Longitudinal Associations Between School-, Staff-, and Student-Level Factors with Student Mental Health and Wellbeing

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Stevens, Kate Maston, Joanne R. Beames, Bridianne O’Dea, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7341749/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract School characteristics are associated with student mental health cross-sectionally, but little is known about effects of school factors over time. This study assessed whether school-level (regional, administrative, and student characteristics), staff-level (school culture and promotion of wellbeing), and student-level factors (school climate and connectedness) were associated with students’ distress and wellbeing cross-sectionally, and two years later. The sample consisted of N = 1548 adolescents in Year 8 ( M age =13.9) from 35 schools in Australia. Results showed that greater student-level socioeconomic advantage was associated with better wellbeing cross-sectionally. Higher levels of student-rated school connectedness and climate were associated with greater wellbeing and lower distress cross-sectionally. Longitudinally, only higher student-rated school connectedness was associated with higher wellbeing two years later. No school-level factors were associated with student wellbeing or distress, cross-sectionally or two years later. Findings highlight the importance of students’ sense of connectedness with their school community on wellbeing over time. Health sciences/Health care Biological sciences/Psychology Social science/Psychology schools adolescence mental health wellbeing psychological distress Introduction Adolescence is a critical period for the development of mental health disorders, with epidemiological studies finding that more than half of disorders emerge before the age of 18 1–3 . Concerningly, the prevalence of adolescent mental health diagnoses is rising globally 4 , which has led to increased attention to the role that environmental and community-level factors may play in promoting or mitigating risk for adolescent mental health. For example, an emerging area of interest to both researchers and policy makers is how the school context may influence the mental health of students, a priority that has been highlighted both in a recent United Nations policy review as well as in Australia’s National Child Mental Health and Wellbeing Strategy 5 , 6 . Schools provide not only an important educational influence on adolescent development, but provide a setting within which important cognitive, social, and emotional milestones are supported, providing the foundations for adulthood 7 . Adolescents spend a significant proportion of their time at school, and school experiences are theorized to impact their mental health and wellbeing through multiple pathways 8 . A number of studies have identified cross-sectional associations between school region (i.e. whether the school is located in an urban or rural location), administrative (i.e. structural, financial, and staffing information), and cultural factors (i.e. perceptions of the overall culture and connectedness of the school community) with student mental health and wellbeing 9 – 12 . These findings highlight the need to better understand which aspects of the school context are most important for student mental health, to inform public policies and initiatives that support student mental health and wellbeing. There is substantive literature assessing the influence of school-level factors, such as demographic characteristics, aspects of the school administration and structure of the school, and student body demographic characteristics, on adolescent academic achievement 13 – 16 . Emerging evidence suggests that some of these characteristics may also be associated with mental health and wellbeing outcomes. A recent cross-sectional investigation of school-related factors and student mental health observed that students attending schools in urban areas had greater psychopathology than schools in more rural locations 11 . This study also found that having a higher percentage of students eligible for free school meals (a proxy for socioeconomic disadvantage) was associated with poorer student mental health. Structural factors of schools may matter as well, as there is evidence to suggest that being enrolled in a single gender school, relative to a coeducational school 17 , a private school, relative to a public school 18 are associated with better student mental health in cross-sectional studies. Other characteristics related to the composition of the student body may be relevant, particularly in the context of students from marginalized groups. For example, higher racial/ethnic peer density (i.e. a higher proportion of a particular racial or ethnic group) is associated with better student mental health 10 . While these studies point to a potential influence of school-level factors on student mental health, it is important to note that the literature is currently dominated by cross-sectional findings. More comprehensive assessments looking at multiple domains of school-level factors longitudinally would be valuable to provide insight into which of these aspects of the school context may be most impactful to students’ mental health and wellbeing, and whether these factors are associated with mental health over time. Perceptions of both staff and students’ experiences of school connectedness, culture, and climate are among the most robust predictors of student mental health and have been investigated both cross-sectionally and longitudinally. Notably, while school climate, connectedness, and culture are highly interconnected constructs, they are often conflated within the literature 19 . Importantly, they represent distinct aspects of how staff and students view the school community. School culture refers to the prevailing psychological attitudes or beliefs of a school community 20 , while school climate refers to how those prevailing beliefs or attitudes influence the interpersonal dynamics within a school community 21 . School connectedness, on the other hand, measures how strongly students feel connected with other members of the school community 22 . These constructs are robustly associated with the mental health of both students and staff within a school community cross-sectionally with school climate and connectedness also demonstrating longitudinal associations 11 , 12 , 19 , 20 , 22 – 28 . While the literature assessing how these varied aspects of the school context influence student mental health continues to grow, there is limited research assessing school-, staff-, and student-level factors comprehensively within the same sample, and even less assessing the impact of these factors over time. Longitudinal examinations which include both school-level factors alongside staff- and student-rated experiences from within the same schools would provide much-needed insight into which of these factors are most impactful on student mental health and wellbeing. However, to date only one study has taken this approach 20 . This representative study of N = 8376 UK adolescents examined school-, staff-, and student-level predictors using a previously developed theoretical model 11 to examine factors grouped by locational/structural school factors, characteristics of the school community, and operational features of the school on student mental health. This study found that although certain school-level structural and operational factors were associated with student mental health cross-sectionally, only teacher- and student-rated perspectives of school climate were associated with lower risk of depression and lower social-emotional difficulties over time. Notably, this study did not include assessment of school culture or connectedness within the school. Further comprehensive longitudinal research, ideally in other national school-based samples, is necessary to provide insight into the impact of these school-, staff-, and student-level factors on student mental health over time, which could inform targeted interventions and support policy initiatives to improve student mental health within schools. To address this need, the current study used data from the Future Proofing Study, a large national longitudinal study of adolescent mental health, to assess whether school-, staff-, and student-level factors were associated with student psychological distress and wellbeing both cross-sectionally and two years later. In line with other previous research using a theoretic framework to guide their comprehensive approach to this question 11 , 20 , this study drew on Ecological Systems theory 29 to assess factors by different levels of proximity to the student; grouping factors at the school-level (regional characteristics, school administrative characteristics, student body characteristics), staff-level (school culture and promotion of wellbeing) and student-level factors (school climate and connectedness). Our first aim was to identify school-, staff-, and student-level factors associated with student psychological distress and wellbeing cross-sectionally among Year 8 students. Our second aim was to assess whether any of these factors predicted student psychological distress and wellbeing two years later, when students were in Year 10. Due to the limited literature and varied methodology in this field, we took an exploratory approach to all analyses and did not have directional hypotheses. Methods Participants and Procedure The current study used data collected as part of the Future Proofing Study, a school-based longitudinal cohort of adolescent mental health in Australia. The Future Proofing Study included an embedded cluster randomized controlled trial (cRCT) assessing the efficacy of a digital intervention in preventing adolescent depression 30 . Results from the cRCT showed a null effect. For the current study, a sub cohort of 35 schools (from the total school N = 134) in the intervention arm comprised the sample. This subsample was chosen for the current study because school staff members (teachers, wellbeing officers, school psychologists, and deputy principals) from these 35 schools participated in a process evaluation of the broader cRCT 31 , allowing examination of school, staff, and student factors comprehensively within this subsample. Ethical approval was provided by the University of New South Wales Human Research Ethics Committee (HC180836/iRECS4468), the State Education Research Applications Process for the NSW Department of Education (SERAP2019201), and relevant Catholic Schools Dioceses across Australia. The