, A., Su, C., Vaillancourt, T., Boucher, D., & Gale,

O. (2016). The Child–Adolescent Perfectionism Scale: Development,

psychometric properties, and associations with stress, distress, and

psychiatric symptoms. Journal of Psychoeducational Assessment, 34(7), 634-

652. https://doi.org/10.1177/0734282916651381

Flett, G. L., Panico, T., & Hewitt, P. L. (2011). Perfectionism, type A behavior, and

self-efficacy in depression and health symptoms among adolescents. Current

Psychology, 30(2), 105-116. https://doi.org/10.1007/s12144-011-9103-4

143

Flett, G., Sherry, S. B., & Hewitt, P. (2001). Perfectionism, parental punitiveness,

and anxious parental rearing. Unpublished manuscript.

Frost, R. O., Marten, P., Lahart, C., & Rosenblate, R. (1990). The dimensions of

perfectionism. Cognitive therapy and research, 14(5), 449-468.

https://doi.org/10.1007/BF01172967

Frost, R. O., Lahart, C. M., & Rosenblate, R. (1991). The development of

perfectionism: A study of daughters and their parents. Cognitive therapy and

research, 15(6), 469-489. https://doi.org/10.1007/BF01175730

Frost, R. O., Heimberg, R. G., Holt, C. S., Mattia, J. I., & Neubauer, A. L. (1993). A

comparison of two measures of perfectionism. Personality and Individual

Differences, 14(1), 119-126. https://doi.org/10.1016/0191-8869(93)90181-2

Frost, R. O., & Steketee, G. (1997). Perfectionism in obsessive-compulsive disorder

patients. Behaviour Research and Therapy, 35(4), 291-296.

https://doi.org/10.1016/S0005-7967(96)00108-8

Fry, P. S., & Debats, D. L. (2009). Perfectionism and the five-factor personality

traits as predictors of mortality in older adults. Journal of Health Psychology,

14(4), 513-524. https://doi.org/10.1177/1359105309103571

Fung, H., Lieber, E., & Leung, P. W. (2003). Parental beliefs about shame and moral

socialization in Taiwan, Hong Kong and the United States. In K. S. Yang, K.

K. Hwang, P. B. Pedersen, & I. Daibo (Eds.), Progress in Asian social

psychology: Conceptual and empirical contributions (pp. 83-109). Westport,

CT: Praeger.

Ganske, K. H., & Ashby, J. S. (2007). Perfectionism and career decision‐making

self‐efficacy. Journal of employment counseling, 44(1), 17-28.

https://doi.org/10.1002/j.2161-1920.2007.tb00021.x

144

Gaudreau, P., & Thompson, A. (2010). Testing a 2× 2 model of dispositional

perfectionism. Personality and Individual Differences, 48(5), 532-537.

https://doi.org/10.1016/j.paid.2009.11.031

Geary, D. C. (2010). Male, female: The evolution of human sex differences (2nd

ed.). Washington, DC, US: American Psychological Association.

http://dx.doi.org/10.1037/12072-000

Gilman, R., Adams, R., & Nounopoulos, A. (2011). The interpersonal relationships

and social perceptions of adolescent perfectionists. Journal of research on

adolescence, 21(2), 505-511. https://doi.org/10.1111/j.1532-

7795.2010.00689.x

Gotwals, J. K. (2011). Perfectionism and burnout within intercollegiate sport: A

person-oriented approach. The Sport Psychologist, 25(4), 489-510.

https://doi.org/10.1123/tsp.25.4.489

Hamachek, D. E. (1978). Psychodynamics of normal and neurotic perfectionism.

Psychology: A Journal of Human Behavior, 15(1), 27-33.

Herman, K. C., Wang, K., Trotter, R., Reinke, W. M., & Ialongo, N. (2013).

Developmental trajectories of maladaptive perfectionism among African

American adolescents. Child Development, 84(5), 1633-1650.

https://doi.org/10.1111/cdev.12078

Hewitt, P L., Blasberg, J. S., Flett, G. L., Besser, A., Sherry, S. B., Caelian, C., … &

Birch, S. (2011). Perfectionistic self-presentation in children and adolescents:

Development and validation of the Perfectionistic Self-Presentation Scale-

Junior Form. Psychological assessment, 23(1), 125-142.

https://doi.org/10.1037/a0021147

145

Hewitt, P. L., & Flett, G. L. (1990). Perfectionism and depression: A

multidimensional analysis. Journal of social behavior and personality, 5(5),

423.

