Youth strengths predictive of superior mental health - A resilience perspective

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1 Youth strengths predictive of superior mental health - A resilience perspective Study group Postdoc Rikke Wesselhöft, MD PhD, Research Unit of E-mental Health, Mental Health Services in the Region of Southern Denmark, Institute of Clinical Research, University of Southern Denmark (PI) Associated Professor Anne Mette Skovgaard, MD DrMedSc, Institute of Public Health, Faculty of Health Sciences, University of Copenhagen Associated Professor Charlotte Ulrikka Rask, MD PhD, Research Clinic for Functional Disorders and Psychosomatics, Aarhus University Hospital Senior lecturer Argyris Stringaris, MD PhD, Dept. of Child and Adolescent Psychiatry, King s College London, United Kingdom Docent Ida Skytte Jakobsen PhD, University College Lillebælt Statistician Anders Bo Bojesen, Research Unit of E-mental Health, Mental Health Services in the Region of Southern Denmark Background International as well as Danish population-based studies document that mental disorders in childhood are frequent and disabling (Costello et al., 2005; Costello et al., 2006; Costello et al., 2003; Elberling et al., 2016; Petersen et al., 2006). Furthermore, childhood mental disorders are a considerable cost to society and reduce the affected child s quality of life significantly (Petrou et al., 2010; Whiteford et al., 2013). During adolescence, there is a steep rise in incidence of psychiatric disorders (Ford et al., 2003; Kessler et al., 2012; Pedersen et al., 2014; Wesselhoeft et al., 2015) and of suicidal behaviour (World Health Organization, 2014). Many of these adolescent onset disorders persist into adulthood showing a relapsing course (Patel et al., 2007). Therefore, timing plays a central role in prevention of mental disorders and preadolescence is considered a critical window of opportunity (Jackson-Newsom and Shelton, 2010). So far, national (Due et al., 2014) and international (Rutter et al., 2008) mental health programs aiming to prevent youth mental disorders have focused on at-risk children and 1

2 adolescents. However, risk factors cannot always be eliminated or reduced, which challenges the efficacy of a risk-based preventive approach. Furthermore, experiencing stressors might even be strengthening, if the child holds sufficient coping mechanisms (Rutter, 1985), which underlines the complex causality of mental problems. Therefore, a paradigm shift in mental health programs has evolved focusing on strengths rather than risks (Kalisch et al., 2015). Strengths-based interventions target child attributes and resources as the focus for change instead of deficits and shortcomings. This approach reduces the risk for stigma and is strongly supported by the World Health Organisation (World Health Organization, 2014) and the American Academy of Pediatrics ( A British longitudinal study (Vidal-Ribas et al., 2015) finds that youth positive attributes measured by the Youth Strengths Inventory (YSI) represent a construct significantly different from that of psychiatric symptoms, measured by the Strengths and Difficulties Questionnaire (SDQ) (Goodman, 2001). Furthermore, it shows that youth strengths protect children from developing psychopathology, even when adjusting for baseline psychiatric symptoms (Vidal- Ribas et al., 2015). The findings are supported by a Brazilian study that in addition finds youth strengths to predict a better school outcome both independently and by buffering the effect of psychopathology (Hoffmann et al., 2016). The term resilience means a dynamic process encompassing positive adaptation within the context of significant adversity (Luthar et al., 2000). Hence, a resilient child development only occurs in the presence of significant risk, also described as: healthy development in the face of risk (Fergus and Zimmerman, 2005). Focusing on resilience rather than risk in mental health issues holds a substantial potential for development of new effective preventive and treatment interventions (Kalisch et al., 2015). Importantly though, there are substantial cultural differences in child resilience, and what is observed a protective factor in one setting cannot automatically be assumed a protective factor in another. For instance, democratic family decision making is considered a resource in the Nordic countries but induces a poorer outcome for African-American youth in a high-risk environment (Gutman et al., 2002). Therefore, resilience studies of youth mental health are needed in different cultural settings. For this purpose, the use of questionnaires that identify the personal assets of adolescents is recommended (Taliaferro and Borowsky, 2012), and a longitudinal design is mandatory. Very few data sets have information on Danish children s strengths, experienced life stressors and 2