sampling, recruitment, and data collection procedures of the broader Future Proofing Study 32 and the process evaluation of the cRCT 33 have previously been published. Prior to student data collection, informed consent was obtained from both the student and their parent/caregiver. Student data in the current study are drawn from the baseline (Year 8, ages 13–14) and 24-month follow up (Year 10, ages 15–16) assessment points. Teachers and staff who participated in the process evaluation first went through an informed consent process and completed online surveys at baseline only. Baseline data was collected between the years of 2020–2021, and for student-level outcomes, the 24-month follow up data was collected between the years of 2022–2023. Measures School Measures Regionality . The regionality of the school was assessed through the Accessibility and Remoteness Index of Australia (ARIA+; Australian Institute of Health and Welfare, 2004) which categorized the schools as “major cities”, “inner regional”, “outer regional”, “remote”, and “very remote” in line with the Ministerial Council on Education, Employment, Training, and Youth Affairs Remoteness Classification 2001. This data was collected by the Australian Curriculum, Assessment and Reporting Authority (ACARA) and retrieved via the MySchool® website 34 . As our sample was comprised of schools categorized as “major cities”, “inner regional”, and “outer regional”, the regionality variable was then dichotomized as either metropolitan (major cities) or regional (inner regional, outer regional). School-level socioeconomic advantage . School-level socioeconomic advantage was measured by the Index of Community Socio-educational Advantage (ICSEA) which uses student family background data to create an index value reflective of educational level socioeconomic advantage 35 . Scores have a median of 1000 and a standard deviation of 100, with higher scores reflective of higher school-level socioeconomic advantage. The 2020 and 2021 ICSEA values for participating schools were collected from the MySchool® website 34 . ICSEA values used in analyses were reflective of the year that data collection took place at that the school. School sector . Data categorizing participating schools as a “government school” (i.e. a public school) and a “non-government school” (i.e. a private, religious, or independent school) was collected from the MySchool® website 34 . A dummy code was created to represent this categorical variable such that a value of “0” indicated that the school was a government school, and a value of “1” indicated that the school was a non-government school. School gender . Data categorizing participating schools as a co-educational school, a boys only school, or a girls only school was collected from the MySchool® website 34 . These categories were then dichotomized, and a dummy variable was created such that a value of “0” indicated that the school was a co-educational school, and a value of “1” indicated that the school was a single gender school. Gross income per student . Financial data reporting the gross income per student (a cumulative sum of income from the Australian Government, state and territory government, school fees, charges, parent contributions, and other private sources) for each participating school for the years 2020 and 2021 were collected from the MySchool® website 34 . Values used in analyses were reflective of the year that data collection took place at that the school. Student/teacher ratio . Data reporting the number of teaching staff employed by the school as well as the total student enrolments for the school in the years 2020 and 2021 were collected from the MySchool® website 34 . Student-to-teacher ratio values for 2020 and 2021 were then created by dividing the student enrolments by the number of employed teaching staff. Values used in analyses were reflective of the year that baseline data collection occurred at the school. Percentage of culturally and linguistically diverse (CALD) and Indigenous students. Data reporting the percentage of full-time equivalent student enrolments that identified as Indigenous and CALD for each school was collected from the MySchool® website for the years 2020 and 2021 34 . For both variables, values used in the analyses were reflective of the year in which the baseline data was collected at the school. School attendance rate . Rates of student attendance at each participating school for the year 2021 was collected from the MySchool® website 34 . As 2020 data was not made publicly available due to inconsistencies in school response and reporting during the COVID-19 pandemic, 2021 data was used in all analyses. Staff-Rated Measures School promotion of wellbeing . In order to assess staff-rated perspectives on the degree to which their schools’ promoted wellbeing initiatives, the teacher/staff sample completed the Survey of School Promotion of Emotional and Social Health (SSPESH), a 14-item scale assessing to what degree a school has instituted policies and practices for the promotion of mental health and wellbeing 36 . Teachers and staff were asked to respond how well established a particular practice is (e.g. “Our school has a clear referral pathway with local mental health services and supports families to access these services”) at their institution on a scale from 0 (“not yet in place”) to 3 (“completely in place”). Higher scores on the SSPESH are reflective of more advanced promotion of mental health and wellbeing at their school. As between 1–4 teachers or staff completed this measure at each school, a mean score was created from respondents to represent each individual school’s staff-rated promotion of wellbeing. Internal consistency for the SSPESH was found to be good (α = .87). School culture . To assess teacher/staff rated school culture, a 9-item questionnaire assessing culture within a healthcare setting was adapted for use within a school setting 37 . Respondents were asked to rate the general culture of the school on a 5-point scale ranging from 1 (“strongly agree”) to 5 (“strongly disagree”). Item scores were then reverse coded and summed to create a total score where higher scores were indicative of higher levels of school culture. Internal consistency for this measure was found to be good (α = .88). Student Measures Demographics . Students reported their date of birth, gender identity (male/female/gender diverse), Aboriginal and/or Torres Strait Islander identity (yes or no), language spoken at home (English or a language other than English), and residential postcode. Mental health history . To obtain students’ mental health history, at baseline, they were asked “Have you ever been diagnosed by a professional (e.g. a doctor or psychologist) with any of the following mental health problems? Pick all that apply”, and presented with the following choices: major depression, social anxiety disorder or social phobia, generalized anxiety disorder, obsessive compulsive disorder, panic disorder, separation anxiety disorder, alcohol use disorder, substance use disorder, attention deficit hyperactivity disorder (ADD or ADHD), posttraumatic stress disorder, or schizophrenia/psychosis. In this study, we created a dichotomous variable such that any student who indicated a previous diagnosis of any of these disorders was coded as “1”, with all others coded as “0”. Student home area-level socioeconomic advantage . Participants’ home area-level socioeconomic advantage was assessed using the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD) 38 . This index uses census-level data to create a composite index of relative socioeconomic advantage and disadvantage. Participant residential postcodes were used to identify their IRSAD score at the SA4 level, reported in deciles (range 1–10) with higher numbers reflective of higher home area-level socioeconomic advantage. Student-rated school connectedness . Students’ levels of school connectedness were assessed using the Organisation for Economic Co-operation and Development (OECD) Programme for International Student Assessment 39 . Six items from this scale were administered with participants being asked to endorse how strongly they agreed with a particular item (e.g., “I make friends easily at school”) on a scale from 1 (“strongly disagree”) to 4 (“strongly agree”). Negatively worded item scores were reverse coded, and scores were then summed to create a total score. Scores on this measure ranged from 6 to 24, with higher scores indicating greater levels of school connectedness. This measure was found to have good internal consistency among participants (α = .87). Student-rated school climate . Student ratings of school climate was assessed using a 7- item measure created for a large school-based study assessing predictors of school bullying 40 ; this measure has shown to have good internal validity in an adolescent sample. The measure asks participants to rate their agreement with statements related to school climate (e.g. “We can talk to teachers about problems”) on scale from 0 (“never”) to 2 (“always”). Scores were summed to create a total score where high scores indicated higher levels of school climate. Internal consistency for the 7-item measure was found to be good (α = .85). Student psychological distress . Student levels of psychological distress were assessed using the 5-item Distress Questionnaire-5 (Batterham et al., 2016). Participants were asked to rate the frequency with which they had certain experiences (e.g., “My worries overwhelmed me.”) on a Likert scale ranging from 1 (“never”) to 5 (“always”). Higher total scores indicated higher levels of psychological distress. Internal consistency was found to be good at both baseline (α = .88) and 24-month assessments (α = .89). Student mental wellbeing . Student wellbeing was measured using the Short Warwick-Edinburgh Mental Well-Being Scale 41 , a 7-item measure asking participants to rate how often a particular statement (e.g. “I’ve been feeling optimistic about the future”) was true for them on a scale from 1 (“none of the time”) to 5 (“all of the time”). Scores ranged from 7–35 such that higher scores were reflective of higher levels of wellbeing. Raw scores were then transformed to metric scores using pre-existing guidelines 42 . Internal consistency was found to be good at both baseline (α = .88) and 24-month follow up (α = .91). Statistical Analysis All analyses were conducted using R version 4.4.3, Trophy Case 43 . In line with previous research 11 , 20 , predictors of interest were grouped into separate models based on regional characteristics (student home area-level socioeconomic