ArticlePDF AvailableLiterature Review

Resilience to emotional distress in response to failure, error or mistakes: A systematic review

November 2016
Clinical Psychology Review 52

DOI:10.1016/j.cpr.2016.11.007

Authors:

Judith Johnson

University of Manchester

Maria Panagioti

The University of Manchester

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Perceptions of failure have been implicated in a range of psychological disorders, and even a single experience of failure can heighten anxiety and depression. However, not all individuals experience significant emotional distress following failure, indicating the presence of resilience. The current systematic review synthesised studies investigating resilience factors to emotional distress resulting from the experience of failure. For the definition of resilience we used the Bi-Dimensional Framework for resilience research (BDF) which suggests that resilience factors are those which buffer the impact of risk factors, and outlines criteria a variable should meet in order to be considered as conferring resilience. Studies were identified through electronic searches of PsycINFO, MEDLINE, EMBASE and Web of Knowledge. Forty-six relevant studies reported in 38 papers met the inclusion criteria. These provided evidence of the presence of factors which confer resilience to emotional distress in response to failure. The strongest support was found for the factors of higher self-esteem, more positive attributional style, and lower socially-prescribed perfectionism. Weaker evidence was found for the factors of lower trait reappraisal, lower self-oriented perfectionism and higher emotional intelligence. The majority of studies used experimental or longitudinal designs. These results identify specific factors which should be targeted by resilience-building interventions.

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RUNNING HEAD: Resilience to emotional distress in response to failure

Resilience to emotional distress in response to failure, error or mistakes: A systematic

review

Published in Clinical Psychology Review

Accepted November 2016

Judith Johnson*ab, Maria Panagiotic, Jennifer Bassa1, Lauren Ramseya2, and Reema Harrisond3

*Corresponding author; j.johnson@leeds.ac.uk; Tel: +44 (0)113 3435724; Fax: +44 (0)113

3435749

a. School of Psychology, University of Leeds, Leeds, LS29JT, UK

b. Bradford Institute of Health Research, Bradford Royal Infirmary, Bradford, BD9 6RJ, UK

c. NIHR School for Primary Care Research and Manchester Academic Health Science

Centre, University of Manchester, Manchester, M13 9PL, UK;

maria.panagioti@manchester.ac.uk

d. School of Public Health, University of Sydney, Sydney 2006, Australia

1. Present address: Cardiology Department, E floor, Jubilee Wing, Leeds General Infirmary,

Leeds, LS1 3EX; jenniferbass@nhs.net

2. Present address: Inhealthcare, 58 Netherwood Avenue, Castleford, WF10 2QW, UK;

lauren.ramsey@inhealthcare.co.uk

3. Present address: School of Public Health & Community Medicine, Samuels Building,

University of New South Wales, Sydney 2052, Australia; reema.harrison@unsw.edu.au

Resilience to emotional distress in response to failure, error or mistakes: A

systematic review

Judith Johnson, Maria Panagioti, Jennifer Bass, Lauren Ramsey, Reema Harrison

Abstract

Perceptions of failure have been implicated in a range of psychological disorders,

and even a single experience of failure can heighten anxiety and depression. However, not

all individuals experience significant emotional distress following failure, indicating the

presence of resilience. The current systematic review synthesised studies investigating

resilience factors to emotional distress resulting from the experience of failure. For the

definition of resilience we used the Bi-Dimensional Framework for resilience research (BDF)

which suggests that resilience factors are those which buffer the impact of risk factors, and

outlines criteria a variable should meet in order to be considered as conferring resilience.

Studies were identified through electronic searches of PsycINFO, MEDLINE, EMBASE and

Web of Knowledge. Forty-six relevant studies reported in 38 papers met the inclusion

criteria. These provided evidence of the presence of factors which confer resilience to

emotional distress in response to failure. The strongest support was found for the factors of

higher self-esteem, more positive attributional style, and lower socially-prescribed

perfectionism. Weaker evidence was found for the factors of lower trait reappraisal, lower

self-oriented perfectionism and higher emotional intelligence. The majority of studies used

experimental or longitudinal designs. These results identify specific factors which should be

targeted by resilience-building interventions.

Resilience; failure; stress; self-esteem; attributional style; perfectionism

Introduction

Impact of failure experiences

A large body of research suggests that experiencing failure has marked emotional

and psychological consequences across a range of individuals and settings. Longitudinal

studies indicate that academic failure in adolescents increases risk for clinical depression in

adulthood (McCarty et al., 2008; Reinherz, Giaconia, Hauf, Wasserman, & Silverman, 1999),

and in those who are depressed, perceived failure has been associated with suicide

attempts (Bulik, Carpenter, Kupfer, & Frank, 1990). Even a single experience of failure in

non-clinical groups can have significant emotional sequelae. In athletes, match failure has

been linked with elevated feelings of depression, humiliation and guilt (Jones & Sheffield,

2007; Wilson & Kerr, 1999), and in healthcare professionals, involvement in medical errors

or patient safety failures is reported to result in feelings of shame, depression and anxiety,

which can then increase the risk of further errors (Sirriyeh, Lawton, Gardner, & Armitage,

2010; West, Tan, Habermann, Sloan, & Shanafelt, 2009). The reliable impact of failure

experiences on mood makes false failure feedback tasks suitable for use as negative mood

inductions in experimental settings (Nummenmaa & Niemi, 2004). Studies employing these

tasks have found that manipulated failure feedback consistently increases feelings of

sadness, defeat and frustration (Johnson, Gooding, Wood, Taylor, & Tarrier, 2011a;

Johnson, Tarrier, & Gooding, 2008b; Nummenmaa & Niemi, 2004) and may have a

detrimental impact upon cognitive functioning such as reducing the accuracy of memory

recall (Johnson et al., 2008b).

However, not all individuals experience significant emotional distress in response to

failure, and several psychological models highlight the role of psychological responses to

failure in the development of failure-related distress and emotional disorder. For example,

cognitive models of suicide have emphasised the role of situation appraisals, suggesting that

suicidal thoughts occur when individuals appraise their circumstances in terms of failure

(termed ‘defeat’) and entrapment (Johnson, Gooding, & Tarrier, 2008a; Williams, 1997). Yet

such models have been criticised for their acceptance of an overly negative, disorder-based

approach to understanding mental health (Johnson & Wood, 2016). By focusing on the

development of mental health problems rather than mental wellbeing, it has been suggested

that such approaches fail to identify and capitalise on natural coping mechanisms (Johnson

& Wood, 2016). As such, they may be missing potential points for psychological

interventions to target and develop.

Resilience-based approaches

An alternative to these models are resilience-based approaches (Bonanno, 2004;

Masten, 2001; Masten & Powell, 2003). These aim to understand the factors that enable

individuals to withstand stressors and avoid psychological distress rather than focusing on

the mechanisms that lead to distress and disorder. Resilience-based approaches have the

potential to highlight skills and tendencies that individuals can develop to maintain

psychological health, leading to a more positively oriented approach to wellbeing. However,

this body of literature has suffered from two main limitations.

First, there has been a lack of clarity concerning the criteria for identifying a ‘resilient’

outcome. The common definition of resilience as factors which reduce negative outcomes in

the face of adversity would suggest that resilience variables are those which moderate or

attenuate the association between risk factors and negative outcomes. In contrast, many

studies of resilience have used a correlational approach. These studies have assumed that

resilience variables are those which are ‘positive’, and have investigated whether high levels

of a proposed resilience variable (e.g., high perceived social support) is directly associated

with lower levels of a negative outcome (e.g., suicidal thoughts). However, as has been

highlighted elsewhere (Johnson & Wood, 2016; Johnson, Wood, Gooding, Taylor, & Tarrier,

2011b), every negative variable exists on a continuum with its positive inverse. Returning to

the above example, using this approach, it could just as easily be suggested that low

perceived social support is a risk factor for suicidal thoughts.

Second, this research failed to lead the field towards more nuanced understandings

of resilience. A common approach has been to propose a concept of resilience, develop a

questionnaire to measure this, and to investigate the association of this variable in relation to

various outcome variables in different populations. This approach does not enable the

proposed resilience variable itself to evolve in order to accommodate new research findings.

Indeed, despite fifty years of resilience research, key questions regarding the nature of

resilience remain, which may be linked to the limitations of this approach. These concern i)

whether factors which confer resilience vary depending on the outcome under consideration

(i.e., whether resilience to general mental wellbeing is similar to resilience to negative

behavioural outcomes such as suicidality), and ii) whether factors which confer resilience

vary according to the risk factor/adversity individuals are facing.

In line with these broader limitations, despite a large growth of interest in resilience,

and an increasing awareness of the emotional impact of failure experiences, very few

studies have aimed to investigate resilience to emotional distress in response to failure in

particular. Of the two studies we identified which have explicitly focused on this, the first

investigated whether learning orientation buffered state self-esteem in response to a test

result in students, but no significant effect was found (Niiya, Crocker, & Bartmess, 2004).

The second investigated the impact of explanatory style on response to sports failure in

children, using heart rate acceleration as an indicator of emotional arousal (Martin-Krumm,

Sarrazin, Peterson, & Famose, 2003). This suggested that individuals with a pessimistic

explanatory style showed a greater increase in heart rate following failure than individuals

with an optimistic explanatory style. However, all individuals in the study were exposed to

failure, and no analyses investigated whether explanatory style acted as a buffer or

moderator of the association between failure and heart rate response.

Given that failure and failure-related distress have been implicated in the

development of a range of mental health disorders (Bulik et al., 1990; Johnson et al., 2008a;

Reinherz et al., 1999), a fuller and more detailed understanding of resilience in relation to

failure could have important implications for psychological interventions. This knowledge

could be particularly important for groups likely to experience significant failure events in

their occupations, such as health professionals, most of whom will be involved in patient

safety failure and clinical errors during their career (Sirriyeh et al., 2010). It could also be

pertinent for young adults in the education system, which has been criticised for becoming

increasingly assessment focused (Putwain, 2008), with the pressure of failure cited as

contributing to increasing rates of mental health problems in this group (McManus,

Bebbington, Jenkins, & Brugha, 2016).

The Bi-Dimensional Framework for Resilience Research

The Bi-dimensional Framework for investigating resilience (BDF; Johnson, 2016;

Johnson et al., 2014; Johnson et al., 2011b) was proposed to address these criticisms of the

field of resilience research, and to enable the development of evidence-based concepts of

resilience. The BDF outlines clear criteria that a variable should meet in order to be

considered as conferring resilience. In line with common definitions of resilience, it suggests

that resilience factors are those which interact with (or statistically moderate) the likelihood

that risk will lead to negative outcomes (Johnson et al., In press). Individuals who are low on

resilience will show increasing evidence of negative outcomes with increasing risk, but high

resilience individuals will maintain low levels of a given negative outcome, despite risk

exposure (see Figure 1). As such, it purports that any investigation of resilience should

include three variables, i) the risk factor, ii) the resilience factor, and iii) the outcome variable,

and studies directly investigating associations between a predictor variable and an outcome

are insufficient to establish a resilience effect. In line with the observations that all variables

lie on a continuum from positive to negative, the BDF proposes that all factors can be viewed

as ‘bipolar’, and whether they are framed in positive or negative terms is essentially arbitrary

(see Figure 2). As such, unlike previous resilience approaches the emphasis of the BDF is

not upon identifying ‘positive’ factors which are inversely linked with negative outcomes, but

upon identifying psychological factors which can alter the impact of risk.