Hewitt, P. L., & Flett, G. L. (1991). Dimensions of perfectionism in unipolar

depression. Journal of abnormal psychology, 100(1), 98.

https://doi.org/10.1037/0021-843X.100.1.98

Hewitt, P. L., & Flett, G. L. (1991). Perfectionism in the self and social contexts:

conceptualization, assessment, and association with psychopathology.

Journal of personality and social psychology, 60(3), 456.

https://doi.org/10.1037/0022-3514.60.3.456

Hewitt, P. L., & Flett, G. L. (2004). Multidimensional Perfectionism Scale (MPS-

HF): Technical manual. Toronto, Ontario, Canada: Multi-Health Systems.

Hewitt, P. L., Habke, A. M., Lee-Baggley, D. L., Sherry, S. B., & Flett, G. L. (2008).

The impact of perfectionistic self-presentation on the cognitive, affective, and

physiological experience of a clinical interview. Psychiatry: Interpersonal

and Biological Processes, 71(2), 93-122.

https://doi.org/10.1521/psyc.2008.71.2.93

Hewitt, P. L., Flett, G. L., Turnbull-Donovan, W., & Mikail, S. F. (1991). The

Multidimensional Perfectionism Scale: Reliability, validity, and

psychometric properties in psychiatric samples. Psychological Assessment: A

Journal of Consulting and Clinical Psychology, 3(3), 464.

https://doi.org/10.1037/1040-3590.3.3.464

Hill, A. (Ed.). (2016). The psychology of perfectionism in sport, dance and exercise.

England: Routledge. https://doi.org/10.4324/9781315661100

146

Hill, A. P., & Curran, T. (2016). Multidimensional Perfectionism and Burnout: A

Meta-Analysis. Personality and Social Psychology Review, 20(3), 269-288.

https://doi.org/10.1177/1088868315596286

Hill, R. W., Huelsman, T. J., & Araujo, G. (2010). Perfectionistic concerns suppress

associations between perfectionistic strivings and positive life outcomes.

Personality and Individual Differences, 48(5), 584-589.

https://doi.org/10.1016/j.paid.2009.12.011

Hill, R. W., Huelsman, T. J., Furr, R. M., Kibler, J., Vicente, B. B., & Kennedy, C.

(2004). A new measure of perfectionism: The Perfectionism Inventory.

Journal of personality assessment, 82(1), 80-91.

https://doi.org/10.1207/s15327752jpa8201_13

Hollender, M. H. (1965). Perfectionism. Comprehensive psychiatry, 6(2), 94-103.

https://doi.org/10.1016/S0010-440X(65)80016-5

Hutchinson, A. J., & Yates, G. C. (2008). Maternal goal factors in adaptive and

maladaptive childhood perfectionism. Educational Psychology, 28(7), 795-

808. https://doi.org/10.1080/01443410802320402

Jager, J., Putnick, D. L., & Bornstein, M. H. (2017). II. More than just convenient:

The scientific merits of homogenous convenience samples. Monographs of

the society for research in child development, 82(2), 13-30.

https://doi.org/10.1111/mono.12296

Johnson, D. P., & Slaney, R. B. (1996). Perfectionism: Scale development and a

study of perfectionistic clients in counseling. Journal of College Student

Development, 37(1), 29-41.

147

Kawamura, K. Y., Frost, R. O., & Harmatz, M. G. (2002). The relationship of

perceived parenting styles to perfectionism. Personality and Individual

Differences, 32(2), 317-327. https://doi.org/10.1016/S0191-8869(01)00026-5

Kawamura, K. Y., Hunt, S. L., Frost, R. O., & DiBartolo, P. M. (2001).

Perfectionism, anxiety, and depression: Are the relationships independent?.

Cognitive Therapy and Research, 25(3), 291-301.

https://doi.org/10.1023/A:1010736529013

Kennedy, C. (2001). Comprehensive Measure of Perfectionism: A thesis,

Appalachian State University, Boone, NC

Kmet, L. M., Lee, R. C., & Cook, L. S. (2004). Standard Quality Assessment

Criteria for Evaluating Primary Research Papers from a Variety of Fields.

