Seeking help is essential if people are to access appropriate mental health services. While there are different sources of help, both formal and informal (Rickwood et al., 2005), there is acknowledged value in seeking formal help, in particular talking therapies and psychological services (NICE, 2004). It is therefore essential that people feel they can access them. In universities, amongst a constituency that is often perceived as having a high risk of suicide (Borges et al., 2010), these services are seen as an important arm of general pastoral care and student support (Bishop, 1990; Kitzrow, 2003). Indeed provision of services that are close, on campus are viewed as a key spend in these difficult financial times. For this reason the current study looks at help-seeking in students

and how it is affected, negatively by social forces such as stigma as well as positively by a sense of belonging at university.

Students are an important group for the study of help-seeking. They have high prevalence rates of mental health problems and suicidal ideation. For example, one web-based study of 763 students showed that around one-third were experiencing a mental health problem at the time of test, of which 60% were present 2-years later (Zivin et al., 2009). In addition, a large survey of over 26,000 students in the US, showed that 18% of undergraduates had seriously considered taking their own lives (Drum et al., 2009). Commentators suggest numerous reasons for this trend including the stressors and pressures of student life, and the adjustment to life away from home and family (Furr et al., 2001), with risk factors including financial difficulty, poverty, substance abuse, sexual victimization, and issues related to sexual identity (Eisenberg et al., 2007). However, many students with mental health problems, particularly suicidal ideation, do not seek help from formal sources of support such as university counseling services or mental health services (Drum et al., 2009; Hunt and Eisenberg, 2010). This is despite the fact that these are often the most accessible forms of support for students, particularly for those living away from home.

The single most commonly cited barrier to professional helpseeking is stigma (Corrigan, 2004; Vogel et al., 2009). Mental health stigma can be conceptualized as a set of negative attitudes that represent prejudice or negative stereotypes about people with mental ill health, and in some cases can lead to significant discrimination (Corrigan and Penn, 1999; Corrigan, 2004; Masuda and Latzman, 2011). Stigma toward mental health is generally associated with negative help-seeking attitudes (Leong and Zachar, 1999; Vogel et al., 2005), and this has been shown to be particularly true for people who are experiencing suicidal thoughts (Rickwood et al., 2005; Batterham et al., 2013). Research demonstrates that this may potentially be due to less openness to and a lower perceived value of professional treatment amongst those with a higher stigma of mental health (Coppens et al., 2013). Previous research has also highlighted a desire for social distance from people with mental health issues or seeing mental ill health as a personal weakness as being related to a reluctance to seek professional help (Schomerus et al., 2009; Mojtabai, 2010; Griffiths et al., 2011).

There has been increasing recognition in recent years for the need to focus on reducing the stigma surrounding suicide in order to positively influence help-seeking attitudes amongst at-risk individuals, something that has been highlighted by the National Action Alliance for Suicide Prevention's Research Prioritization Task Force in their 2014 prioritized research agenda (Pearson et al., 2014). Evidence to date has shown that such strategies may be successful; a suicide prevention initiative implemented within a university setting successfully reduced the stigma of mental health problems and improved students' attitudes toward talking about mental health problems and suicide (Pearce et al., 2003). Stigma is far from the only factor influencing help-seeking behaviors however with a growing body of evidence detailing how it is not just attitudinal but also experiential variables that may impact upon how professional help is viewed.

Past experience with help-seeking has consistently been shown to influence attitudes toward help-seeking for mental health and suicide. These may be either personal experiences (e.g., Rickwood et al., 2005), or knowing someone else that has previously engaged with mental health professionals. Research suggests that attitudes toward formal support services for mental health and suicide are at least partially transmitted through an individual's social network, which also plays a vital role in determining whether a person makes the choice to seek professional help (Rickwood and Braithwaite, 1994; Angermeyer et al., 1999; Vogel et al., 2007). For example, university students who actually sought mental health services knew someone else who had sought help 92–95% of the time, and those who knew someone who had previously sought help had more positive attitudes toward mental health services (Vogel et al., 2007). Of course where these experiences have been negative they can have the opposite effect. A review focusing on determinants of help-seeking amongst young people experiencing issues with suicide found that when past experiences of seeking help were negative, particularly when the young person felt they were not helped or that their problems weren't taken seriously, they acted as substantial barriers to future help-seeking intentions and impacted heavily upon attitudes toward professional help (Rickwood et al., 2005).

Help-seeking attitudes may also be influenced by past exposure to suicide or experience with suicidal behaviors. Whilst some studies found no significant relationship between exposure to suicide and help-seeking attitudes or intentions (Calear et al., 2014), others found that exposure to suicide led to more negative attitudes toward help-seeking (Chan et al., 2014). Moreover, research also suggests that attitudes may differ dependent on the amount of exposure. Just 5% of Irish men would turn to a mental health professional as a source of support for suicide if they had no previous exposure to suicide. This increased to 19% when they knew one person who died by suicide but dropped to 8% again when they knew of more than one suicide (Begley et al., 2004).

Therefore, whilst it seems that this factor may influence attitudes toward help-seeking, the way in which this relationship works has not yet been fully established. On the one hand it is thought that past experience with help-seeking may act as a form of knowledge or mental health literacy which is deemed important in the help-seeking process (Gulliver et al., 2010; Coppens et al., 2013). Students who know someone that have accessed mental health services and that have positive expectations about how friends and family would think of them if they sought this type of service professional help are more likely to have positive attitudes to help-seeking (Gulliver et al., 2010; Coppens et al., 2013). These findings implicate shared attitudes and feelings of belonging, two important components of social identity, in determining help-seeking behavior which is entirely consistent with recent research which has pointed to the importance of shared social identities in determining access and availability to social support (Haslam et al., 2005).

Recent empirical evidence demonstrates that where individuals share group membership, they are more likely to provide each other with support, receive support, and interpret support offered in the manner in which it is intended, in comparison to those where shared membership is absent (Reicher et al., 2006). However, the capacity for this social support to affect appraisal depends on the match between group membership of the support provider and recipient. So support does not always have the same or equivalent impact (Haslam et al., 2005). It seems to vary systematically as a function of the group membership of the support provider. For example, university students who were informed that a task was challenging rather than stressful appraised the task more positively and demonstrated less cardiac reactivity when the information provided came from an ingroup member rather than an outgroup member (Haslam et al., 2004; Gallagher et al., 2014; For a review of the potentially harmful effects that intense emotions, particularly stress, can have on cardiovascular health, see Steptoe and Kivimäki, 2013) This suggests that legitimacy of informational exchanges is shaped by a perceiver's belief that it originates from a relevant ingroup member who has direct personal experience and is therefore qualified to comment on the particular event (Haslam et al., 1996; Levine, 1999). Importantly however, it also suggests that support is socially mediated and will interact with its content (Gallagher et al., 2014). So whilst support offered by an ingroup source often appears to be the most beneficial, the impact of availing of support from within the group where it is potentially stigmatizing is less well-understood.

The current study then will investigate student attitudes toward help-seeking from a university source, which have been shown to be highly predictive of actual help-seeking behaviors (Vogel et al., 2005). It is hypothesized that stigma of helpseeking from a source within the ingroup (i.e., the university) will be successfully predicted by the factors discussed above which have previously been shown to be influential, namely stigma of suicide, experience of help-seeking, and exposure to suicide. As gender differences have continuously been noted in helpseeking behaviors and attitudes (Andrews et al., 2001; Gonzalez et al., 2005; Vogel et al., 2011) this will also be included in our predictive model. We further hypothesize that identification with the ingroup will predict stigma of help-seeking from a university source over and above the already known predictors and demographics. Based on previous research it can be expected that high group identification will result in a lower stigma of help-seeking from formal university support services, whilst low identification with the ingroup may act as a barrier to helpseeking when the source of help is drawn from that group.

# Materials and Methods

We administered a comprehensive battery of questionnaires online using a web-based interface, SurveyMonkey, which allows the collection of quantitative and qualitative data. The study received full approval from the Education and Health Sciences Research Ethics Committee at the University of Limerick (2014\_06\_26\_EHS).

### Participants

The study sample comprised of students enrolled at the University of Limerick in the mid-west of Ireland. This population is largely comprised of Irish students, with 91% of the 14,300 students enrolled in the University of Limerick claiming Irish nationality. All registered students at the university were invited to participate in the study via an email web-link, with 693 volunteers clicking on the web-link in the first instance. The first page of the survey provided study information, assuring volunteers that participation was voluntary and anonymous, and screening questions relevant to the exclusion criteria. These were that participants had to be a current student and over the age of 18, which eliminated 33 respondents. The final sample consisted of 493 students who completed all elements of the survey, of whom 193 were male (39.1%). Participant ages ranged from 18 to 61 (M = 25.22, SD = 9.56). The majority of students that were excluded from the final sample due to non-completion did not proceed past either the information sheet (n = 63), or providing their demographic information at the beginning of the survey, and so did not respond to any of the measures assessing our key variables of interest. For those that completed the demographic information, One-Way ANOVA's revealed that there was no significant difference between completers and non-completers in either age [F(1, 659) = 0.96, p = 0.27] or gender [F(1, 659) = 0.74, p = 0.38]. Although the final sample of 493 students is representative of the total Irish third-level student population of 217,520 (2014/2015; HEA, 2015), with 384 participants required to achieve a 95% confidence level and confidence interval of 5, the participants in this study were all drawn from a single university.

### Measures

#### Exposure to Suicide

Exposure to suicide was measured by two questions that were composed for this study, "Do you know somebody who has died by suicide?" and "Have you direct personal experience with suicidal thoughts, feelings or behaviors?." Answers were in a Yes/No format with "No" given a score of zero and "Yes" given a score of one. A total score for exposure to suicide was then obtained by summing these two items, with a potential range of 0–2 and higher scores indicating more exposure.

### Experience with Help-seeking

Experience with seeking help was assessed through a single question that again was composed for this study: "Have you or somebody you know ever received professional help for any issues related to mental health?." Responses were in a Yes/No format (No = 0, Yes = 1).

### Stigma of Suicide

Stigma of suicide was measured using the Stigma of Suicide Attempt (STOSA; Scocco et al., 2012) scale. This 12-item scale is based on Link's (1987) Perceived Discrimination-Devaluation Scale (PDD) and measures the perceived public stigma of those who attempted suicide. This particular scale was chosen as measuring public stigma rather than personal stigma has been shown to remove the potential social desirability response bias and give a more accurate reflection of internalized stigma (Griffiths et al., 2006; Peluso and Blay, 2009; Calear et al., 2011). Moreover, unlike most measures of suicide stigma, STOSA questions are oriented toward a person who attempted suicide rather than a person who died by suicide. Survivors of suicide attempts have been reported to be particularly stigmatized and often dismissed as attention-seekers, with little in the way of support offered (Sudak et al., 2008). As such this group can be seen to reflect the extent of negative attitudes and stigma amongst the general public toward suicide and suicidal behaviors. We also reasoned that by framing questions toward suicide attempts rather than the person who died by suicide underlying stigma may be revealed as the traditional reluctance of people to stray from the rhetoric of "never speaking ill of the dead" is eliminated. The 12 questions in the STOSA scale follow the semantic structure of the PDD, but investigate attempted suicide rather than depression, e.g., "Most people would treat a person who has attempted suicide just as they would treat anyone." Responses were scored on a 4-point Likert scale ranging from 1 (strongly agree) to 4 (strongly disagree), with half the items reverse-scored. Mean scores were calculated with higher scores indicating higher levels of stigma (α = 0.85).

#### Group Identification

Ingroup identification was assessed using Leach et al.'s (2008) 10-item Self-Investment scale which was used to measure identification with the individual's university. The scale design stipulates that for each item the researcher should insert the name of the group under investigation in place of "[Ingroup]." This widely used measure is comprised of three subscales, Solidarity (α = 0.84), e.g., "I feel committed to people in my university," Satisfaction (α = 0.90), e.g., "I think that people in my university have a lot to be proud of " and Centrality (α = 0.82), e.g., "Being in my university is an important part of how I see myself," but only the overall scale was used in the current study. Items are scored on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), with a higher score indicating a greater level of identification with the ingroup (α = 0.90).