advantage, a metropolitan vs. regional school location), school administrative characteristics (government vs. non-government school, co-educational vs. single gender school, gross income per student, student/teacher ratio, and school-level socioeconomic advantage), student body characteristics (percentage of CALD students, percentage of Indigenous students, attendance rate), staff ratings of school culture and promotion of wellbeing, and student ratings of school connectedness and climate. All continuous predictors were grand mean centered to aid in interpretability of results. To determine the best approach to account for school-level clustering in our data, a series of null random intercept models were run for each of the four outcome variables (psychological distress at baseline and 24-months, wellbeing at baseline and 24-months). Intraclass correlations showed the percentage of variance due to school-level clustering to be low, ranging from 0.020–0.047. Given this low level of clustering, cross-sectional and longitudinal associations between school-, staff-, and student-level factors were assessed using ordinary least squares fixed effects modelling approach with cluster robust standard errors to account for clustering at the school level. Separate models were run for each category of school-, teacher-, and student-level factors on wellbeing and psychological distress. Given the well documented impact of gender and mental health diagnosis history on wellbeing and psychological distress 44 – 46 , we then reran all models adjusting for these two factors. Longitudinal models included baseline levels of the outcome (wellbeing or psychological distress) as a fixed effect in each model in addition to covariates. To adjust for multiple comparisons, Benjamini-Hochberg adjustments were calculated using the “ltm” package in R. Results Participant Characteristics A total of N = 1548 students were included in the current analytic sample; a subsample of schools from the process evaluation which included 24% of the overall Future Proofing Study cohort. Their demographic characteristics are reported in Table 1 . Demographic characteristics of the subsample did not differ from the broader baseline cohort (Werner-Seidler et al., 2022). At baseline, all adolescents were enrolled in Year 8 ( M age =13.9). A total of N = 1040 students (67% of baseline sample) completed the 24-month follow up survey and were included in the longitudinal analyses. Table 1 Sample characteristics. Age at baseline, mean (SD) 13.9 (0.5) Gender, n (%) Male 693 (44.8%) Female 766 (51.8) Other identities 51 (3.4%) Language spoken most at home, n (%) English 1428 (92.3%) Others 119 (7.7%) Aboriginal and/or Torres Strait Islander identity, n (%) Not Aboriginal and/or Torres Strait Islander 1420 (91.7%) Aboriginal and/or Torres Strait Islander 89 (5.7%) Prefer not to answer 39 (2.5%) Socioeconomic background (IRSAD decile), n (%) Below 50th percentile 532 (34.3%) Above 50th percentile 1016 (65.6%) Geographic location, n (%) Metropolitan area 1031 (66.6%) Regional area 517 (33.4%) School Sector, n (%) Government school 1186 (76.6%) Non-government school 362 (23.4%) School Gender, n (%) Coeducational 1289 (83.3%) Boys’ Only and Girls’ Only 259 (16.7%) Additionally, a total of N = 55 teachers and school staff ( M age =39.47, SD = 11.24) completed measures relating to the culture and promotion of wellbeing at their school (outlined in detail below). This sample was mostly female ( n = 43, 78.2%) with the remainder identifying as male ( n = 12, 21.8%). Participants were employed as a guidance/wellbeing officer or school psychologist ( n = 29, 53.7%), a secondary school teacher or year advisor ( n = 21, 38.9%) or a principal or deputy principal ( n = 4, 7.4%) and had been employed in their schools for an average of 6.68 years. Of the 35 schools in the subsample, n = 18 were located in a metropolitan area, n = 29 were government (public) schools, and n = 30 were coeducational schools. A total of n = 20 schools scored above the median on the ICSEA measure of school-level advantage. Full descriptive characteristics of the schools are reported in Supplementary Table 1. Attrition Analysis and Assessment of Missingness Attrition analysis was conducted using binary logistic regression with cluster robust standard errors assessing primary predictors, baseline outcomes, and covariates/demographics as potential predictors of 24-month follow up completion. Results from attrition analyses showed having a previous history of mental health diagnosis, lower baseline school climate, and lower baseline wellbeing were associated with being less likely to complete the 24-month follow up assessment. Full results of these analyses are reported in Supplementary Table 2. Potential bias due to previous history of mental health diagnosis and lower baseline wellbeing is partially mitigated by their inclusion as covariates in longitudinal models. Notably, the odds ratios for both baseline school climate and wellbeing were quite low (< 1.10), indicating a negligible risk of biasing models. Missing data on variables not attributable to attrition was found to be very low at both baseline (< 2.4%) and 24-month follow up (< 2.9%). Given this low level of missingness, listwise deletion was used in both baseline and longitudinal models. As such, the N s of baseline and longitudinal models vary due to this small degree of missingness. Main Analyses The results of all cross-sectional models can be found in Table 2 . Among location/regional characteristics, models adjusting for covariates (gender identity and history of mental health diagnosis) showed that higher levels of student home area-level socioeconomic advantage were significantly associated with higher wellbeing at baseline (unstandardized B = 0.20, p = .021). In the models assessing student ratings of school climate and connectedness, higher school connectedness was associated with higher wellbeing (unstandardized B = 0.60, p < .001) and lower psychological distress (unstandardized B =-0.55, p < .001) after adjusting for covariates. Similarly, higher student-rated school climate was significantly associated with higher wellbeing (unstandardized B = 0.33, p < .001) and lower psychological distress (unstandardized B =-0.19, p < .001) adjusting for covariates. No variables in the models assessing student body characteristics or teacher ratings of school culture or promotion of wellbeing were associated with baseline levels of student wellbeing or psychological distress. Table 2 Results from baseline wellbeing and distress models. Predictor Distress Wellbeing Distress (Covariates) Wellbeing (Covariates) B 95% CI p B 95% CI p B 95% CI p B 95% CI p Location Characteristics IRSAD (Decile) -0.11 -0.29, 0.08 .944 0.21 0.08, 0.35 .021 -0.08 -0.20, 0.05 .614 0.20 0.08, 0.33 .018 Metro vs. Rural Location 0.07 -1.16, 1.30 .614 0.41 -0.44, 1.28 .588 0.12 -0.71, 0.94 .927 0.38 -0.30, 1.06 .371 School Administrative Characteristics Government vs. Private School 0.44 -0.81, 1.68 .815 -0.51 -1.22, 0.19 .369 -0.57 -1.35, 0.22 .473 0.01 -0.58, 0.60 .999 Coed vs. Single Gender School -0.68 -1.87, 0.51 .614 0.98 -0.19, 2.15 .305 -0.89 -1.67, -0.11 .189 1.07 0.26, 1.88 .062 Gross Income Per Student 0.10 -0.09, 0.28 .657 0.06 -0.09, 0.21 .618 0.05 -0.06, 0.159 .801 0.07 -0.03, 0.18 .342 Student/Teacher Ratio 0.13 -0.27, 0.53 .815 -0.00 -0.31, 0.30 .999 -0.05 -0.33, 0.22 .927 0.07 -0.14, 0.27 .607 ICSEA -3.98 -11.75, 3.79 .657 6.49 1.68, 11.29 .050 0.366 -4.65, 5.38 .933 4.61 -0.00, 9.22 .156 Student Body Characteristics CALD Percentage -0.01 -0.02, 0.00 .444 0.00 -0.01, 0.02 .755 0.01 -0.01, 0.02 .614 -0.01 -0.02, 0.01 .607 Indigenous Percentage 0.01 -0.07, 0.09 .927 -0.02 -0.07, 0.03 .643 -0.00 -0.05, 0.05 .992 -0.03 -0.08, 0.03 .999 Attendance Rate -0.06 -0.23, 0.10 .815 0.08 -0.03, 0.19 .369 -0.08 -0.19, 0.02 .445 0.08 -0.01, 0.17 .820 Student Rated School Community School Connectedness -0.71 -0.79, -0.62 <.001 0.63 0.56, 0.69 < .001 -0.55 -0.62, -0.48 < .001 0.60 0.53, 0.68 < .001 School Climate -0.21 -0.30, -0.12 <.001 0.34 0.26, 0.41 < .001 -0.19 -0.27, -0.10 < .001 0.33 0.24, 0.41 < .001 Staff Rated School Community School Promotion of Wellbeing -0.07 -0.15, 0.01 .423 -0.02 -0.09, 0.05 .683 -0.03 -0.09, 0.04 .801 -0.05 -0.11, 0.02 .342 School Culture -0.19 -1.18, 0.80 .927 0.81 0.15, 1.47 .084 -0.51 -1.23, 0.21 .477 0.95 0.13, 1.78 .096 Note : N s vary due to missing data. Models including covariates are adjusted for history of mental health diagnosis and gender. IRSAD = Index of Relative Socioeconomic Advantage and Disadvantage, ICSEA = Index of Community Socio-educational Advantage, CALD = culturally and linguistically diverse. Results of all longitudinal models are reported in Table 3 . Among all predictors, higher levels of student-rated school connectedness were significantly associated with higher levels of wellbeing at 24-month follow up (unstandardized B = 0.17, p = .035). No other significant relationships were detected. Table 3 Results from models predicting psychological wellbeing and distress at 24-month follow up. Predictor Distress Wellbeing Distress (Covariates) Wellbeing (Covariates) B 95% CI p B 95% CI p B 95% CI p B 95% CI p Location Characteristics IRSAD (Decile) 0.11 -0.02, 0.23 .426 0.04 -0.10, 0.19 .683 0.03 -0.71, 0.35 .815 0.09 -0.04, 0.21 .342 Metro vs. Rural Location 0.08 -0.53, 0.70 .927 0.17 0.31, 0.48 .776 -0.18 -0.05, 0.10 .815 -0.39 -0.37, 1.16 .401 School Administrative Characteristics Government vs. Private School 0.85 -0.33, 2.02 .473 -0.90 -1.93, 0.14 .305 -0.11 -0.92, 0.71 .927 -0.59 -1.51, 0.32 .349 Coed vs. Single Gender School 0.58 -0.53, 1.69 .657 -0.33 -1.40, 0.73 .683 0.21 -0.36, 0.78 .815 -0.24 -1.21, 0.73 .689 Gross Income Per Student 0.01 -0.16, 0.17 .952 0.15 -0.03, 0.32 .305 -0.02 -0.13, 0.10 .927 0.16 0.01, 0.31 .112 Student/Teacher Ratio 0.09 -0.20, 0.37 .822 0.17 -0.16, 0.52 .567 -0.03 -0.21, 0.16 .927 0.21 -0.09, 0.51 .342 ICSEA -0.75 -7.42, 5.92 .927 3.25 -1.50, 8.00 .406 0.39 -4.68, 5.47 .933 3.21 -1.23, 7.64 .342 Student Body Characteristics CALD Percentage -0.02 -0.03, -0.00 .157 0.01 -0.01, 0.03 .999 -0.00 -0.01, 0.01 .815 0.00 -0.01, 0.02 .689 Indigenous Percentage -0.05 -0.12, 0.01 .426 0.03 -0.03, 0.08 .567 -0.06 -0.13, 0.01 .428 -0.03 -0.02, 0.08 .349 Attendance Rate -0.01 -0.11, 0.10 .933 0.04 -0.07, 0.15 .643 -0.08 -0.16, 0.01 .423 0.06 -0.04, 0.44 .349 Student Rated School Community School Connectedness -0.13 -0.24, -0.02 .189 0.20 0.08, 0.31 .009 -0.12 -0.23, -0.02 .189 0.17 0.05, 0.28 .035 School Climate -0.03 -0.16, 0.10 .921 0.06 -0.08, 0.20 .617 -0.05 -0.16, 0.07 .801 0.07 -0.06, 