Alberta, Canada: Alberta Heritage Foundation for Medical Research.

Lloyd, S., Schmidt, U., Khondoker, M., & Tchanturia, K. (2015). Can psychological

interventions reduce perfectionism? A systematic review and meta-analysis.

Behavioural and cognitive psychotherapy, 43(6), 705-731.

https://doi.org/10.1017/S1352465814000162

Lo, A., & Abbott, M. J. (2013). Review of the Theoretical, Empirical, and Clinical

Status of Adaptive and Maladaptive Perfectionism. Behaviour Change, 30(2),

96-116. https://doi.org/10.1017/bec.2013.9

Markus, H. R., & Kitayama, S. (2010). Cultures and selves: A cycle of mutual

constitution. Perspectives on psychological science, 5(4), 420-430.

https://doi.org/10.1177/1745691610375557

McArdle, S., & Duda, J. L. (2008). Exploring the Etiology of Perfectionism and

Perceptions of Self‐worth in Young Athletes. Social Development, 17(4),

980-997. https://doi.org/10.1111/j.1467-9507.2007.00456.x

148

McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemica medica,

22(3), 276-282. https://doi.org/10.11613/BM.2012.031

McVey, G. L., Pepler, D., Davis, R., Flett, G. L., & Abdolell, M. (2002). Risk and

protective factors associated with disordered eating during early adolescence.

The Journal of Early Adolescence, 22(1), 75-95.

https://doi.org/10.1177/0272431602022001004

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. The PRISMA Group (2009)

Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The

PRISMA Statement. PLoS Medicine 6(7): e1000097.

https://doi.org/10.1371/journal.pmed.1000097

Molnar, D. S., Flett, G. L., Sadava, S. W., & Colautti, J. (2012). Perfectionism and

health functioning in women with fibromyalgia. Journal of Psychosomatic

Research, 73(4), 295-300. https://doi.org/10.1016/j.jpsychores.2012.08.001

Nilsson, J. E., Paul, B. D., Lupini, L. N., & Tatem, B. (1999). Cultural differences in

perfectionism: A comparison of African American and White college

students. Journal of College Student Development, 40(2), 141-150.

Nilsson, K., Sundbom, E., & Hägglöf, B. (2008). A longitudinal study of

perfectionism in adolescent onset anorexia nervosa‐restricting type.

European Eating Disorders Review: The Professional Journal of the Eating

Disorders Association, 16(5), 386-394. https://doi.org/10.1002/erv.850

O'Connor, R. C., & Sheehy, N. P. (2001). Suicidal behaviour. The Psychologist,

14(1), 20-24. Retrieved from:

https://thepsychologist.bps.org.uk/volume-14/edition-1/suicidal-behaviour-0

149

O'Connor, R. C., Rasmussen, S., Miles, J., & Hawton, K. (2009). Self-harm in

adolescents: self-report survey in schools in Scotland. The British Journal of

Psychiatry, 194(1), 68-72. https://doi.org/10.1192/bjp.bp.107.047704

O'Connor, R.C., Dixon, D. & Rasmussen, S. (2009) The structure and temporal

stability of the Child and Adolescent Perfectionism Scale. Psychological

Assessment, 21 (3). pp. 437-443. ISSN 1040-3590 ,

http://dx.doi.org/10.1037/a0016264

Parker, W. D. (2000). Healthy perfectionism in the gifted. Journal of Secondary

Gifted Education, 11(4), 173-182. https://doi.org/10.4219/jsge-2000-632

Peterson, J. S. (2002). An argument for proactive attention to affective concerns of

gifted adolescents. Journal of Secondary Gifted Education, 14(2), 62-70.

https://doi.org/10.4219/jsge-2003-419

Pettit, G. S., Laird, R. D., Dodge, K. A., Bates, J. E., & Criss, M. M. (2001).

Antecedents and behavior‐problem outcomes of parental monitoring and

psychological control in early adolescence. Child development, 72(2), 583-

598. https://doi.org/10.1111/1467-8624.00298

Randall, E. T., Smith, K. R., Kronman, C. A., Conroy, C., Smith, A. M., & Simons,

L. E. (2018). Feeling the Pressure to be Perfect: Effect on Pain-Related

Distress and Dysfunction in Youth With Chronic Pain. The Journal of Pain,

19(4), 418-429. https://doi.org/10.1016/j.jpain.2017.11.012

Rhéaume, J., Freeston, M. H., Dugas, M. J., Letarte, H., & Ladouceur, R. (1995).