#### Stigma of Help-seeking from the Ingroup

The Self-Stigma of Seeking Help scale (SSOSH; Vogel et al., 2006) measures a person's self-evaluation for seeking professional psychological help. This 10-item scale is scored on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), with five items scored inversely. A higher total score indicates a higher stigma of seeking help. In the current study the SSOSH was used to predict attitudes and willingness of a person to seek professional help from the mental health service in their university if they were experiencing issues related to suicide or mental health, and the wording was adjusted to reflect this; for example, "It would make me feel inferior to ask a therapist in my university for help." This yielded a Cronbach's alpha of 0.87, which was in line with the range of internal consistencies demonstrated in previous college samples (0.86–0.90; Vogel et al., 2006).

# Analytic Procedure

### Preliminary Analysis

Pearson's correlation coefficients (point-biserial correlation coefficients for dichotomous variables) were computed in order to investigate the relationships between variables (see **Table 1**). These revealed significant positive relationships between the dependent variable (stigma of help-seeking) and all predictor

#### TABLE 1 | Pearson's correlation coefficients for study variables.

\*p < 0.05, \*\*p < 0.01 (two-tailed). N = 493. #Coefficient for gender represents a point-biserial correlation given that it is a dichotomous variable).

variables other than exposure to suicide. Although a positive relationship was expected for stigma of suicide based on previous research, the direction of this relationship was more surprising for group identification and experience with helpseeking. Gender differences for study variables were assessed using a series of analyses of variance to see if there was a need to conduct analysis separately for males and females.

#### Regression Analysis

Following preliminary analysis, a hierarchical multiple regression was conducted using IBM SPSS Statistics, Version 21, in order to predict stigma of help-seeking from an ingroup source. This analytic technique allowed for the additional predictive value of our key variable of interest (group identification) to be established while controlling for previously known predictors. Variables were added in two blocks with known predictors of help-seeking entered in Block 1 (gender, sigma of suicide, exposure to suicide, and experience with help-seeking) and group identification added in Block 2.

# Results

#### Descriptive Statistics

Exposure to suicide was high amongst survey respondents with 74.6% of participants (n = 368) indicating that they knew someone who died by suicide and 66.9% (n = 330) reporting that they had direct personal experience with suicidal thoughts, feelings of behaviors. Experience with professional help-seeking was also high; 72.6% (n = 358) of the sample knew someone who had received professional help for issues related to mental health. Stigma of help-seeking was prominent amongst participants, with the mean score of 33.83 (SD = 7.26) falling within the range that Vogel et al. (2006) class as being high (32+). Gender differences for stigma of suicide, group identification and stigma of help-seeking were explored using a series of analyses of variances, the findings of which are presented in **Table 2**. Although some gender differences were noted the overall trend in the relationship between our key variables of interest remained the same (i.e., for both males and females stigma of help-seeking increased with higher group identification; see **Figure 1**), meaning they were not treated separately for the main analysis.

TABLE 2 | Analysis of variances for gender differences in study variables.

#### Regression Analysis

A hierarchical multiple regression analysis was carried out with stigma of help-seeking as the outcome variable. As gender, experience with help-seeking, exposure to suicide, and stigma of suicide are already known predictors of help-seeking these were entered into the model in Block 1. Group identification was then added to the model in Block 2 to establish the added predictive value of this variable once the known predictors were controlled for. Regression statistics are reported in **Table 3**.

At Block 1, the model was found to be significant, F(3, 488) = 14.54, p < 0.001, with gender, experience with help-seeking, exposure to suicide and stigma of suicide accounting for 10.7% of the variance in stigma of help-seeking, and each predictor with the exception of exposure to suicide making a significant individual contribution. Adding group identification to the model in Block 2 accounted for an additional 1.8% of variance and this change in R <sup>2</sup> was significant, F(1, 487) = 10.12, p = 0.002. Together these four variables explained 12.5% of the variance in stigma of help-seeking. Each of the variables entered in Block 1 one remained significant predictors once group identification was added to the model, with the exception of exposure to suicide which remained non-significant.

Stigma of suicide was the strongest predictor; for every additional unit on the stigma of suicide scale, stigma of helpseeking increases by 4.03. This was followed by experience with

TABLE 3 | Hierarchical regression coefficients for variables predicting stigma of help-seeking.

\*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001 (two-tailed). N = 493.

help-seeking, with those who knew someone that had received professional help for mental health problems scoring higher on the stigma of help-seeking scale by 1.46. Our key variable of interest, group identification had a positive relationship with stigma of help-seeking. Every additional unit on the group identification scale resulted in a 0.10 increase on the stigma of help-seeking scale.

# Discussion

This study aimed to predict students' stigma of seeking help from their university mental health service using a combination of already known predictors in addition to a previously overlooked factor, group identification. These variables, namely gender, experience with help-seeking, exposure to suicide, stigma of suicide, and group identification, were found to significantly predict stigma of help-seeking from the university. Unexpectedly, higher levels of group identification, in this case identification with the university, were found to predict higher levels of stigma of help-seeking from the ingroup over and above the other known predictors. Thus, students who identified more strongly with their university demonstrated higher stigma in seeking help from university mental health services. These findings were not as we had predicted.

Similar to previous studies (Corrigan, 2004; Vogel et al., 2009), those perceiving higher stigma of suicide also demonstrated a higher stigma of help-seeking. For those who knew someone who had received professional mental health support in the past however, stigma of help-seeking was also higher. This contradicts previous findings showing that past experience with help-seeking is generally a facilitator of future help-seeking (e.g., Angermeyer et al., 1999; Vogel et al., 2007), but supports Rickwood et al. (2005) claims that such experience can also act as a barrier if the experience with mental health services was negative. Females were found to have a higher stigma toward help-seeking than males, which again deviates from past findings that demonstrate the opposite (Andrews et al., 2001; Gonzalez et al., 2005; Vogel et al., 2011). This may be due to the fact that the current sample was self-selected, with the possibility that only males who had an interest or awareness around mental health participated in the study.

In terms of theory, these findings add to the growing body of literature that link social identity and shared social relationships to both mental and physical health (Cohen, 2004). Social support it would appear depends on the match between group membership of the support provider and recipient, and support does not always have the same or equivalent impact (Haslam et al., 2005). We believe the results evident in this study are particularly congruent with self-categorization theory (Turner et al., 1987, 1994) which has an emphasis on the consequences of dynamics within groups in determining behavior. Our study provides evidence that it is those who are most identified with their university that has the most difficulty seeking help from its counseling services. Normative fit, a key concept associated with self-categorization theory (Turner et al., 1987), is an important element of the explanation for the findings in this study. This concept can be described as the extent to which the perceived behavior or attributes of group members conforms to the perceiver's knowledge-based expectations about the social meaning of group membership (Oakes et al., 1994). If a person seeking help perceives their normative fit to the group to be poor because of their problem (in this case a stigmatized mental health issue), availing of help from an ingroup source is very problematic as they are unlikely to want to expose that they are violating the perceived social norms of the group. As it was perceived stigma of suicide amongst ingroup members that was the strongest predictor of the stigma of help-seeking in this study, this concept is particularly relevant.

In terms of practice our findings suggest that help-seeking and offering support to students through university counseling is particularly challenging, not only because of the stigma of mental health issues but also because of the sense of community that being part of a university invokes. Whilst previous research has shown that identification with a particular group can be a basis for both giving and receiving social support, this study is the first to consider the role of group identification in seeking help. Shared social identities are of course associated with shared values and characteristics (Turner, 1975) and if these are values that stigmatize an issue, the ability to avail of support for that issue within the group is compromised. Importantly social identities have performative elements, they can drive the things we do as well as the how we feel and think (Walsh et al., 2015). So whilst a university counseling service has the advantage of shared university affiliation when it offers support to its students, students may be motivated to avoid availing of this service to avoid stigma within their own group. Indeed, that is what was found in the current study with students who strongly identified with their university demonstrating greater stigma toward helpseeking than those who identified less as a university student.

This leaves university counseling services with a dilemma because identification with the university also has considerable benefits. These include higher levels of wellbeing and better adjustment to university life (e.g., Bettencourt et al., 1999; Amiot et al., 2010). In order to address these conflicting processes it may be necessary for universities to reevaluate the organization of their mental health services. It is possible that counseling services off campus, offered by external agents may be more attractive to those students who are strongly affiliated to their institution; if counseling services were perceived as more independent of the institution in terms of physical proximity, embeddedness and because of their branding, students may be more likely to seek help. This is not to suggest that mental health services should be removed in their entirety from university campuses however. These are vital resources that are utilized by a vast number of students and for the most part provide an invaluable source of help and support. Rather a variety of sources may be the solution, with both internal and external options made available to students to ensure the needs of widest possible range are met.

It is important to note here that in the university where this study was conducted, counseling services are very much embedded within the university and its systems, including by proximity, by their very clear presence in all guidance offered to students, and the role they play in supporting students with academic processes (i.e., mitigation). Thus, it is important that future research compares institutions where counseling services are more or less embedded and perceived as part of the ingroup in order to further understand the practice implications of the effects we have reported here. Other limitations of the current study include the way in which participants were recruited. All of the students in our institution were emailed and asked to participate in this study. Our final sample represents a selfselected sample of this total population and as a consequence these respondents may not be representative of the wider student pool. Our sense is that students that were particularly interested in mental health issues may have been more inclined to complete the study. In addition, the population from which this sample was drawn represents a particularly homogenous group in terms of nationality and background, with 91% of all students in the university where the study was conducted identifying as Irish. Although this homogeneity may have contributed to the overall high level of identification with their university, it must also be noted that findings may differ in student bodies that are more diverse, or indeed amongst different cultures.

Future research is needed to address both this and other issues. As the effect sizes in this study were quite small, there is a need for more research to confirm our findings. This should also take into consideration additional factors that may influence help-seeking but were not included in the current study. For example, beliefs about the usefulness or effectiveness of mental health services have previously been shown to be important predictors of helpseeking behavior (Downs and Eisenberg, 2012) whilst intentions to seek help are thought to be influential here too (Schomerus and Angermeyer, 2008). Although past experience with suicide and help-seeking was measured, these questions did not go into depth or probe for the closeness of that experience, for example whether it was oneself, family member, friend, or other person. Furthermore, the current mental health status of the sample may be influential, and should be incorporated into future research. It should also be explored if students' stigma of help-seeking differs for internal and external (e.g., GP, independent counseling service) sources of help. Finally, our study was based solely on self-report measures as stigma and group identification are entirely subjective concepts and are crucial to decisions to seek help. However, this does mean that the study should be interpreted with due caution as a consequence of shared variance associated with the method, particularly as our results are correlational. Future research could usefully employ a

# References

longitudinal design to explore stigma and group identification as true determinants of help-seeking.

In conclusion, the current study found that that identification with their university may influence student attitudes toward seeking help from the university mental health service. After controlling for already known predictors of help-seeking for issues related to suicide and mental health (stigma of suicide, gender, experience with help-seeking, and exposure to suicide), it was found that students who identified more strongly with their university demonstrated a higher stigma of seeking help from this source. Possible explanations for this lie with the self-categorization theory and normative fit. This finding has potential implications for mental health service provision across higher level institutes, who may need to consider the need for a greater separation from university involvement in such services.

# Acknowledgments

This research was funded by the Irish Research Council Enterprise Partnership Scheme in conjunction with Pieta House.

European countries baseline survey prior to the OSPI-Europe intervention. J. Affect. Disord. 150, 320–329. doi: 10.1016/j.jad.2013.04.013

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Kearns, Muldoon, Msetfi and Surgenor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# The impact of anticipated stigma on psychological and physical health problems in the unemployed group

*Aisling T. O'Donnell\*, Fiona Corrigan and Stephen Gallagher*

*Department of Psychology and Centre for Social Issues Research, University of Limerick, Limerick, Ireland*

Previous research has demonstrated that the unemployed suffer increased psychological and physical health problems compared to their employed counterparts. Further, unemployment leads to an unwanted new social identity that is stigmatizing, and stigma is known to be a stressor causing psychological and physical health problems. However, it is not yet known whether being stigmatized as an unemployed group member is associated with psychological and physical health in this group. The current study tested the impact of anticipated stigma (AS) on psychological distress (PD) and physical health problems, operationalized as somatic symptoms (SSs), in a volunteer sample of unemployed people. Results revealed that AS had a direct effect on both PD and SSs, such that greater AS significantly predicted higher levels of both. Moreover, the direct effect on SSs became non-significant when PD was taken into account. Thus, to the extent that unemployed participants anticipated experiencing greater stigma, they also reported increased PD, and this PD predicted increased SSs. Our findings complement and extend the existing literature on the relationships between stigmatized identities, PD and physical health problems, particularly in relation to the unemployed group. This group is important to consider both theoretically, given the unwanted and transient nature of the identity compared to other stigmatized identities, but also practically, as the findings indicate a need to orient to the perceived valence of the unemployed identity and its effects on psychological and physical health.