Figure 1.

Low resilience

e.g. Negative

self-appraisals

Risk High Risk e.g.

Single

Low Risk

e.g. Married

High resilience

e.g. Positive self-

appraisals

Resilience

Figure2.

A particular strength of the framework is that it offers a way to aggregate and review

existing studies based on i) a particular outcome of interest (e.g., emotional/behavioural

outcome), ii) whether a psychological factor has been included, and iii) whether a

psychological factor has been examined as a moderator of a risk factor. Importantly, studies

that meet these criteria may not have self-identified as having investigated ‘resilience’. As

such, although there have been few studies which have explicitly aimed to investigate

resilience to failure, by using the framework, it is possible to define failure experiences as the

risk variable of interest, measures of emotional distress as the outcome variable, and

psychological factors as the potential resilience variable, and to use these terms to search

the literature. This approach offers a systematic route to identifying factors which confer

resilience to emotional distress/dysfunction in response failure. Given the centrality of

emotional distress most mental health disorders, results from this review could have broad

relevance to psychological interventions. The BDF was initially developed to investigate

resilience to suicidality (Johnson, Gooding, Wood, & Tarrier, 2010a; Johnson et al., 2010b),

and underpinned a systematic review in this area. This review suggested that attributional

style, sense of agency and lower perfectionism and hopelessness conferred resilience.

However, risk factors investigated in these studies varied and only two investigated

resilience to failure, neither of which reported on emotional distress/dysfunction as an

outcome, instead focusing on suicidal related thoughts (Priester & Clum, 1992, 1993).

Objectives

We undertook a systematic review and evidence synthesis on resilience to failure

and error, aiming:

To investigate whether there are psychological factors which confer resilience to

emotional distress in response to failure, error and mistakes

To evaluate and compare the evidence for different types of psychological variables

in conferring resilience

Methods

Methods and results are reported in line with the Preferred Reporting Items for

Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher, Liberati, Tetzlaff, &

Altman, 2009).

Protocol and registration

The review was registered with the PROSPERO International prospective register of

systematic reviews, DOI: 10.15124/CRD42015026761. It is available online at

http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42015026761.

Search strategy

Four electronic bibliographic databases were searched (from inception to September

2014, and then updated to April 2016): PsycInfo, Ovid Medline, EmBase and Web of

Knowledge. We searched for papers containing at least one term from each of the following

blocks: (fail* or error* or defeat or mistake*) and (interact* or moderat* or buffer* or amplif*)

and (anxiety or anxious or depression or depressed or emotion* or affect or mood or shame

or guilt or PTSD or trauma or insomnia). A combination of Medical Subject Headings (MESH

terms) and text words were used in our searches (see Supplementary File 1 for the Medline

search strategy). No previous reviews were identified in the area.

Eligibility criteria

Studies were eligible for inclusion if they met the following criteria:

Population: We included studies which were conducted among adults.

Setting: Our focus was not restricted to studies conducted in a particular setting, such

as healthcare or educational settings.

Design

oQuantitative research designs. We included studies with any type of

quantitative research design ranging from experimental studies to

observational studies (cohort and cross-sectional studies).

oWe included studies which examined moderators of the association between

error/failure and emotional distress/dysfunction, or factors which interact with

the experience of error/failure to predict psychological outcome (using

moderated regression or other statistical methods of investigating two-way

interactions).

Outcome measure

oWe included studies which reported data on outcome measures of emotional

distress or dysfunction which could encompass a range of outcomes such as

general positive and negative affect, depression/depressive symptoms,

anxiety and self-esteem (Ridner, 2004).

Resilience variable

oVariables in the moderation/interaction analysis could be regarded as a

potential ‘psychological resilience factor’, i.e., a psychological quality of

individuals, such as a belief, tendency or ability.

oAs the review was interested in naturally occurring resilience, studies where

resilience variables had been manipulated via experimental manipulation

were excluded.

Experience of error or failure

oWe included studies where some or all of the participants experienced error

or failure, either naturally occurring or experimentally manipulated.

Exclusion criteria:

oStudies that were not in the English Language, did not involve human

participants and grey literature studies were excluded.

oStudies which only investigated 3-way interactions were excluded, as the

relationships tested in these studies were very complex.

oAs demographic factors and clinical disorders (including narcissism) are not

considered potential resilience factors by resilience frameworks, studies of

these variables were excluded.

oDue to the complex nature of social interactions, and the range of causes that

can contribute to relationship breakdown, studies of social rejection or

perceived social failure were excluded.

oStudies where participants only imagined failure events were excluded.

Study selection

Initially 20% of the titles/abstracts were screened by three reviewers independently to

reach consensus within the team regarding the study selection criteria (JJ;JB; LR). All the

remaining titles/abstracts were screened independently by two of these reviewers. The full

texts of studies assessed as potentially eligible for the review were then retrieved and

checked against the inclusion and exclusion criteria by two researchers working

independently (JJ and MP or RM). Any disagreements were resolved by discussion.

Data extraction

A data extraction table was devised in Microsoft Excel and initially piloted on five

studies. We extracted the following descriptive data: country, year of publication, participant

characteristics (population, number, mean age, percentage male), research design,

statistical analysis conducted, proposed resilience variable, failure/error type or

manipulation, outcome variable, key results of the interactions (moderation analyses), and

critical appraisal information. Data were extracted by the first author, with any uncertainties

addressed in discussion with the second author.

Risk of bias assessment

The majority of the studies included in the review were experimental studies, with

observational cross-sectional and longitudinal studies also included. As well as

distinguishing between these different designs, we also assessed for the following risk of

bias criteria:

1. Whether measures of the resilience and outcome variables used validated

questionnaires

2. Whether the statistical analysis controlled for confounders (e.g., baseline levels of the

outcome measure/s)

3. Whether response rate or data capture among eligible participants was recorded and

found to be at 70% or greater at baseline

4. Whether response rate was recorded and found to be at 70% or greater at follow-up

(for longitudinal studies only)

5. Whether participants were randomly assigned to conditions (for experimental studies

only)

6. Whether random assignment was based on random sequence generation (for

experimental studies only)

7. Whether use of allocation concealment to conditions was employed (for experimental

studies only).

These criteria were based upon Cochrane risk of bias criteria (Higgins & Green, 2008)

and guidance for the assessment of observational studies (CRD, 2009) . Studies were

assigned a rating of 1 for each criterion met (maximum rating of 4 for cross-sectional

observational studies, 5 for longitudinal studies and 7 for experimental studies).

Data synthesis

Assessment of the strength of the moderating impact of potential resilience variables

between failure and emotional distress through meta-regression would have been desirable

(Schmidt & Hunter, 2014). However, this was not possible due to wide heterogeneity

between studies regarding the measurement of the emotional distress outcome. A narrative

synthesis was therefore undertaken, which integrated review results in a non-quantitative

but connected way (Keeley, Storch, Merlo, & Geffken, 2008; Knopp, Knowles, Bee, Lovell, &

Bower, 2013). Where more than one study had investigated the same proposed resilience

variable, we used a box-score approach. In the box-score approach, the relationship

between moderating variables and outcomes is tabulated in terms of significance and

direction (negative, positive, or no relationship) (Green & Hall, 1984). Studies within each

respective group were tallied and the majority of studies within any specific category was

considered to indicate the likely relationship between the potential resilience variable and the

outcome (Light & Smith, 1971). The advantages of the box-score approach were that it

enabled basic quantification of reported moderator effects and identification of patterns

across collated studies. It also enabled quantification of the relationship between quality of

analyses and reported effects.

Results

Overall, 5071 titles and abstracts were screened for eligibility. Following screening,

38 papers (reporting 46 relevant studies) met the inclusion criteria (see PRISMA flow chart

displayed in Figure 3).

Figure 3.

Characteristics of studies and populations

Included studies had a total of 5905 participants (m sample size = 128.37, SD = 83.8,

range = 46-399). The mean age of participants ranged from 18.6 to 47.6 (data missing for 25

studies), and the majority of studies were amongst undergraduate students, with only one

study conducted in a clinical population (Johnson et al., 2011a). The gender split varied

across studies, but overall participant groups comprised slightly more females (m = 38.6%

male participants, SD = 22.6, data missing for 5 studies). Most studies were experimental

(80.43%), with the remainder using longitudinal (15.22%) and cross-sectional (4.35%)

designs. Studies were from a range of countries, but a large proportion (60.87%) was

conducted in the USA.

Tables 1 and 2 here

Characteristics of resilience, failure and emotional distress variables

A number of potential resilience factors were investigated. The single factor most

frequently studied was self-esteem (see Table 3 for the box-score review), with a total of 15

studies (32.6%) investigating this. Other factors investigated a range of trait coping and

personality constructs, such as attributional style, emotional intelligence, perfectionism and

reappraisal. Resilience factors were measured using validated questionnaires in 40 studies

(87%). Similarly, a range of emotion distress outcome variables were studied, including

depression (n=13, 28.3%), anxiety (n=8, 17.4%), general affect (n=18, 39.1%) and negative

self-relevant emotions (n=9, 19.6%). Thirty studies (62.5%) used validated questionnaires to

measure the outcome variable (or at least one outcome variable, where more than one was

investigated), 18 (60%) of which reported significant results. Of these, nine studies used

validated measures of depressed or anxious mood, such as the Beck Depression Inventory

(Beck, 1967), the State–Trait Anxiety Inventory (Spielberger, Gorsuch, Lushene, Vagg, &

Jacobs, 1983) and the Multiple Affect Adjective Checklist (Zuckerman & Lubin, 1965), and 6

(66%) reported significant results.

In order to study reactions to failure, the majority of studies used an experimental

approach and a false failure paradigm. In these paradigms the task is fixed to be too difficult

to pass, the feedback received by participants is fixed to report failure regardless of

performance, or a combination of both of these are applied. The single most common false

failure task used was the Remote Associates Task (RAT) (Mednick, 1962) or an adapted

version of this (n = 12, 26.1%). In the RAT task, participants guess a target word from three

indicator words which are fixed to be easy or difficult in order to lead to failure or success.

Purported intelligence tests were used to induce failure in six (13%) studies and insoluble

anagram tasks were used in five (10.9%) studies. Of the eight longitudinal studies, seven

investigated reactions to exams or academic grades, and one investigated acceptance or

rejection to university.

Table 3 here

Risk of bias assessment

The results of the risk of bias assessment are displayed in Figure 4. Out of a total

possible score of 7, experimental studies scored between 0 and 4 (m = 2.95, SD = .91).