Perfectionism, responsibility and obsessive-compulsive symptoms.

Behaviour Research and Therapy, 33(7), 785-794.

https://doi.org/10.1016/0005-7967(95)00017-R

150

Rheaume, J., Freeston, M. H., Ladouceur, R., Bouchard, C., Gallant, L., Talbot, F.,

& Vallieres, A. (2000). Functional and dysfunctional perfectionists: are they

different on compulsive-like behaviours? Behaviour Research and Therapy,

38(2), 119-128. https://doi.org/10.1016/S0005-7967(98)00203-4

Rhéaume, J., Ladouceur, R., Freeston, M. H., & Letarte, H. (1995). Inflated

responsibility in obsessive compulsive disorder: Validation of an operational

definition. Behaviour Research and Therapy, 33(2), 159-169.

https://doi.org/10.1016/0005-7967(94)E0021-A

Rhéaume, J., Ladouceur, R., & Freeston, M. H. (2000). The prediction of obsessive–

compulsive tendencies: Does perfectionism play a significant role?.

Personality and Individual Differences, 28(3), 583-592.

https://doi.org/10.1016/S0191-8869(99)00121-X

Rice, K. G., & Aldea, M. A. (2006). State dependence and trait stability of

perfectionism: A short-term longitudinal study. Journal of Counseling

Psychology, 53(2), 205. https://doi.org/10.1037/0022-0167.53.2.205

Rice, K. G., Ashby, J. S., & Slaney, R. B. (2007). Perfectionism and the five-factor

model of personality. Assessment, 14(4), 385-398.

https://doi.org/10.1177/1073191107303217

Rice, K. G., Choi, C. C., Zhang, Y., Morero, Y. I., & Anderson, D. (2012). Self-

critical perfectionism, acculturative stress, and depression among

international students. The Counseling Psychologist, 40(4), 575-600.

https://doi.org/10.1177/0011000011427061

Rice, K. G., Leever, B. A., Christopher, J., & Porter, J. D. (2006). Perfectionism,

stress, and social (dis) connection: A short-term study of hopelessness,

depression, and academic adjustment among honors students. Journal of

151

Counseling Psychology, 53(4), 524. https://doi.org/10.1037/0022-

0167.53.4.524

Rice, K. G., Richardson, C. M., & Tueller, S. (2014). The short form of the revised

almost perfect scale. Journal of personality assessment, 96(3), 368-379.

https://doi.org/10.1080/00223891.2013.838172

Rice, K. G., & Stuart, J. (2010). Differentiating adaptive and maladaptive

perfectionism on the MMPI–2 and MIPS Revised. Journal of Personality

Assessment, 92(2), 158-167. https://doi.org/10.1080/00223890903510407

Rice, K. G., Tucker, C. M., & Desmond, F. F. (2008). Perfectionism and depression

among low-income chronically ill African American and white adolescents

and their maternal parent. Journal of Clinical Psychology in Medical

Settings, 15(3), 171-181. https://doi.org/10.1007/s10880-008-9119-6

Roxborough, H. M., Hewitt, P. L., Kaldas, J., Flett, G. L., Caelian, C. M., Sherry, S.,

& Sherry, D. L. (2012). Perfectionistic self‐presentation, socially prescribed

perfectionism, and Suicide in Youth: A Test of the Perfectionism Social

Disconnection Model. Suicide and Life‐Threatening Behavior, 42(2), 217-

233. https://doi.org/10.1111/j.1943-278X.2012.00084.x

Shafran, R., & Mansell, W. (2001). Perfectionism and psychopathology: A review of

research and treatment. Clinical Psychology Review, 21(6), 879-906.

https://doi.org/10.1016/S0272-7358(00)00072-6

Shahar, G., Blatt, S. J., Zuroff, D. C., Krupnick, J. L., & Sotsky, S. M. (2004).

Perfectionism impedes social relations and response to brief treatment for

depression. Journal of Social and Clinical Psychology, 23(2), 140-154.

https://doi.org/10.1521/jscp.23.2.140.31017

152

Sherry, S. B., Mackinnon, S. P., Macneil, M. A., & Fitzpatrick, S. (2013).

