Master of Arts (MA)
When using a bidimensional mental health (BDMH) model, psychological distress and wellbeing are measured. This study used a mental health screening measure, with equal number of items measuring each mental health dimension (i.e., wellbeing and distress) to classify students into one of four possible mental health groups: mentally healthy (MH), mentally unhealthy (MU), symptomatic but content (SBC), and asymptomatic but discontent (ABD). First, prevalence rates for each group in a sample of youth from the 2009–10 Health Behavior in School-aged Children Survey in the United States (N = 6,345) were explored; about a quarter of the population experienced mixed mental health (i.e., SBC or ABD). The second purpose was to investigate how demographic variables (e.g., gender, ethnicity) influenced a student’s BDMH; these variables did not have a practically meaningful relationship to BDMH. The third purpose was to investigate the effect of BDMH classification (i.e., MH, MU, SBC, or ABD) on relevant student behavior variables (i.e., school performance perceptions, class climate, bullying victimization and perpetration, family support, life satisfaction, somatic symptoms, alcohol, cigarette, and marijuana use). Results indicated that MH students experienced the most advantageous, and MU students the most deleterious, concurrent outcomes. However, ABD students (not identified by a traditional screener) experienced concurrent outcomes worse than or similar to their MU peers. Taken together, the results suggest that measuring wellbeing has value-added in differentiating students with varying levels of risk, and identifying students with potential need for intervention. Implications of these results and considerations regarding measurement of psychological wellbeing in mental health screening procedures in schools are discussed.
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Bolognino, Sarah, "Examining the Prevalence Rates, Demographic Differences, and Concurrent Validity Associated with a Universal Bidimensional Mental Health Screener for Youth in Schools" (2015). LSU Master's Theses. 2051.