0.21 .371 Staff Rated School Community School Promotion of Wellbeing -0.07 -0.15, 0.01 .423 -0.02 -0.10, 0.07 .999 0.01 -0.05, 0.06 .927 -0.05 -0.12, 0.03 .369 School Culture -0.19 -1.18, 0.80 .927 0.54 -0.37, 1.46 .510 -0.07 -0.74, 0.60 .927 0.75 0.14, 1.36 .084 Note : N s vary due to missing data. Models including covariates are adjusted for history of mental health diagnosis, gender, and baseline levels of the outcome variable (wellbeing or distress). Key: IRSAD = Index of Relative Socioeconomic Advantage and Disadvantage, ICSEA = Index of Community Socio-educational Advantage, CALD = culturally and linguistically diverse. Discussion The purpose of this study was to explore school-, staff-, and student-level factors associated with student psychological distress and mental wellbeing, both cross-sectionally and longitudinally in a national sample of Australian secondary school students. Results showed that higher student home area-level socioeconomic advantage was associated with higher wellbeing, and greater student-rated school climate and school connectedness were associated with both lower psychological distress and higher wellbeing at baseline. Longitudinally, greater student-rated school connectedness was associated with greater student wellbeing two years later, consistent with prior studies 22 , 24 . This suggests that finding ways to augment students’ connectedness throughout high school may positively impact their wellbeing over time. Our finding that higher student home area-level socioeconomic advantage is associated with higher wellbeing cross-sectionally is in line with previous recent research 9 , 11 . As the socioeconomic advantage of the area an adolescent is raised in has the potential to influence so many domains of their life, including safety, access to educational support, and access to both physical and mental health care 9 , 47 , 48 , there are many ways that socioeconomic advantage is likely to be associated with wellbeing. While there has been increasing attention given to the identification of the most salient social determinants of mental health 49 , socioeconomic advantage remains a multifaceted construct requiring more nuanced investigation to determine what aspects of advantage play the largest role in terms of promoting mental wellbeing. Our cross-sectional findings contribute to the growing evidence suggesting a need to determine how best to reduce and mitigate the effects of socioeconomic disadvantage through changes in social and health policy. Notably, no relationships between school-level factors and students’ wellbeing and psychological distress were observed cross-sectionally or longitudinally. This is somewhat surprising, given that the conceptual groupings and factors were drawn from literature showing relevance to overall school efficacy, academic achievement, and student mental health 10 , 11 , 13 – 16 , 18 , 20 . Despite these factors supporting important aspects of school functioning and academic achievement as shown in previous research, school-level characteristics related to the regionality, administration, and student body of the school were not associated with wellbeing or distress in this sample. Our longitudinal findings are in line with the only other study to take a comprehensive approach to exploring the influence of many levels of factors in one sample 20 ; however, further research taking this approach in school-based national samples is needed to replicate these findings both cross-sectionally and over time. Our findings relating to staff- and student- rated perspectives of the school community found that student-rated school climate and student-rated school connectedness were both associated with lower psychological distress and higher wellbeing cross-sectionally. This finding contributes to a growing literature demonstrating that supportive and connected school communities play an important role in supporting the mental health and wellbeing of students. Notably, no significant associations were found between teacher-rated school culture and either student wellbeing or psychological distress. Although previous studies have found relationships between teacher-rated school culture and adolescent mental health both cross-sectionally 11 and longitudinally 20 , concordance has not consistently been observed between teacher and student’s perceptions 50 , 51 . It is possible that our findings may be indicative of a potential disconnect between staff and students’ perceptions of their school community. Further research assessing underlying contributors to concordance and discordance between staff and student ratings of these factors over time would aid researchers to better understand the broader social dynamics of the school community, as well as potentially identify areas to target for those looking to improve school culture in both staff and students. Our findings also identified student-rated school connectedness as being associated with higher levels of wellbeing cross-sectionally and two years later. This finding demonstrates not only how impactful a supportive school community may be on adolescent wellbeing above and beyond other school-level factors but provides important longitudinal evidence that feeling connected to one’s school and peers at school is likely to be key factor in sustaining and improving student wellbeing over time. Improving school connectedness is a rising area of importance to policy makers 52 , 53 , and emerging intervention research provides some evidence that school-based programs designed to improve school connectedness may also be useful in improving student mental health and wellbeing 54 , 55 . Notably, we did not find an association between school connectedness and psychological distress two years later. In evidence-supported psychological theories such as the Dual Continuum Model of Mental Health 56 , distress and wellbeing are posited to be related but distinct psychological dimensions contributing to an individual’s mental health, with distress encompassing a broad range of emotional symptoms, and wellbeing capturing feelings related to life satisfaction and sense of purpose 57 – 59 . Our findings suggest that students’ feelings of connectedness with their school community may promote their mental health through improving their sense of positivity and ability to find meaning even when experiencing periods of emotional difficulty. Our study has several important limitations to consider when interpreting these findings. First, although it can be considered a strength that our student sample is broadly representative of the Australian adolescent population 32 , it was beyond the scope of this study to assess whether these relationships differed among subgroups known to be more vulnerable to psychopathology. Future research should consider whether certain school-level factors may be more important in supporting groups at greater risk. Second, results from our attrition analyses showed that our longitudinal sample significantly differed from our baseline sample on mental health history, baseline school climate, and baseline wellbeing. While these effects were either found to be of negligible size or included as covariates in our longitudinal models, these factors may have influenced our longitudinal findings. Additionally, the sample of teachers and school staff who completed our measures of school culture and promotion of student wellbeing was small ( N = 55) relative to the student sample, and the number of representatives from each of our 35 schools varied between 1–4 members from each school. This may have contributed to the discordance in staff and student assessments of school community characteristics, at least in part. Future research should include larger staff samples to both ensure a more representative measurement of staff-rated school culture as well as enable further examinations of the concordance between staff- and student-level data. Finally, while our study included many school-, staff-, and student-level factors across several theoretical domains, it cannot be said that our list of potential factors was exhaustive of all potential school-related factors that may influence student mental health. Other school characteristics (such as uniform policy, access to green space, class size) found to be associated with student academic outcomes 60 – 62 may be worthy of examination in regard to their associations with student mental health, particularly as student mental health and academic achievement are associated outcomes 63 , 64 . Results from this study highlight that among multiple dimensions of school-related factors, students’ sense of connectedness with their school’s community is the most robust predictor of their wellbeing over time. This has important implications for both policy and future research, as school connectedness is a modifiable factor which emerging evidence shows can be improved through intervention 54 , 55 . Future research should examine the relationship between fluctuations in school connectedness and student mental health with greater nuance, investigating the potential bidirectional influence of these factors on one another, as well as assessments of what aspects of student connectedness are most important to student wellbeing, to further inform targeted interventions. Our findings also demonstrate that difficult to change, systemic factors such as socioeconomic advantage are associated with student mental health, representing an important consideration for social policy. However, targeting modifiable factors such as school connectedness may have the potential to improve student mental health more swiftly, while systemic factors are slower to address. Our findings demonstrate that school connectedness may be a promising candidate for intervention and policy initiatives designed to support student mental health and wellbeing at school. Declarations Acknowledgements We would like to thank the students and school communities who participated in this study. Competing Interests The authors have no competing interests to disclose. Data Availability Data and code from this study are available upon reasonable request to the corresponding author, subject to ethical approval and governance processes. Funding Statement This project was funded by a NHMRC Project Grant awarded to Helen Christensen (GNT1138405), a NHMRC Emerging Leader Fellowship awarded to Aliza Werner‐Seidler (GNT1197074) and Alison L. Calear (GNT1173146), SPRF NHMRC Fellowship to Helen Christensen (GNT 1155614), and a NHMRC Fellowship (GNT1158707) to Philip J. Batterham. The funders had no role in any aspect of the study. Author contributions K.M., A.W-S., and S.K.S. conceived the study. S.K.S. conducted the analyses and wrote the original manuscript draft. P.B. provided statistical oversight. A.W-S, H.C., A.L.C, M.T., B.O.D. and P.B. conceived the trial and were awarded the funding, and J.R.B. supported data collection. All authors reviewed the manuscript. References Kessler, R. C. et al. Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization’s World Mental Health Survey Initiative. World Psychiatry 6 , 168–176 (2007). McGrath, J. J. et al. Age of onset and cumulative risk of mental disorders: a cross-national analysis of population surveys from 29 countries. Lancet Psychiatry 10 , 668–681 (2023). Solmi, M. et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol. Psychiatry 27 , 281–295 (2022). Shorey, S., Ng, E. D. & Wong, C. H. J. 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A Sense of Belonging and Help Seeking: Examining Factors Related to the Mental Health of High School Students with High Autistic Traits without Diagnosis. Child. Basel Switz. 10 , 1927 (2023). Riekie, H., Aldridge, J. M. & Afari, E. The role of the school climate in high school students’ mental health and identity formation: A South Australian study. Br. Educ. Res. J. 43 , 95–123 (2017). Bronfenbrenner, U. & Morris, P. A. The Bioecological Model of Human Development. in Handbook of Child Psychology (John Wiley & Sons, Ltd, 2007). doi:10.1002/9780470147658.chpsy0114. Werner-Seidler, A. et al. Future Proofing Study: a cluster randomised controlled trial evaluating the effectiveness of a universal school-based cognitive–behavioural programme for adolescent depression. BMJ Ment. Health 28 , e301426 (2025). Beames, J. R. et al. Implementing a Digital Depression Prevention Program in Australian Secondary Schools: Cross-Sectional Qualitative Study. JMIR Pediatr. Parent. 6 , e42349 (2023). Werner‐Seidler, A. et al. The Future Proofing Study: Design, methods and baseline characteristics of a prospective cohort study of the mental health of Australian adolescents. Int. J. Methods Psychiatr. Res. 32 , e1954 (2022). Beames, J. R. et al. Protocol for the process evaluation of a complex intervention delivered in schools to prevent adolescent depression: the Future Proofing Study. BMJ Open 11 , e042133 (2021). ACARA. My School provides information that helps parents and the community in understanding the performance of schools over time. My School https://myschoolprodwebpmv3.azurewebsites.net/ (2020). ACARA. Guide to Understanding ICSEA Values. (2020). Dix, K. L. et al. The Survey of School Promotion of Emotional and Social Health (SSPESH): A Brief Measure of the Implementation of Whole-School Mental Health Promotion. School Ment. Health 11 , 294–308 (2019). Fernandez, M. E. et al. Developing measures to assess constructs from the Inner Setting domain of the Consolidated Framework for Implementation Research. Implement. Sci. 13 , 52 (2018). Australian Bureau of Statistics. Socio-Economic Indexes for Areas (SEIFA), Australia, 2021 | Australian Bureau of Statistics. https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/latest-release (2023). OECD. Learning for Tomorrow’s World. Learning for Tomorrow’s World https://www.oecd.org/en/publications/learning-for-tomorrow-s-world_9789264006416-en.html (2004). Fink, E., Patalay, P., Sharpe, H. & Wolpert, M. Child- and school-level predictors of children’s bullying behavior: A multilevel analysis in 648 primary schools. J. Educ. Psychol. 110 , 17–26 (2018). Ng Fat, L., Scholes, S., Boniface, S., Mindell, J. & Stewart-Brown, S. Evaluating and establishing national norms for mental wellbeing using the short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS): findings from the Health Survey for England. Qual. Life Res. Int. J. Qual. Life Asp. Treat. Care Rehabil. 26 , 1129–1144 (2017). Stewart-Brown, S. et al. Internal construct validity of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS): a Rasch analysis using data from the Scottish Health Education Population Survey. Health Qual. Life Outcomes 7 , 15 (2009). R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing (2021). Lam, J. R., Park, H. R. P. & Gatt, J. M. Measuring mental wellbeing in clinical and non-clinical adolescents using the COMPAS-W Wellbeing Scale. Front. Psychiatry 15 , (2024). Marquez, J., Humphrey, N., Black, L., Cutts, M. & Khanna, D. Gender and sexual identity-based inequalities in adolescent wellbeing: findings from the #BeeWell Study. BMC Public Health 23 , 2211 (2023). Yoon, Y., Eisenstadt, M., Lereya, S. T. & Deighton, J. Gender difference in the change of adolescents’ mental health and subjective wellbeing trajectories. Eur. Child Adolesc. Psychiatry 32 , 1569–1578 (2023). Cummings, J. R. Contextual Socioeconomic Status and Mental Health Counseling Use Among U.S. Adolescents with Depression. J. Youth Adolesc. 43 , 1151–1162 (2014). Santiago, C. D. C., Wadsworth, M. E. & Stump, J. Socioeconomic status, neighborhood disadvantage, and poverty-related stress: Prospective effects on psychological syndromes among diverse low-income families. J. Econ. Psychol. 32 , 218–230 (2011). Yang, P., Hernandez, B. S. & Plastino, K. A. Social determinants of mental health and adolescent anxiety and depression: Findings from the 2018 to 2019 National Survey of Children’s Health. Int. J. Soc. Psychiatry 69 , 795–798 (2023). Hirata, I. et al. Multifaceted perception of school climate: association between students’ and teachers’ perceptions and other teacher factors. Front. Educ. 9 , (2024). Molinari, L. & Grazia, V. A multi-informant study of school climate: student, parent, and teacher perceptions. Eur. J. Psychol. Educ. 38 , 1403–1423 (2023). Allen, K.-A. et al. School belonging policy. in 139–146 (2021). doi:10.4324/9781003025955-19. New South Wales Department of Education. 4. What can I do about my students’ sense of belonging? https://education.nsw.gov.au/about-us/education-data-and-research/what-works-best/student-belonging/making-sense-of-belonging/what-can-i-do-about-my-students-sense-of-belonging.html (2024). Bonell, C. et al. Effects of the Learning Together intervention on bullying and aggression in English secondary schools (INCLUSIVE): a cluster randomised controlled trial. Lancet Lond. Engl. 392 , 2452–2464 (2018). Shinde, S. et al. Promoting school climate and health outcomes with the SEHER multi-component secondary school intervention in Bihar, India: a cluster-randomised controlled trial. The Lancet 392 , 2465–2477 (2018). Iasiello, M. & van Agteren, J. Mental health and/or mental illness: A scoping review of the evidence and implications of the dual-continua model of mental health. Evid. Base J. Evid. Rev. Key Policy Areas 1–45 (2020) doi:10.3316/informit.261420605378998. Kraiss, J. T., Kohlhoff, M. & Ten Klooster, P. M. Disentangling between- and within-person associations of psychological distress and mental well-being: An experience sampling study examining the dual continua model of mental health among university students. Curr. Psychol. N. B. NJ 1–12 (2022) doi:10.1007/s12144-022-02942-1. Mason Stephens, J., Iasiello, M., Ali, K., van Agteren, J. & Fassnacht, D. B. The Importance of Measuring Mental Wellbeing in the Context of Psychological Distress: Using a Theoretical Framework to Test the Dual-Continua Model of Mental Health. Behav. Sci. Basel Switz. 13 , 436 (2023). Spence, M. & Karvatsky, Y. Wellbeing: more than being well. Nat. Ment. Health 3 , 159–159 (2025). Ansari, A., Shepard, M. & Gottfried, M. A. School uniforms and student behavior: is there a link? Early Child. Res. Q. 58 , 278–286 (2022). Browning, M. H. E. M. & Rigolon, A. School Green Space and Its Impact on Academic Performance: A Systematic Literature Review. Int. J. Environ. Res. Public. Health 16 , 429 (2019). Shin, I. S. & Chung, J. Y. Class size and student achievement in the United States: A meta-analysis. KEDI J. Educ. Policy 6 , 3–19 (2009). Riglin, L., Frederickson, N., Shelton, K. H. & Rice, F. A longitudinal study of psychological functioning and academic attainment at the transition to secondary school. J. Adolesc. 36 , 507–517 (2013). Wickersham, A. et al. Systematic Review and Meta-analysis: The Association Between Child and Adolescent Depression and Later Educational Attainment. J. Am. Acad. Child Adolesc. Psychiatry 60 , 105–118 (2021). Additional Declarations No competing interests reported. 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Concerningly, the prevalence of adolescent mental health diagnoses is rising globally \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, which has led to increased attention to the role that environmental and community-level factors may play in promoting or mitigating risk for adolescent mental health. For example, an emerging area of interest to both researchers and policy makers is how the school context may influence the mental health of students, a priority that has been highlighted both in a recent United Nations policy review as well as in Australia\u0026rsquo;s National Child Mental Health and Wellbeing Strategy \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Schools provide not only an important educational influence on adolescent development, but provide a setting within which important cognitive, social, and emotional milestones are supported, providing the foundations for adulthood \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAdolescents spend a significant proportion of their time at school, and school experiences are theorized to impact their mental health and wellbeing through multiple pathways \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. A number of studies have identified cross-sectional associations between school region (i.e. whether the school is located in an urban or rural location), administrative (i.e. structural, financial, and staffing information), and cultural factors (i.e. perceptions of the overall culture and connectedness of the school community) with student mental health and wellbeing \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. These findings highlight the need to better understand which aspects of the school context are most important for student mental health, to inform public policies and initiatives that support student mental health and wellbeing.