CH2_Renshaw_Covitality 1

Transcription

1 CH2_Renshaw_Covitality 1 (in press) In M. J. Furlong, R. Gilman, & E. S. Huebner (Eds.), Handbook of Positive Psychology in the Schools (2 nd ed.). New York, NY: Routledge/Taylor & Francis. Covitality: A Synergistic Conception of Adolescents Mental Health TYLER L. RENSHAW Department of Psychology, Louisiana State University, Baton Rouge, Louisiana, USA MICHAEL J. FURLONG, ERIN DOWDY, and JENNICA REBELEZ Department of Counseling, Clinical, and School Psychology, University of California Santa Barbara, Santa Barbara, California, USA DOUGLAS C. SMITH Department of Psychology, Southern Oregon University, Ashland, Oregon, USA MEAGAN D. O MALLEY WestEd, Los Alamitos, California USA SUENG-YEON LEE Department of Psychology, Ewha Womans University, Seoul, Korea IDA FRUGÅRD STRØM Norwegian Centre for Violence and Traumatic Stress Studies Building, Oslo, Norway

2 CH2_Renshaw_Covitality 2 DEFINITIONS AND THEORY BASE Toward Complete Mental Health Interest in promoting youths psychological well-being has traditionally taken a onedimensional model of mental health. This perspective considers psychological distress and wellbeing as being opposite states of human functioning that are represented as opposing poles of a single mental health continuum. Taking from this perspective, reductions in youths psychological distress (e.g., emotional or behavioral symptoms) are synonymous with enhancements to their well-being (e.g., happiness or prosocial behavior), and vice versa (cf. Keyes, 2007). Although this traditional model is parsimonious and intuitive, whether it is comprehensive enough to adequately describe youth mental health has been questioned in recent years as emerging research has examined multiple component (e.g., two-continua or dual-factor) models of mental health. Compared to a one-dimensional model, multicomponent models propose that the elements of psychological distress and well-being are related-yet-distinct aspects of human functioning and they should be represented as separate-yet-associated mental health continua. Several studies have yielded evidence supporting a two-dimensional model of youth mental health by showing that both the presence of distress and the absence of well-being are independently associated with impairments in youths school performance (Suldo & Shaffer, 2008). Both positive and negative indicators of mental health have been shown to have additive value in predicting students attendance and academic achievement over time (Suldo, Thalji, & Ferron, 2011). Given these emerging findings, we propose that there is a need to attend to both symptoms of distress and personal strengths and assets when considering youths complete mental health. From Positive Traits to CoVitality During the past decade and a half, educational scholars and practitioners have given increasing attention to the influence of strengths and assets on youth development, particularly as framed under the banner of positive psychology (e.g., Chafouleas & Bray, 2004; Huebner & Gilman, 2003; Huebner & Hills, 2011; Seligman, Ernst, Gillham, & Linkins, 2009). The nature and scope of this positive oriented work has, so far, followed a multiphase trajectory that is similar to previous traditional, negative oriented mental health work conducted with youth. The first phase of positive psychology s work with youth (a) sought to identify and assess isolated traits (e.g., gratitude, mindfulness, and hope), the majority of which were generalized downwards from previous empirical work with adults and (b) investigated the relations of these individual traits with each other as well as with key quality-of-life outcomes (e.g., positive relationships, physical health, and school achievement). Although this initial measurement phase is still in progress, the validation of several brief instruments for assessing youths strengths and assets has paved the way for another phase of work, which has been characterized by the development and testing of interventions aiming to cultivate or enhance particular positive traits of youth (e.g., the counting blessings exercise for cultivating gratitude and the mindful breathing exercise for enhancing mindfulness). Although this targeted intervention phase is still in progress, a third and more integrative phase of work has also emerged.

3 CH2_Renshaw_Covitality 3 The third phase of positive psychology work with youth, particularly in schools, has been largely shaped by interests in population-based service delivery and is characterized by the development and testing of screening instruments and intervention packages (or curricula) targeting an array of positive psychological assets in youth (Seligman et al., 2009). The overarching aim of this phase has been to create and validate practices that can be integrated into multitiered systems of student support and function to facilitate psychologically healthy educational environments for [all] children (Huebner, Gilman, Reschly, & Hall, 2009, p. 565). Within the broader positive psychology sphere of interest, for example, Seligman (2011) has offered that it is the combination of positive emotions, engagement, relationships, meaning, and accomplishment (PERMA) that forms the foundation for a flourishing life, with this model being applied in some school settings (e.g., White, 2013). Driven primarily by prevention logic, this phase has drawn inspiration from the childhood risk and resilience scholarship, which has demonstrated that increased numbers of external assets (e.g., supportive family and school relationships) and internal assets (e.g., achievement motivation and coping skills) are predictive of better school achievement and other quality-of-life outcomes for youth (e.g., Scales, 1999). Although the major thrust of this phase has been investigating new multiasset measures (e.g., Positive Experiences at School Scale; Furlong, You, Renshaw, O Malley, & Rebelez, 2013) and interventions (e.g., Strong Kids; Harlacher & Merrell, 2010), it has also yielded some new conceptual developments, such as the covitality construct (e.g., Jones, You, & Furlong, 2013). As the counterpart to comorbidity, covitality has been described as the synergistic effect of positive mental health resulting from the interplay among multiple positive-psychological building blocks (Furlong, You, Renshaw, Smith, O Malley, in press). More technically, it is the latent, second-order positive mental health construct accounting for the presence of several co-occurring, first-order positive mental health indicators (Furlong et al., in press). The first study to investigate the applicability of this metaconstruct with youth found that covitality was a better predictor of elementary students (Grades 4 6) prosocial behavior, caring relationships, school acceptance, and school rejection than were the individual contributions of several schoolgrounded positive traits (i.e., gratitude, zest, optimism, and persistence). In a parallel study from a cognitive therapy perspective, Keyfitz, Lumley, Hennig, and Dozois (2013) examined the relations among core positive constructs and self-reported aspects of youths (average age 11 years) problematic and positive development. These authors found that the combination of selfreported self-efficacy, optimism, trust, success, and worthiness was more strongly negatively correlated with scores on scales measuring depression and anxiety and positively correlated with a measure of resilience than were the positive constructs individually. Building on this initial empirical groundwork, we have proposed and investigated an expanded model of covitality for adolescents, which is described and discussed throughout the remainder of this chapter. A Model of Adolescent Covitality Insert Figure 2.1 about here To investigate the validity and utility of the covitality construct among adolescents, we developed a conceptual model that maps onto a testable measurement model (see Figure 2.1).