Keywords: anticipated stigma, stigmatization, psychological distress, depression, anxiety, physical health symptoms, unemployment, unemployed identity

# Introduction

Previous research has demonstrated that the unemployed suffer increased health problems compared to their employed counterparts. This is important as the aftereffects of the global financial crisis mean that unemployment rates are still high at the time of writing. In Ireland, the context of the current paper, the unemployment rate was 9.9% for the first quarter of 2015 (CSO, 2015), representing a large increase on 10 years previously (only 4.2%; CSO, 2005) and higher than the harmonized average for the OECD area for mid-2014 of 7.3% (OECD, 2014). Such high levels of unemployment can have far-reaching effects on health: there is evidence that unemployment is associated with both increased psychological health problems (Paul and Moser, 2009; Eriksson et al., 2010; Blau et al., 2013; Breslin and Breslin, 2013) and increased physical health problems, including self-rated physical health, illness and symptoms (McKee-Ryan et al., 2005) and

#### *Edited by:*

*Gianluca Castelnuovo, Università Cattolica del Sacro Cuore, Italy Donal Gerard Fortune, Health Service, Ireland*

#### *Reviewed by:*

*Roger Christopher McIntosh, University of Miami, USA Caroline Heary, NUI Galway, Ireland*

#### *\*Correspondence:*

*Aisling T. O'Donnell, Department of Psychology and Centre for Social Issues Research, University of Limerick, Limerick, Ireland<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Psychology for Clinical Settings, a section of the journal Frontiers in Psychology*

> *Received: 10 April 2015 Accepted: 07 August 2015 Published: 25 August 2015*

#### *Citation:*

*O'Donnell AT, Corrigan F and Gallagher S (2015) The impact of anticipated stigma on psychological and physical health problems in the unemployed group. Front. Psychol. 6:1263. doi: 10.3389/fpsyg.2015.01263* psychosomatic disorders such as headache, stomach ache and sleeping disorders (Linn et al., 1985; Rantakeisu et al., 1997). Current known or hypothesized reasons for this include the impact of financial strain (Breslin and Breslin, 2013), stress associated with income loss (Eriksson et al., 2010), but also latent deprivation of employment-related functions (time structure, social contact, collective purpose, status, and activity; Jahoda, 1982; see also Creed and McIntyre, 2001). There is also a more general proposition that unemployment is in itself a stressful event (Linn et al., 1985; McKee-Ryan et al., 2005; Eriksson et al., 2010). Following on from this, and as noted in the literature (Eriksson et al., 2010; Quinn and Earnshaw, 2011), one missing piece of the puzzle in explaining health disparities between advantaged and disadvantaged groups – such as the unemployed – may be the effect of stigma. Stigma is the social devaluation of a person or group on the basis of some characteristic (Goffman, 1963) – in this case, unemploymentrelated stigma. To expand on this, stigmatization involves labeling someone as different, associating them with some negative stereotype on this basis, and discriminating against them (Link and Phelan, 2006). To date, the research on stigma and health among the unemployed is sparse, and given the negative impact of stigma for other stressed groups (Kaur and Van Brakel, 2002; Nyblade et al., 2003; Jacoby et al., 2004), it is worthy of investigation.

While all individuals are said to have a varied self-concept that is partly made up of many different social identities, some chosen (e.g., scientist) and some ascribed at birth (e.g., woman; Tajfel and Turner, 1979), other identities, such as unemployment, are thrust upon them. It is known that unemployment leads to an unwanted new social identity that is stigmatizing (Cullen and Hodgetts, 2001; Letkemann, 2002). Further, studies at both the population and individual level show that employers discriminate by declining to employ those who are already unemployed. In some of these studies it is assumed that there is a 'stigma effect'; that is, that the unwillingness to hire the unemployed is driven by inferences that their unemployment is due to personal failings (e.g., Oberholzer-Gee, 2008; Biewen and Steffes, 2010; Contini and Richiardi, 2012). However, in other studies, people's stigmatized views of the unemployed have been directly measured (e.g., Furåker and Blomsterberg, 2003) and indeed greater stigmatization of the unemployed has been shown to predict reduced willingness to employ them (e.g., Ho et al., 2011; see also Karren and Sherman, 2012, for a review). Consistent with this evidence, there has also been research focusing on the experience of unemployment, which demonstrates that the unemployed perceive it as stigmatizing (e.g., Rantakeisu et al., 1997; Kulik, 2000; Cullen and Hodgetts, 2001; Letkemann, 2002; Lee et al., 2005). Despite these studies showing the unemployed experience stigma, to our knowledge, the association between stigma and health in this group has yet to be examined.

Stigma is widely understood to be a stressor causing psychological and physical health problems. We know from previous research that stress in general impacts well-being. For example, it has been shown that stress can lead to psychological distress (PD; e.g., Schulz et al., 1995; Phillips et al., 2015) and that collectively, stress and PD can impact physical health (e.g., Cohen and Williamson, 1991; Hoge et al., 2007; Springer et al., 2007; Springer, 2009; Gallagher and Whiteley, 2013). Particularly relevant to the current study is the large body of evidence related to stigmatized identities other than unemployment, demonstrating that these stigmatized identities impact negatively on health and well-being in terms of: depression and/or anxiety (Markowitz, 1998; Meyer, 2003; Link and Phelan, 2006; Cluver et al., 2008; Quinn and Chaudoir, 2009; Quinn et al., 2014), post-traumatic stress (Katz and Nevid, 2005; Cluver et al., 2008), reduced quality of life (Earnshaw and Quinn, 2011; Earnshaw et al., 2011), reduced self-esteem (Chaudoir and Quinn, 2010), negative affect (Hatzenbuehler et al., 2009) and poor physical health, such as increased illness symptoms (e.g., chest pain, nausea, coughing; Quinn and Chaudoir, 2009), and even chronic illness comorbidity and low CD4 count in individuals with HIV/AIDS (Earnshaw et al., 2013). Importantly, many of these studies refer to stigmatized identities that are concealable, such as HIV/AIDS, mental illness and certain chronic diseases. Unemployment is also a concealable stigmatized identity, but it has not yet been clearly demonstrated how stigmatization associated with this particular identity is associated with increased PD and physical health problems.

At this point it should be noted that in the case of some stigmatized identities, it is clear that physical health problems precede stigmatization and PD because the stigma relates to a physical health problem (e.g., in the case of HIV/AIDS) which then leads to PD. In the case of unemployment, while there has been some suggestion that people experiencing ill health disproportionately self-select into unemployment, there is also evidence that there is a detrimental effect of unemployment on physical health that is not caused by self-selection (Korpi, 2001; Wanberg, 2012). Moreover, it is possible to investigate whether unemployment precedes psychological and physical ill health by controlling for illnesses experienced prior to the onset of unemployment.

It has not yet been demonstrated whether the belief that one is being stigmatized as an unemployed group member might drive the negative impact of unemployment on psychological and physical health. The current study will address this gap in the literature. Given that the anticipation of stigma has been identified as particularly relevant in studies of other concealable stigmatized identities (e.g., Earnshaw and Quinn, 2011; Earnshaw et al., 2011, 2013), and given that it can be even more disruptive to people's lives than experienced discrimination (Gilbert and Walker, 2010), the current study will focus on the impact of anticipated stigma (AS) associated with unemployment. We measure PD as a composite of depression and anxiety, both outcomes that have been identified as important and relevant in the literatures on unemployment (Linn et al., 1985; McKee-Ryan et al., 2005; Paul and Moser, 2009; Wanberg, 2012), stress (Schulz et al., 1995; Springer et al., 2007), and stigma (Markowitz, 1998; Cluver et al., 2008; Quinn and Chaudoir, 2009; Quinn et al., 2014). Finally we operationalize physical health via self-report of somatic symptoms (SSs), again a commonly used measure of physical health complaints (e.g., Hoge et al., 2007; Springer et al., 2007). We then test whether higher levels of AS are associated with increased PD and SSs (i.e., physical health problems) and also whether any effect of AS on SSs is carried by the effect of AS on PD.

# Materials and Methods

# Participants

Forty-eight people based in a small city in Ireland and currently experiencing unemployment took part in the study (15 male, 33 female). Their ages ranged from 18 to 65 years (*M* = 33.49, SD = 13.14; one participant did not indicate their age). The majority of participants (87.5%) reported that they had not been diagnosed with any mental or physical illness before becoming unemployed. Participants had been unemployed for a minimum of 1 month and a maximum of 120 months (10 years). The mean length of time unemployed was 20 months (1 year and 8 months; SD = 28.99). In terms of education level, participants ranged from those who had attended some secondary school but not completed it, to those with postgraduate degrees. The most common level of education among the sample was holding an undergraduate degree. Most participants were either single (45.8%) or married/cohabiting (43.8%), with a smaller proportion reporting being either separated/divorced (6.3%), widowed (2.1%), or declining to indicate marital status (2.1%). Household income for the participants ranged from less than €20,000 to somewhere between €60,001 and 80,000; however, the modal income bracket was the lowest one (€0–20,000).

## Procedure

Ethical approval was granted by our Faculty's Research Ethics Committee, and indeed the research was conducted in line with the ethical principles of the Declaration of Helsinki and the American Psychological Association (APA, 2010). Participants were recruited to take part in the study either online, via advertisements circulated on Twitter and Facebook, or in person at Social Welfare offices, and through groups and organizations geared toward helping the unemployed. It was possible to complete the survey either online, using Questback software, or using a pen-and-paper version of the questionnaire, depending on the participant's preference. Online advertisements included a link to the online survey, but those recruited online could still opt to receive a paper version of the survey if preferred, and likewise those recruited in person could also choose the online version. By necessity, those recruited in person had some contact with the research team, although they completed the surveys themselves, while those recruited online had no contact. All participants were informed that the study was investigating the health outcomes of unemployment. Participants indicated their informed consent either by signing or by ticking a box, depending on their mode of participation. Participants did not receive compensation for completing the survey.

### Measures

Participants first responded to demographic items and then completed the following measures, all of which are reliable and valid as outlined below. As indicated in the Introduction, AS was measured as a predictor variable, PD as a mediator variable, and SSs as an outcome variable.

Anticipated Stigma An adapted version of the Day-to-Day Discrimination scale (Kessler et al., 1999) was used to measure AS. A similarly adapted measure has previously been used to assess AS amongst a sample possessing various concealable stigmatized identities (Quinn and Chaudoir, 2009). The original scale lists nine examples of discrimination, and participants must respond how often these have occurred to them in the past. In the present study, the same nine items were used, but the instruction was adapted to ask participants to indicate how likely or unlikely they think each one would be to occur if people knew about their unemployment status. In this way, the measure was used to capture the extent to which participants anticipated being socially stigmatized if they were to reveal their unemployed identity. Two example items were "People acting as if you are inferior" and "Being treated with less respect than others." Participants indicated their responses on a scale ranging from 1 (Not at all likely) to 5 (Very likely). Total scores can range from 9 to 45 with higher scores indicating greater AS. This scale has shown good internal reliability and construct validity in previous studies (Paradies, 2006), and in the current study also demonstrated high internal reliability (α = 0.90).

Psychological Distress Psychological distress was measured by assessing participants' levels of depression and anxiety using the Hospital Anxiety and Depression Scale (HADS; Zigmond and Snaith, 1983). This measure has been demonstrated as effective in assessing the severity of anxiety and depression symptoms in the general population as well as psychiatric and primary care patients (Bjelland et al., 2002), and has also been utilized in previous research with unemployed samples (Berth et al., 2003; Limm et al., 2012). In the present study, internal reliability was very good (α = 0.91). Responses to this 14-item scale were indicated on four point scales ranging from 0 to 3, although anchors varied depending on the item. Seven items were reverse scored so that higher scores denoted more PD (scores can range from 0 to 42).

Somatic Symptoms Participants' experience of SSs was measured using the 14 item Physical Health Questionnaire (PHQ; Schat et al., 2005). Participants indicated how often they experienced various SSs, including headaches, constipation/diarrhea and colds, over the last year using a scale ranging from 1 (Not at all) to 7 (All of the time). One item was reverse scored, such that higher scores denoted more impaired physical well-being. In the present study, all items were summed into one total score, which has been done in previous research (e.g., Schat and Kelloway, 2003; Arnold and Dupré, 2012). Total scores can range from 14 to 98. As noted by Dupré and colleagues, self-perceived health status has been shown to accurately predict actual health outcomes in prior research (Dupré and Day, 2007; Arnold and Dupré, 2012). This particular scale has been used to measure somatic health in other distressed samples (Cantwell et al., 2014) and has also been employed in previous research with an unemployed sample (Carnicella, 2013). In the present study it demonstrated high internal reliability (α = 0.88).