3 mental health outcomes in a prospective design and hence the ability to examine resilient development in large population-based samples. We will examine resilience processes in Danish children by using specific measures that assess positive attributes and life stressors as well as mental health outcomes. Our study will be the first of its kind, identifying specific child personal attributes that promote a resilient mental development over time. Aims The overall aim of our study is to identify specific child-related protective factors that predict good mental health in early adolescence despite the presence of risk factors. The study is based on two Danish birth cohorts, where data was collected at time 1 (T1: 5-7 or 8-10 years), time 2 (T2: years), and time 3 (T3: 13 years) for the current study. The specific aims are divided into four: 1. To examine if child strengths measured at T1 by either a. The Strengths and Difficulties Questionnaire (SDQ) strengths subscale score (SDQstrengths - see Methods), b. The Youth Strengths Inventory (YSI), c. The Social Aptitude Scale (SAS), or d. The Friendship Questionnaire (FQ) represent constructs that are significantly different from the psychiatric symptoms construct measured concurrently by the SDQ composite score (SDQcomp - see Methods) 2. To examine if child strengths (measured by the questionnaires SDQstrengths, YSI, SAS, FQ) predict reduced psychopathology at T2 (measured by SDQcomp and SDQ total difficulties score (SDQtotal) - see Methods) or psychiatric register diagnoses at T3 3. To identify T1 childhood life stressors (measured by DAWBA background section or Soma Assessment Interview (SAI) - see Methods) that predict psychopathology at T2 (measured by SDQcomp and SDQtotal) or psychiatric register diagnoses at T3 4. To identify T1 child strengths that reduce the effect that T1 life stressors induce on psychopathology at T2 or T3 (measured by SDQ and psychiatric register diagnoses respectively) 3

4 Hypotheses Related to our aims, we consider four main hypotheses: H1: Child strengths are constructs empirically discriminable from child psychiatric symptoms H2: Child strengths protect against development of psychopathology (measured dimensionally and categorically) H3: Child stressors increase the risk for development of psychopathology (measured dimensionally and categorically) H4: Some child strengths induce resilience by minimizing the effect of stressors on development of psychopathology Figure 1 illustrates the hypotheses H2-H4. H2 and H3 deal with the potential protective factors (strengths) and potential risk factors (stressors). H4 evaluates the capacity of strengths to reduce the direct effects of stressors. Hypothetically, we will identify specific strengths that promote resilience by inhibiting the stressor-induced development of psycopathology. Strengths (SDQstrengths, YSI, SAS, FQ) H2 Stressors (DAWBA, SAI EFQ) H4 H3 T2 Psychiatric symptoms (SDQtotal, SDQcomp) T3 Psychiatric disorders (Register) Time: Baseline Follow up Figure 1. Three causal models considering hypotheses 2-4 Methods Design The design is a longitudinal study based on prospectively collected data from two Danish birth cohorts. The timing of data collection differed slightly between cohorts (see Figure 2). 4

5 Study participants (sample 1) A subsample of children (N=3,450) from the Danish National Birth Cohort (DNBC) ( (Olsen et al., 2001). Study participants were assessed by mother report at child age 8-10 years (T1) (Wesselhoeft et al., under review), and reassessed by child and mother report at child age 11 years (T2). Figure 2a shows the data collected for use in this study. T1 (8-10 years) SDQ Strengths (SDQ strengths ) symptoms (SDQ comp ) DAWBA YSI SAS FQ Stressors EFQ T2 (11 years) SDQ symptoms (SDQ total, SDQ comp ) T3 (13 years) Central Research register diagnoses Figure 2a. Data collection flow chart (DNBC - sample1) Exposure variables (risk factors in red, protective factors in green) and psychiatric variables (blue) are outlined. Study participants (sample 2) A subsample of children (N=1,585) from the Copenhagen Child Cohort (CCC2000) ( (Elberling et al., 2010). Study participants were assessed by mother report at child age 5-7 years (T1) and 827 of these were reassessed by child and mother report at child age years (T2). Figure 2b shows the data collected for use in this study. CCC2000 study participants are representative of children born in Denmark regarding key perinatal characteristics (Olsen et al., 2007). 5