4 CH2_Renshaw_Covitality 4 Our conceptual model of adolescent covitality posits 12 lower-order constructs, which we refer to as positive psychological building blocks. These lower-order traits are ones that have been widely examined by researchers interested in positive psychology (e.g., Toner, Haslam, Robsinson, & Williams, 2012) and positive youth development (e.g., Lynch, Lerner, & Leventhal, 2013). Our proposed model seeks to make a contribution by suggesting that these 12 lower-order traits all contribute to four core constructs, which we call positive mental health domains. At its core, the proposed model is cognitively based in that it sees adolescents as actively constructing a worldview of who they are and coming to conclusions about their fit within their social contexts. The conceptual grounding for these domains draws on social psychology (e.g., Lips, 1995), self-concept (Chi-Hung, 2005), and cognitive therapy (e.g., Dozois, Eichstedt, Collins, Phoenix, & Harris, 2012; Young, Klosko, & Weishaar, 2003) research, which have suggested that as youth develop and mature they increasingly develop broad cognitive schemas that are used to efficiently make sense of and organize their life experience. Markus (1977) suggested that self-schemata are cognitive generalizations about the self, derived from past experience, that organize and guide the processing of self-related information contained in the individual s social experiences (p. 64). Subsequently, much of this body of research has focused on the development of maladaptive self-schemas because of legitimate concerns about how they might disrupt positive development, as when they lead to depression (e.g., Carlson, 2001), perceptions of a hostile attribution bias (e.g., Pornari & Wood, 2010), or justification for aggressive behavior (e.g., Calvete & Orue, 2012). However, just as self-schemas can contribute to negative developmental outcomes, it is increasingly recognized that the formation of adaptive self-schemas are associated with resilience (Dozois et al., 2012). In fact, we propose that the vast paradigm-changing resilience research (e.g., Masten & Wright, 2010; Werner, 2013) and the rapidly building positive psychology literature (e.g., Norrish & Vella- Brodrick, 2009; Yates & Masten, 2004) are fundamentally about understanding how positive self-schemas are formed, how they are related to adaptive and thriving developmental outcomes, and how they can be fostered across the lifespan. Our model proposes four positive core mental health domains or self-schemas. The first, belief-in-self, is comprised of three constructs investigated in the social-emotional learning (SEL) literature: self-efficacy (e.g., I can work out my problems ), self-awareness ( There is a purpose to my life ), and persistence ( I try to answer all the questions asked in class ). The second domain, belief-in-others, consists of three constructs studied primarily in the childhood resilience literature: school support ( At my school there is a teacher or some other adult who believes that I will be a success ), peer support ( I have a friend my age who really cares about me ), and family support ( There is a feeling of togetherness in my family ). Similar to the first domain, the third domain, emotional competence, is also comprised of three constructs researched primarily in the SEL literature: emotional regulation ( I can deal with being told no ), empathy ( I feel bad when someone gets their feelings hurt ), and behavioral regulation ( I can wait for what I want ). And, the final positive mental health domain, engaged living, is composed of