### Data Analysis

The impact of AS on both PD and SSs was tested using simple linear regression analyses. Bootstrapping methods (Hayes, 2009) were then used to determine whether the effect of AS on SSs might be partly accounted for by the effect of AS on PD. We chose bootstrapping because it allows for the analysis of data that are not normally distributed, and because it works by taking repeated samples from the dataset, thousands of times, and estimating the indirect effect with each of these resampled datasets. This is particularly useful for datasets that are relatively small, such as this one. We used IBM SPSS 20 to analyze the data, and to carry out the mediation analysis we used the custom dialog PROCESS for SPSS by Hayes (2013).

# Results

### Descriptive Statistics

**Table 1** presents the means, standard deviations and correlations between AS, PD, and SSs. It also contains data on potential confounds, i.e., the socio-demographic variables discussed earlier. Mean levels of AS were moderate, being slightly below the mid-point of the scale, which is comparable to studies of other stigmatized identities (e.g., Earnshaw et al., 2013; Quinn et al., 2014). Mean levels of PD would be classified as mild (Zigmond and Snaith, 1983). Classifications are not available for the PHQ, but the mean score is just under the mid-point and is comparable with levels observed in other recent studies (e.g., Cantwell et al., 2014) so can be considered moderate.

As can be seen below, AS, PD, and SSs were significantly correlated with one another. These associations were positive, such that unemployed people who reported higher AS reported both greater PD and more SSs; similarly, those who reported higher PD also reported more SSs. There were no significant correlations between these variables and any of the potentially confounding variables, but the duration of unemployment in months was marginally associated with PD and SSs.

# Testing the Effect of Anticipated Stigma on Somatic Symptoms as Mediated by Psychological Distress

The aim of this analysis was to test whether the direct effect of AS on SSs would be mediated by PD. We tested for mediation by regressing the predictor variable, AS, on the outcome variable, SSs, while also including the proposed mediator, PD. We first conducted these analyses including the six potential confounds identified above as covariates, specifically because one of them was found to be marginally associated with two of the key measures. None of the covariates was significant in the model, and the results were the same as when we conducted the analyses without the covariates. As such, here we report the results without controlling for these variables, as it allows us to include the Kappa squared (κ2) effect size (Preacher and Kelley, 2011), which cannot be calculated for models that include covariates.

The mediation analysis was conducted using 5000 bootstrap samples and confirmed that there was a significant direct effect of AS on SSs, but that as predicted, this was rendered nonsignificant when the effect of PD was also taken into account (see **Table 2** below for parameter estimates, and **Figure 1** for an illustration of the effects). Thus, it appears that the association between AS and SSs in unemployed adults is underlined by PD.

It can be seen that collectively, AS and PD account for 44% of the variance in SSs. Moreover, the Kappa squared effect size was found to be 0.38, which represents a large effect (Preacher and Kelley, 2011).

# Discussion

The current study aimed to investigate whether the anticipation of being stigmatized as an unemployed group member might drive the negative impact of unemployment on psychological and physical health. To address this question, we surveyed a sample of people experiencing unemployment to ascertain their selfreported levels of AS, PD, and SSs. As predicted, results showed that higher levels of AS were associated with both increased PD and increased SSs. Moreover, the effect of AS on SSs disappeared when PD was taken into account. This suggests that AS directly

∗ ∗*Correlation is significant at the 0.001 level;* <sup>∗</sup>*correlation is significant at the 0.01 level;* †*correlation is marginal (p* <sup>≤</sup> *0.06).*

TABLE 2 | Parameter estimates of the model examining the mediating role of psychological distress in the relationship between anticipated stigma and somatic symptoms.

*We have also illustrated regression weights for a, b, c, and c' in Figure 1. For information, R*<sup>2</sup> *(y, x) is the proportion of variance in y explained by x, R*<sup>2</sup> *(m, x) is the proportion of variance in m explained by x and m. the 95% CI for a* × *b is obtained by the bias-corrected bootstrap with 5000 resamples. AS (anticipated stigma) is the predictor variable (x), PD (psychological distress) is the mediator (m), and SSs (somatic symptoms) is the outcome (y). CI (lower), lower bound of 95% confidence interval; CI (upper), upper bound of 95% confidence interval.*

affects levels of PD, and that this then impacts on SSs, either in terms of actual differences in symptoms or in interpretation and report of symptoms. These findings add to our understanding of the relationship between unemployment and health, and suggest that interventions aiming to reduce AS, or improve coping mechanisms, would have the potential to offer health benefits to this cohort.

Our first finding, that anticipating greater levels of stigma predicted both increased PD and more SSs, fits with prior research on other stigmatized identities which shows they are associated with impaired well-being (e.g., Markowitz, 1998; Cluver et al., 2008; Hatzenbuehler et al., 2009; Quinn and Chaudoir, 2009; Earnshaw et al., 2013; Quinn et al., 2014). While it was known from previous research on unemployment that becoming unemployed leads to a new social identity that is stigmatized (e.g., Rantakeisu et al., 1997; Cullen and Hodgetts, 2001; Letkemann, 2002; Furåker and Blomsterberg, 2003; Lee et al., 2005), the specific link between unemployment stigma and impaired health has not been demonstrated before.

As such, our findings extend the stigmatized identities literature by demonstrating that this negative effect of AS on health also applies to the unemployed identity. Importantly, they also advance the unemployment literature by demonstrating the impact of a psychosocial factor – stigma – on the experience of impaired health in the unemployed group. This is particularly significant given that much research on stigma and unemployment has focused more on its impact on reemployment than its impact on health.

Moreover, and importantly, the current study also showed that there was an indirect effect of AS on SSs via PD. While there has been some evidence that unemployment is associated with poor physical health and that stigma is associated with poor health, we believe this is the first study showing that anticipated unemployment stigma affects PD and that this impacts self-reported physical health. Based on the existing literature, we suggest that stigma might exert such effects on both psychological and physical health by heightening levels of stress. While unemployment itself has been identified as a stressor (Linn et al., 1985; Wanberg, 2012), stigma is also a chronic stressor (Link and Phelan, 2006). Specifically, knowing that others are labeling and judging you can lead to withdrawal from support systems, which might otherwise provide a buffering effect, and hence increased stress (Markowitz, 1998). Of course, it must be noted that causality cannot be inferred when using mediation analysis on cross-sectional data. However, our predicted causal pathway is supported by previous research showing that more generally, stress can lead to PD (Schulz et al., 1995; Phillips et al., 2015) and that collectively, stress and PD can impact physical health (Cohen and Williamson, 1991; Hoge et al., 2007; Springer et al., 2007; Springer, 2009).

Finally, the current research also adds to the literature seeking to explain the association between unemployment and health problems, which demonstrates there is an impact of unemployment on health over and above any self-selection effect of people who are unwell into unemployment. In the current sample previous illness was uncommon, and moreover had no impact on the relationships between AS, PD, and SSs.

Our findings add to a small but growing literature showing that, while self-selection may indeed exert an effect, this does not explain all health problems in the unemployed group. Rather, research now suggests there is also a distinct effect of unemployment on health (Korpi, 2001; Wanberg, 2012). The current study uniquely adds to our understanding in this area as it shows that the stigma related to being unemployed has an undesirable impact on one's health, in addition to the documented impact that it already has on reemployment.

Although the study contributes in a novel way to multiple literatures, naturally it has some limitations that could be addressed in future research. First, the study provides crosssectional data suggesting there is an indirect effect of AS on SSs through PD. Ideally, future research should investigate this longitudinally in order to establish causality. The sample in this study was also small, which is actually not untypical of research on the unemployed group, and difficulties with recruitment have been noted by other researchers (e.g., Blau et al., 2013). While our findings are very much in line with previous research on unemployment and health, nonetheless, it must be acknowledged that the small sample size means our study is underpowered. As such, in order to further advance research in this area, researchers must consider how best to promote recruitment of this vulnerable group, many of whom understandably do not wish to be asked about their experiences.

Future research should also incorporate objective measures of physical health outcomes, to disentangle whether PD is affecting actual SSs, the interpretation and reporting of same, or both. There has been some suggestion in the literature that effects may relate more so to perceptions of health than health itself (Cohen and Williamson, 1991), but it would be advisable to gather more evidence on this matter.

It would also be prudent to expand the measurement of stigma to include both experienced stigma and internalized stigma as well as AS. These measures have been identified as highly important in determining the impact of other concealable stigmatized identities (e.g., Earnshaw and Quinn, 2011), but have not yet been studied much in relation to the unemployed group. Internalized stigma in particular may be highly relevant to the unemployed group as unemployment is an identity that one acquires, having most likely had preconceptions about the group beforehand (Quinn and Earnshaw, 2011). Future research could also in some way take into account the economic climate, as previous findings suggest stigmatization may be highest when unemployment is low (Furåker and Blomsterberg, 2003; Ho et al., 2011; Karren and Sherman, 2012). Although unemployment is currently high in Ireland, the unemployment rate is also steadily dropping (CSO, 2015), and in any case, *perceptions* of this rate are perhaps more relevant to experienced, anticipated and internalized stigma, than the objective rate itself.

Finally, it would be ideal for future studies in this area to sample a more accurate gender representation relative to the entire unemployed group. In the present study, two thirds of our participants were female, which does not reflect the gender

breakdown in the unemployment figures for Ireland (CSO, 2013). The most recent figures suggest that while women are less likely to be employed than men (55.9% of women are employed, compared to 65.7% of men), they are also less likely to be identified as *un*employed (9.9% of women compared to 13.9% of men). As such, the gender imbalance in the present study is likely to be due to women's greater willingness to take part in surveys (Mackety, 2007). Although in the present study gender was not demonstrated to affect our results, more accurate gender representation in future research is important, as previous research has identified that unemployment can affect men and women differently, in terms of both stigma and PD outcomes. For example, unemployed men may feel more stigma than women due to work being more central to their sense of self (Kulik, 2000), and may experience more anxiety and mental health problems while women suffer more in terms of reduced self-esteem (Breslin and Breslin, 2013).

Overall, our findings are consistent with prior literature suggesting that stigma may be one missing piece of the puzzle in explaining health disparities between advantaged and disadvantaged groups (e.g., Eriksson et al., 2010; Quinn and Earnshaw, 2011), in this case, unemployment-related stigma. This empirical evidence is valuable as there has not been much research focusing on how the experience of stigmatization might help explain poor health in the context of unemployment. Unemployment is known to be stressful and to impact on psychological and physical health, and it is important to understand the processes by which it has these impacts.

In seeking to go beyond existing incomplete understandings of these processes, we argue it is vital to take into account social factors such as stigma. Stigma is especially important as it can be considered to exert effects at both the socio-structural level and the psychosocial level. That is, the low status of the unemployed group in the social structure leads people to experience actual discrimination due to unemployment-related stigma in the minds of others, but the expectation of such stigmatization and discrimination also has a negative effect on the well-being and functioning of the unemployed person at the psychological level. Aside from the clear theoretical implications, the research therefore has strong practical implications as well. For example, while stigmatization itself may be extremely hard to tackle, there is scope to expand job skills training to incorporate techniques for coping with stigmatization. In conclusion, our ability to boost people's psychological and physical health during unemployment is likely to be far increased if we take into account social factors such as stigma.

# Acknowledgments

The authors wish to acknowledge Mary M. Molloy and Rachel Sumner for their help with data collection. The research was also supported by funding from the Irish Research Council awarded to the third author.