Whilst 89.2% of these studies used a validated questionnaire for the resilience variable and

81.1% used random assignment (with this variable not applying to an additional 5.4% of

studies which used repeated measures), fewer (54.1%) controlled for confounders such as

baseline mood. Furthermore, no studies reported whether they used random sequence

generation, and only 1 reported using allocation concealment. Out of a total possible score

of 5, longitudinal studies scored between 2 and 4 (m=2.86, SD=.69). All studies used a

validated resilience questionnaire, and most (71.4%) controlled for confounders and used a

validated emotional distress outcome questionnaire. However, few (28.6%) reported the

response rate at follow-up and found this to be >70%. There were two cross-sectional

studies with a maximum possible score of 4. One of these studies, one scored 2, the other

scored 0.

Figure 4.

Are there factors which confer psychological resilience to emotional distress in

response to failure?

The review identified a number of studies which reported psychological variables

which interact with experiences of failure, errors or mistakes in order to predict mood.

Notably, there were eight potential resilience variables which were tested in more than one

study (see Table 3 for a box-score review of these). Four of these (self-esteem, attributional

style, socially prescribed perfectionism and trait reappraisal) were found to significantly

moderate the association between failure and emotional distress in >50% of the studies in

which they were tested, two drew a balance of significant and null findings (self-oriented

perfectionism and emotional intelligence) and two drew only null findings (academic self-

worth and trait emotion suppression).

Which potential resilience factors have the most supporting evidence?

Of the four potential resilience variables with the most supporting evidence, three

drew significant results in two-thirds of the studies which tested them (self-esteem,

attributional style and socially prescribed perfectionism). Self-esteem was the most

frequently tested of these. It was investigated in three longitudinal studies (all of which

reported a significant moderation effect) and 12 experimental studies (seven of which

reported a significant moderation effect). Twelve studies measured self-esteem using the

same measure, the Rosenberg Self-Esteem Scale (Rosenberg, 1965). Two of these

included a validated measure of depressed mood as the outcome (Abela, 2002; Sweeney &

Wells, 1990). Both of these were longitudinal studies of reactions to naturally occurring

failure. The remaining self-esteem studies used a range of mood and affect measures,

including the Feelings of Self Worth Scale (Brown & Dutton, 1995) which measures the

extent to which participants are proud, pleased with themselves, humiliated and ashamed.

The risk of bias score of studies which reported significant results (m=2.5) was similar to that

of studies reporting non-significant results (m=2) suggesting that quality variation is unlikely

to have affected significance of findings.

Attributional style was tested in six studies, including three experimental studies (two

of which reported significant results), two longitudinal studies (one of which reported a

significant moderation effect) and one cross-sectional study (which reported a significant

moderation effect). Three studies (Follette & Jacobson, 1987; Morris & Tiggemann, 1999;

Stiensmeier‐Pelster, 1989) used a version of the Attributional Style Questionnaire (ASQ;

Peterson et al., 1982), two used a single item (Brown & Cai, 2010), and one used an non-

validated three-item scale (Forsyth & McMillan, 1981). The three which did not use a version

of the ASQ asked about attributions for a specific event. Validated questionnaires of

depressed mood were used to measure the emotional distress outcome in two studies, with

the remainder using the Feelings of Self Worth Scale (Brown & Dutton, 1995), Visual

Analogue Scales (one study) and a measure of general affect (one study). The risk of bias

score of studies reporting significant results (m=1.75) was similar to that of studies reporting

non-significant results (m=2).

Socially-prescribed perfectionism was tested in three studies which each used an

experimental design; two of these reported a significant interaction. Two studies measured

the emotion outcome with scales developed for the study (one of which reported a significant

interaction), and the third measured the emotion distress outcome with validated measures

of anxiety, depression and anger. This third study found significant interactions for each of

these emotion outcomes. The pattern of interactions was such that lower levels of

perfectionism were protective against emotional distress in response to failure. The risk of

bias scores of the three studies were similar (the study reporting non-significant results

scored three, compared to a score of four for the two remaining studies).

Only one potential resilience variable, trait reappraisal was found to interact with

failure in each study in which it was tested (Johnson et al., 2011a), but this is may be due to

the small number of studies in which this was included (two in total). Emotional distress

outcomes were measured using visual analogue scales (both studies) and a validated

measure of general affect (one study). The pattern of the interactions was such that lower

levels of trait reappraisal buffered individuals from higher levels of negative mood in

response to failure. Conversely, two variables (self-oriented perfectionism and emotional

intelligence) drew equivocal findings and two (academic self-worth and trait emotion

suppression) were not significant moderators of failure in any of the studies in which they

were tested.

Three-way interactions between two resilience variables and failure

In four studies reported in three papers (Abela, 2002; Niiya & Crocker, 2008; Park,

Crocker, & Kiefer, 2007), results from the two-way interactions between potential resilience

variables and failure were qualified by significant three-way interactions involving a second

potential resilience variable (see Supplementary File 2). These interactions suggested that

the moderating impact of one proposed resilience variable on emotional response to failure

varies depending on the degree of another proposed resilience variable. In three of the four

studies, self-esteem was included as one of the resilience variables. Together, these results

suggest that the moderating impact of self-esteem on emotional response to failure varies

according to pessimism and the extent to which self-worth is contingent on academic

performance. In particular, individuals with either pessimistic inferential style or higher

contingencies of self-worth in combination with low-self-esteem were more vulnerable to low

mood in response to failure.

Discussion

The first objective of the current review was to investigate whether there are

psychological constructs which can buffer the association between experiences of failure,

errors or mistakes, and emotional distress or dysfunction. The second objective was to

identify specific psychological factors which may have this buffering effect, and which can be

regarded as conferring resilience to failure. The review used the Bi-dimensional Framework

for resilience research (BDF; Johnson et al., 2011b) which proposes that resilience factors

are those which statistically moderate the likelihood that risk factors, such as failure

experiences, will lead to negative outcomes such as emotional distress.

Summary of findings

The review found clear evidence for the existence of psychological factors which

buffer the association between failure experiences and emotional distress or dysfunction. A

range of personality and coping constructs were investigated, and the strongest support was

found for the factors of higher self-esteem, more positive attributional style and lower levels

socially prescribed perfectionism. Several other variables had a weaker evidence base due

to smaller number of studies or more equivocal results, but may also buffer emotional

distress in response to failure. These included lower levels of trait reappraisal, lower self-

oriented perfectionism and higher emotional intelligence. Two variables, academic self-worth

and trait emotion suppression, were investigated in more than one study but were not found

to be significant moderators, suggesting that these do not confer resilience to failure.

Implications for psychological resilience-building interventions for clinical and non-

clinical populations

The concept of building resilience has long been an implicit aspect of psychological

interventions in populations with psychological disorders. For example, Cognitive-Behaviour

Therapy (CBT) aims to help clients develop skills and techniques for managing low mood

and stress which they can put into practice in daily life when the need arises (Beck, 1976).

Although the focus of the therapy may be on alleviating the client’s current distress, an

underlying assumption has been that these skills will be a source of resilience for the client

after therapy has ceased. Recent years have seen a growing focus on this element of

interventions, with therapeutic approaches being developed or refined specifically to prevent

subsequent relapses (Williams et al., 2014). There has also been increasing interest in

resilience-focused interventions in populations which are not currently experiencing

psychological disorder, but may be at heightened risk. These include children and young

adults (Dray et al., 2014; Lynch, Geller, & Schmidt, 2004), military families (Saltzman et al.,

2011) and healthcare staff (Goldhagen, Kingsolver, Stinnett, & Rosdahl, 2015; Mealer et al.,

2014).

These interventions have been designed and developed on the basis of clinical

knowledge and factors which predict symptoms over time. However, there has been a lack

of evidence regarding factors which can buffer individuals from emotional distress in

response to subsequent stressors, such as failure, which is a strong and consistent trigger of

emotional distress (Bulik et al., 1990; Johnson et al., 2011a; McCarty et al., 2008; Reinherz

et al., 1999). By identifying factors that these psychological interventions can target in order

to reduce risk of emotional distress in response to subsequent failure experiences, results

from the review provide an evidence-base for these interventions to draw on. These results

are supported by the experimental and longitudinal design of most of the studies, which

provide evidence that the proposed resilience variables may have a causational impact on

subsequent mood. In particular, the review suggests that resilience-building interventions

should aim to increase levels of self-esteem, develop a more positive attributional style, and

reduce levels of perfectionism (particularly socially prescribed perfectionism).

In addition to clinical groups, resilience-based interventions could have important

implications for groups who may not currently suffering from mental health difficulties, but

who are regularly confronted with failure as part of their training or work. One such group are

healthcare professionals, who may undertake ongoing training and assessment alongside

their practice and who may also be involved in medical errors (Sirriyeh et al., 2010).

Research suggests that involvement in medical errors can cause significant emotional

distress, and that experiencing distress can then increase the risk of involvement in

subsequent errors (Hall, Johnson, Watt, Tsipa, & O’Connor, 2016; Sirriyeh et al., 2010; West

et al., 2009). In this group, resilience-based interventions could enable the development of

psychological resources which may both reduce emotional distress in response to failure

and errors, and improve patient safety.

Comparison with previous findings and Implications for future research

There has been growing interest in the concept of resilience, but the field has

suffered from two main limitations which have prevented the development of increasingly

advanced and nuanced understandings of resilience. First, there has been a lack of clarity

concerning the criteria that a variable should meet in order to be regarded as a resilience

factor, and second, the approach to investigating resilience has too often been top-down;

proposing a concept of resilience and then exploring this concept in different settings. This

has prevented the natural evolution of concepts of resilience in response to new research

findings. Consistent with these limitations, very few studies have sought to investigate

resilience to emotional distress in response to failure in particular. Of the two studies we

identified which had focused on this topic prior to undertaking the review, neither had

reported evidence that a psychological variable conferred resilience to emotional distress in

response to failure (Martin-Krumm et al., 2003; Niiya et al., 2004). The current study

reviewed the literature using the Bi-Dimensional Framework for resilience research (BDF)

which was developed to address limitations in the resilience literature (Johnson, 2016). It

suggests that resilience factors are those which statistically moderate or attenuate the

association risk factors and negative outcomes, such that at high levels of resilience, the

association between exposure to risk factors and negative outcomes is weakened (see

Figure 1). This approach identifies relevant studies according to the methodology studies

have used, overcoming the terminology used by the authors, and as such allows a broader

number of studies to be identified. Using this approach, we found 46 relevant studies, which

together drew strong support for the factors of higher self-esteem, more positive attributional

style, and lower socially-prescribed perfectionism. Weaker support was drawn for the factors

of lower trait reappraisal, lower self-oriented perfectionism and higher emotional intelligence.

Given the previous sparsity of research in this area, these results provide a strong

foundation for further research into resilience in the face of failure.

These results can also be compared to resilience findings drawn from other areas. Of

particular interest is one previous review which used the same framework (the BDF) to

synthesise studies investigating resilience to suicidality (Johnson et al., 2011b), identifying

attributional style, perfectionism, agency and hopelessness as key buffering factors, with

weaker evidence for self-esteem. Factors identified in the current review overlap with these,

providing support for these findings and suggesting that factors which confer resilience to

suicidality may also buffer individuals from emotional distress in response to failure. The

convergence of results is particularly interesting given clear variations between these two

reviews. For example, whereas the previous review included studies investigating a range of

risk factors, both internal (e.g., depression) and external (e.g., life stress), with only two

studies investigating failure experiences in particular (Priester & Clum, 1992, 1993) the

current review focused only on a specific, discrete and external risk factor (failure).