5 CH2_Renshaw_Covitality 5 three constructs derived from the positive psychology literature: gratitude (frequency of feeling thankful) zest (frequency of feeling energetic) and optimism ( I usually expect to have a good ). This model recognizes that these positive domains are correlated, however, as noted previously in this chapter, we extended this reasoning by proposing that these four domains map on to a higher-order construct that we call covitality. Based on a cumulative resilience model, we have prosed that the influences of lower-order positive psychology building blocks are enhanced when present in combination (Jones, You, & Furlong, 2012; Furlong et al., in press.) When transformed into a measurement model, the 12 positive psychological building blocks are the only constructs from our conceptual model that are measured directly, as both the four positive mental health domains and the overarching covitality construct are inferred as latent constructs. In the next section, we further expand upon our model by providing operational definitions and reviewing relevant research for the 12 positive-psychological building blocks that we situate as the foundation of adolescent covitality and review research on the development of the Social Emotional Health Survey (SEHS; Furlong et al., 2013) that operationalizes the measurement model. See Furlong et al. (2013) for a full description of the SEHS. REVIEW OF KEY RESEARCH STUDIES Operational Definitions Operational definitions for the 12 positive psychological building blocks underlying our adolescent covitality model are provided in Table 2.1. Although these positive-mental-health constructs are not novel, we recognize that our operationalizations may differ slightly from those used in previous works, and that some of our conceptualizations are broader in scope than those employed in several of the studies cited in Table 2.1. For example, while we operationalize our first indicator, self-awareness, as perceiving and attending to the private and public aspects of one s self (see Table 2.1), the studies we cite in support of this indicator were all investigations of youths mindfulness, which was conceptualized in one study as simply attending to one s present moment experience (Drake, Duncan, Sutherland, Abernethy, & Henry, 2008) and in other studies as present-moment attention accompanied by a receptive attitude toward one s experiences (Ciarrochi Kashdan, Leeson, Heaven, & Jordan., 2011; Greco, Baer, & Smith, 2011). A comparison of these definitions with our operationalization of self-awareness, as well as a content analysis of the three items making up the self-awareness scale for the SEHS (see Table 2.1), suggests that although our conception of self-awareness encompasses mindfulness, it also extends beyond the boundaries of mindfulness including awareness of one s purpose in life and an intuitive understanding of one s behavior, which are subphenomena of awareness that have heretofore been uninvestigated in youth. Given this situation, we encourage interested readers to consider the nuances between our definitions of the 12 positive-psychological building blocks and the definitions employed in previous studies. Insert Table 2.1 about here Quality-of-Life Correlates In addition to operational definitions, Table 2.1 also provides an overview of the available correlational evidence for the relations among the 12 positive psychological building

6 CH2_Renshaw_Covitality 6 blocks and selected quality-of-life (QOL) outcomes namely, subjective well-being (SWB) and school/student achievement (S/SA). Given that this overview of the research is purely correlational in nature and focuses on just two key QOL outcomes, we encourage interested readers to explore the additional concurrent validity evidence available for each indicator. For instance, in addition to being positively associated with SWB and S/SA, youths gratitude has also been shown to be positively associated with perceived social support, provision of emotional support to others, and greater social integration (e.g., Froh et al., 2011), whereas optimism has also been demonstrated to be positively associated with successful coping with stress and illness, better college adjustment, more prosocial relationships, better physical health, and greater persistence (e.g., Gillham & Reivich, 2004). Such wider concurrent validity evidence can be found for most of the 12 indicators included in our model. Moreover, further evidence supporting many of these psychological building blocks (including empathy, emotional regulation, and behavioral self-control) is available via findings from treatment studies, such as those demonstrating the effectiveness of school-based universal-level SEL interventions (Durlak, Weissberg, & Pachan, 2010; Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011). Thus, the citations provided in Table 2.1 are best viewed as an introduction to, and not an exhaustive review of, the relevant research literature supporting each indicator. MEASUREMENT APPROACHES AND ISSUES Initial Development and Validation of the SEHS The initial study reporting on the development and validation of the SEHS was conducted with a sample of 4,189 California students in Grades 8, 10, and 12 (Furlong et al., 2013). The overarching purpose of this study was to investigate the SEHS s underlying theoretical and measurement model, which we conceptualized as representing adolescent covitality (see Figure 2.1). This study also aimed to develop a psychometrically sound and socially-valid instrument that could be used to assess covitality, its four positive-mental-health domains, and its 12 positive-psychological building blocks. The original version of SEHS consisted of 51 items that were drafted to represent the 12 core positive psychological building blocks. Following an initial confirmatory factor analysis (CFA) conducted with a split-half of the original sample (n = 2,056), the 51-item SEHS was shortened to a 36-item version, which consisted of the three highestloading items for each subscale. Using the other half of the original sample (n = 2,133), a CFA was conducted on the shortened 36-item version of the SEHS, with findings indicating an overall adequate model fit. All items loaded uniquely onto their respective subscales (no double loadings), the 12 subscales loaded onto their respective hypothesized first-order latent constructs (representing the positive mental health domains), and the four first-order latent constructs further loaded onto one second-order latent construct (representing covitality). In addition to these factor analyses, results from a structural equation path-model indicated that the covitality construct was a significant predictor of adolescents subjective wellbeing. Other analyses indicated that the SEHS had full factorial invariance for males and females supporting its utility as a sound measure of complete mental health for both genders. Moreover, this study yielded initial convergent and divergent validity evidence in favor of the