# References

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2015 O'Donnell, Corrigan and Gallagher. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Changes in aspects of social functioning depend upon prior changes in neurodisability in people with acquired brain injury undergoing post-acute neurorehabilitation

*Dónal G. Fortune1,2\*, R. Stephen Walsh1,2, Brian Waldron2, Caroline McGrath2, Maurice Harte2, Sarah Casey2 and Brian McClean2*

*<sup>1</sup> Centre for Social Issues, Department of Psychology, University of Limerick, Limerick, Ireland, <sup>2</sup> Acquired Brain Injury Ireland, Dun Laoghaire, Ireland*

#### *Edited by:*

*Gianluca Castelnuovo, Università Cattolica del Sacro Cuore, Italy*

#### *Reviewed by:*

*Matthew M. Antonucci, Institute of Clinical Neuroscience and Rehabilitation, USA Robin W. Wilkins, Joint School of Nanoscience and Nanoengineering, USA*

#### *\*Correspondence:*

*Dónal G. Fortune, Unit 8, St. Stephen's Hospital, HSE South, Glanmire, County Cork, Ireland<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Psychology for Clinical Settings, a section of the journal Frontiers in Psychology*

*Received: 28 May 2015 Accepted: 25 August 2015 Published: 08 September 2015*

#### *Citation:*

*Fortune DG, Walsh RS, Waldron B, McGrath C, Harte M, Casey S and McClean B (2015) Changes in aspects of social functioning depend upon prior changes in neurodisability in people with acquired brain injury undergoing post-acute neurorehabilitation. Front. Psychol. 6:1368. doi: 10.3389/fpsyg.2015.01368* Post-acute community-based rehabilitation is effective in reducing disability. However, while social participation and quality of life are valued as distal outcomes of neurorehabilitation, it is often not possible to observe improvements on these outcomes within the limited time-frames used in most investigations of rehabilitation. The aim of the current study was to examine differences in the sequence of attainments for people with acquired brain injury (ABI) undergoing longer term post-acute neurorehabilitation. Participants with ABI who were referred to comprehensive home and communitybased neurorehabilitation were assessed at induction to service, at 6 months and again at 1.5 years while still in service on the Mayo-Portland Adaptability Index (MPAI-4), Community Integration Questionnaire, Hospital Anxiety and Depression Scale, and World Health Organisation Quality of Life measure. At 6 months post-induction to service, significant differences were evident in MPAI abilities, adjustment, and total neurodisability; and in anxiety and depression. By contrast, there was no significant effect at 6 months on more socially oriented features of experience namely quality of life (QoL), Community Integration and Participation. Eighteen month follow-up showed continuation of the significant positive effects with the addition of QoL-related to physical health, Psychological health, Social aspects of QoL and Participation at this later time point. Regression analyses demonstrated that change in QoL and Participation were dependent upon prior changes in aspects of neurodisability. Age, severity or type of brain injury did not significantly affect outcome. Results suggest that different constructs may respond to neurorehabilitation at different time points in a dose effect manner, and that change in social aspects of experience may be dependent upon the specific nature of prior neurorehabilitation attainments.

 ABIs can result from a number of causes including traumatic brain injury [including road traffic accidents, assault or falls, cerebrovascular accidents (e.g., strokes or bleeds), or other internal processes (encephalitis, infection, anoxia, etc.)]. ABI brings with it the significant potential for life-long functional changes encompassing a range of physical, cognitive, emotional, behavioral and social changes, which mandate a process of often lengthy rehabilitation to enable the person with ABI to optimize their recovery (Turner-Stokes, 2008; Cicerone et al., 2011).

The value of specialized rehabilitation for brain injury, including community-based rehabilitation, is becoming increasingly apparent in terms of both functional outcomes (Schnitzler et al., 2014), and cost effectiveness (van Heugten et al., 2012; Oddy and Ramos, 2013). Evidence based reviews have generally reported positive outcomes of engagement in comprehensive holistic home and community-based rehabilitation programs (Turner-Stokes, 2008; Geurtsen et al., 2010; Cicerone et al., 2011; van Heugten et al., 2012), although with some exceptions depending on the outcomes assessed (Institute of Medicine, 2011; Brasure et al., 2012).

A number of features of participant's experience have been suggested to be important targets for, and outcomes of, intervention. Changes in neurodisability is one of the most prominent outcomes and in addition to targeting changes in physical and cognitive abilities and mental health, rehabilitation programs increasingly utilize more socially moderated factors such as quality of life and participation in society (Eicher et al., 2012; Stiers et al., 2012; Altman et al., 2013; Malec et al., 2015). Such social/community integration factors are becoming important features of outcome (Haslam et al., 2008; Cicerone et al., 2011; Algurén et al., 2012; Brasure et al., 2012; Stalder-Lüthy et al., 2013; Walsh et al., 2015).

Mental health difficulties, particularly anxiety and depression have relatively common currency in ABI and pose a significant barrier to rehabilitation progress (Gould et al., 2011; Bertisch et al., 2013; Stalder-Lüthy et al., 2013). Indeed the odds of developing depression following brain injury are more than five times higher than in the general population (Osborn et al., 2014). A number of studies have suggested that 6 months following ABI, one third of individuals develop clinically relevant symptoms of depression (Stalder-Lüthy et al., 2013), and that in the first year, over 60% have a diagnosable psychiatric disorder, principally anxiety, and depression (Gould et al., 2011). While it has been suggested that rehabilitation may improve psychological difficulties (Geurtsen et al., 2010; Stalder-Lüthy et al., 2013), inadequate follow-up has hampered the information that can be derived from such studies (Brown et al., 2011). It is compelling that a recent meta-analysis of psychological interventions for depression following ABI expressed "amazement" at the small number of published studies available for analysis despite the high prevalence of mental health difficulties in ABI (Stalder-Lüthy et al., 2013).

Community participation and quality of life (QoL) are increasingly valued as neurorehabilitation outcomes (Cicerone et al., 2011). Participation has much in common with social and community reintegration and relates to acceptable levels of function in social roles or relationships (Whiteneck et al., 2011). The most recent review specifically examining participation outcomes reported that the available evidence was too limited to draw robust conclusions about the effects of neurorehabilitation on participation (Brasure et al., 2013). Thus while participation and indeed QoL are important pragmatic outcomes in rehabilitation, relatively brief periods of intervention, limited opportunity to address the application of interventions to everyday functioning, lack of follow-up assessing community functioning, and failure to include relevant outcome measures has led to limited data in this area (Cicerone et al., 2011).

In terms of QoL, Geurtsen et al. (2011), reported improvements in QoL, societal participation and community integration, and emotional well-being that were maintained in 96% of cases at 1 year follow-up, but did not increase at 3 years follow-up (Geurtsen et al., 2012). In people with cerebrovascular accident (CVA), Algurén et al. (2012) reported that in the first 3 months of rehabilitation, body functions, activities, and participation explained the majority of the variance in participants' QoL. At 1 year, only body functions and environmental factors accounted for significant variance in QoL. This difference in outcome across time raises the question as to whether a dose effect of rehabilitation duration significantly affects outcome or whether a sequence effect is evident with certain prior attainments needing to be set in place to bolster subsequent changes in these outcomes.

There is some recent evidence supporting a dose-effect relationship on outcome of neurorehabilitation. In a large study of a cohort of people with CVA (Altman et al., 2013), participants who completed their full neurorehabilitation program – what the authors term a full dose – had improved outcomes in terms of neurodisability when compared with those who were precipitously discharged and thus did not complete their full program. A dose effect of multidisciplinary intervention would seem plausible and indeed in terms of cortical plasticity, Kolb and Muhammad (2014), make the point that an effective treatment for individuals after brain injury would have to be intense, regular, and interdisciplinary including cognitive, behavioral, social, and physical/biological aspects of intervention. While there are a number of studies examining intake factors that may predict rehabilitative outcome (van Heugten et al., 2012; Hayden et al., 2013; Snell et al., 2013), there is a paucity of studies that have addressed the effects of participants' prior attainment of within-program outcomes on subsequent attainment of further outcomes. Moreover, a recent landmark review of evidence based cognitive rehabilitation (Cicerone et al., 2011), makes the point that although social participation and quality of life are valued as the distal health-related outcomes of neurorehabilitation, it is often not possible to observe improvements on these outcomes within the limited time-frames used in most investigations of neurorehabilitation.

The objectives of the current study were therefore, firstly to examine whether participants demonstrate significant improvement on a broad number of domains assessed at shorter and longer durations of community-based neurorehabilitation: namely neurodisability, community integration, mental health, and quality of life. Secondly to examine the contribution of differences in clinical features of injury such as age at onset, injury severity, type and duration of brain injury, age, and sex on changes from pre-treatment to follow-up. Thirdly to investigate whether changes in the more socially oriented factors including QoL, participation and social/community integration occurred later than changes in neurodisability and mental health outcomes and furthermore whether such changes in QoL, participation and community integration may be dependent upon prior changes in neurodisability and mental health outcomes.

# Materials and Methods

#### Participants

Eighty three people were eligible for participation in the cohort study. A total of six participants dropped out of the study between their initial induction assessment and follow-up assessment. Given that there was only one significant difference between the induction data for these six participants and the cohort (with people who dropped out reporting marginally lower quality of life related to physical health at induction – Mann–Whitney *U* = 118.5, *p* = 0.047), for parsimony, these six participants were excluded from further analysis. The final cohort consisted of 77 participants who were assessed at induction to service (time 1), 6 months later (time 2) and at 1.5 years post-induction (time 3). In addition to the cohort of participants followed up over three time points during their service, a total of 151 additional people with ABI who were referred to service after the cohort had been established, during this 2 years period were assessed at induction to the service for comparison purposes with all induction data of the cohort. The purpose of this cross sectional sample was to examine goodness of fit of the cohort to those routinely referred to post-acute neurorehabilitation services.

Inclusion criteria for participation in this study were age > 18 years, clinical confirmation of ABI specifying acquired non-progressive injury to the brain, onset of ABI < 65 years, and sufficient proficiency in English to undertake the study. All participants were engaged in an individualized Home and Community Based Rehabilitation program accredited by the Commission for Accreditation of Rehabilitation Facilities (CARFs).

#### Procedure

The protocol was approved by the ABI Ireland national research ethics committee and all participants provided full consent for participation. Assessments were administered by staff as semi structured interviews. All clients of the service were eligible for participation where the inclusion criteria was deemed appropriate by members of the Clinical Service Team.

#### Measures

Demographic, clinical and social information was recorded at induction to the study (**Table 1**).

Injury Severity Injury severity in TBI was calculated using the standard assessments of severity using Glasgow Coma Scale (GCS) scores, duration of Post-Traumatic Amnesia, and Loss of Consciousness (LOC) using the following procedure: Severe Brain Injury = GCS TABLE 1 | Demographics, injury characteristics, and clinical features of cohort.

score less than 9, LOC longer than 24 h, or PTA longer than 1 week. Moderate Brain Injury = GCS score of 9–12, LOC of 30 min to 24 h, or PTA of 24 h to 1 week. Mild Brain Injury = GCS score higher than 12, LOC less than 30 min, or PTA less than 24 h. If more than one indicator was present and differed in level of severity, the more severe level was assigned. For other causes (e.g., CVA, encephalitis, anoxia, and tumor), severity was assessed by multidisciplinary team discharge report from acute (hospital based) rehabilitation services specifying moderate and severe disability.

Participants completed the following measures of Neurodisability, Community Integration, Mental Health, and Quality of Life at induction to post-acute neurorehabilitation, at 6 months follow-up and at 1.5 years post-induction.

# NeuroDisability – Mayo Portland Adaptability

Inventory – (MPAI-4) The MPAI-4 is a widely used measure of limitations imposed by brain injury (Malec, 2004; Malec and Lezak, 2008). The measure yields a total score reflecting overall disability, as well as three subscale scores for the Ability Index (e.g., mobility, cognitive functioning, communication), Adjustment Index (e.g., pain, mood, fatigue), and Participation Index (e.g., social contact, independent living, employment). Prior studies have demonstrated satisfactory internal consistency and construct validity, as well as concurrent and predictive validity, for the full measure and its indices (Wilde et al., 2010; Kean et al., 2011; Malec et al., 2012). The MPAI-4 has been shown to be sensitive to clinical change in studies of rehabilitation interventions (Eicher et al., 2012), and that all 30 items could be mapped to components and categories in the WHO-ICF (Lexell et al., 2012). In the current study, internal consistency was good for the MPAI total scale score (0.91), Abilities (0.74), Adjustment (0.82), and Participation Indices (0.85).