Furthermore, whereas the previous review included a number of cross-sectional studies and

no experimental studies, the great majority of studies in the current review were of an

experimental or longitudinal design. Particularly notable is that no individual study appeared

in both reviews. As such, the current review both supports and extends the previous review,

providing evidence that self-esteem, attributional style and perfectionism could be key

resilience factors for both suicidality and emotional distress which may have a causal role in

protecting individuals from the negative impact of failure. In supporting these previous

results, the current review also provides further evidence of the utility of the BDF for

evidence synthesis. Like the previous review, only a small number of the included studies

self-identified as investigations of ‘resilience’. However, by using the BDF, methodology was

used to select relevant studies instead of terminology, removing this limitation.

The review identified both factors which confer resilience to failure, and those which

did not. In particular, academic self-worth and trait emotion suppression were investigated in

more than one study but not found to be significant moderators, suggesting that these do not

confer resilience to failure. This provides clear indications for factors which future resilience

research may build on, and those which can be precluded. Given the similarities between

these non-significant variables with those which drew more significant interaction effects

(e.g., academic self-worth with self-esteem), conceptual clarity is likely to be important when

investigating resilience.

The majority of studies included in the review were experimental, with a smaller

number using longitudinal approaches. No studies were identified which investigated

resilience using a daily-diary or experience-sampling method. These methods provide a rich

data source, allowing for the investigation of associations between resilience factors and

day-to-day (or hour-to-hour) fluctuations in mood. Like longitudinal studies, they offer both

evidence regarding causality and an ecologically valid design, but provide a larger number of

time points on which to base conclusions. Given that mood can vary dramatically over time,

this prevents spurious conclusions being drawn on the basis of one dip in mood, for

example. Future resilience research would benefit from extending the current evidence base

by using these designs.

The present review took took a systematic approach to investigating resilience to

failure, but as it was not a meta-analysis, it was unable to report effect sizes. The main

contribution of this review is that it builds the evidence base and supports the formation of

specific hypotheses to be tested meta-analytically by future studies. However, in future, a

meta-analysis of key supported moderators such as self-esteem is highly encouraged. Such

meta-analysis could examine (through meta-regression analysis) the moderating effects of

self-esteem on emotional distress independent of whether the primary studies tested

interaction effects.

Furthermore, the current study focused on investigating resilience to discrete failure

experiences, excluding studies which investigated reactions to perceived social failures and

rejections. This decision was made due to the more complex nature of social interactions,

which are complex and can have a range of contributors, and which may extend and vary

over time. However, given the importance of social relationships to psychological wellbeing

and mental health (e.g., Cohen & Hoberman, 1983; Hovey, 1999), investigating resilience to

these events may represent an important avenue for future reviews to explore.

Strengths and limitations

The study had several strengths. It is the first systematic review to synthesise

literature investigating resilience to failure, and it approached this using a theoretically

informed approach. It was conducted and reported according to PRISMA guidelines (Moher

et al., 2009). The searches were designed to be comprehensive, and drew a large number of

results eligible for inclusion. The majority of included studies used experimental or

longitudinal designs which provide some evidence of causality. In all experimental studies

apart from two (reported in one paper; Brown & Cai, 2010) the proposed resilience variable

was measured at baseline, preventing the possibility that measurement of these was

affected by the failure experience (e.g., Chung et al., 2014).

The review also had limitations. The majority of studies were conducted amongst

undergraduate students, and only one study used a clinical population. However, this study

was reported in a two-part paper (Johnson et al., 2011a), where the same experiment was

repeated in both undergraduate and clinical populations. Results were replicated in both

studies, suggesting that the resilience factor (low trait reappraisal) had the same buffering

impact in both populations. This provides evidence that although most of these studies were

not in clinical populations, results may generalise. Furthermore, nine studies used validated

measures of depression and anxiety which are often used in clinical settings (e.g., BDI,

State-Trait anxiety inventory) in order to measure the emotional distress outcome. The

majority of these found significant results, indicating that the impact of the resilience factors

tested by these studies is significant enough to influence clinical levels of mood change.

Study results were aggregated using the box-score approach which allowed for the

visual display of significance of findings. A limitation of using this approach was that it was

not possible to consider the magnitude of reported effects. As such, it may have led to a

more conservative interpretation of the evidence (Green & Hall, 1984; Knopp et al., 2013).

The review only included papers published in peer-reviewed journals. It is now

increasingly recognised that grey literature is an additional useful source of research data

which can help minimise the possibility of publication and study selection biases in

systematic reviews. However, we decided to exclude grey literature from this study because

it is very difficult to search, synthesise and appraise the quality of data from grey literature

(Mahood, Van Eerd, & Irvin, 2014).

Conclusion

This is the first systematic review to identify resilience factors that may buffer

emotional distress or dysfunction resulting from failure, mistakes or errors. Results

suggested that higher self-esteem, more positive attributional style and lower levels of

socially prescribed perfectionism may confer resilience to emotional distress in response to

failure, and that academic self-worth and trait emotion suppression are not linked with

resilience. These results suggest that these factors may be useful targets for resilience-

building interventions, and should be incorporated into concepts of resilience. These findings

also support the utility of the Bi-Dimensional Framework for the synthesis of studies

investigating potential resilience factors.

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Table 1

Characteristics of included experimental studies

Author/

year

Country Study design Resilience

variable

Outcome

variable/s

Failure

manipulation

Significant

interactions

Pattern of the

interaction

Participant

sample

Sample

size

Men

(%)

Age M

Angoli et

al. (2015;

Study 1)

Italy Experimental Emotional

Intelligence

(Emotional

Intelligence

Questionnaire–

Short Form

(Petrides &

Furnham, 2006)

30 items from the

PANAS-X

(Watson & Clark,

1990), measuring

sadness, guilt,

fatigue, joviality

and self-

assurance affect

False feedback -

positive or

negative feedback

on a

computerised

task. Task

involved helping a

child

Emotional

intelligence

interacted with

failure to

predict

sadness and

guilt

Positive feedback

predicted reduction

in sadness and guilt

in low Emotional

Intelligence but not

high Emotional

Intelligence

individuals

Undergraduates 63 55.6 24.1

Angoli et

al. (2015;

Study 2)

Italy Experimental Emotional

Intelligence

(Emotional

Intelligence

Questionnaire–

Short Form

(Petrides &

Furnham, 2006)

30 items from the

PANAS-X

(Watson & Clark,

1990), measuring

sadness, guilt,

fatigue, joviality

and self-

assurance affect

False feedback -

positive or

negative feedback

on a

computerised

task. Task did not

involve helping

another person

None Not applicable -

there were no

significant

interactions

Undergraduates 59 53.3 24.52

Anshel &

Mansouri

(2005)

USA Experimental Perfectionism

(Organisation

subscale of The

Multiple

Perfectionism

Scale; Frost et al.,

1990)

Negative and

positive affect

(Children’s

Arousal Scale –

Adult version;

Anshel & Martin,

1996)

No feedback

(control condition)

or false failure

feedback

(experimental

condition) on a

body-balancing

task on a

stabilometer for

20 trials

None Not applicable -

there were no

significant

interactions

College-aged

male athletes

30 100 Mean

age not

available

. Range:

19.6-

22.8

Basgall &

Snyder

(1988)

USA Experimental Locus of Control

(Internal-External

Locus of Control

Scale; Nowicki &

Duke, 1974)

Anxiety,

depression and

hostility (Multiple

Affect Adjective

Checklist;

Zuckerman &

Lubin, 1965)

False success or

failure feedback

on a purported

test of social

perceptiveness.

Locus of

control

interacted with

failure

Individuals with

external locus of

control became

more depressed

after failure than

individuals with

internal locus of

control

Undergraduates

scoring in the

upper and lower

quartiles on

Locus of Control

from an initial

sample of 600

96 0 Not

available

Besser et

al. (2004)

Israel Experimental Self-Oriented

Perfectionism and

Socially-

Prescribed

Perfectionism

(Multidimensional

Perfectionism

Positive affect,

dysphoria, hostility

and anxiety

measured using

visual analogue

scales of 18 mood

False success or

failure feedback

on a

computerised

task.

Self-Oriented

Perfectionism

interacted with

feedback to

predict positive

affect

Under negative

feedback, high self-

oriented

perfectionists

reported a decrease

in post-task positive

affect. When the

Undergraduates 100 50 21.75

Scale; Hewitt &

Flett 1991).

adjectives. feedback was

positive, high self-

oriented

perfectionists

reported a

significant increase

in positive affect

Besser et

al. (2008)

Israel Experimental Self-Oriented

Perfectionism and

Socially-

Prescribed

Perfectionism

(Multidimensional

Perfectionism

Scale; Hewitt &

Flett 1991).

Positive affect,

dysphoria, hostility

and anxiety

measured using

visual analogue

scales of 18 mood

adjectives;

Performance self-

esteem and social

self-esteem

(modified version

of the Current

Thoughts Scale ;

Heatherton &

Polivy, 1991)

1) False feedback

- positive or

negative feedback

on a

computerised

task, and 2)

Objective

errors/mistakes

Socially

prescribed

perfectionism

moderated the

impact of

objective

performance

on dysphoria

and positive

affect, and the

impact of

feedback on

positive affect

and

performance

self esteem.

High socially

prescribed

perfectionism was

associated with 1)

low post-task

performance self-

esteem and this

was stronger under

negative feedback,

2) increased

dysphoria and

reductions in

positive affect when

there were higher

levels of objective

errors, 3) decreases

in positive affect in

response to

negative feedback

Undergraduates 200 50 23.63

Bodroza

(2011)

Serbia Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self-esteem

(global self-

esteem scale;

Opacic &

Bodroza, in

preparation at the

time of

publication)

Depression,

anxiety and anger

(Pofile of affective

states; Popov,

2007).

False success or

failure feedback

on a

computerised

task.

None Not applicable -

there were no

significant

interactions

Undergraduates 90 0 21.25

Brockner USA Experimental Self esteem Confident, upset, Insoluble None Not applicable - Undergraduates 78 33 Not

(1983;

Study 1)

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

(revised Janis-

Field Scale; Eagly

1967) and self-

consciousness

(Private self-

consciousness

subscale of the

Self-

Consciousness

Scale; Fenigstein,

Scheier & Buss,

1975)

frustrated, angry,

and depressed,

measured using a

41-item measure

anagrams task

(control condition

v failure)

there were no

significant

interactions

available

Brockner

(1983;

Study 2)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self esteem

(revised Janis-

Field Scale; Eagly

1967) and self-

consciousness

(Private self-

consciousness

subscale of the

Self-

Consciousness

Scale; Fenigstein,

Scheier & Buss,

1975)

Confident, upset,

frustrated, angry,

and depressed,

measured using a

41-item measure

Insoluble

anagrams task

(control condition

v small failure v

extended failure)

None Not applicable -

there were no

significant

interactions

Undergraduates 119 52 Not

available

Brown &

Cai (2010;

Study 1)

USA (but

included

Chinese

participants

only)

Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

Attributional style -

single item

measuring the

extent to which

participants

thought their

performance was

due to their

integrative

orientation abilityb

Self relevant

emotions (proud,

pleased with

myself, ashamed,

humiliated, e.g.,

Brown & Dutton,

1995). Some

validation

information

provided.

