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Significant progress has been made toward a robust understanding of mental health, inclusive of both the absence of distress symptoms and the presence of positive health indicators (Greenspoon & Saklofske, 2001; Keyes, 2002). This conceptualization of mental health recognizes that the absence of distress alone is insufficient to assume wellbeing, and that it is necessary to focus on social-emotional strengths and assets (Scales, 1999). Dual-factor, or twocontinua, mental health models propose that positive (e.g., subjective well-being, social-emotional strengths) and negative (e.g., internalizing or externalizing distress) mental health indicators are related, yet distinct, constructs and that both need to be considered when assessing the mental health functioning of youths (Suldo & Shaffer, 2008). Concurrent with this expanded conceptualization of mental health, there has been an increased understanding of the need to proactively and universally assess youths' mental health in schools (Kamphaus, Reynolds, & Dever, 2014). Considering research highlighting the variety of negative educational and life outcomes associated with mental health problems (e.g., Bradley, Doolittle, & Bartolotta, 2008), universal school-based screening has been proposed as an essential first step toward identifying the mental health needs of students (Glover & Albers, 2007). Then, data-based decisions can be made to inform prevention, early intervention, and promotion efforts to relieve symptoms of distress and foster youths' thriving (Furlong, Dowdy, Carnazzo, Bovery, & Kim, 2014). Complete mental health screening is a contemporary approach to early identification that is aligned with dual-factor, expanded definitions of mental health (Furlong, You, Renshaw, Smith, & O'Malley, 2014). In this screening approach, symptoms of distress and indicators of strengths are both assessed to provide a comprehensive picture of youths' mental health functioning. When assessing youth's mental health functioning, it is essential to ask the students themselves about the positive and negative aspects of their life experiences (Furlong, Dowdy, et al., 2014). In addition, students are generally viewed as the best informants when measuring internalizing symptoms or their own perceptions or feelings (Dowdy & Kim, 2012). Complete mental health screening via student self-report provides a structured opportunity for students to provide information about their well-being. Approaches to complete mental health screening have generally involved coadministering multiple measures, with at least one measure focused on symptoms of distress and another focused on the presence of strength indicators 749871A EIXXX10.

Considering the many positive outcomes associated with adolescents’ sense of school belonging, including psychological functioning, it is possible that including an assessment of school belonging within a complete mental health screening process could contribute to the prediction of students’ future mental health status. This exploratory study used complete mental health screening data obtained from a central California high school (N = 1,159). At Time 1 (T1) schoolwide screening was used to identify complete mental health groups by applying a dual-factor strategy and concurrently measuring students’ school belonging. One year later at Time 2 (T2), social-emotional wellbeing and internal distress were assessed. Cross-sectional T1 results indicated that there were significant differences in school belonging between students who reported low global life satisfaction and those who reported average or high global life satisfaction, regardless of reported level of psychological distress. A comparison of T1 to T2 data revealed that global life satisfaction and psychological distress were predictive of wellbeing and internal distress. However, contrary to study expectations, school belonging at T1 added little to the prediction of T2 psychological distress beyond the information already provided by the T1 dual-factor screening framework. Implications for practice and future directions are discussed.

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The current study analyzed 502 responses from members of the education workforce on the Resilience at Work (RAW) scale and other measures of health and job satisfaction as part of an initiative offering training and technical assistance to support student and staff well-being. A latent profile analysis using scores on components of the RAW identified three resilience profiles: lower, moderate, and higher capacities for resilience. Profiles were differentiated across components related to resilience capacity including alignment of work and personal values, level of social support, and ability to manage stress. Differences between profiles were observed across days of poor physical health, days of poor mental health, days of activity restriction, general health rating, and domains of burnout, compassion satisfaction, and secondary traumatic stress. These findings reinforce calls to support the education workforce through changes that allow access to meaningful work, an evaluation of demands including workload, relevant training on emotional wellness, positive experiences, connections with others, and stress management.