Community Integration Questionnaire The Community Integration Questionnaire (CIQ; Corrigan and Deming, 1995; Salter et al., 2011), is a brief assessment of community integration that comprises 15 items assessing effective role performance in three domains: home integration (active participation in the operation of the home or household), social integration (participation in social activities outside the home) and productivity (regular performance of work, school or volunteer activities). Internal consistency in previous studies has been reported as good, with Cronbach's alpha's ranging from 0.76 to 0.84 for total scale scores (Corrigan and Deming, 1995). The CIQ is predominately linked to the major life areas (35%), community, social and civic life (31%), and domestic life (19%) chapters of the WHO ICF (Salter et al., 2011). A measure of Minimal Clinically Important Difference (MCID) of 4.2 CIQ points has been provided for the CIQ (Cicerone et al., 2004). Internal consistency was good in the current study for CIQ total score (0.71) and Home integration subscale (0.83), but was unacceptably low for Social integration (0.45), and Productivity (0.23). As such it was decided not to use the Social Integration and Productivity subscales further in the analyses.

Hospital Anxiety and Depression Scale The Hospital Anxiety and Depression Scale (HADS; Zigmond and Snaith, 1983), a 14-item measure, was used to assess symptoms of anxiety and depression. Items are rated on a 0–3 point scale indicating the strength of agreement with each item. Thus, scores for each subscale range from 0 to 21. It has been widely used in studies with patients with brain injury and has been shown to be an appropriate measure of anxiety and depression and of distress more generally (Dawkins et al., 2006; Schönberger and Ponsford, 2010). A score of >7 on either scale indicates the presence of clinically relevant distress. In the current study, the anxiety and depression subscales yielded good internal consistency scores (0.79 and 0.76 respectively).

# World Health Organisation's Quality of Life Scale

(WHOQoL- BREF) The WHOQoL-BREF is a 26 item international cross-culturally comparable quality of life assessment instrument. The assessment examines a person's Quality of Life in relation to four domains: QoL related to Physical Health, Psychological Health, Social Relationships, and the person's living Environment. Higher scores denote better QoL. The measure has demonstrated appropriate reliability and validity (WHOQOL Group, 1998; Skevington et al., 2004), and has been used successfully in people with ABI (Chiu et al., 2006; Polinder et al., 2015). In the current study, internal consistency was good for the QoL subscales of Physical Health (0.72), Psychological Health (0.78), and environmental aspects of QoL (0.79). While the Social aspects of QoL subscale was somewhat lower (0.61), it was decided to retain this particular subscale as the alpha was more likely due to the small number of items in the subscale rather than problem in psychometrics (e.g., intercorrelations between items were good).

### Statistical Analysis

Descriptive statistics were computed for variables relating to injury and demographics. Q-Q plots and Kolmogorov–Smirnov test were used to examine the distribution of outcome data. Given that outcome data showed no significant deviation from normality (*Z*'s > 1.21, *p*'s > 0.14), means and standard deviations were calculated for the four main outcome measures and subscales as appropriate. Repeated measures analysis of variance models were used to model the means of each of the outcome measures over time. Effect sizes [Partial eta squared (η<sup>2</sup> p)] were considered small when between 0.5 and 0.10, medium when between 0.10 and 0.20, and large when greater than 0.20. *Post hoc* pairwise comparisons were conducted and a Bonferroni adjustment (α = 0.004) was performed to examine differences between outcomes at time 1 and time 2, and between time 2 and time 3. Categorical data were analyzed by Chi square test and longitudinal categorical data by Cochrane's *Q*-test for three time points and the McNemar test for two time points. Repeated measures ANCOVA was used to examine differences in outcome for the two principal causes of ABI; injury resulting from an external force (TBI), or injury resulting from an internal disease process (CVA, encephalitis, hypoxia, or tumor), and severity of injury. Zero order correlations and multiple regression analysis were used to examine the potential influence of prior changes in neurodisability and mental health on subsequent changes in QoL and Participation.

# Results

**Table 1** details demographics, injury characteristics and clinical features of the sample. Participants were predominantly male, and TBI was the most common mechanism of injury, chiefly resulting from road traffic accidents and falls. The majority of participants had a severe brain injury.

# Comparison of the Induction Data of the Cohort with Induction Data of Referrals within the Lifetime of the Study

There were no significant differences between the cohort (*N* = 77) and people who were referred for service in the 2 years of the study (*N* = 158) on any of the outcome assessments at induction (*t*<sup>226</sup> < 2.31, *p* > 0.02). There were also no significant differences between the cohort and single assessment groups on participants' age, age at onset of their ABI, or duration with ABI (*t*'s215 < 2.27, *p* > 0.03), or on clinical severity of their injury (χ<sup>2</sup> <sup>=</sup> 2.35, *<sup>p</sup>* <sup>=</sup> 0.13). There was also no significant difference between the cohort and people who completed their assessments at induction on numbers of people with CVA vs. TBI (χ<sup>2</sup> <sup>=</sup> 0.71, *p* = 0.41). The cohort was therefore not unrepresentative of the profile of people with ABI routinely referred to post-acute neurorehabilitation services in the Republic of Ireland.

## Demographic Effects on the Cohort at Induction

At induction to the study, cohort participants' performance on neurodisability, community integration, distress and QoL did not differ as a function of gender (*t*'s < 2.24, *p* > 0.03), participants' age, duration with ABI, or age at onset of their injury (*r*'s < 0.27, *p* > 0.03).

Independent *t*-tests (α < 0.004) demonstrated that when compared to participants with mild/moderate injury, people who had sustained a severe brain injury were functioning at a poorer level at induction in terms of the MPAI assessment of Abilities (*t*<sup>77</sup> = −4.40, *p* = 0.001), Adjustment (*t*<sup>77</sup> = −4.08, *p* = 0.001), and Participation (*t*<sup>77</sup> = −5.27, *p* = 0.001). Whether a person sustained a moderate or severe brain injury did not significantly affect scores on Community Integration, Mental Health or QoL at induction (*t*'s77 < 1.50, *p* > 0.0.13). Means and standard deviations for all outcome measures are presented in **Table 2**.

#### Neurodisability

A single repeated measures analysis of variance was used to model the MPAI Abilities, Adjustment, Participation, and Total scale score over the three time points. Significant increases were apparent for people with ABI in terms of their Abilities (*F*1,<sup>76</sup> <sup>=</sup> 15.29, *<sup>p</sup>* <sup>=</sup> 0.001, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.17), Adjustment (*F*1,<sup>76</sup> = 36.87, *<sup>p</sup>* <sup>=</sup> 0.001, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.33), Participation (*F*1,<sup>76</sup> = 19.33, *p* = 0.001, η2 <sup>p</sup> = 0.20), and total Neurodisability (*F*1,<sup>76</sup> = 33.82, *p* = 0.001, η2 <sup>p</sup> = 0.31). To permit comparisons with previously published studies, the standardized T score for the total MPAI was 48.58 at induction and 39.81 at the final assessment time-point (lower scores = better outcomes).

Pairwise comparisons revealed significant induction to 6 months follow-up improvements for Abilities (*t*<sup>76</sup> = 3.11, *p* = 0.003), Adjustment (*t*<sup>76</sup> = 4.44, *p* = 0.001), and total Neurodisability (*t*<sup>76</sup> = 3.12, *p* = 0.003), but not for Participation (*t*<sup>76</sup> = 0.93, *p* = 0.35).

Significant pairwise comparisons of 6 months to 1.5 years data were found for Adjustment (*t*<sup>76</sup> = 4.82, *p* = 0.001), Participation (*t*<sup>76</sup> = 5.97, *p* = 0.001), and total Neurodisability (*t*<sup>76</sup> = 5.27, *p* = 0.001). However, changes in Abilities failed to reach significance (*t*<sup>76</sup> = 2.44, *p* = 0.01).

Given that participants with severe brain injury performed more poorly than participants with moderate brain injury in terms of their MPAI performance at induction, an adjusted model was fit to the data which included an interaction effect for time by severity of ABI. The interaction term was significant for Abilities (*F*1,<sup>75</sup> <sup>=</sup> 7.09, *<sup>p</sup>* <sup>=</sup> 0.002, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.08) and total scale score (*F*1,<sup>75</sup> <sup>=</sup> 5.90, *<sup>p</sup>* <sup>=</sup> 0.003, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.07), but not for Participation (*F*1,<sup>75</sup> = 1.91, *p* = 0.15, η<sup>2</sup> <sup>p</sup> = 0.02), or Adjustment (*F*1,<sup>75</sup> = 2.64, *<sup>p</sup>* <sup>=</sup> 0.07, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.03). Effect sizes were small.

#### Community Integration

A single repeated measures analysis of variance was used to model the total Community Integration scale score and Home Integration scores over time. Neither Home Integration (*F*1,<sup>75</sup> <sup>=</sup> 2.21, *<sup>p</sup>* <sup>=</sup> 0.09, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.03), or total Community Integration (*F*1,<sup>75</sup> <sup>=</sup> 2.58, *<sup>p</sup>* <sup>=</sup> 0.07, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.03) showed statistically significant improvements over time.

Using published MCID scores (Cicerone et al., 2004), for the total scale score of the CIQ (MCID = 4.2), 16% of participants had achieved the MCID score at 6 months, with 35% achieving it at 1.5 years. McNemar's test demonstrated that this change from time 2 to time 3 was significant (*p* = 0.009).

## Mental Health

Depression Repeated measures ANOVA demonstrated that mean reductions in depression scores over time were statistically significant (*F*1,<sup>75</sup> = 6.82, *p* = 0.001, η<sup>2</sup> <sup>p</sup> = 0.09) albeit with a modest effect size. Pairwise comparisons also showed significant pre-treatment to 6 months improvements (*t*<sup>76</sup> = 2.78, *p* = 0.001), however, the 6 months to 1.5 years data was not significant (*t*<sup>77</sup> = 1.55, *p* = 0.12).

Using the established cut-offs for the presence of clinical distress, at induction to the study 39% of clients (*n* = 30/77) scored above the cut-off for clinically relevant depressive symptoms (HADS Depression subscale > 7). This figure had fallen to 24.6% (*n* = 19/77) after 6 months of rehabilitative intervention, and to 20% (*n* = 15), 1 year later (1.5 years post-baseline). This represented a significant effect (Cochrane's *Q* = 11.31, df 2, *p* = 0.003). *Post hoc* McNemar test with Bonferroni correction suggested that the principal difference was between induction and 6 months follow-up only (*p* = 0.01).

Anxiety Repeated measures ANOVA suggested that mean differences in anxiety over time were statistically significant (*F*1,<sup>75</sup> = 9.90, *<sup>p</sup>* <sup>=</sup> 0.001, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.12). Pairwise comparisons also showed significant improvements from induction to 6 months (*t*<sup>76</sup> = 3.96, *p* = 0.001) but not 6 months to 1.5 years (*t*<sup>76</sup> = 3.96, *p* = 0.001). Mean (*SD*) scores are presented in **Table 2**.

In terms of clinically relevant anxiety (HADS Anxiety subscale > 7), at induction 31.2% of clients assessed (*n* = 24/77), scored above the cut-off for clinically relevant symptoms of anxiety. This figure had fallen to 14.3% (*n* = 11/77) after 6 months of rehabilitative intervention, and had increased slightly to 15.6% (*n* = 12/77) 1 year later. Cochrane's *Q*-test suggested this represented a significant effect (Cochrane's *Q* = 13.08, df 2, *p* = 0.001), with *post hoc* McNemar tests again finding that the significant reduction was between induction and 6 months only (*p* = 0.001).

#### Quality of Life

A single repeated measures analysis of variance was used to model the Quality of Life data. Significant mean differences over time were evident for QoL related to Physical Health (*F*1,<sup>75</sup> <sup>=</sup> 9.49, *<sup>p</sup>* <sup>=</sup> 0.001, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.11), Psychological Health (*F*1,<sup>75</sup> <sup>=</sup> 10.31, *<sup>p</sup>* <sup>=</sup> 0.001, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.12 ), and Social aspects of QoL (*F*1,<sup>75</sup> <sup>=</sup> 3.61, *<sup>p</sup>* <sup>=</sup> 0.03, <sup>η</sup><sup>2</sup> <sup>p</sup> = 0.05), but not environmental aspects (*F*1,<sup>75</sup> = 2.66, *p* = 0.07, η<sup>2</sup> <sup>p</sup> = 0.03).

Pairwise comparisons (α < 0.004) demonstrated no significant induction to 6 months follow-up improvements for any of the quality of life measures (*t*<sup>75</sup> < 1.86, *p* = 0.06). Comparisons of 6 months to 1.5 years follow-up revealed significant improvements on QoL related to Physical Health (*t*<sup>76</sup> = −3.31, *p* = 0.001), Psychological health (*t*<sup>76</sup> = 2.83, *p* = 0.003), but not Social aspects of QoL (*t*<sup>76</sup> = 2.09, *p* = 0.03).