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Mednick, 1962)

None, but

there was a

trend towards

an interaction

between

attributional

style

moderating the

association

between

No significant

interactions,

however, there was

a trend. In the

failure condition,

both high and low

ability attribution

individuals report

the same levels of

self-worth, but in the

Undergraduates 55 25 19.46

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

success/failure

and feelings of

self worth

(p=.065).

success condition,

high ability

attribution

individuals report

higher levels of self-

worth

Brown &

Cai (2010;

Study 2)

USA (but

included

American

and

Chinese

participants

)

Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Attributional style -

single item

measuring the

extent to which

participants

thought their

performance was

due to their

integrative

orientation abilityb

Self relevant

emotions (proud,

pleased with

myself, ashamed,

humiliated, e.g.,

Brown & Dutton,

1995). Some

validation

information

provided.

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Mednick, 1962)

Attributional

style

moderated

associations

between

success/failure

and feelings of

self worth

Cross-over effect -

those with high

ability attribution

showed higher

feelings of self-

worth in the

success condition,

but lower feelings of

self-worth in the

failure condition

Undergraduates 310 (144

Chinese)

29 Not

available

Brown &

Dutton

(1995;

Study 1)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg, 1965)

8-item emotion

scale. The scale

consisted of two

subscales: (1)

outcome-

dependent

emotion (glad,

happy, sad,

unhappy) and (2)

self relevant

emotions (proud,

pleased with

myself, ashamed,

humiliated).

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Mednick, 1962)

Self-esteem

interacted with

failure to

predict levels

of self relevant

emotions

High self-esteem

buffers individuals

from reduced

positive emotion in

the face of failure

Undergraduates 172 23 Not

available

Brown &

Dutton

(1995;

Study 2)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg, 1965)

8-item emotion

scale. The scale

consisted of two

subscales: (1)

outcome-

dependent

emotion (glad,

happy, sad,

unhappy) and (2)

self relevant

emotions (proud,

pleased with

myself, ashamed,

humiliated).

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Mednick, 1962)

Self-esteem

interacted with

failure to

predict levels

of self relevant

emotions

High self-esteem

buffers individuals

from reduced

positive emotion in

the face of failure

Undergraduates 129 39 Not

available

Brown &

Marshall

(2001;

Study 2)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self-esteem

measured with i)

Self-Esteem

Questionnaire

(Rosenberg,

1965), and ii)

Texas Social

Behavior

Inventory

(Helmreich &

Stapp, 1974)

Self relevant

emotions (proud,

pleased with

myself, ashamed,

humiliated, e.g.,

Brown & Dutton,

1995).

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Mednick, 1962)

Self-esteem

measured

using both the

SEQ and the

TSBI

interacted with

failure to

predict

emotion

High self-esteem

buffered the

association

between failure and

higher levels of

negative self-

relevant emotions

Undergraduates 291 32 Not

available

Brown &

Marshall

(2001;

Study 3)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg, 1965)

Self-relevant

emotion scale

formed from four

items (proud,

pleased with

myself,

humiliated,

ashamed, e.g.,

Brown & Dutton,

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Mednick, 1962)

Self-esteem

interacted with

failure to

predict self-

relevant

emotions

High self-esteem

buffered the

association

between failure and

higher levels of

negative self-

relevant emotions

Undergraduates 72 32 Not

available

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

1995); Non-self-

relevant emotions

measured using

18 items from the

Positive and

Negative Affect

Scales (the total

scale minus

“proud” and

“ashamed”;

PANAS; Watson

1988).

Dalal &

Sethi

(1988)

India Experimental Need for

achievement

(Indian version of

the Edwards

Personality

Preference

Schedule; Dhavan

1982)

Single mood scale

measuring

positive-negative

affect (created

from 10 bipolar

emotion-related

adjectives

responded to on

7-point scales)

Anagrams task.

Success or failure

manipulated by

the giving of easy

(success

condition) or

difficult (failure

condition) tasks

None Not applicable -

there were no

significant

interactions

Undergraduates 48 Not

avail

able

Not

available

Dutton &

Brown

(1997;

Study 1)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg, 1965)

Self relevant

emotions (proud,

pleased with

myself, ashamed,

humiliated, e.g.,

Brown & Dutton,

1995). Some

validation

information

provided.

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Mednick, 1962)

Self-esteem

interacted with

failure to

predict

emotion

Plot indicates that

high self-esteem

buffers individuals

from experiencing

negative emotions

in the face of failure

Undergraduates 191 33 Not

available

Dutton &

Brown

(1997;

Study 2)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg, 1965)

and a single

composite

Self relevant

emotions (proud,

pleased with

myself, ashamed,

humiliated, e.g.,

Brown & Dutton,

False success or

failure feedback

on a

computerised task

(Remote

Associates Test;

Both measures

of self-esteem

interacted with

failure to

predict

emotions

Plots indicate that

high self-esteem

buffers individuals

from experiencing

negative emotions

in the face of failure

Undergraduates 136 31 Not

available

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

measure based

on how well

participants

thought 10

positive and

negative attributes

described them

(e.g., intelligent,

athletic, attractive,

uncoordinated,

unattractive,

inconsiderate).

1995). Some

validation

information

provided.

Mednick, 1962)

Frost et

al. (1995)

USA Experimental

, but it is

unclear

whether

baseline

affect was

controlled for

in the

analysis

Concern Over

Mistakes (CM)

subscale of the

Multidimensional

Perfectionism

Scale (Frost,

1990)

Negative affect

(measure not

clearly defined in

paper)

Number of

mistakes in a

computerised

task, high

mistakes v low

mistakes

Concern over

mistakes

interacted with

number of

mistakes to

predict

negative affect

Low perfectionism

buffers the impact

of being in the high-

mistake task on low

mood

Undergraduates 64 Not

avail

able

Not

available

Hill et al.

(2011)

UK Experimental

, but all

participants

received the

failure

condition,

and their

scores were

compared to

their own

baseline

scores.

Self-oriented

perfectionism

subscale of the

Multidimensional

Perfectionism

Scale (Hewitt and

Flett 1991)

Positive and

Negative Affect

measured using

the Positive and

Negative Affect

Scales (PANAS;

Watson 1988)

Performance

feedback on a

cycling task

manipulated to

ensure failure to

meet personal

goals. All

participants

received the

failure induction,

scores on

outcome measure

compared pre and

post

None Not applicable -

there were no

significant

interactions

Undergraduates 68 71 19.75

Ingram et

al. (1992;

Study 1)

USA Experimental Private self-

consciousness

measured using

10 items from the

Self-

Consciousness

Scale (Fenigstein,

1975)

Multiple Affect

Adjective

Checklist

(MAACL;

Zuckerman &

Lubin, 1965).

Comprises three

subscales:

Anxiety,

depression and

False failure or

success feedback

on a bogus

intelligence paper-

and-pencil test

None, although

there were

trends towards

self-

consciousness

interacting with

failure to

predict the

overall mood

score and

Not applicable -

there were no

significant

interactions

Undergraduates 58 Not

avail

able

Not

available

hostility. Overall

score and the

three subscales

were investigated

depression.

Johnson

et al.

(2011a;

Study 1)

UK Experimental Trait Suppression

and Trait

Reappraisal

measured using

the Emotion

Regulation

Questionnaire

(Gross & John

2003)

Positive and

Negative Affect

measured using

the Positive and

Negative Affect

Scales (PANAS;

Watson 1988),

and Visual

Analogue Scales

(VAS) of five

mood states

(defeat, sadness,

calmness,

happiness, and

frustration )

False success or

failure feedback

on a task (Remote

Associates Test;

Mednick, 1962)

Trait

reappraisal

interacted with

failure to

predict

negative affect

on the PANAS

and VAS

scales of

defeat,

sadness and

calmness

Low levels of trait

reappraisal buffer

the association

between failure and

higher negative

mood, and amplify

feelings of

calmness in the

face of failure

Undergraduates 120 23 20.53

Johnson

et al.

(2011a;

Study 2)

UK Experimental Trait Suppression

and Trait

Reappraisal

measured using

the Emotion

Regulation

Questionnaire

(Gross & John

2003)

Visual Analogue

Scales of five

mood states

(defeated, sad,

calm, happy, and

frustrated )

False success or

failure feedback

on a task (Remote

Associates Test;

Mednick, 1962)

Trait

reappraisal

interacted with

failure to

predict defeat

Low levels of trait

reappraisal buffer

the association

between failure and

feelings of defeat

Adults with a

diagnosis of a

schizophrenia-

spectrum

disorder

77 77 42.3

Jones et

al. (2013)

USA Experimental Chronic promotion

failure measured

using the

Computerized

Selves

Questionnaire

(CS; Jones et al.,

2009). This

measures the

discrepancy

between

participants' goals

for themselves

and where they

perceive

themselves to be

Dejection and

Quiescence

measured using

items from the

Sadness and

Serenity

subscales of

Positive and

Negative Affect

Scale – Expanded

Form (PANAS-X;

Watson & Clark,

1990)

Writing task to

elicit memories of

'promotion failure',

'prevention failure'

or control

memories

Chronic

promotion

failure

interacted with

failure

condition to

predict

dejection

Low levels of

chronic promotion

failure buffer the

impact of failure

memories on

dejection

Undergraduates 78 21 26.37

Karabenic USA Experimental Projective 7-point bipolar False failure or None Not applicable - Undergraduates 252 0 Not

k &

Marshall

(1974)

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting

measure of fear of

success using

fear of success

stories (Horner

1968); Fear of

failure measured

using the

Debilitating

Anxiety Scale of

the Achievement

Anxiety Test

(Alpert & Haber,

1960)

emotion scales of

depression-

pleasure;

unembarassment-

embarrassment;

luck-skill; happy-

unhappy;

uncomfortable-

comfortable;

superior-inferior;

relaxed-nervous

success or neutral

[equal] feedback

on a paper task.

Some participants

were compared

directly to a

confederate

opponent, others

to normed scores

there were no

significant

interactions

available

Mendelso

n & Gruen

(2005)

USA Experimental

. Mood

change was

measured

immediately

following the

failure

induction and

again 24

hours later

Self-criticism and

dependency

(Depressive

Experiences

Questionnaire;

Blatt et al., 1976)

Three types of

depressive affect:

Introjective and

anaclitic

depressive affect

(Emotion

Questionnaire,

Zuroff &

Mongrain, 1987)

and Depression–

Dejection

(subscale from the

Profile of Mood

States, McNair,

Lorr, &

Droppleman,

1971)

In the failure

condition, false

feedback was

provided in

response to a

version of the

Ravens

Progressive

Matrices (Raven,

Court & Raven,

1985). In the

control condition,

participants sat

quietly with a

book of nature

pictures

Self-criticism

interacted with

failure to

predict

changes in

introjective

depressive

affect

immediately

following the

failure. Self-

criticism and

dependency

interacted with

failure to

predict

anaclitic

depression

immediately

following the

failure

Pattern of the

interactions not

displayed or

described

Undergraduates 125 36.8 19.42

Niiya et al.