\u003c/p\u003e\u003cp\u003eThere is substantive literature assessing the influence of school-level factors, such as demographic characteristics, aspects of the school administration and structure of the school, and student body demographic characteristics, on adolescent academic achievement \u003csup\u003e\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Emerging evidence suggests that some of these characteristics may also be associated with mental health and wellbeing outcomes. A recent cross-sectional investigation of school-related factors and student mental health observed that students attending schools in urban areas had greater psychopathology than schools in more rural locations \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. This study also found that having a higher percentage of students eligible for free school meals (a proxy for socioeconomic disadvantage) was associated with poorer student mental health.\u003c/p\u003e\u003cp\u003eStructural factors of schools may matter as well, as there is evidence to suggest that being enrolled in a single gender school, relative to a coeducational school \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, a private school, relative to a public school \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e are associated with better student mental health in cross-sectional studies. Other characteristics related to the composition of the student body may be relevant, particularly in the context of students from marginalized groups. For example, higher racial/ethnic peer density (i.e. a higher proportion of a particular racial or ethnic group) is associated with better student mental health \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. While these studies point to a potential influence of school-level factors on student mental health, it is important to note that the literature is currently dominated by cross-sectional findings. More comprehensive assessments looking at multiple domains of school-level factors longitudinally would be valuable to provide insight into which of these aspects of the school context may be most impactful to students\u0026rsquo; mental health and wellbeing, and whether these factors are associated with mental health over time.\u003c/p\u003e\u003cp\u003ePerceptions of both staff and students\u0026rsquo; experiences of school connectedness, culture, and climate are among the most robust predictors of student mental health and have been investigated both cross-sectionally and longitudinally. Notably, while school climate, connectedness, and culture are highly interconnected constructs, they are often conflated within the literature \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Importantly, they represent distinct aspects of how staff and students view the school community. School culture refers to the prevailing psychological attitudes or beliefs of a school community \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, while school climate refers to how those prevailing beliefs or attitudes influence the interpersonal dynamics within a school community \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. School connectedness, on the other hand, measures how strongly students feel connected with other members of the school community \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. These constructs are robustly associated with the mental health of both students and staff within a school community cross-sectionally with school climate and connectedness also demonstrating longitudinal associations \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26 CR27\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile the literature assessing how these varied aspects of the school context influence student mental health continues to grow, there is limited research assessing school-, staff-, and student-level factors comprehensively within the same sample, and even less assessing the impact of these factors over time. Longitudinal examinations which include both school-level factors alongside staff- and student-rated experiences from within the same schools would provide much-needed insight into which of these factors are most impactful on student mental health and wellbeing. However, to date only one study has taken this approach \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This representative study of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8376 UK adolescents examined school-, staff-, and student-level predictors using a previously developed theoretical model \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e to examine factors grouped by locational/structural school factors, characteristics of the school community, and operational features of the school on student mental health. This study found that although certain school-level structural and operational factors were associated with student mental health cross-sectionally, only teacher- and student-rated perspectives of school climate were associated with lower risk of depression and lower social-emotional difficulties over time. Notably, this study did not include assessment of school culture or connectedness within the school. Further comprehensive longitudinal research, ideally in other national school-based samples, is necessary to provide insight into the impact of these school-, staff-, and student-level factors on student mental health over time, which could inform targeted interventions and support policy initiatives to improve student mental health within schools.\u003c/p\u003e\u003cp\u003eTo address this need, the current study used data from the Future Proofing Study, a large national longitudinal study of adolescent mental health, to assess whether school-, staff-, and student-level factors were associated with student psychological distress and wellbeing both cross-sectionally and two years later. In line with other previous research using a theoretic framework to guide their comprehensive approach to this question \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, this study drew on Ecological Systems theory \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e to assess factors by different levels of proximity to the student; grouping factors at the school-level (regional characteristics, school administrative characteristics, student body characteristics), staff-level (school culture and promotion of wellbeing) and student-level factors (school climate and connectedness). Our first aim was to identify school-, staff-, and student-level factors associated with student psychological distress and wellbeing cross-sectionally among Year 8 students. Our second aim was to assess whether any of these factors predicted student psychological distress and wellbeing two years later, when students were in Year 10. Due to the limited literature and varied methodology in this field, we took an exploratory approach to all analyses and did not have directional hypotheses.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants and Procedure\u003c/h2\u003e\u003cp\u003eThe current study used data collected as part of the Future Proofing Study, a school-based longitudinal cohort of adolescent mental health in Australia. The Future Proofing Study included an embedded cluster randomized controlled trial (cRCT) assessing the efficacy of a digital intervention in preventing adolescent depression \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Results from the cRCT showed a null effect. For the current study, a sub cohort of 35 schools (from the total school \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;134) in the intervention arm comprised the sample. This subsample was chosen for the current study because school staff members (teachers, wellbeing officers, school psychologists, and deputy principals) from these 35 schools participated in a process evaluation of the broader cRCT \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, allowing examination of school, staff, and student factors comprehensively within this subsample. Ethical approval was provided by the University of New South Wales Human Research Ethics Committee (HC180836/iRECS4468), the State Education Research Applications Process for the NSW Department of Education (SERAP2019201), and relevant Catholic Schools Dioceses across Australia.\u003c/p\u003e\u003cp\u003eThe sampling, recruitment, and data collection procedures of the broader Future Proofing Study \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and the process evaluation of the cRCT \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e have previously been published. Prior to student data collection, informed consent was obtained from both the student and their parent/caregiver. Student data in the current study are drawn from the baseline (Year 8, ages 13\u0026ndash;14) and 24-month follow up (Year 10, ages 15\u0026ndash;16) assessment points. Teachers and staff who participated in the process evaluation first went through an informed consent process and completed online surveys at baseline only. Baseline data was collected between the years of 2020\u0026ndash;2021, and for student-level outcomes, the 24-month follow up data was collected between the years of 2022\u0026ndash;2023.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eSchool Measures\u003c/h2\u003e\u003cp\u003e\u003cb\u003eRegionality\u003c/b\u003e. The regionality of the school was assessed through the Accessibility and Remoteness Index of Australia (ARIA+; Australian Institute of Health and Welfare, 2004) which categorized the schools as \u0026ldquo;major cities\u0026rdquo;, \u0026ldquo;inner regional\u0026rdquo;, \u0026ldquo;outer regional\u0026rdquo;, \u0026ldquo;remote\u0026rdquo;, and \u0026ldquo;very remote\u0026rdquo; in line with the Ministerial Council on Education, Employment, Training, and Youth Affairs Remoteness Classification 2001. This data was collected by the Australian Curriculum, Assessment and Reporting Authority (ACARA) and retrieved via the MySchool\u0026reg; website \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. As our sample was comprised of schools categorized as \u0026ldquo;major cities\u0026rdquo;, \u0026ldquo;inner regional\u0026rdquo;, and \u0026ldquo;outer regional\u0026rdquo;, the regionality variable was then dichotomized as either metropolitan (major cities) or regional (inner regional, outer regional).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSchool-level socioeconomic advantage\u003c/b\u003e. School-level socioeconomic advantage was measured by the Index of Community Socio-educational Advantage (ICSEA) which uses student family background data to create an index value reflective of educational level socioeconomic advantage \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Scores have a median of 1000 and a standard deviation of 100, with higher scores reflective of higher school-level socioeconomic advantage. The 2020 and 2021 ICSEA values for participating schools were collected from the MySchool\u0026reg; website \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. ICSEA values used in analyses were reflective of the year that data collection took place at that the school.