6 T1 (5-7 years) SDQ Strengths (SDQ strengths ) symptoms (SDQ composite ) SAI Stressors T2 (11-12 years) SDQ symptoms (SDQ total, SDQ comp ) T3 (13 years) Central Research register diagnoses Figure 2b. Data collection flow chart (CCC sample 2) Exposure variables (risk factors in red, protective factors in green) and psychiatric variables (blue) are outlined. Baseline measures (cohort data) Potential protective factors The Strengths and Difficulties Questionnaire (SDQ) (Goodman, 2001) was used at baseline (T1) in both cohorts. The SDQ is a brief mental health questionnaire for children aged 4-17 years that amongst other information includes information on child strengths (Goodman, 2001; Goodman and Scott, 1999). An SDQ strengths score (0-10; from now on referred to as SDQstrengths) is created based on five prosocial items (considerate of other people s feelings, shares readily with others, often volunteers to help, kind to younger children, and helpful if someone is hurt) (Appendix 1). The Development and Well-Being Assessment (DAWBA) parent report was also used in both cohorts at baseline (T1) (Goodman et al., 2000). The DAWBA is a diagnostic assessment that covers most current child psychopathology (Ford et al., 2003; Heiervang et al., 2007). In addition, DAWBA holds the opportunity to collect information on potential protective factors like personal attributes, social skills and friendships, by the use of three questionnaires: The Youth Strengths Inventory (YSI) parent report (Appendix 2) was used in the DNBC at baseline. It consists of 24 items describing child positive attributes (fi. caring, affectionate, generous) and what the child does to please others (Vidal-Ribas et al., 2015). The YSI has shown good psychometric properties (Vidal-Ribas et al., 2015) and a good ability to discriminate between typically developed children (as opposed to SDQ that shows good ability to discriminate between atypically developing children) (Hoffmann et al., 2016). 6

7 The Social Aptitudes Scale (SAS) (Appendix 2) is a 10-item questionnaire addressing social skills like the ability to compromise or apologize, mentalisation capacity and the ability to recognize inappropriate behaviour etc. (Liddle et al., 2009). The SAS was used in both cohorts at baseline. The Friendship Questionnaire (FQ) (Appendix 2) provides information (8 items) on the ability to make and keep friends and the quality of the friendships. The FQ was used in the DNBC at baseline. Potential risk factors Information on exposure to potential risk factors was collected in the DNBC at T1 (Wesselhoeft et al. under review). The DAWBA has an optional background section that covers which life stressors the child experiences. Some of the reported life stressors are; poor physical health, school problems, family stressors, and stressful life events in the past year. Furthermore, DAWBA optionally includes the 10-item parent self-report Everyday Feelings Questionnaire (EFQ) that assesses parental anxious and depressive symptomatology (Uher and Goodman, 2010). In the CCC2000, information on stressors like poor physical health and child physical complaints were collected at T1 using the Soma Assessment Interview (SAI) (Rask et al., 2012). The SAI has been validated in Danish children showing good discrimination between community and clinical samples (Rask et al., 2009). Baseline psychopathology At baseline (T1), the Strengths and Difficulties Questionnaire (SDQ) measured child psychopathology in both cohorts. The SDQ covers four problem areas (emotional problems, hyperactivity/inattention, conduct and peer problems), and assesses distress and functional impairment (Goodman, 2001). The SDQ has been validated in different cultures including Denmark (Bourdon et al., 2005; Heiervang et al., 2007; Niclasen et al., 2012). Usually, an SDQ total difficulties score is calculated by summing the four problem subscales (0-40). For the purpose of testing H1 ( Child strengths and psychopathology are distinct constructs ), an SDQ composite score (SDQcomp) was created based on the subscales: emotional problems, hyperactivity/inattention and conduct problems (0-30). Due to the conceptual overlap between the peer problems subscale and strengths and psychopathology, we excluded this 7