7 CH2_Renshaw_Covitality 7 covitality construct, demonstrating that higher overall covitality levels were associated with higher self-reported academic achievement and perceptions of school safety. Lower covitality levels were associated with higher self-reported substance use and experiences of depressive symptoms. Taken together, this study suggested that adolescent covitality, as assessed by the SEHS, was an empirically promising phenomenon warranting further investigation. Further Validation of the SEHS A follow-up investigation of the SEHS was conducted with a sample of 2,240 California students in Grades 9 12 to further examine the concurrent and predictive utility of the adolescent covitality construct (You et al., 2013). Using a split-half of the original sample (n = 1,120), a CFA was conducted to reconfirm the factor structure of the 12 subscales (see Figure 2.1). Findings from this analysis indicated that, similar to the initial development study, an adequate model fit was obtained with all items loading onto their 12 hypothesized subscales. Following this analysis, and using the other split-half of the original sample (n = 1,120), another CFA was conducted to confirm the full hypothesized structure of the SEHS. Findings replicated the initial development study with an adequate model fit. Additional validity analyses using structural equation modeling indicated that covitality was a significant negative predictor of adolescents social-emotional-behavioral symptoms, and that the SEHS had full factorial invariance for younger (ages years) and older (ages years) adolescents providing additional support for its utility as an appropriate measure of complete mental health for all adolescents. Further validity evidence in favor of the covitality construct was found in that higher covitality scores predicted higher course grades at the end of the academic term. In addition to evidence supporting the validity of the SEHS, we found that the total covitality score (summed across all 36 items) has strong reliability (α =.92) and is essentially normally distributed (skewness = -0.54, kurtosis = 0.49). Because the SEHS latent traits are proposed to measure self-schemas, we anticipate that they are consistent over time. To examine this aspect of the SEHS s psychometric properties, 115 adolescents (14-15 years old at Time 1, 55% females) completed the SEHS at two time points, approximately 12 months apart (Furlong et al., 2013). The stability coefficients reflected trait-like stability for all of the SEHS latent constructs: belief-in-self (r12 =.56), belief-in-others (r12 =.57), emotional competence (r12 =.57), engaged living (r12 =.45), and covitality (r12=.60). In sum, the SEHS has promising psychometric properties for assessing adolescents mental health and the covitality construct is significantly related to and predictive of key school-based and quality-of-life outcomes. One of the advantages of the SEHS is that because it is normally distributed it measures a full continuum both high and low scores of covitality provide meaningful information. As such, it has potential to be used as part of a more general approach to assess complete mental health. We turn now to a discussion of how the SEHS and its covitality construct is being used by educators to assess complete mental health via a schoolwide universal screening process. EDUCATIONAL APPLICATIONS Schoolwide Mental Health Screening

8 CH2_Renshaw_Covitality 8 Within a schoolwide screening initiative, the SEHS can be used as an instrument for assessing youths mental health, to identify which students are most likely to need preventive or early intervention services (Doll & Cummings, 2008; Severson, Walker, Hope-Doolittle, Kratochwill, & Gresham, 2007). Although the practice of schoolwide mental health screening is nascent, the majority of available screeners are designed to assess risk factors or clinical symptoms, which are endorsed by no more than 20% of students. Thus, resources are expended to identify a small group of needful or troubled students. One way to remedy this problem and provide information that is relevant to 100% of students is to use a screener that assesses positive aspects of youths psychological development to compliment the traditional risk-and-symptomsfocused screening process. As both high and low scores on the SEHS provide meaningful information, its use in schoolwide screening might be particularly relevant to expand the applicability of schoolwide mental health screening to the entire student body. All students, regardless of their level of impairment or risk, have strengths that can be identified and cultivated to facilitate more optimal developmental outcomes. Given this context, school-based student care teams might use SEHS data in conjunction with traditional mental health screening data to gain a better understanding of youths complete mental health, which could, in turn, help them provide more comprehensive and well-rounded services for improving the academic performance and other QOL outcomes for all students at a given school. To help school-based practitioners and researchers understand how the SEHS could be used for such purposes, we offer, in the next subsection, an example of our use of this measure as a positive mental health screener within a secondary school context. An Example of Universal Screening with the SEHS We recently used the SEHS as a part of a complete mental health screening initiative in a large, urban high school in California (Grades 9-12; see Dowdy et al. [2013] for a more detailed description). Prior to beginning the initiative, university-based personnel and school-district personnel met to discuss the aims of the screening project, which included identifying which students were in need of additional supports and gathering an overall profile of the mental health functioning of all the students at the school so that schoolwide services could be appropriately tailored to fit the school s and the students needs. Two self-report instruments were chosen to assess students complete mental health, the SEHS and the Behavior Assessment System for Children-2 (BASC-2) Behavioral and Emotional Screening System Student (BESS), which is a 30-item behavior rating scale designed to measure risk for behavioral and emotional problems (Kamphaus & Reynolds, 2007). In the first month of the academic school year, during one hour of the regular school day, members of the school staff and research team canvassed the high school, providing each class with a brief explanation of the screening procedures. All students who consented to participate completed the SEHS and the BESS. Completed surveys were received from approximately 83% of the enrolled student population. An overall T score was provided for each student, which was used to classify each adolescent into one of three risk-level categories: normal, elevated, and extremely elevated, per standard BESS procedures. Based on previous research showing that the