(2004)

USA Experimental Academic

subscale of the

Contingencies of

Self-Worth Scale

(Crocker, et al.,

2003)

State self-esteem

(Heatherton &

Polivy, 1991),

comprising three

correlated factors:

performance,

social, and

False success

(i.e., a score of

97th percentile) or

failure (i.e., a

score of 45th

percentile)

feedback on a

None Not applicable -

there were no

significant

interactions

Undergraduates 128 26.6 Not

available

appearance state

self-esteem

Graduate Record

Examination

(GRE) test

composed of

reading

comprehension,

quantitative

comprehension,

and analytical

reasoning

questions

Park et al.

(2007;

Study 1) a

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg,

1965); Academic

subscale of the

Contingencies of

Self-Worth Scale

(Crocker, et al.,

2003)

State self-esteem

adapted from the

Rosenberg Self-

Esteem

Questionnaire to

measure feelings

at that moment;

Positive and

negative affect

measured using

7-point rating

scales for positive

affect items (e.g.,

happy, cheerful; 7

items) and

negative affect

(e.g., angry,

depressed; 7

items)

Remotes

Associates Test

(McFarlin &

Blascovich, 1984).

Participants in the

control condition

rated words for

their favourite,

and were given no

evaluative

feedback

None Not applicable -

there were no

significant

interactions

Undergraduates 122 35.2 19.01

Park et al.

(2007;

Study 2) a

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg,

1965); Academic

subscale of the

Contingencies of

Self-Worth Scale

(Crocker, et al.,

2003)

Implicit affect

measured using

the IAT

(Greenwald et al.,

1998), a

computerized

reaction time task

that measures the

relative speed of

associations

made between

target concepts

and attributes.

Participants

categorized words

Remotes

Associates Test

(McFarlin &

Blascovich, 1984).

Participants in the

non-failure

condition

completed an

easy version of

the test which

ensured success

None Not applicable -

there were no

significant

interactions

Undergraduates 109 53.2 19.79

susceptible

to selective

reporting

related to the self

and other with

words related to

failure (e.g.,

worthless, failure,

incompetent) and

words related to

success (e.g.,

worthy, success,

competent)

Riketta &

Ziegler

(2007)

Germany Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting

Experienced

ambivalence (e.g.,

“I have positive

and negative

feelings toward

myself at the

same time”;

Riketta & Ziegler,

2005); Structural

ambivalence (e.g.,

“please consider

only the positive

(negative) aspects

of yourself-image..

how positive do

you find

yourself?”;

Thompson et al.,

1995); Self-

esteem (Self-

Esteem

Questionnaire;

Rosenberg, 1965)

Two outcomes.

The first was self-

feeling items of

proud, ashamed,

humiliated and

satisfied and

mood items of

depression, good-

humour, sad and

happy (Brown &

Dutton, 1995).

The second was

state self-esteem

(Heatherton &

Polivy, 1991)

Computerised

task fixed to

produce success

(easy version) or

failure (hard

version). Based

on the Ravens

Advanced

Progressive

Matrices (APM), a

standardized

nonverbal

intelligence test

Four

hierarchical

regression

analyses

tested each

type of

ambivalence

separately in

relation to the

two outcomes.

Of those

testing

structural

ambivalence,

structural

ambivalence

interacted with

failure to

predict state

self-esteem.

Self-esteem

interacted with

failure to

predict self-

feelings and

mood. Of

those testing

experienced

ambivalence,

self-esteem

interacted with

failure to

predict self-

feelings and

mood.

Low structural

ambivalence

buffered against the

negative impact of

failure upon state

self-esteem. High

self-esteem

buffered

participants from a

drop in state self

esteem in response

to failure.

Undergraduates 87 54 21.84

Sanna

(1996;

Study 4)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting

Defensive

pessimism/optimis

m (the propensity

to use defensive

pessimistic or

optimistic

strategies in

academic

achievement

situations; Norem

& Illingworth,

1993).

Participants

scoring in the

upper third were

classed as

"optimists" and in

the lower third, as

"pessimists".

Participants were

selected from a

larger group of

454 for scoring

high or low on this

scale

Participants

indicated the

extent to which a

series of positive

and negative

adjectives

reflected their

mood with regard

to the upcoming

exam. All items

were scored to

produce a single

mood outcome

variable

Anagrams task.

The same task

was given in

success and

failure conditions

but feedback

manipulated to tell

the participant

they had either

scored in the top

20th (success

condition) or

bottom 20th

(failure condition)

centiles

None Not applicable -

there were no

significant

interactions

Undergraduates 87 Not

avail

able

Not

available

Shalon &

Strube

(1988)

USA Experimental

. However,

baseline

scores were

not recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Type A/ Type B

behaviour pattern

measured using

the Jenkins

Activity Survey

Form (Krantz,

Glass, & Snyder,

1974. Participants

classified as Type

A's (scores of 9 or

greater) or Type

Bs (scores of 8 or

less)

Mood scales of

anxiety,

nervousness,

frustration, anger,

and depression

Anagrams task

(success v

failure). In the

success condition,

participants

completed easy

anagrams and

were told that

their score was

better than; or

equal to, 78%of

students. In the

failure condition,

participants

completed a very

difficult set of

anagrams and

were told that

42% of the people

taking the test did

None, although

there was a

trend towards

Type A/Type B

behaviour

moderating the

association

between failure

and anxiety

(p<0.55).

Not available Undergraduates 80 50 Not

available

better than them

Steinsmei

er-Pelster

(1989)

Germany Experimental Attributional style

was assessed

with the negative

items from the

German

Attributional Style

Questionnaire

(GASQ,

Stiensmeier et al ,

1985), based on

the original ASQ

(Peterson et al.,

1982)

Mood index was

created by

totalling the

Carefreeness

(reverse-scored),

Happiness

(reverse-scored),

and Depression

scales from the

Mehrdimensionale

Stimmungsfrageb

ogen (Hecheltjen

& Mertesdorf,

1973)

Participants

completed the

task together with

a confederate.

Two versions of

the Raven

Progressive

Matrices (Raven,

1974/1975) were

used. The

difficulty level of

the tasks and the

behavior of the

confederate were

manipulated to

induce failure and

success. False

feedback not

given

Failure

interacted with

attributional

style to predict

mood

Negative

attributional style

amplified negative

mood in the failure

condition only.

Undergraduates 46 0 20.4

Stoeber et

al. (2014)

UK Experimental

, but mood

was not

recorded at

baseline. As

such, for the

interactions

testing mood

after the first

task, findings

could be

explained by

baseline

differences.

For analyses

of mood after

the second

task, prior

mood was

included as a

control

variable

Self-oriented

perfectionism and

socially prescribed

perfectionism

(Multidimensional

Perfectionism

Scale; Hewitt &

Flett 2004)

Three mood

measures. Anxiety

(a short form of

the State–Trait

Anxiety Inventory;

Spielberger,Gorsu

ch, Lushene,

Vagg, & Jacobs,

1983); depression

(subscale from a

short form of the

Profile of Mood

States, McNair,

Lorr, &

Droppleman,

1971); anger

(Feeling Angry

subscale of the

State–Trait Anger

Expression

Inventory;

Spielberger,

1999). Mood

measured after

the first failure and

False feedback to

induce success

and failure

provided in

response to

computerised

tasks involving

identifying

whether pictures

of rotated figures

were the same

figure. Each

participant

completed two

similar tasks and

mood was

measured after

each task

Socially

prescribed

perfectionism

interacted with

failure to

predict anxiety,

depression

and anger after

the first task.

Socially

prescribed

perfectionism

interacted with

failure to

predict anger

after the

second task

and self-

oriented

perfectionism

interacted with

failure to

predict anxiety

after the

second task

Socially prescribed

perfectionism

amplified the

association

between failure and

anxiety, depression

and anger after the

first task. Socially

prescribed

perfectionism

amplified the

association

between failure and

anger after the

second task, and

self-oriented

perfectionism

amplified the

association

between failure and

anxiety after the

second task.

Undergraduates 100 50 21.35

again after the

second failure

Thompso

n & Dinnel

(2007)

Australia Experimental

. However,

baseline

scores of

dependent

variables

were not

recorded,

and as such,

post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self-worth

protection (the

extent to which

participants want

to avoid failure

measured using

the Self-Worth

Protection Scale;

Thompson &

Dinnel, 2003).

Participants were

selected from a

larger group of

235 for scoring

high (upper third)

or low (lower third)

on this scale.

Negative affect

index created

using three items

(guilt, shame,

humiliation) from

the PANAS

(Watson, Clark, &

Tellegen, 1988)

Three conditions,

success, face-

saving failure

(where

participants were

informed that

ability on the task

had not been

found to be a

particularly good

indicator of overall

ability) and

humiliating failure

(where

participants were

informed that

ability on the task

was a reliable

indicator of

general

intelligence). Task

was a computer

discrimination

task. In the failure

conditions, false

failure feedback

was given. In the

success condition,

feedback was

related to

performance

Self-worth

protection

interacted with

performance

feedback

condition to

predict

negative affect.

Students high in

self-worth protection

reported greater

negative affect

following humiliating

failure than students

low in self-worth

protection, as was

the case following

success, but not

following face-

saving failure.

Undergraduates 72 48.6 22.85

Thompso

n et al.

(2000)

Australia Experimental

. However,

baseline

scores of

dependent

variables

were not

recorded (or

in the case of

STAI anxiety,

simply not

controlled

Imposter fears

(modified version

of the Clance

Impostor

Phenomenon

scale; Clance,

1985).

Participants who

scored as

"imposters" or

"non-imposters"

were drawn from

Four outcome

measures:

positive affect,

negative affect

(PANAS Scales;

Watson, Clark &

Tellegen, 1988),

post-task anxiety

(State-Trait

anxiety Inventory,

Spielberger,T.

Gorsuch,

Computerised

version of the

Stroop task. Real

feedback given,

and incorrect

responses

emphasised with

an "uh oh" sound.

Two versions of

this: high

mistakes

frequency and low

Imposter

status

interacted with

failure to

predict single-

item anxiety

and positive

mood

Being a non-

imposter buffers

against a drop in

positive

mood/increased

anxiety in response

to failure

Undergraduates 60 18.3 21

for), and as

such, post-

experimental

findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting

an initial sample

of 318 students

Lushene, Vagg &

Jacobs, 1983) and

a single-item

anxiety measure

mistakes

frequency. Low

mistakes

frequency task

extremely easy,

simply a patch of

colour presented

on a screen

Wytykows

ka &

Gobinska

(2015)

Poland Experimental Promotion vs.

prevention

orientation (Polish

version of

Regulatory Focus

Questionnaire;

Pikuła, 2012).

Measures

orientations (i.e.

anticipatory goal

reactions) to new

tasks or goals.