8 variable from the psychopathology construct, similar to Hoffman and colleagues (Hoffmann et al., 2016). Mental health outcomes As recommended, we examine resilience trajectories using both dimensional and categorical mental health outcomes (Kalisch et al., 2015). Dimensional outcomes (T2) The Strengths and Difficulties Questionnaire (SDQ) was also used at T2 in both cohorts, and at this time point it included child report in addition to parent report (Goodman, 2001). Both an SDQ total difficulties score (0-40) and the SDQcomp (0-30) will be considered as dimensional mental health outcomes. Categorical outcomes (T3) Information on whether the child was assigned with a mental disorder diagnosis in the time period between T1 and T3 (age 13 years) will be achieved from the Danish Psychiatric Central Research Register (PCR) (Mors et al., 2011) on all study participants assessed at T1 (N=5,035). The PCR contains data on all contacts to inpatient and outpatient mental health services from 1995 onwards. From 1994 the diagnostic system used was the Danish modification of International Classification of Diseases, 10 th revision, Diagnostic Criteria for Research (ICD-10-DCR) (World Health Organization, 1993). Data analysis First, we use confirmatory factor analyses (CFA) to examine the baseline discriminant validity between child psychiatric symptoms (SDQcomp) and child strengths, measured by four different strengths scales (SDQstrengths, YSI, SAS and FQ). In line with hypothesis H1, we expect that psychiatric symptoms and child strengths represent distinct constructs, showing low levels of correlation. Next, we use strengths scales measured at baseline (T1) as predictors in a set of regression models of mental health outcomes: psychiatric symptoms at T2 (measured by SDQtotal and SDQcomp) and psychiatric disorders at T3 (register diagnoses). SDQ scales are modeled as 8

9 latent variables with ordered categorical indicators. Register diagnoses are modeled in logistic regressions. Third, we use stressors measured at baseline (DAWBA stressors, EFQ, SAI) as predictors in regression models of mental health outcomes: psychiatric symptoms at T2 (measured by SDQtotal and SDQcomp) and psychiatric disorders at T3 (register diagnoses). Finally, for the fourth hypothesis (H4), we let the strengths moderate the effect of stressors on the mental health outcomes by introducing an interaction term in the regression model. In all regression models, we will adjust for relevant confounding variables (baseline psychopathology, gender, age, parental mental disorder, parental marital status, socioeconomic status and educational level). Power calculations based on the smallest cohort (CCC2000, N=827) suggest that even small effects (F 2 < 0.02) are detectable in a multiple linear regression with one predictor and three control variables (power at 80%, significance at p<0.05). F 2 denotes the ratio between explained and unexplained variance for one particular predictor given other covariates are included in the model at the same time. Ethics The study is approved by the Danish Data Protection Agency and the National Committee on Health Research Ethics has been consulted. Perspectives Our study will be the first of its kind identifying child-specific strengths that promote a resilient developmental trajectory towards good mental health in early adolescence. It is a crucial step towards a strengths-based approach in Danish youth mental health. Based on our results, it will be possible to identify specific strengths of a given child by the use of questionnaires. This could be followed by personalized support and improvement of these particular positive attributes in treatment or preventive interventions. The interventions could feasibly take place in schools, where moderate-strong effects have been documented in low- and middle-income countries (Barry et al., 2013), and promising results are found in Denmark as well (Nielsen et al., 2015). Also, online youth mental health promotion and preventive interventions show promising results (Clarke et al., 2015) and could be implemented in a Danish context. 9

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