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSchool sector\u003c/b\u003e. Data categorizing participating schools as a \u0026ldquo;government school\u0026rdquo; (i.e. a public school) and a \u0026ldquo;non-government school\u0026rdquo; (i.e. a private, religious, or independent school) was collected from the MySchool\u0026reg; website \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. A dummy code was created to represent this categorical variable such that a value of \u0026ldquo;0\u0026rdquo; indicated that the school was a government school, and a value of \u0026ldquo;1\u0026rdquo; indicated that the school was a non-government school.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSchool gender\u003c/b\u003e. Data categorizing participating schools as a co-educational school, a boys only school, or a girls only school was collected from the MySchool\u0026reg; website \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. These categories were then dichotomized, and a dummy variable was created such that a value of \u0026ldquo;0\u0026rdquo; indicated that the school was a co-educational school, and a value of \u0026ldquo;1\u0026rdquo; indicated that the school was a single gender school.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGross income per student\u003c/b\u003e. Financial data reporting the gross income per student (a cumulative sum of income from the Australian Government, state and territory government, school fees, charges, parent contributions, and other private sources) for each participating school for the years 2020 and 2021 were collected from the MySchool\u0026reg; website \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Values used in analyses were reflective of the year that data collection took place at that the school.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudent/teacher ratio\u003c/b\u003e. Data reporting the number of teaching staff employed by the school as well as the total student enrolments for the school in the years 2020 and 2021 were collected from the MySchool\u0026reg; website \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Student-to-teacher ratio values for 2020 and 2021 were then created by dividing the student enrolments by the number of employed teaching staff. Values used in analyses were reflective of the year that baseline data collection occurred at the school.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePercentage of culturally and linguistically diverse (CALD) and Indigenous students.\u003c/b\u003e Data reporting the percentage of full-time equivalent student enrolments that identified as Indigenous and CALD for each school was collected from the MySchool\u0026reg; website for the years 2020 and 2021 \u003csup\u003e34\u003c/sup\u003e. For both variables, values used in the analyses were reflective of the year in which the baseline data was collected at the school.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSchool attendance rate\u003c/b\u003e. Rates of student attendance at each participating school for the year 2021 was collected from the MySchool\u0026reg; website \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. As 2020 data was not made publicly available due to inconsistencies in school response and reporting during the COVID-19 pandemic, 2021 data was used in all analyses.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStaff-Rated Measures\u003c/h3\u003e\n\u003cp\u003e\u003cb\u003eSchool promotion of wellbeing\u003c/b\u003e. In order to assess staff-rated perspectives on the degree to which their schools\u0026rsquo; promoted wellbeing initiatives, the teacher/staff sample completed the Survey of School Promotion of Emotional and Social Health (SSPESH), a 14-item scale assessing to what degree a school has instituted policies and practices for the promotion of mental health and wellbeing \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Teachers and staff were asked to respond how well established a particular practice is (e.g. \u0026ldquo;Our school has a clear referral pathway with local mental health services and supports families to access these services\u0026rdquo;) at their institution on a scale from 0 (\u0026ldquo;not yet in place\u0026rdquo;) to 3 (\u0026ldquo;completely in place\u0026rdquo;). Higher scores on the SSPESH are reflective of more advanced promotion of mental health and wellbeing at their school. As between 1\u0026ndash;4 teachers or staff completed this measure at each school, a mean score was created from respondents to represent each individual school\u0026rsquo;s staff-rated promotion of wellbeing. Internal consistency for the SSPESH was found to be good (α\u0026thinsp;=\u0026thinsp;.87).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSchool culture\u003c/b\u003e. To assess teacher/staff rated school culture, a 9-item questionnaire assessing culture within a healthcare setting was adapted for use within a school setting \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Respondents were asked to rate the general culture of the school on a 5-point scale ranging from 1 (\u0026ldquo;strongly agree\u0026rdquo;) to 5 (\u0026ldquo;strongly disagree\u0026rdquo;). Item scores were then reverse coded and summed to create a total score where higher scores were indicative of higher levels of school culture. Internal consistency for this measure was found to be good (α\u0026thinsp;=\u0026thinsp;.88).\u003c/p\u003e\n\u003ch3\u003eStudent Measures\u003c/h3\u003e\n\u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e. Students reported their date of birth, gender identity (male/female/gender diverse), Aboriginal and/or Torres Strait Islander identity (yes or no), language spoken at home (English or a language other than English), and residential postcode.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMental health history\u003c/b\u003e. To obtain students\u0026rsquo; mental health history, at baseline, they were asked \u0026ldquo;Have you ever been diagnosed by a professional (e.g. a doctor or psychologist) with any of the following mental health problems? Pick all that apply\u0026rdquo;, and presented with the following choices: major depression, social anxiety disorder or social phobia, generalized anxiety disorder, obsessive compulsive disorder, panic disorder, separation anxiety disorder, alcohol use disorder, substance use disorder, attention deficit hyperactivity disorder (ADD or ADHD), posttraumatic stress disorder, or schizophrenia/psychosis. In this study, we created a dichotomous variable such that any student who indicated a previous diagnosis of any of these disorders was coded as \u0026ldquo;1\u0026rdquo;, with all others coded as \u0026ldquo;0\u0026rdquo;.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudent home area-level socioeconomic advantage\u003c/b\u003e. Participants\u0026rsquo; home area-level socioeconomic advantage was assessed using the Index of Relative Socio-economic Advantage and Disadvantage (IRSAD) \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. This index uses census-level data to create a composite index of relative socioeconomic advantage and disadvantage. Participant residential postcodes were used to identify their IRSAD score at the SA4 level, reported in deciles (range 1\u0026ndash;10) with higher numbers reflective of higher home area-level socioeconomic advantage.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudent-rated school connectedness\u003c/b\u003e. Students\u0026rsquo; levels of school connectedness were assessed using the Organisation for Economic Co-operation and Development (OECD) Programme for International Student Assessment \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Six items from this scale were administered with participants being asked to endorse how strongly they agreed with a particular item (e.g., \u0026ldquo;I make friends easily at school\u0026rdquo;) on a scale from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 4 (\u0026ldquo;strongly agree\u0026rdquo;). Negatively worded item scores were reverse coded, and scores were then summed to create a total score. Scores on this measure ranged from 6 to 24, with higher scores indicating greater levels of school connectedness. This measure was found to have good internal consistency among participants (α\u0026thinsp;=\u0026thinsp;.87).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudent-rated school climate\u003c/b\u003e. Student ratings of school climate was assessed using a 7- item measure created for a large school-based study assessing predictors of school bullying \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e; this measure has shown to have good internal validity in an adolescent sample. The measure asks participants to rate their agreement with statements related to school climate (e.g. \u0026ldquo;We can talk to teachers about problems\u0026rdquo;) on scale from 0 (\u0026ldquo;never\u0026rdquo;) to 2 (\u0026ldquo;always\u0026rdquo;). Scores were summed to create a total score where high scores indicated higher levels of school climate. Internal consistency for the 7-item measure was found to be good (α\u0026thinsp;=\u0026thinsp;.85).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudent psychological distress\u003c/b\u003e. Student levels of psychological distress were assessed using the 5-item Distress Questionnaire-5 (Batterham et al., 2016). Participants were asked to rate the frequency with which they had certain experiences (e.g., \u0026ldquo;My worries overwhelmed me.\u0026rdquo;) on a Likert scale ranging from 1 (\u0026ldquo;never\u0026rdquo;) to 5 (\u0026ldquo;always\u0026rdquo;). Higher total scores indicated higher levels of psychological distress. Internal consistency was found to be good at both baseline (α\u0026thinsp;=\u0026thinsp;.88) and 24-month assessments (α\u0026thinsp;=\u0026thinsp;.89).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudent mental wellbeing\u003c/b\u003e. Student wellbeing was measured using the Short Warwick-Edinburgh Mental Well-Being Scale \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, a 7-item measure asking participants to rate how often a particular statement (e.g. \u0026ldquo;I\u0026rsquo;ve been feeling optimistic about the future\u0026rdquo;) was true for them on a scale from 1 (\u0026ldquo;none of the time\u0026rdquo;) to 5 (\u0026ldquo;all of the time\u0026rdquo;). Scores ranged from 7\u0026ndash;35 such that higher scores were reflective of higher levels of wellbeing. Raw scores were then transformed to metric scores using pre-existing guidelines \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Internal consistency was found to be good at both baseline (α\u0026thinsp;=\u0026thinsp;.88) and 24-month follow up (α\u0026thinsp;=\u0026thinsp;.91).