Discrepancies confer vulnerability to depressive symptoms: A three-wave

longitudinal study. Journal of Counseling Psychology, 60(1), 112.

https://doi.org/10.1037/a0030439

Sironic, A., & Reeve, R. A. (2012). More evidence for four perfectionism subgroups.

Personality and Individual Differences, 53(4), 437-442.

https://doi.org/10.1016/j.paid.2012.04.003

Slaney, R. B., Ashby, J. S., & Trippi, J. (1995). Perfectionism: Its measurement and

career relevance. Journal of Career Assessment, 3(3), 279-297.

https://doi.org/10.1177/106907279500300303

Slaney, R., & Johnson, D. G. (1992). The Almost Perfect Scale. Unpublished

manuscript, Pennsylvania State University.

Slaney, R., Rice, K, G., Mobley, M., Trippi, J., & Ashby, J. (2001). The Revised

Almost Perfect Scale. Measurement and Evaluation in Counseling and

Development, 34(3), 130-145.

Smith, M. M., Sherry, S. B., Gautreau, C. M., Mushquash, A. R., Saklofske, D. H.,

& Snow, S. L. (2017a). The intergenerational transmission of perfectionism:

Fathers’ other-oriented perfectionism and daughters’ perceived psychological

control uniquely predict daughters’ self-critical and personal standards

perfectionism. Personality and Individual Differences, 119, 242-248.

http://dx.doi.org/10.1016/j.paid.2017.07.030

Smith, M. M., Sherry, S. B., Mushquash, A. R., Saklofske, D. H., Gautreau, C. M.,

& Nealis, L. J. (2017b). Perfectionism erodes social self-esteem and

generates depressive symptoms: Studying mother-daughter dyads using a

153

daily diary design with longitudinal follow-up. Journal of Research in

Personality, 71, 72-79. https://doi.org/10.1016/j.jrp.2017.10.001

Smith, M. M., Sherry, S. B., Glowacka, M., Speth, T. A., Stewart, S. H., Saklofske,

D. H., & Etherson, M. E. (2019). Who is the most demanding of them all? A

multisource investigation of other-oriented perfectionism, socially prescribed

perfectionism, and depressive symptoms. Personality and Individual

Differences, 138, 328-332. https://doi.org/10.1016/j.paid.2018.09.023

Soenens, B., Elliot, A. J., Goossens, L., Vansteenkiste, M., Luyten, P., & Duriez, B.

(2005a). The intergenerational transmission of perfectionism: parents'

psychological control as an intervening variable. Journal of family

psychology, 19(3), 358. https://doi.org/10.1037/0893-3200.19.3.358

Soenens, B., Luyckx, K., Vansteenkiste, M., Luyten, P., Duriez, B., & Goossens, L.

(2008). Maladaptive perfectionism as an intervening variable between

psychological control and adolescent depressive symptoms: a three-wave

longitudinal study. Journal of Family Psychology, 22(3), 465.

https://doi.org/10.1037/0893-3200.22.3.465

Soenens, B., Vansteenkiste, M., Luyten, P., Duriez, B., & Goossens, L. (2005b).

Maladaptive perfectionistic self-representations: The mediational link

between psychological control and adjustment. Personality and Individual

Differences, 38(2), 487-498. https://doi.org/10.1016/j.paid.2004.05.008

Stöber, J. (1998). The Frost Multidimensional Perfectionism Scale revisited: More

perfect with four (instead of six) dimensions. Personality and individual

differences, 24(4), 481-491. https://doi.org/10.1016/S0191-8869(97)00207-9

154

Stoeber, J. (2018). Comparing Two Short Forms of the Hewitt-Flett

Multidimensional Perfectionism Scale. Assessment, 25(5), 578-588.

https://doi.org/10.1177/1073191116659740

Stoeber, J., & Otto, K. (2006). Positive conceptions of perfectionism: Approaches,

evidence, challenges. Personality and social psychology review, 10(4), 295-

319. https://doi.org/10.1207/s15327957pspr1004_2

Stoeber, J., Otto, K., & Dalbert, C. (2009). Perfectionism and the Big Five:

Conscientiousness predicts longitudinal increases in self-oriented

perfectionism. Personality and Individual Differences, 47(4), 363-368.

https://doi.org/10.1016/j.paid.2009.04.004

Travers, L. V., Randall, E. T., Bryant, F. B., Conley, C. S., & Bohnert, A. M. (2015).