9 CH2_Renshaw_Covitality 9 sum of the 36 SEHS items was approximately normally distributed (Furlong et al., in press), the composite scores were used to classify each student into one of four categories: low strengths (< 1 SD), low-average strengths (1 SD to 0 SD), high-average strengths (> 0 SD to 1 SD), or high strengths (> 1 SD). Both schoolwide and student-level results were provided to school personnel. Results describing the school s overall profile of student mental health functioning were presented to school administrators and staff. For example, a graph depicting the percent of students with low, middle, and high scores for the personal strengths were provided (see Figure 2.2). In response, school personnel discussed strategies to increase peer support and enhance the academic persistence of students. Insert Figure 2.2 about here Additionally, students responses to both the BESS and the SEHS were combined (see Figure 2.3), resulting in each student being placed into one of the following nine complete mental health functioning categories: Highest Risk (extremely elevated BESS score, low or lowaverage SEHS score), Moderate Risk (elevated BESS score, low SEHS score), Lower Risk (elevated BESS score, low-average SEHS score), Languishing (normal BESS score, low SEHS score), Getting By (normal BESS score, low-average SEHS score), Moderate Thriving (normal BESS score, high-average SEHS score), High Thriving (normal BESS score, high SEHS score), and Inconsistent (elevated or extremely elevated BESS score, high-average or high SEHS score). Using these data, individual student reports, organized by risk-level, were provided to school personnel, who used the information to determine which students needed additional supports. A triage process was developed to determine the priority of needs, as resources were insufficient to serve all students immediately, and services were provided for students in the Highest Risk group. Overall, using the SEHS as one part of a multicomponent complete mental health assessment resulted in richer information regarding the mental health functioning of each student. Its use facilitated the development of interventions and supports that were grounded in building student strengths, not just remedying symptoms. Most importantly, data provided by the SEHS enabled the school s student care team to consider the complete mental health status of all students, as opposed to focusing on the negative functioning of only a few students, and thus empowered them to develop support services aiming to benefit the entire student body. Insert Figure 2.3 about here Individual Assessments The SEHS is likely to be useful as a schoolwide mental health screener, providing schools with the opportunity to assess covitality among all students, in hopes that by identifying strengths to build upon and deficits to remediate evidence-based support services can be provided. However, the SEHS can also be incorporated into preexisting individualized assessment frameworks, serving as an instrument for measuring and synthesizing strength-based information for use within comprehensive evaluations for determining eligibility for special education. Including strengths-based information within this individualized assessment process provides a broader, more comprehensive perspective on students functioning, which is likely to facilitate increased satisfaction with assessment and resulting intervention services (Cox, 2006;

10 CH2_Renshaw_Covitality 10 Epstein, Hertzog, & Reid, 2001; Walrath, Mandell, Holden, & Santiago, 2004). Although further research is needed to demonstrate the sensitivity of the SEHS to change in response to intervention, the brevity and breadth of the measure suggest that it might also serve as a practical progress-monitoring instrument to evaluate the effects of interventions designed to enhance students positive mental health. The SEHS may be useful to evaluate the effectiveness of both individual and group-counseling interventions designed to increase student s strengths and assets. Thus, the SEHS might be used at varying points within a comprehensive service delivery model, from population-based screening to individual assessments to progress monitoring and evaluation of interventions. DIVERSITY AND DEVELOPMENTAL CONSIDERATIONS As a unifying construct, covitality potentially offers a framework for understanding the dynamic interplay of a wide range of internal and external assets that work synergistically to enhance overall well-being among youth. A fundamental question remains as to whether and to what extent the covitality framework applies to a broad range of students manifesting individual differences with regard to age, gender, cultural background, and other relevant factors. Although responding to these questions will require considerably more empirical effort, our research group has begun to address the covitality model s applicability to diverse populations by including samples of students across grade levels and from countries outside the United States. In addition to the SEHS described in this chapter, our efforts have included the development of additional covitality scales appropriate for use with students ranging from elementary to university school settings. With each scale, our intention is to determine structural invariance according to age, gender, and nationality, as well as to determine the predictive utility of such scales. With regard to age and gender differences, the 12 lower-order traits measured by the SEHS have been shown to demonstrate full factorial invariance for males and females in our original California samples, as well as factorial invariance for younger and older secondary level students. There is a need to further examine the SEHS s factorial invariance across more diverse samples of students who may differ, not only in terms of age and gender, but also with regard to factors such as socioeconomic status, cognitive dimensions including language skills, and broader distinctions related to culture and ethnicity. In an effort to examine the role of covitality as a predictor of younger students wellbeing and engagement in school, Furlong, You, Renshaw, O Malley, and Rebelez (2013) developed the Positive Experiences at School Scale (PEASS) for elementary school children. Utilizing a combination of four psychological building blocks including gratitude, zest, optimism, and persistence, the PEASS was administered to 1,995 students from Grades 4-6 from four school districts located in central California. Similar to the findings reported for the SEHS, analyses provided support for covitality as a unifying construct for young students, providing better predictive utility in terms of students positive school development than the four positive psychological traits considered individually. In addition, the model was found to be sufficiently invariant across males and females in this sample.