The higher the

score, the more

promotion-

focused the

person is

considered to be

Eight emotions

were taken into

account – feeling

depressed, tense,

uneasy,

discouraged,

excited, pleased,

interested, and

calmness

False feedback on

a computerised

task. There were

three conditions:

positive, negative

and control. All

participants

completed a

computerised task

where they were

initially

successful. After

this, participants

completed two

further tasks,

where they scored

roughly the same

as the first task

(control

condition), worse

than previously

(failure condition)

or better than

previously

(success

condition)

Promotion vs.

prevention

orientation

interacted with

feedback

(failure v

success) to

predict tension,

calmness and

feeling pleased

Prevention focus

amplified the impact

of failure on tension.

Pattern of the

interaction for

calmness and

feeling pleased

unclear

Senior

secondary

school students

190 43.1

18.6

a This study reported a significant three-way interaction between two potential resilience variables and failure. Please see Supplementary File 2.

b In this study, the proposed resilience variable was measured after the experimental induction, which may have introduced bias in responding.

Table 2

Characteristics of included cross-sectional and longitudinal studies

Author/

year

Country Study design Resilience

variable

Outcome

variable/s

Failure

experience/

measure

Significant

interactions

Pattern of the

interaction

Participant

sample

Sample

size

Men

(%)

Age M

Abela

(2002)a

USA Longitudinal Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg,

1965); Inferential

style (Cognitive

Style

Questionnaire;

Abramson &

Metalsky, 1986)

Residual

difference

between state

depressed mood

at baseline and i)

on the day of

receiving

admissions

outcome, and ii)

four days later

(Multiple Affect

Adjective

Checklist;

Zuckerman &

Lubin, 1965)

Acceptance or

rejection from

Penn University

Self-esteem

interacted with

failure to

predict

depression

four days after

receiving

admissions

outcome

No plot or

description of

pattern provided

University

applicants

136 47.1 Not

availabl

Follette &

Jacobson

(1987)

USA Longitudinal Attributions

measured using

(1) three

subscales of the

Expanded

Attributional Style

Questionnaire

(EASQ; Peterson

& Seligman,

1984), and (2) the

control subscale

of the EASQ

Depression

subscale of the

Multiple Affect

Adjective

Checklist

(MAACL;

Zuckerman &

Lubin, 1965).

The difference

between expected

and received

university course

grade

None Not applicable -

there were no

significant

interactions

Undergraduates 110 25 Not

availabl

Forsyth &

MacMilla

n(1981)

USA Cross-

sectional

Attributions

measured using

three items,

asking about

perceptions of

controllability,

locus of causality

and stability

Visual analogue

scales measuring

degree to which

participants were

experiencing 16

mood states

Perceived

examination

performance

Locus of

causality

attributions

interacted with

examination

performance to

predict overall

mood

No plot or

description of

pattern provided

Undergraduates 223 38 19.3

Kernis et

al. (1989)

USA Longitudinal,

but emotion

measure only

Tendency to

overgeneralize

from bad

Participants

scored the extent

to which they

Examination

performance.

Participants were

Self-esteem

interacted with

performance to

High self esteem

and low

overgeneralization

Undergraduates 149 50 Not

availabl

completed

once at the

end of the

study. These

studies are

susceptible

to selective

reporting

experiences to the

overall self-

concept

(overgeneralizatio

n subscale of the

Attitudes Toward

Self Scale; ATS,

Carver &

Ganellen, 1983);

Self-esteem (Self

Esteem

Questionnaire;

Rosenberg, 1965)

were experiencing

40 specific

emotions at that

moment. These

were factor

analysed, and

pleasant and

unpleasant affect

indexes were

formed.

Unpleasant affect

contained 23

words and

pleasant affect

contained12

words

placed into the

high performance

group if they had

received an A or B

grade and their

grade was either

the same or better

than they had

expected; they

were placed into

the low

performance

group if they had

received a C or

lower and this was

the same or lower

than they had

expected. Other

participants (n =

48) were excluded

from the analysis

predict

negative affect.

Overgeneraliza

tion interacted

with

performance to

predict

negative affect

and positive

affect

conferred resilience

to higher negative

emotion in

response to failure,

and low

overgeneralization

conferred resilience

to reduced positive

affect in response

to failure

Morris &

Tiggeman

n (1999)

Australia Longitudinal Attributional Style

Questionnaire

(Seligman,

Abramson,

Semmel, & von

Baeyer, 1979). A

negative

generality score

was obtained by

averaging the

ratings of the

globality and

stability

dimensions. An

overall composite

was also obtained

by averaging all

three attributional

dimensions

Depressive

reaction was

assessed by the

Beck Depression

Inventory - Short

Form (Beck,

1967), both

immediately

following the

exam and at the

end of the

academic year

Subjective

performance on

an examination

(naturally

occurring).

Calculated as

actual grade

minus the grade

they would be

satisfied with

(reported before

the exam)

Composite

attributional

style interacted

with subjective

performance to

predict

depression

immediately

following the

exam feedback

and also at the

end of the

academic year.

Attributional

style generality

interacted with

subjective

performance to

predict

depression at

the end of the

year.

Pattern of the

interaction not

plotted.

Correlations

suggest that

attributional styles

were only

associated with

end-of-year

depression scores

in the failure group

Undergraduates 363 30 22.04

Niiya &

Crocker

USA Longitudinal Academic

subscale of the

Rosenberg Self-

Esteem Inventory

Grade on an

assignment which

None Not applicable -

there were no

Undergraduates 142 23.9 19.8

(2008)aContingencies of

Self-Worth Scale

(Crocker, et al.,

2003); Mastery

goals subscale of

Achievement Goal

Scale (Elliot &

Church, 1997);

Ability-Validation

Goal Scale

modified from

Grant and Dweck

(2003), which

measures striving

to demonstrate or

prove ability

(Rosenberg,

1965) to which the

words “right now”

were added to the

instructions

accounted for

15% of the final

course grade

(naturally

occurring)

significant

interactions

Sellers et

al. (2011)

USA Cross-

sectional

High-active

coping (measured

with 12 items,

e.g., “I’ve always

felt that I could

make my life

pretty much what I

wanted to make of

it”).

Mental health was

measured using

the Mental Health

Component

Summary of the

Medical

Outcomes Study

Short Form-12

(Ware, Kosinski, &

Keller, 1998)

“Goal striving

stress" (three

items capturing

the discrepancy

between

aspirations and

achievement,

weighted by the

level of

disappointment

associated with

failing to achieve

life goals)

None Not applicable -

there were no

significant

interactions

Black college

educated men

who were

members of a

historically black

national fraternal

organisation

399 100 47.6

Sweeney

& Wells

(1990)

USA Longitudinal

but mood

was not

recorded at

baseline. As

such findings

could be

explained by

baseline

differences.

These

studies are

susceptible

to selective

reporting.

Self-esteem (Self-

Esteem

Questionnaire;

Rosenberg, 1965)

Three measures

used to create an

“affective index”.

1) single item,

“How satisfied

were you with the

score you

received on your

exam? (1 = very

unsatisfied, 7 =

very satisfied).” 2)

emotional reaction

to the professor

“How happy are

you with the

instructor’s

Grade on a mid-

term college

examination

Self-esteem

with exam

performance to

predict

affective index

scoree

Self-esteem

amplified the impact

of success/failure

on affect

Undergraduates 187 47.1 Not

availabl

performance thus

far in the term?”( 1

= very happy, 2 =

pretty happy, 3 =

not too happy). 3)

Center for

Epidemiological

Studies,

Depression Scale

(CES-

D, Radloff, 1977)

Woo &

Mix

(1997)

USA Longitudinal

but mood

was not

recorded at

baseline.

These

studies are

susceptible

to selective

reporting

Performance self-

esteem

(Performance

Self-esteem

scale; Stake,

1979)

Immediately after

exam feedback,

positive affect

(two items) and

negative affect

(eight items) was

measured

Exam

performance. One

week prior to the

exam, participants

indicated their

own criteria for

"success".

Participants

whose actual

grades equaled or

exceeded their

criterion

performance were

classified as the

"success" group

and those whose

grades fell below

this were the

"failure" group

None Not applicable -

there were no

significant

interactions

Undergraduates 72 25 Not

availabl

a This study reported a significant three-way interaction between two potential resilience variables and failure. Please see Supplementary File 2.

Table 3

Box-score review of interaction effects of proposed resilience variables on the association between failure and emotional distress

Moderator

variable

Number of

studies

Academic

Self-worth

4 0000

Attributional

style

6++++00

Emotional

Intelligence

2+0

Self-esteem 15 ++++++++++00000

Self-oriented

perfectionism

4++00

Socially-

prescribed

perfectionism

3++0

Trait

Reappraisal

2++

Trait

Suppression

2 00

NB. + = interaction effect significant, 0 = interaction effect significant. Pattern of the interaction not reported here as the complexities of this are beyond the scope of

simple symbolic descriptions.

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Mar 2024
BMC HEALTH SERV RES

Background Critical care nurses (CCNs) are routinely exposed to highly stressful situations, and at high-risk of suffering from work-related stress and developing burnout. Thus, supporting CCN wellbeing is crucial. One approach for delivering this support is by preparing CCNs for situations they may encounter, drawing on evidence-based techniques to strengthen psychological coping strategies. The current study tailored a Resilience-boosting psychological coaching programme [Reboot] to CCNs. Other healthcare staff receiving Reboot have reported improvements in confidence in coping with stressful clinical events and increased psychological resilience. The current study tailored Reboot for online, remote delivery to CCNs (as it had not previously been delivered to nurses, or in remote format), to (1) assess the feasibility of delivering Reboot remotely, and to (2) provide a preliminary assessment of whether Reboot could increase resilience, confidence in coping with adverse events and burnout. Methods A single-arm mixed-methods (questionnaires, interviews) before-after feasibility study design was used. Feasibility was measured via demand, recruitment, and retention (recruitment goal: 80 CCNs, retention goal: 70% of recruited CCNs). Potential efficacy was measured via questionnaires at five timepoints; measures included confidence in coping with adverse events (Confidence scale), Resilience (Brief Resilience Scale), depression (PHQ-9) and burnout (Oldenburg-Burnout-Inventory). Intention to leave (current role, nursing more generally) was measured post-intervention. Interviews were analysed using Reflexive Thematic Analysis. Results Results suggest that delivering Reboot remotely is feasible and acceptable. Seventy-seven nurses were recruited, 81% of whom completed the 8-week intervention. Thus, the retention rate was over 10% higher than the target. Regarding preliminary efficacy, follow-up measures showed significant increases in resilience, confidence in coping with adverse events and reductions in depression, burnout, and intention to leave. Qualitative analysis suggested that CCNs found the psychological techniques helpful and particularly valued practical exercises that could be translated into everyday practice. Conclusion This study demonstrates the feasibility of remote delivery of Reboot and potential efficacy for CCNs. Results are limited due to the single-arm feasibility design; thus, a larger trial with a control group is needed.