The cost of perfection with apparent ease: Theoretical foundations and

development of the Effortless Perfectionism Scale. Psychological

assessment, 27(4), 1147. https://doi.org/10.1037/pas0000109

Trull, T. J., & Durrett, C. (2005). Categorical and Dimensional Models of

Personality Disorder. Annual Review of Clinical Psychology, 1, 355-380.

https://doi.org/10.1146/annurev.clinpsy.1.102803.144009

Van Gastel, W., Legerstee, J. S., & Ferdinand, R. F. (2009). The role of perceived

parenting in familial aggregation of anxiety disorders in children. Journal of

anxiety disorders, 23(1), 46-53. https://doi.org/10.1016/j.janxdis.2008.03.014

Vieth, A. Z., & Trull, T. J. (1999). Family patterns of perfectionism: An examination

of college students and their parents. Journal of personality assessment,

72(1), 49-67. https://doi.org/10.1207/s15327752jpa7201_3

Wang, K. T., Yuen, M., & Slaney, R. B. (2009). Perfectionism, depression,

loneliness, and life satisfaction: A study of high school students in Hong

155

Kong. The counseling psychologist, 37(2), 249-274.

https://doi.org/10.1177/0011000008315975

Werner, E. E. (2000). Protective factors and individual resilience. In Shonkoff, J. P.,

& Meisels, S. J. (Eds.), Handbook of early childhood intervention (pp. 115-

132). New York: Cambridge University Press.

https://doi.org/10.1017/CBO9780511529320.008

Yang, K. S. (1997). Theories and research in Chinese personality: An indigenous

approach. In H. S. Kao & D. Sinha (Eds.), Asian perspectives on psychology

(pp. 236-262). New Delhi, India: Sage.

Yee, C. (2003, September 23). Committee unveils Women’s Initiative report. The

Chronicle. Retrieved from

https://www.dukechronicle.com/article/2003/09/committee-unveils-womens-

initiative-report

Yeh, C. J., & Hwang, M. Y. (1999). The sociocultural context of Asian Pacific

American ethnic identity and self: Implications for counseling. In D. S.

Sandhu (Ed.), Asian and Pacific Islander Americans: Issues and concerns for

counseling and psychotherapy (pp. 59-69). New York: Nova Sciences.

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Appendix

A. Quality Appraisal Tool

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Appendix A: Quality Appraisal Tool

Literature Review Quality Appraisal Tool

Adapted from Downs, S. H., & Black, N. (1998). The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. Journal of Epidemiology & Community Health, 52(6), 377-384.And Kmet, L. M., Cook, L. S., & Lee, R. C. (2004). Standard quality assessment criteria for evaluating primary research papers from a variety of fields.

Criteria Yes

1

No

0

Unable to determine

01 Is the hypothesis or objective of the study clearly

described?2 Is the research design evident and appropriate to

answer study question? Design is easily identified and is appropriate to address the study question/objective

3 Are the main outcomes to be measured clearly described in the Introduction or Methods section? If the main outcomes are first mentioned in the Results section, the question should be answered no.

4 Is the method of subject selection described and appropriate? Selection strategy designed to obtain an unbiased sample of the relevant target population or the entire population of interest. Where applicable, inclusion/exclusion criteria are described and defined. Studies of volunteers: methods and setting of recruitment reported. Surveys: sampling frame/ strategy clearly described and appropriate.

5 Are the subject characteristics clearly described? Sufficient relevant baseline/ demographic e.g. age/sex information clearly characterizing the participant is provided (or reference to previously published baseline data is reported).

6 Are the main findings of the study clearly described? Simple outcome data (including denominators and numerators) should be reported for all major findings so that the reader can check the major analyses and conclusions. (This question does not cover statistical tests which are considered below).

7 Were the statistical tests used to assess the main outcomes appropriate? The statistical techniques used must be appropriate to the data. For example nonparametric methods should be used for small sample sizes. Where little statistical analysis has been undertaken but where there is no evidence of bias, the question should be answered yes. If the distribution of the data (normal or not) is not described it must be

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assumed that the estimates used were appropriate and the question should be answered yes.