11 CH2_Renshaw_Covitality 11 In an examination of the covitality model with university students, Jones et al. (2012) explored the combination of six first-order positive psychological constructs including selfefficacy, hope, life satisfaction, optimism, happiness, and gratitude with a sample of 528 undergraduate students attending a university in Southern California. Although only five of the six first-order constructs were independently identified on the basis of factor analysis, all of these significantly loaded onto the second-order covitality factor, which itself proved to be a good predictor of positive aspects of mental health, as well as negative symptoms of mental distress. The fact that we were able to identify and replicate the higher-order latent covitality construct as a viable predictor of positive student outcomes with student samples from elementary school through college provides impressive support for an additive, multiple positive psychological traits model of youth mental health. The high degree of factorial invariance across genders garners additional support for its utility as a sound measure of covitality for students of both sexes. The evaluation of ethnic and cultural variations with regard to covitality presents numerous measurement challenges for researchers because cross-cultural comparisons can involve cultural differences as well as language differences. At present, we have translated the SEHS into several languages and have collected or are in the process of collecting SEHS data from students in Australia, Japan, Korea, and Peru, with plans to extend this to other Pacific Rim countries. Preliminary analysis of a Japanese translation of the SEHS administered to a sample of approximately 600 public and private school students in and around Tokyo, again supported the notion of covitality as a valid, second-order latent construct for predicting a wide range of positive youth outcomes including school engagement and performance (Smith, Ito, & Furlong, 2013). Our future plans also include examining data collected from eight California comprehensive high schools that will allow structural comparisons of SEHS data with more diverse ethnic populations, including students from African-American and Asian-American backgrounds. As this research goes forward, there is a need to explore other iterations of the covitality model, perhaps including additional positive psychological dispositions or supportive assets with diverse samples of youth. It may well be true that specific combinations of psychological assets differentially predict a variety of positive outcomes for youth, and these differences may be further influenced by cultural and ethnic factors. In addition, there remains a need to establish structural invariance of existing measurement tools (e.g., PEASS, SEHS) with other populations of students from within the United States as well as internationally. CONCLUSION Significant advances have been made towards a more comprehensive understanding of youth s well-being. It has become increasingly clear that there is value in assessing for personal strengths and assets in addition to solely assessing for psychological distress. It is also known that increased numbers of personal strengths and assets are associated with more positive outcomes and educators are beginning to learn about how those strengths and assets can combine in powerful ways. This chapter introduced covitality as the synergistic effect of positive mental

12 CH2_Renshaw_Covitality 12 health resulting from the combination of multiple positive psychological strengths and assets. We provided a conceptual model of adolescent covitality along with development and validity evidence in support of the SEHS, a measure designed to provide an overall measure of covitality. The SEHS represents a potential advancement, as now researchers and practitioners have a psychometrically sound and widely applicable tool to measure and further examine covitality. We wish to make it clear that we do not present our model as being exhaustive in scope because it was not designed to account for all preexisting, empirically-promising indicators of positive youth development. Rather, we put forth our current model as a parsimonious, wellrounded, and conceptually-sound representation of core positive psychological indicators that have both face validity and empirical promise as predictors and facilitators of students wellbeing, school success, and other quality-of-life outcomes. Thus, although we offer a particular conception of covitality, future research might expand on, reduce, and revise our model when such changes are warranted on both theoretical and empirical grounds. The development of the covitality construct is only in the beginning stages of understanding its complexities and which sub-components are most related to important educational and QOL outcomes. We continue to be interested to identify: (a) profiles of personal strengths that might exist, (b) combinations of assets that are necessary for positive development, and (c) combinations of assets that are sufficient for positive outcomes. Our initial findings suggest that it is the combination of strengths and assets that is the most powerful, rather than any of the unique constructs in isolation. It is also likely that there may be more optimal ways to intervene to enhance covitality, rather than developing each skill (e.g., gratitude) in isolation. However, our understanding of the mechanisms involved in the interplay among these constructs is limited, which, in turn, limits our understanding of how to best intervene and help students achieve optimal developmental outcomes. We hope that this current lack of understanding will provide impetus for future conceptual, assessment, and intervention work. In the same way that the study of comorbidity offered new insights into the assessment and treatment of youth with co-occurring problems, we hope that the continued study of covitality will provide further information regarding how to best help students achieve optimal developmental outcomes.

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17 CH2_Renshaw_Covitality 17 professional practices. Journal of School Psychology, 45, doi: /j.jsp Smith, D. C., Ito, A., & Furlong, M. J. (2013). Covitality and school performance and engagement among Japanese youth. Manuscript submitted for publication. Stewart, T., & Suldo, S. (2011). Relationships between social support sources and early adolescents mental health: The moderating effect of student achievement level. Psychology in the Schools, 48, doi: /pits Suldo, S. M., & Shaffer, E. J. (2008). Looking beyond psychopathology: The dual-factor model of mental health in youth. School Psychology Review, 37, Suldo, S. M., Thalji, A., & Ferron, J. (2011). Longitudinal academic outcomes predicted by early adolescents subjective well-being, psychopathology, and mental health status yielded from a dual-factor model. The Journal of Positive Psychology, 6, doi: / Toner, E., Haslam, N., Robinson, J., & Williams, P. (2012). Character strengths and wellbeing in adolescence: Structure and correlates of the values in action inventory of strengths for children. Personality and Individual Differences, 52, doi: /j.paid Vecchio, G. M., Gerbino, M., Pastorelli, C., Del Bove, G., & Caparara, G. V. (2007). Multi-faceted self-efficacy beliefs as predictors of life satisfaction in late adolescence. Personality and Individual Differences, 43, doi: /j.paid Vera, E., Thakral, C., Gonzales, R., Morgan, M., Conner, W., Caskey, E., Dick, L. (2008). Subjective well-being in urban adolescents of color. Cultural Diversity and Ethnic Minority Psychology, 14, doi: / Veronese, G., Castiglioni, M., Tombolani, M., & Said, M. (2012). My happiness is the refugee camp, my future Palestine : optimism, life satisfaction and perceived happiness in a group of Palestinian children. Scandinavian Journal of Caring Sciences, 26, doi: /j x Vidal Roderio, C. L., Emery, J. L., & Bell, J. F. (2012). Emotional intelligence and academic attainment of British secondary school children: A cross-sectional survey. Educational Studies, 38, doi: / Vieno, A., Santinello, M., Pastore, M., & Perkins, D.D. (2007). Social support, sense of community in school, and self-efficacy as resources during early adolescence: an integrative model. American Journal of Community Psychology, 39, doi: /s Vukman, K. B., & Licardo, M. (2010). How cognitive, metacognitive, motivational and emotional self-regulation influence school performance in adolescence and early adulthood. Educational Studies, 36, doi: / Walrath, C. M., Mandell, D., Holden, E. W., & Santiago, R. L. (2004). Assessing the strengths of children referred for community-based mental health services. Mental Health Services Research, 6(1), 1 8. Werner, E. E. (2013). What can we learn about resilience from large-scale longitudinal studies? In S. Goldstein & R. B. Brooks (Eds.), Handbook of resilience in children (pp ). New York, NY: Springer. doi: / _6 White, M. A. (2013). Positive education at Geelong grammar school. In Proceeding of the Richard and Janet Southby Visiting Fellows Program (pp ). New York, NY: Oxford University Press. Available from Wong, S. S., & Lim, T. (2009). Hope versus optimism in Singaporean adolescents: Contributions to depression and life satisfaction. Personality and Individual Differences, 46, doi: /j.paid Yates, T. M., & Masten, A. S. (2004). Fostering the future: Resilience theory and the practice of positive psychology. In P. A. Linley & S. Joseph (Eds.), Positive psychology in practice (pp ). Hoboken, NJ: Wiley. Retrieved from You, S., Dowdy, E., Furlong, M. J., Renshaw, T. L., Smith, D. C., & O Malley, M. D. (2013). Further validation of the Social and Emotional Health Survey for High School students. Manuscript submitted for publication. Young, J. E., Klosko, J. S., & Weishaar, M. E. (2003). Schema therapy: A practitioner s guide. New York, NY:

18 CH2_Renshaw_Covitality 18 Guilford. Zhu, Y. Q., Chen, L. Y., Chen, H. G., & Chern, C. C. (2011). How does Internet information seeking help academic performance? The moderating and mediating roles of academic self-efficacy. Computers and Education, 57, doi: /j.compedu Zuffiano, A., Alessandri, G., Gerbino, M., Luengo Kanacri, B. P., Di Giunta, L., Milioni, M., & Vittorio Caprara G. V. (2013). Academic achievement: The unique contribution of self-efficacy beliefs in self-regulated learning beyond intelligence, personality traits, and self-esteem. Learning and Individual Differences, 23, doi: /j.lindif

19 CH2_Renshaw_Covitality 19 CHAPTER SUMMARY: COVITALITY In contrast to a unidimensional model of mental health, a bidimensional model recognizes that psychological well-being and distress are separate-but-associated states of human functioning, and that both positive and negative indicators of mental health deserve consideration. Covitality is a positive construct that is a result of the interplay among multiple co-occurring positive psychological mental health indicators. The covitality model presented consists of 12 positive psychological building blocks that contribute to four core mental health domains or self-schemas (belief-in-self, belief-in-others, emotional competence, and engaged living), which all load on to the higher-order construct called covitality. The Social Emotional Health Survey has sound psychometric properties for assessing covitality, its four positive-mental-health domains and its 12 positive-psychological building blocks, and is significantly related to and predictive of important quality-of-life and schoolbased outcomes. The SEHS can be used as part of a complete mental health screening initiative in schools to expand the applicability of results to all students, and may be useful as an individual assessment and progress-monitoring tool. Most of the current SEHS research involved Californian samples with a preponderance of Latino/a students. The positive psychometric characteristics or structural invariance by gender and age needs to be extended to include other sociocultural groups in the United States and in other countries. Continued research on covitality is needed to better understand how to further enhance youths developmental outcomes.

20 CH2_Renshaw_Covitality 20 SUGGESTED READINGS: COVITALITY Furlong, M. J., You, S., Renshaw, T. L., O Malley, M. D., & Rebelez, J. (2013). Preliminary development of the Positive Experiences at School Scale for elementary school children. Child Indicators Research. Advanced online publication. doi: /s This article provides detailed presentation of the development and validation of the 16- item Positive Experiences at School Scale (PEASS). The PEASS includes subscales that measure persistence, gratitude, optimism, and zest with support that they all map on to the higher-order covitality construct. Furlong, M. J., You, S., Renshaw, T. L., Smith, D. C., & O Malley, M. D. (in press). Preliminary development and validation of the Social and Emotional Health Survey for secondary students. Social Indicators Research. The study presents detailed information about the development and validation of the Social Emotional Health Survey that is described in this chapter. The analyses include multigroup invariance and latent means analyses comparing males and females Keyfitz, L., Lumley, M. N., Hennig, K. H., & Dozois, D. J. A. (2013). The role of positive schemas in child psychopathology and resilience. Cognitive Therapy and Research, 37(1), doi: This study uses a small sample to present the preliminary development of the Positive Schema Questionnaire for children ages Psychometric properties are presented as well as concurrent validity analyses. Park, N., & Peterson, C. (2006b). Moral competence and character strengths among adolescents: The development and validation of the Values in Action Inventory of Strengths for Youth. Journal of Adolescence, 29, doi: /j.adolescence The psychometric properties of an adaptation of the Values in Action Survey, based on Seligman and Perterson s Character Strengths framework, is presented. Suldo, S. M., Thalji, A., & Ferron, J. (2011). Longitudinal academic outcomes predicted by early adolescents subjective well-being, psychopathology, and mental health status yielded from a dual-factor model. The Journal of Positive Psychology, 6, doi: / Suldo is a key contributor to research that examines the use of a dual-factor model of mental health in school contexts. This study further describes the dual-factor model and examines its relations with academic achievement.