Coaching for Staff Well-Being

Chapter

Sep 2024

Susanne Knowles

The second purpose of patient safety coaching is to support staff wellbeing so they continue to keep patients safe from harm. Staff who are enthusiastic and motivated at work deliver excellent patient care. Those who are overloaded with staff shortages, lack of resources, equipment failures, or systemic/cultural issues may burnout and leave the organization. To prevent a staff exodus, healthcare organizations are now realizing that they need to provide developmentally focused interventions to support staff wellbeing. They are realizing the power of coaching to bring staff back from work overload and trauma-induced emotions and help them return to work reenergized and recommitted to their work’s purpose. Staff who participate in a coaching program become more resilient, emotionally strong, and resourceful. They learn to value each day and repeat the experiences that bring them joy and happiness. At the same time, they bring a greater joy to their work environment, including to patients who benefit from their uplifted mood. Staff who present to shift alert, self-aware, and confident in their ability to perform well are able to navigate through the trauma that may result following an adverse event. Those who are motivated, enthusiastic, and empowered demonstrate the emotional strength that inspires confidence in all around them. Patients benefit when staff operate “in the flow” on a daily basis, supported by leaders who coach them when necessary to help them learn, grow, and develop to become excellent clinical practitioners.

Exploring Protective Factors for Stress Among University Students: A Theoretical Perspective

Chapter

Aug 2024

Anna Hako

The chapter explores protective factors that can reduce stress in university students, highlighting cultural differences in stress responses. Using a literature review and document analysis method, it emphasizes holistic stress management, highlighting the importance of resilience, self-care, social support, coping abilities, and financial stability. The study suggests creating a welcoming campus environment, promoting social interactions, and providing resources to safeguard students' well-being.

Association between non-restorative sleep and psychotic-like experiences among Chinese college students: A latent profile and moderated mediation analysis

Article

Jun 2024

Static and Temporal Dynamic in Functional Connectivity of Large-scale Brain Networks During Acute Stress Regulate Stress Resilience Differently: The Promotion Role of Trait Resilience

Article

May 2024

Healthcare Staff Wellbeing, Burnout, and Patient Safety: A Systematic Review

Article

Full-text available

Jul 2016
PLOS ONE

Objective: To determine whether there is an association between healthcare professionals' wellbeing and burnout, with patient safety. Design: Systematic research review. Data sources: PsychInfo (1806 to July 2015), Medline (1946 to July 2015), Embase (1947 to July 2015) and Scopus (1823 to July 2015) were searched, along with reference lists of eligible articles. Eligibility criteria for selecting studies: Quantitative, empirical studies that included i) either a measure of wellbeing or burnout, and ii) patient safety, in healthcare staff populations. Results: Forty-six studies were identified. Sixteen out of the 27 studies that measured wellbeing found a significant correlation between poor wellbeing and worse patient safety, with six additional studies finding an association with some but not all scales used, and one study finding a significant association but in the opposite direction to the majority of studies. Twenty-one out of the 30 studies that measured burnout found a significant association between burnout and patient safety, whilst a further four studies found an association between one or more (but not all) subscales of the burnout measures employed, and patient safety. Conclusions: Poor wellbeing and moderate to high levels of burnout are associated, in the majority of studies reviewed, with poor patient safety outcomes such as medical errors, however the lack of prospective studies reduces the ability to determine causality. Further prospective studies, research in primary care, conducted within the UK, and a clearer definition of healthcare staff wellbeing are needed. Implications: This review illustrates the need for healthcare organisations to consider improving employees' mental health as well as creating safer work environments when planning interventions to improve patient safety. Systematic review registration: PROSPERO registration number: CRD42015023340.

The effect of emotions, promotion vs. prevention focus, and feedback on cognitive engagement

Article

Full-text available

Sep 2015

The purpose of the current study was to explore the role of emotions, promotion-prevention orientation and feedback on cognitive engagement. In the experiment participants had the possibility to engage in a categorization task thrice. After the first categorization all participants were informed that around 75% of their answers was correct. After the second categorization, depending on the experimental conditions, participants received feedback either about success or failure. Involvement in the third categorization was depended on the participants’ decision whether to take part in it or not. Each time, before and after categorization, the emotional state was assessed. Results showed that promotion orientation predicts experiencing curiosity before the task, which in turn led to a higher cognitive engagement in the first categorization. Promotion and prevention orientation moderated the type of emotional response to positive feedback. Promotion orientation also predicts cognitive engagement after the feedback of success was provided. Generally results confirmed the positive effect of positive emotions as well as promotion orientation on cognitive engagement.

Integrating Positive and Clinical Psychology: Viewing Human Functioning as Continua from Positive to Negative Can Benefit Clinical Assessment, Interventions and Understandings of Resilience

Article

Full-text available

Jun 2017
COGNITIVE THER RES

In this review we argue in favour of further integration between the disciplines of positive and clinical psychology. We argue that most of the constructs studied by both positive and clinical psychology exist on continua ranging from positive to negative (e.g., gratitude to ingratitude, anxiety to calmness) and so it is meaningless to speak of one or other field studying the " positive " or the " negative ". However, we highlight historical and cultural factors which have led positive and clinical psychologies to focus on different constructs; thus the difference between the fields is more due to the constructs of study rather than their being inherently " positive " or " negative ". We argue that there is much benefit to clinical psychology of considering positive psychology constructs because; (a) constructs studied by positive psychology researchers can independently predict wellbeing when accounting for traditional clinical factors, both cross-sectionally and prospectively, (2) the constructs studied by positive psychologists can interact with risk factors to predict outcomes, thereby conferring resilience, (3) interventions that aim to increase movement towards the positive pole of well-being can be used encourage movement away from the negative pole, either in isolation or alongside traditional clinical interventions, and (4) research from positive psychology can support clinical psychology as it seeks to adapt therapies developed in Western nations to other cultures.

A resilience framework for research, policy, and practice: Contributions from Project Competence

Article

Jan 2003

Harvard Educational Review

Article

Jan 1971

The roles of self-esteem and self-consciousness in the Wortman-Brehm model of reactance and learned helplessness.

Article

Jan 1983

Jo Brockner

• Studied the conditions under which failure would enhance or inhibit subsequent task performance. Based on the theory of C. B. Wortman and J. W. Brehm (1975), it was expected that small amounts of failure would produce reactance (manifested by improved performance at a subsequent task); large amounts would lead to learned helplessness (i.e., impaired later performance). It was further expected that individual differences in self-esteem and private self-consciousness would serve as moderator variables for the effects. In Exp I, 78 college students were exposed to either a small amount or no failure before working on an anagrams task. As predicted, Ss high in self-consciousness, who showed greater reactance arousal in attitude change studies, performed better on the anagrams task than Ss low in self-consciousness in the small-failure condition, but not in the no-failure condition. In Exp II, 119 Ss were pretreated with either a small amount of failure, an extended amount of failure, or no failure before working on the task. A significant Self-Esteem by Helplessness Training interaction emerged. Low self-esteem Ss (low SEs) performed marginally better than did high SEs in the small-failure condition but significantly worse than high SEs in the extended-failure condition. Questionnaire data from Exp II were consistent with the notion that enhanced performance reflected reactance, whereas impaired performance signified helplessness. (20 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved) • Studied the conditions under which failure would enhance or inhibit subsequent task performance. Based on the theory of C. B. Wortman and J. W. Brehm (1975), it was expected that small amounts of failure would produce reactance (manifested by improved performance at a subsequent task); large amounts would lead to learned helplessness (i.e., impaired later performance). It was further expected that individual differences in self-esteem and private self-consciousness would serve as moderator variables for the effects. In Exp I, 78 college students were exposed to either a small amount or no failure before working on an anagrams task. As predicted, Ss high in self-consciousness, who showed greater reactance arousal in attitude change studies, performed better on the anagrams task than Ss low in self-consciousness in the small-failure condition, but not in the no-failure condition. In Exp II, 119 Ss were pretreated with either a small amount of failure, an extended amount of failure, or no failure before working on the task. A significant Self-Esteem by Helplessness Training interaction emerged. Low self-esteem Ss (low SEs) performed marginally better than did high SEs in the small-failure condition but significantly worse than high SEs in the extended-failure condition. Questionnaire data from Exp II were consistent with the notion that enhanced performance reflected reactance, whereas impaired performance signified helplessness. (20 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Self-enhancing reactions to performance feedback in an academic setting

Article

Jan 1997

College students' affective and cognitive reactions to evaluative feedback and the role that their self-esteem played in these reactions were investigated in an academic setting. Seventy-two students completed a questionnaire containing a performance self-esteem scale and questions that assessed how they defined "successful" performance one week prior to a midterm exam. Participants' reactions were then assessed immediately after they were given the exam results. Both affective and cognitive reactions provided overwhelming support for the "weak" form of self-enhancement theory (Shrauger, 1975) and virtually no support for the self-consistency theory (Swann, Griffin, Predmore, & Gaines, 1987). Regardless of their self-esteem levels, students who performed successfully reported higher levels of positive affect, lower levels of negative affect, and were more satisfied with their performance than those who received failure feedback. These "success" students were also more likely to view the feedback as accurate, the exam as a good diagnostic tool, grades as a valid indicator of effort, and make internal attributions of their performances. Students' beliefs that grades reflected their ability was the only reaction that showed a greater self-enhancing tendency among the high self-esteem students.

Mastery goals and contingent self-worth: A field study

Article

Jan 2008

Academic failure lowers self-esteem among students whose self-esteem is contingent on academics; laboratory experiments show that learning orientations reduce this vulnerability. To test whether mastery goals reduce ego-involvement or simply alter the circumstances under which failure lowers self-esteem, we examined students' vulnerability to poor grades in the classroom. One week prior to receiving grades on a term paper, 142 college students completed measures of baseline trait self-esteem, mastery goals, and academic contingency of self-worth; after receiving their grade, they completed a measure of state self-esteem. Controlling for trait self-esteem, we found a Mastery Goal X Contingency X Grade interaction on posttest state self-esteem. Among highly contingent students, mastery goals predicted greater self-esteem vulnerability to grades and ability-validation goals fully mediated the Mastery Goal X Grade interaction. This study suggests that mastery goals do not always create resilient self-esteem among highly contingent students.

Defensive pessimism, optimism, and stimulating alternatives: Some ups and downs of prefactual and counterfactual thinking.

Article

Nov 1996

Lawrence J. Sanna

Four studies investigated the prefactual (alternative preoutcome predictions) and counterfactual (alternative postoutcome "what might have beens") mental simulations of defensive pessimists and optimists. In Study 1, defensive pessimists engaged in upward (better than expected) prefactual thinking, whereas optimists engaged in downward (worse than actuality) counterfactual thinking in reaction to a course exam. In Study 2, defensive pessimists preferred upward prefactual thinking and optimists preferred no prefactual thinking when prefactual thoughts were directly manipulated. In Studies 3 and 4, defensive pessimists and optimists differed in reactions to manipulated success and failure, and these reactions were further moderated by the opportunity to engage in prefactual thinking and the possibility of a second try. Individual differences in strategies of prefactual and counterfactual thinking are discussed.

Influences of perfectionism on motor performance, affect, and causal attributions in response to critical information feedback

Article