8 Were the main outcome measures used accurate (valid and reliable)? For studies where the outcome measures are clearly described, the question should be answered yes. For studies which refer to other work or that demonstrates the outcome measures are accurate, the question should be answered as yes.

9 Did the study have sufficient power to detect a clinically important effect where the probability value for a difference being due to chance is less than 5%? Sample sizes have been calculated to detect a difference of x% and y%.

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Part III: Summary of Clinical Experience

Year One: Adult Placement (1 year)

In the first year of clinical training I was on a split placement, working in both a community

service supporting individuals diagnosed with Chronic Fatigue Syndrome/ Myalgic

Encephalomyelitis (CFS/ME) and a Community Neurorehabilitation Service.

My role in the CFS/ME service involved providing psychological assessment and

intervention using an integrative approach based on current NICE Guidance. Assessment and

formulation drew on both Bio-Psycho-Social and CBT models to design time-limited,

patient-centred psychological interventions using approaches such as CBT and ACT.

Psychological interventions aimed to support people with a diagnosis of CFS/ME to manage

symptoms of the condition to improve function, symptom severity and quality of life through

skills development, such as lifestyle management strategies.

Psychological assessment and intervention also aimed to support individuals living with

multiple co-morbid physical and mental health difficulties such as trauma, anxiety and

depression. Interventions were delivered through one-to-one sessions and psychoeducational/

lifestyle management groups with individuals as well as carers and/or family members.

My role allowed me to work as part of a multi-disciplinary team made up of a psychiatrist,

psychologists, clinical nurse specialists and a physiotherapist. I routinely worked jointly/

alongside other health professionals in both one-to-one and group settings as well as with

other organisations, both statutory and voluntary.

In addition to clinical responsibilities, during my placement I evaluated the efficacy of a

group intervention in fulfilment of the Service Related Project assignment. I also delivered

teaching to the team on working with individuals with a diagnosis of personality disorder.

My role in the Community Neurorehabilitation Team involved providing Assessment and

Intervention for individuals following a brain injury, most commonly stroke. Assessment

included Neuropsychological assessment to determine the impact of brain injury on cognitive

functioning. Psychological intervention included supporting individuals and their carers/

family with difficulties such as emotional adjustment, mood disorders and behavioural issues.

My role in the team involved working jointly with other practitioners including Occupational

Therapists, Physiotherapists and Specialist Nurses.

Year Two: Intellectual Disabilities Placement (6 months)

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My second placement involved working with Adults diagnosed with Intellectual Disabilities.

During this placement I provided one to one psychology therapy, which was adapted to make

it more accessible and person-centred. I used a range of interventions including CBT, positive

behavioural support (PBS) and Acceptance and Commitment Therapy (ACT). Whilst on this

placement I drew heavily on Systemic models and attachment theory to inform my practice

when working with systems around an individual including schools, care-home staff and

families. This involved sharing psychological formulations and recommendations in both

MDT and network meetings to support clients and their families. I also worked to support the

team in managing complex cases, often involving issues of capacity and risk management

and was involved in an assessment of capacity to consent to sexual relationships. Another

part of my role was also to provide neuropsychological assessments as part of the assessment

for a formal diagnosis of intellectual disability. I also delivered training at a local day centre

for staff and service users on anxiety and self-care strategies.

Year Two: Children and Young People Placement (6 months)

My child placement was split between a specialist Child and Adolescent Mental Health Team

(CAMHS) and another specialist Child and Adolescent Mental Health Team for Children

with Learning Disabilities (CAMHS LD). My main role in both services was to provide

assessment, formulation and psychological intervention to young people with mental health

difficulties. In the mainstream CAMHS service, I worked with children and young people

with a range of difficulties including trauma, anxiety, depression and behavioural difficulties.

I used a range of psychological approaches in my work including CBT, Trauma-focused

CBT, ACT and mindfulness, drawing heavily on Systemic and Attachment theories to inform

assessment and formulation. During this placement, I also worked in the Family Therapy

Team, providing systemic family therapy as part of a wider reflective team. I worked with

families of children and young people referred to CAMHS using systemic and narrative

approaches to facilitate communication and understanding.