21 CH2_Renshaw_Covitality 21 Table 2.1. Definitions and Correlates of Covitality Indicators Covitality Indicator Construct Definition Range of r with SWB 1 [95% CI] References Range of r with SA 2 [95% CI] References BELIEF-IN-SELF Self- Awareness Perceiving and attending to the private and public aspects of one s self (Abrams & Brown, 1989) [.17,.43] Ciarrochi et al., 2011; Drake et al., 2008 ~.28 [.23,.33] Greco et al., 2011 Persistence Working diligently to accomplish one s goals, including maintaining interest in the face of adversity and failure (Duckworth et al., 2007) [-.03,.42] Garcia, 2011, [.15,.42] Duckworth & Quinn, 2009; Martin & Marsh, 2006 Self- Efficacy Sensing one s ability to act effectively to meet environmental demands (Bandura et al., 1996) [-.03,.51] Danielsen et al., 2009, 2012; Fogle et al., 2002; Lightsey et al., 2011; Vecchio et al., 2007; Vieno et al., [.06,.51] Capara et al., 2011; Zhu et al., 2011; Zuffiano et al., 2013 BELIEF-IN-OTHERS Peer Support Appraising the caring and helpful nature of one s relationships with peers (Farmer & Farmer, 1996) [.07,.63] Danielsen et al., 2009; Flaspohler et al., 2009; Oberle et al., 2011; Schwarz et al., 2012; Vera et al., [.01,.33] Chen, 2005; Danielsen et al., 2009; Ozer & Schotland, 2011; Rosalind, 2010

22 CH2_Renshaw_Covitality 22 Teacher Support Appraising the caring and helpful nature of one s relationships with teachers (Farmer & Farmer, 1996) [.29,.61] Danielsen et al., 2009; Ferguson et al., 2010; Flaspohler et al., 2009; Stewart & Suldo, [.05,.43] Chen, 2005; Danielsen et al., 2009; Rosalind, 2010; Stewart & Suldo, 2011 Family Support Appraising the caring and helpful nature of one s relationships with family (Farmer & Farmer, 1996) [.29,.72] Danielsen et al., 2009; Ferguson et al., 2010; Oberle et al., 2011; Schwarz et al., 2012; Stewart, & Suldo, 2011; Vieno et al., [.13,.33] Chen, 2005; Danielsen, Samdal, Hetland, & Wold, 2009; Rosalind, 2010; Stewart, Suldo, 2011 EMOTIONAL COMPETENCE Empathy Perceiving, sharing, and considering the emotional states expressed by others (Garaigordobil, 2004) ~.27 [.08,.44] Oberle et al., 2010 No available research Emotional Regulation Effectively expressing one s positive emotions (e.g., happiness) and managing one s negative emotions (e.g., anger; Fry et.al., 2012) [.10,.38] Haga et al., 2009; Saxena et al., [.19,.45] Gail, & Arsenio, 2002; Vidal Roderio et al., 2012; Vukman, & Licardo, 2010 Behavioral Self-Control Effectively expressing and managing one s behavior within given contexts (Hofer et al., 2011) [.27,.55] Fry et al., 2012; Hofer, et al., [.11,.48] Bertrams, 2012; Kuhnle et al., 2012; Vidal Roderio et al., 2012 ENGAGED LIVING

23 CH2_Renshaw_Covitality 23 Gratitude Sensing thankfulness that arises in response to one s benefitting from some kind of transactional means (Emmons, 2007) [.06,.66] Froh et al., 2009; Froh et al., 20; Proctor et al., 2010 ~.28 [.23,.33] Froh et al., 2011 Zest Experiencing one s life in the present moment as exciting and energizing (Park & Peterson, 2006b) [.24,.59] Park & Peterson, 2006a, 2006b No available research Optimism Expecting the occurrence of good events and beneficial outcomes in one s future (Utsey et al., 2008) [.11,.68] Chang et al., 2003; Extremera et al., 2007; Gadermann et al., 2011; Froh et al., 2009; Ho et al., 2010; Lai, 2009; Oberle et al., 2011; Piko et al., 2009;Veronese et al., 2012; Wong & Lim, [.07,.39] Creed et al., 2002; Lounsbury et al., 2002; Vidal Roderio et al., 2012 Note. 1 = Subjective Well-Being, 2 = School/Student Achievement.

24 CH2_Renshaw_Covitality 24 Figure 2.1. Theoretical and measurement model underlying the Social Emotional Health Survey and adolescent covitality.

25 CH2_Renshaw_Covitality 25 Figure 2.2. Example of reporting the results of a complete mental health screening showing the schoolwide covitality building block profile as reported back to the school administrators, teachers, and student care coordination team.

26 CH2_Renshaw_Covitality 26 Figure 2.3. Example of reporting the results of a schoolwide universal complete mental health screening process using the Social Emotional Health Survey (SEHS) for psychological strengths and the Behavioral Emotional Screening System (BESS) for psychological distress. School care coordination team engaged in a triage process to provide supports for students in greatest need and to develop schoolwide programs and activities to promote student thriving.