# Prediction of Quality of Life and Participation Improvements by Prior Improvements in Neurodisability and Mental Health

We next examined whether the significant changes in QoL and Participation from 6 months to 1.5 years were dependent upon prior (induction to 6 months) changes in neurodisability and mental health.

Prior to building the regression model, correlation analysis was undertaken (**Table 3**) which suggested that significant 6 months to 1.5 years changes in Participation was related to prior improvements in the Neurodisability factors of Abilities (*r* = −0.49, *p* = 0.001) and Adjustment (*r* = −0.36, *p* = 0.01) and in prior changes in Depression (*r* = −0.31, *p* = 0.01). *t*-test showed no significant effect of injury severity on 6 months to 1.5 years Participation scores (*t*<sup>76</sup> = 0.96, *p* = 0.34).

The regression model (**Table 4**) for change in Participation was significant for the three variables – prior improvements in Depression, Adjustment to disability and Abilities (*R*<sup>2</sup> <sup>=</sup> 0.24, *F*1,<sup>75</sup> = 14.49, *p* = 0.001). However, only prior improvement in Abilities predicted subsequent improvements in Participation in the final regression equation (β = 0.49, *t* = −3.81, *p* = 0.001).

TABLE 3 | Correlations between changes in disability and distress from induction to 6 months, changes in QoL and participation from 6 months to 1.5 years.

∗*p* < *0.05,* ∗∗*p* < *0.01.*

TABLE 4 | Prediction of improvements in participation and quality of life at 1.5 years post-induction by earlier improvements in neurodisability and mental health.

The significant improvement in QoL related to Physical Health at 1.5 years follow-up was associated with prior significant changes from baseline in Abilities (*r* = −0.31, *p* = 0.01) and Adjustment (*r* = −0.32, *p* = 0.01). Neither changes in QoL related to psychological health nor social aspects of QoL were associated with prior changes in neurodisability or mental health (*r*'s < 0.17). The regression model for positive change in QoLrelated Physical health at time 3 was initially significant for prior improvements in both Abilities and Adjustment (*R*<sup>2</sup> <sup>=</sup> 0.10; *F*1,<sup>75</sup> = 6.26, *p* = 0.01). However, improvements in QoL-related Physical Health was solely predicted by prior improvements in MPAI Adjustment only (β = −32, *t* = −2.50, *p* = 0.01) in the final equations (**Table 4**).

## Discussion

This study has presented data on a prospective cohort of longer-term individuals with moderate to severe brain injury in continuous service at 6 months and 1.5 years on a range of measures that are a common focus of outcome assessment and goal setting with people with ABI. In view of the need to provide outcome information across a broad domain of functioning including physically oriented, social/community oriented, and well-being outcomes, this study has added important additional information on the level of improvement and differences in the rate of improvement for proximal and distal outcomes across time for people with moderate-severe brain injury.

The first two objectives of the study were to examine whether and to what extent people in receipt of home and communitybased neurorehabilitation showed improvements in terms of neuro-disability, community integration, mental health and QoL over time in service, and secondly to investigate whether changes in the more distal outcomes of QoL, Community Integration and Participation occurred at a later stage than changes in more general aspects of neurodisability and mental health. To this end, participants in service showed significant improvement in terms of their cognitive and physical abilities, adjustment to brain injury, in aspects of QoL, and in anxiety and depression. While the use of continuous data did not reach significance for Community Integration, use of published MCID values (Cicerone et al., 2004) showed significant changes in the number of participants attaining Community Integration MCIDs from 6 months to 1.5 years follow-up.

Patient's performance on measures of neurodisability, essentially participants' Abilities and Adjustment to brain injury showed the most consistent improvements over time for the cohort. Using the MPAI-4's standardized T scores for the total scale, the difference in T scores from induction to rehabilitation to 1.5 years follow-up was broadly similar to recent published work on comprehensive community rehabilitation for longer term cases (Altman et al., 2010; Curran et al., 2014), and indeed the difference in T scores in the current study approaches that recently published for people with duration of ABI of more than 1 year (Altman et al., 2013). This suggests a robust improvement across time on this measure in the context of people in continuing service in the current study.

The well-recognized barrier that mental health difficulties can pose to rehabilitation progress (Stalder-Lüthy et al., 2013; Merzenich et al., 2014), was also addressed as an outcome and our results suggest that the significant time for improvement of anxiety and depression is between induction and 6 months in service. Commensurate with this finding, the number of participants whose scores positioned them in the more severe anxiety and depression categories declined and consolidated over the course of the program. However it is apparent that a small but significant proportion of people (14–16%) were dealing with mental health difficulties arising from their ABI that were resistant to change and were continuing to experience on-going mental health challenges at 1.5 years follow-up. Identification and management of this particular group of participants' demands careful assessment at induction to neurorehabilitation programs. Such assessment is required to ensure that participants are triaged toward the most effective content and duration of intervention for their particular mental health needs.

Recent studies have begun to suggest a dose-effect relationship on outcome of neurorehabilitation. Previous research in a cohort of people with CVA (Altman et al., 2013), reported that completing a planned neurorehabilitation program (a full dose) resulted in superior outcomes when compared with those who did not complete their full rehabilitation program, and suggested that that this dose effect relationship may relate to intensity, quality and appropriateness of services and not simply time in the program. The results of the current study extend these finding to the broader ABI population and also adds to this finding by providing data that suggests that the nature of the outcome is related to the dose of neurorehabilitation, but also to the nature of what prior changes have already been set in place by participation in neurorehabilitation. Our results suggest that changes in Qol and Participation were initially associated with prior changes in neurodisability and mental health. However, the

# References

final model suggested that longer-term improvements in QoL and Participation were predicted by Neurodisability factors alone. This finding suggests that change following ABI, particularly in relation to these more nuanced outcomes, may be sequenced and dependent upon the content, duration, and prior attainment of neurodisability aspects of outcome.

## Limitations

The current study is a cohort study and caution should therefore be exercised in drawing any conclusion that neurorehabilitation alone is responsible for the changes observed. The use of long-term cases, while making spontaneous improvement less likely does not remove its possibility. Further, while participants were engaged in a national Home and Community-based rehabilitation program accredited through international best practice (CARF), the participants in this study were individuals at the more severe end of the brain injury spectrum and as such results may not generalize to individuals with less severe brain injuries or with a shorter duration of injury.

# Conclusion

Nonetheless, this study has demonstrated improvements over time for participants in long-term service with moderate to severe brain injury across a range of measures of outcome. Results also suggested the presence of a dose effect which varied as a function of the nature of the outcome, with some outcomes showing the need for increased time duration, and others demonstrating consolidation after a shorter duration of intervention. Importantly, this study revealed that significant changes in more nuanced person-centered and social aspects of outcome such as quality of life and participation only occurred after significant changes in aspects of neurodisability had become established. These results have obvious implications for specifying the sequence of neurorehabilitation interventions in order to best optimize proximal and distal treatment outcomes, and relates, as has been proposed previously (e.g., Walsh et al., 2014), to the need for interventional integration across the physical, psychological and social aspects of the person's experience.

# Acknowledgment

Our thanks to staff and participants who completed assessments for the purposes of this study.

*Minnesota Evidence-based Practice Center under Contract No. 290-2007- 10064-I.) AHRQ Publication No. 12-EHC101-EF.* Rockville, MD: Agency for Healthcare Research and Quality.

neuropsychological perspectives. *Health Psychol. Rev.* 8, 458–472. doi: 10.1080/17437199.2012.733914

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2015 Fortune, Walsh, Waldron, McGrath, Harte, Casey and McClean. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Post-traumatic growth following acquired brain injury: a systematic review and meta-analysis

Jenny J. Grace<sup>1</sup> , Elaine L. Kinsella<sup>2</sup> \*, Orla T. Muldoon<sup>2</sup> and Dónal G. Fortune<sup>2</sup>

<sup>1</sup> Acquired Brain Injury Ireland, Ennis, Ireland, <sup>2</sup> Department of Psychology, Centre for Social Issues Research, University of Limerick, Limerick, Ireland

The idea that acquired brain injury (ABI) caused by stroke, hemorrhage, infection or traumatic insult to the brain can result in post-traumatic growth (PTG) for individuals is increasingly attracting psychological attention. However, PTG also attracts controversy as a result of ambiguous empirical findings. The extent that demographic variables, injury factors, subjective beliefs, and psychological health are associated with PTG following ABI is not clear. Consequently, this systematic review and meta-analysis explores the correlates of variables within these four broad areas and PTG. From a total of 744 published studies addressing PTG in people with ABI, eight studies met inclusion criteria for detailed examination. Meta-analysis of these studies indicated that growth was related to employment, longer education, subjective beliefs about change post-injury, relationship status, older age, longer time since injury, and lower levels of depression. Results from homogeneity analyses indicated significant inter-study heterogeneity across variables. There is general support for the idea that people with ABI can experience growth, and that various demographics, injury-related variables, subjective beliefs and psychological health are related to growth. The contribution of social integration and the forming of new identities post-ABI to the experience of PTG is explored. These meta-analytic findings are however constrained by methodological limitations prevalent in the literature. Clinical and research implications are discussed with specific reference to community and collective factors that enable PTG.

Keywords: brain injury, head injury, trauma, post-traumatic growth, rehabilitation outcomes

# Introduction

Acquired brain injury (ABI) typically occurs as a result of road traffic accidents, assaults or falls, problems in the supply of blood in the brain such as a bleed (hemorrhage) or blockage (stroke), problems in the supply of oxygen (hypoxia) inflammation or swelling of the brain (encephalitis), tumor (meningioma), or surgical issues such as might be involved in tumor management. The incidence of ABI is estimated to be one per 500 of the population globally; children under four, adults under 30, and those over 65 years of age are disproportionately affected (Jones et al., 2011). In fact, ABI is considered one of the most common neurological disorders (Howes et al., 2005). Traumatic brain injury (TBI) is thought to be eight times more common than a combination of breast cancer, AIDS, spinal cord injury, and multiple sclerosis in the USA (Kolb and Whishaw, 2009). Life following ABI is often associated with intense changes including

#### Edited by:

Gian Mauro Manzoni, eCampus University, Italy

### Reviewed by:

Claudia Cormio, National Cancer Research Institute "Giovanni Paolo II," Italy Tamara Ownsworth, Griffith University, Australia

#### \*Correspondence:

Elaine L. Kinsella, Department of Psychology, Centre for Social Issues Research, University of Limerick, Castletroy, Limerick, Ireland<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Psychology for Clinical Settings, a section of the journal Frontiers in Psychology

> Received: 29 May 2015 Accepted: 24 July 2015 Published: 14 August 2015

#### Citation:

Grace JJ, Kinsella EL, Muldoon OT and Fortune DG (2015) Post-traumatic growth following acquired brain injury: a systematic review and meta-analysis. Front. Psychol. 6:1162. doi: 10.3389/fpsyg.2015.01162 significant social, cognitive, and physical challenges. In addition, people can experience intense changes in identity (Gracey and Ownsworth, 2012). Over 40% of people hospitalized with nonfatal ABI sustain impairments that lead to long-term disability and require acute and post-acute neurorehabilitation to facilitate their appropriate re-adjustment into everyday life (Corrigan et al., 2010). Given the severity of disability and the considerable life expectancy for an ABI survivor, research on ABI and in particular, factors that contribute to the health and well-being of survivors is particularly important. Traditionally, research has focused on the negative consequences of ABI. Whilst this is understandable given that 6 months post-ABI approximately one third of survivors develop clinically relevant psychological distress (Hackett et al., 2005; Bombardier et al., 2010), the fact that a substantial proportion of people with ABI do not develop psychological distress means that positive and protective mechanisms are also worthy of consideration.

Applying positive psychological principles to ABI rehabilitation is growing, encapsulated in a movement that emphasizes "building what's strong" rather than "fixing what's wrong" (Evans, 2011). Over the past 13 years more people are subscribing to the idea that positive growth may be possible after ABI, particularly when changes occur in relation to a person's sense of meaning, purpose, heightened spirituality and enhanced relationships after brain injury (Tedeschi and Calhoun, 2004). In fact, some authors have reported that up to half of their research sample reported post-traumatic growth following the occurrence of ABI (Hawley and Joseph, 2008). Previously, the effects of ABI were seen as irreversible due to a perception that brain injury was a fixed outcome unaffected by the idea of brain plasticity—however, current thinking suggests that social and psychological processes can be harnessed to support and recover brain function to improve outcomes in this population (Walsh et al., 2014). Thus, it is important to seek to understand more about the predictors and processes associated with positive psychological outcomes following ABI. At present, it is unclear what the prevalence of PTG is after injury, what factors predict growth, and what the trajectory of growth might look like for people with ABI.