In the CAMHS LD Team I worked as part of an MDT to support children with learning

disabilities experiencing emotional or behavioural difficulties. My role involved working

directly with children in addition to providing support to families and the systems around

them using systemic and PBS approaches.

In both services, I completed cognitive assessments using the Wechsler Intelligence Scale for

Children (WISC) and also had the opportunity to observe assessments for ADHD and Autism

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Spectrum Disorder. I provided training on Trauma with my supervisor to staff new to

working in CAMHS.

Year Three: Older Adults Placement (6 months)

On my older adult placement I was split between a memory assessment service and an older

adult community mental health team, which included working one day a week in a

psychology service based in a general medical setting. In the memory assessment service, I

was responsible for completing assessments for dementia using a battery approach to

neuropsychological tests, observations and clinical interviews.

I also delivered one to one psychological assessment, formulation and intervention with

clients presenting with a range of difficulties including mood disorders, chronic health

conditions, fear of falling and adjustment to dementia diagnosis using an integrative

approach, drawing on CBT, systemic, ACT and mindfulness techniques. I co-facilitated

various workshops and group sessions during the placement on issues such as managing

challenging behaviours in dementia, self-care for carers and managing anxiety and

depression.

5. Specialist Placement in Adult Community Neurorehabilitation (6 months)

My final specialist placement was based in a Community Clinical Neuropsychology

Rehabilitation Service. Here, I worked with adults with brain injuries and their

carers/families. My main role was to provide assessment, formulation and intervention for

people who had experienced a brain injury. The main approach I used on the placement was

neuropsychological, in combination with CBT, ACT and systemic models. My work on this

placement was extremely varied and included assessing the impact of brain injury on

cognitive function and supporting clients and their families/carers with adjustment to brain

injury, cognitive and behavioural rehabilitation, mood disorders and skills development. I

used systemic approaches to work directly and with couples/ families to help people with

challenges to adjustment including; understanding the nature and impact of a brain injury,

communicating with and meeting the person’s needs, coping with change and feelings of

loss, developing support networks and connecting with services in the community, and

psychological difficulties including depression and low mood.

I delivered training to the MDT on BPS Guidance on capacity to consent to sexual relations

and was also involved in developing several business cases with my supervisor. I also took

the lead on developing a paperless proforma for the service in line with national guidance.

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Part IV: Summary of Assessments

Year 1 Assessments

Assessment Title

WAIS WAIS Interpretation (online assessment)

Practice Report of Clinical Activity A Report of Clinical Assessment and

Formulation with a White British Male in

his 20’s Experiencing Anxiety Following

Diagnosis of Chronic Fatigue Syndrome.

Audio Recording of Clinical Activity with

Critical Appraisal

A Critical Appraisal of an Audio recorded

session with a patient struggling to cope

with Chronic Fatigue Syndrome.

Report of Clinical Activity N=1 Report of Clinical Activity using Cognitive

Behavioural Therapy with a White British

Male in his mid-forties diagnosed with

Chronic Fatigue Syndrome/ Myalgic

Encephalomyelitis (CFS/ME) experiencing

anxiety and depression.

Major Research Project Literature Survey What are the factors influencing how

parents and children respond to failure?: A

literature survey

Major Research Project Proposal Gender and Shame in Response to Task

Failure.

Service-Related Project Evaluating the effects of change in the

content and format of a Lifestyle

Management Group on standardized

outcome measures of Chronic Fatigue

Syndrome / Myalgic Encephalomyelitis.

Year II Assessments

Assessment Title

Report of Clinical Activity A systemically informed assessment of

hoarding with a white British man in his

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early fifties diagnosed with an Intellectual

Disability.

PPD Process Account A Reflective Account of a Trainee Clinical

Psychologist’s experience of a Personal and

Professional Development (PPD) Group.

Presentation of Clinical Activity Assessment and Intervention with a young

woman diagnosed with an Intellectual

Disability and Autistic Spectrum Condition

using an Integrative Approach.

Year III Assessments

Assessment Title

Major Research Project Literature Review Parent-Child Perfectionism: A Systematic

Literature Review

Major Research Project Empirical Paper The relationship between gender attitudes

and children’s feelings of shame in response

to imagined failure.

Report of Clinical Activity-Formal

Assessment

A neuropsychological assessment for

possible dementia with Ben, a 69-year-old

male.

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