Until recently there was not sufficient published research on PTG to justify a systematic review. In 2011, Collicutt McGrath published a paper examining the relationship between spirituality and PTG following ABI, including a summary of studies previously published. That article has contributed a solid foundation for us to conduct the first systematic review and meta-analysis of PTG in brain injury survivors, including a more nuanced and thorough analysis of studies published between 1990 and 2014. Here the aim is to address a number of important questions that are previously unanswered in the literature. The review begins by briefly reviewing conceptual and measurement issues in the area of post-traumatic growth. Next, particular attention is paid to the development of PTG in ABI literature and outlining the methods employed here to conduct a systematic review and meta-analysis. The review findings are then presented under four headings. First, the relationship between demographic variables and PTG is considered. Second, the relationship between injury factors and PTG is examined. The remaining two analytic sections consider the relationships between psychological health and PTG, and cognitive processes and PTG. This analysis forms the basis of the subsequent discussion which integrates this work into current conceptual and theoretical debates about PTG and highlights areas where understanding is still poor and/or hampered by methodological controversies. Finally, the implications of this synthesis for clinical practice is considered and an agenda for future research is outlined.

# Current Conceptualizations of Post-traumatic Growth

Positive changes following trauma and adversity have long been recognized in philosophy and religion (Tedeschi and Calhoun, 1995; Tedeschi et al., 1998; Linley and Joseph, 2004), as well as existential (Frankl, 1963; Yalom, 1980) and psychological literature (Park et al., 1996). In research, positive changes have been reported after a range of life challenges (for review, see Linley and Joseph, 2004), including cancer (Collins et al., 1990; Stanton et al., 2006; Cormio et al., 2014, 2015), HIV (Bower et al., 1998), bereavement (Davis et al., 1998), rape (Burt and Katz, 1987; Thompson, 2000), war and conflict (Elder and Clipp, 1989; Waysman et al., 2001), and illness and surgery (Affleck et al., 1987; Tennen et al., 1992). PTG is likely to occur along a continuum, with people differing in their interpretation of the presence and degree of growth experienced. Estimates of perceptions of some degree of growth among people who have experienced psychological trauma typically range from 30 to 80% (Linley and Joseph, 2004).

Three broad areas of positive outcomes after trauma have been identified in the PTG literature. First, individuals report that their relationships with other people are enhanced in some way, including a greater connection to others and greater compassion for others who have suffered. Second, people report changing self-views, including an appreciation of their own personal strength as well as a greater awareness of new possibilities for one's life. Third, individuals report changes in their philosophy about life including changing views about what is important in life. Collectively, these changes have been labeled as posttraumatic growth (PTG: Tedeschi and Calhoun, 1995, 1996), adversarial growth (Linley and Joseph, 2004), benefit finding (Affleck and Tennen, 1996; Tennen and Affleck, 2002; Kangas et al., 2011), and stress-related growth (Park et al., 1996). These terms—particularly PTG and benefit finding—are sometimes used interchangeably. While there are similarities between these constructs, benefit finding is typically described in terms of the acquisition of benefit from adversity, whereas post-traumatic growth is described as the success with which individuals cope or strengthen their perceptions of self, others and the meaning of events after a traumatic event (Brand et al., 2014). Previous studies have also shown that the determinants of PTG and benefit finding are different in other chronic conditions, such as cancer (e.g., Jansen et al., 2011). Thus, for the purposes of the current article, PTG was chosen as the most empirically coherent construct on which to base the meta-analysis.

There has also been confusion regarding the differences between PTG and qualities such as resilience, optimism, hardiness—terms which refer to a person who has adjusted successfully despite adversity (O'Leary and Ickovics, 1995). PTG differs from resilience and recovery in the sense that it is usually understood to refer to an individual moving beyond their baseline functioning in terms of relationships, self-views and opening up of life possibilities, rather than simply returning to baseline (Collicutt McGrath, 2011). Throughout this article the term posttraumatic growth (PTG) is used to refer to perceptions of positive changes following a significant life event or trauma (consistent with Collicutt McGrath, 2011), but other terms are used when referring to literature that has used those same terms.

From a theoretical perspective, PTG has been conceived as an outcome of successful accommodation to a traumatic event (Tedeschi and Calhoun, 1995, 2004) and also, as a means of coping with trauma (Taylor and Armor, 1996). Initial conceptualizations of PTG referred to an objective complex cognitive, behavioral and emotional outcome after an initial struggle to deal with stressful life circumstances (see Tedeschi and Calhoun, 1995, 2004). Those authors argued that the trauma presents a compelling challenge to basic assumptions about the world, and that PTG occurs when the cognitive schemas that represent these assumptions are rebuilt in a more nuanced and complex form, as a result of the traumatic experience (Collicutt McGrath, 2011). Several models have now been proposed regarding the occurrence and development of PTG. Three comprehensive models exist—Functional Descriptive Model (Tedeschi and Calhoun, 1995, 2004), Organismic Valuing Theory (Joseph and Linley, 2005), and Biopsychosocial-Evolutionary Theory (Christopher, 2004). Although each model has a somewhat different emphasis, each suggests that experiencing a highly stressful or traumatic event shatters an individual's selfviews and world-views, and that a meaning-making process or cognitive-affective process occurs in order to adapt or rebuild one's views, resulting in perceptions of growth (Horowitz, 1986; Janoff-Bulman, 2004; Tedeschi and Calhoun, 2004). Most of these theories posit that people are intrinsically motivated toward growth.

Concerns about the theoretical validity of PTG have been raised, where authors suggest that positive cognitive, emotional and behavioral changes are functional illusions. Those researchers (see Taylor, 1983; Affleck and Tennen, 1996; Park and Folkman, 1997; Davis et al., 1998; Filipp, 1999) have argued that perceptions of growth are the result of trying to cope with trauma and reduce feelings of distress. Through this lens, PTG is viewed as a story that we tell ourselves to get throught the challenge, rather than reflecting any real psychological change as a result of struggling with trauma. Other authors (see McMillan and Cook, 2003; Dohrenwend et al., 2004; Cheng et al., 2006) suggest that individuals present themselves in an overly positive light and deny the negative impact of stressful life events, known as defensive denial, as an explanation of PTG. Also, Cognitive Adaptation Theory (Taylor, 1983; Taylor and Brown, 1988) suggests that people have self-protective cognitive biases for seeing positive aspects of negative experiences when they encounter threats—this theory may have relevance for understanding PTG. For example, most people who survive breast cancer report that they are coping as well or better than others facing the same challenge (Wood et al., 1985). Temporal Comparison Theory (Albert, 1977) suggests that individuals make comparisons between their past selves and current selves, and typically distort the past to perceive positive growth. In other words, people sometimes draw the conclusion they are a better version than before (e.g., I am more caring than I used to be). Interpreting PTG as self-enhancing cognitive biases, particularly after ABI where cognitive impairment is often severe, requires a great deal of careful theoretical and empirical attention. It is likely that self-enhancing biases and coping strategies may account for PTG in some individuals. However, It is not possible to distinguish between these processes in the present review.

# Measurement of PTG

Although at least 14 measures of PTG exist, two of the most widely used are the Post-traumatic Growth Inventory (PTGI; Tedeschi and Calhoun, 1996) and the Changes in Outlook Questionnaire (CiOQ; Joseph et al., 1993). The PTGI contains five domains of PTG: (1) new possibilities, (2) relating to others, (3) personal, (4) appreciation of life, and (5) spiritual change. Confirmatory factor analysis has provided further empirical support for this five-factor model (Taku et al., 2008). The CiOQ measures positive changes in the aftermath of trauma in domains similar to that of the PTGI, and has also demonstrated satisfactory psychometric properties (Joseph et al., 2005). There has been some debate in the literature regarding the measurement of PTG. Many scales have been developed to measure growth in response to the incongruencies in its conceptual and theoretical foundations. While overlap exists across these measures, it has been argued that not all are strictly measuring PTG (see Davis et al., 1998; Phipps et al., 2007). The lack of one single definition of PTG has led to measurement difficulties and has caused confusion regarding its correlates, predictors and relation to outcomes. Thus, the current synthesis of existing empirical data on the topic of PTG in ABI, and analysis of the correlates and pathways to growth is particularly timely.

# Method

# Literature Search

A computerized literature search was conducted in EBSCOhost on MEDLINE, PsycINFO, PsycARTICLES, CINAHL, AMED, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, EMBASE, Science Direct, Scopus and Web of Science. To ensure adequate coverage of all PTG relevant papers, searches were conducted using the terms "brain injury," "head injury," "brain tumor," "meningioma," and "stroke" with "posttraumatic growth," "post-traumatic growth," "adversarial growth," "perceived benefits," "stressrelated growth," "benefit finding," "positive growth," "meaningmaking," "positive adjustment," "finding meaning," "positive consequences," "sense-making," and "thriving." In addition, the reference lists of all studies included in the review were examined to identify any further relevant articles, as were the reference lists of any systematic reviews identified through this search strategy.

## Inclusion and Exclusion Criteria

To be included in the systematic review, studies were required to meet the following criteria: (1) be published in English in a peer reviewed journal; (2) report quantitative analysis of post-traumatic growth; (3) involve adults with ABI undergoing rehabilitation as defined by the World Health Organization Definition of Rehabilitation; (4) be based within a health-care or community rehabilitation setting. The title and abstract of each article, and the full article where necessary, were independently screened against the inclusion criteria by two reviewers (Jenny J. Grace and Elaine L. Kinsella). In total 744 studies were identified using the search terms, with this number being reduced to eight using the inclusion and exclusion criteria outlined (**Figure 1**).

The primary reviewers (Jenny J. Grace and Elaine L. Kinsella) independently screened the title and abstract of each article, and the full article where necessary, against the inclusion criteria. Duplicates were removed from the search records (N = 196). There was no disagreement among either reviewer as to the final inclusion of studies obtained through the systematic search. Of the 548 studies identified, articles were excluded because participants had not sustained an ABI (N = 208), included children or adolescents (N = 4), or were review articles, editorials or conference presentations (N = 21). Other exclusion criteria included qualitative analysis of the impact of ABI (N = 30), articles that did not formally examine PTG (N = 211), were animal studies (N = 22), erratums and comment articles (N = 4), dissertations (N = 25), books (N = 5) and theoretical articles (N = 7). Three further studies were excluded as they did not use a validated scale to measure PTG (N = 2), or because the sample was not generalizable to the ABI population (N = 1). Of the final eight studies, three contained insufficient information for calculating the effect size (ES<sup>r</sup> ) for certain constructs. The authors of these articles were contacted, resulting in additional data being provided for one of these studies. In total, the analysis reviewed eight articles with eight independent samples, covering 554 participants and providing 14 ES<sup>r</sup> associations between a variety of constructs and PTG.

# Data Extraction

Study characteristics and statistical information were coded into a database by two authors (Jenny J. Grace and Elaine L. Kinsella) using a data coding manual which was developed and revised to include details of the studies (Lipsey and Wilson, 2001). Coded data included methodological factors (sample size, sampling methods, type of measures, study design), sample characteristics

(age, time since injury, type of injury), and statistical information for calculating effect sizes (e.g., Pearson correlation coefficient).

From the eight studies included in the analysis, two studies used the same sample at different time points. As recommended by Rosenthal (1995), where samples are not independent significance errors can be avoided by treating the non-independent studies as a single study with several dependent variables. The analysis examines only one dependent variable across studies (PTG) and its association with various independent variables, thus the non-independent samples are treated as independent, resulting in eight independent samples.

### Measures

A comprehensive list of measures used to assess PTG and related constructs can be found in **Table 1**.

Seven studies utilized the Post-Traumatic Growth Inventory (PTGI; Tedeschi and Calhoun, 1996) to assess PTG, and one study used the Positive Changes in Outlook questionnaire (CiOP; Joseph et al., 1993). The CiOP examines positive psychological change following trauma and adversity and was deemed suitable to include in the analysis as a measure of growth. The variables measured across each of the eight studies were grouped in line with the classifications of demographics, injury and functional variables, psychological health and cognitive processes (see **Table 2**).

# Data Synthesis and Analysis

#### Effect Size Calculation