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll analyses were conducted using R version 4.4.3, Trophy Case \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. In line with previous research \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, predictors of interest were grouped into separate models based on regional characteristics (student home area-level socioeconomic advantage, a metropolitan vs. regional school location), school administrative characteristics (government vs. non-government school, co-educational vs. single gender school, gross income per student, student/teacher ratio, and school-level socioeconomic advantage), student body characteristics (percentage of CALD students, percentage of Indigenous students, attendance rate), staff ratings of school culture and promotion of wellbeing, and student ratings of school connectedness and climate. All continuous predictors were grand mean centered to aid in interpretability of results. To determine the best approach to account for school-level clustering in our data, a series of null random intercept models were run for each of the four outcome variables (psychological distress at baseline and 24-months, wellbeing at baseline and 24-months). Intraclass correlations showed the percentage of variance due to school-level clustering to be low, ranging from 0.020\u0026ndash;0.047. Given this low level of clustering, cross-sectional and longitudinal associations between school-, staff-, and student-level factors were assessed using ordinary least squares fixed effects modelling approach with cluster robust standard errors to account for clustering at the school level. Separate models were run for each category of school-, teacher-, and student-level factors on wellbeing and psychological distress. Given the well documented impact of gender and mental health diagnosis history on wellbeing and psychological distress \u003csup\u003e\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, we then reran all models adjusting for these two factors. Longitudinal models included baseline levels of the outcome (wellbeing or psychological distress) as a fixed effect in each model in addition to covariates. To adjust for multiple comparisons, Benjamini-Hochberg adjustments were calculated using the \u0026ldquo;ltm\u0026rdquo; package in R.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eParticipant Characteristics\u003c/h2\u003e\u003cp\u003eA total of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1548 students were included in the current analytic sample; a subsample of schools from the process evaluation which included 24% of the overall Future Proofing Study cohort. Their demographic characteristics are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Demographic characteristics of the subsample did not differ from the broader baseline cohort (Werner-Seidler et al., 2022). At baseline, all adolescents were enrolled in Year 8 (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e=13.9). A total of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1040 students (67% of baseline sample) completed the 24-month follow up survey and were included in the longitudinal analyses.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSample characteristics.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge at baseline, mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.9 (0.5)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e693 (44.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e766 (51.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther identities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51 (3.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLanguage spoken most at home, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnglish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1428 (92.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e119 (7.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAboriginal and/or Torres Strait Islander identity, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot Aboriginal and/or Torres Strait Islander\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1420 (91.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAboriginal and/or Torres Strait Islander\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e89 (5.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrefer not to answer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e39 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocioeconomic background (IRSAD decile), n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBelow 50th percentile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e532 (34.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbove 50th percentile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1016 (65.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGeographic location, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetropolitan area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1031 (66.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegional area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e517 (33.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSchool Sector, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGovernment school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1186 (76.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-government school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e362 (23.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSchool Gender, n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoeducational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1289 (83.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBoys\u0026rsquo; Only and Girls\u0026rsquo; Only\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e259 (16.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAdditionally, a total of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;55 teachers and school staff (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e=39.47, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;11.24) completed measures relating to the culture and promotion of wellbeing at their school (outlined in detail below). This sample was mostly female (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;43, 78.2%) with the remainder identifying as male (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12, 21.8%). Participants were employed as a guidance/wellbeing officer or school psychologist (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;29, 53.7%), a secondary school teacher or year advisor (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;21, 38.9%) or a principal or deputy principal (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4, 7.4%) and had been employed in their schools for an average of 6.68 years.\u003c/p\u003e\u003cp\u003eOf the 35 schools in the subsample, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18 were located in a metropolitan area, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;29 were government (public) schools, and \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;30 were coeducational schools. A total of \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20 schools scored above the median on the ICSEA measure of school-level advantage. Full descriptive characteristics of the schools are reported in Supplementary Table\u0026nbsp;1.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAttrition Analysis and Assessment of Missingness\u003c/h2\u003e\u003cp\u003eAttrition analysis was conducted using binary logistic regression with cluster robust standard errors assessing primary predictors, baseline outcomes, and covariates/demographics as potential predictors of 24-month follow up completion. Results from attrition analyses showed having a previous history of mental health diagnosis, lower baseline school climate, and lower baseline wellbeing were associated with being less likely to complete the 24-month follow up assessment. Full results of these analyses are reported in Supplementary Table\u0026nbsp;2. Potential bias due to previous history of mental health diagnosis and lower baseline wellbeing is partially mitigated by their inclusion as covariates in longitudinal models. Notably, the odds ratios for both baseline school climate and wellbeing were quite low (\u0026lt;\u0026thinsp;1.10), indicating a negligible risk of biasing models. Missing data on variables not attributable to attrition was found to be very low at both baseline (\u0026lt;\u0026thinsp;2.4%) and 24-month follow up (\u0026lt;\u0026thinsp;2.9%). Given this low level of missingness, listwise deletion was used in both baseline and longitudinal models. As such, the \u003cem\u003eN\u003c/em\u003es of baseline and longitudinal models vary due to this small degree of missingness.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eMain Analyses\u003c/h2\u003e\u003cp\u003eThe results of all cross-sectional models can be found in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among location/regional characteristics, models adjusting for covariates (gender identity and history of mental health diagnosis) showed that higher levels of student home area-level socioeconomic advantage were significantly associated with higher wellbeing at baseline (unstandardized \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.20, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.021). In the models assessing student ratings of school climate and connectedness, higher school connectedness was associated with higher wellbeing (unstandardized \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.60, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and lower psychological distress (unstandardized \u003cem\u003eB\u003c/em\u003e=-0.55, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) after adjusting for covariates. Similarly, higher student-rated school climate was significantly associated with higher wellbeing (unstandardized \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.33, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and lower psychological distress (unstandardized \u003cem\u003eB\u003c/em\u003e=-0.19, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) adjusting for covariates. No variables in the models assessing student body characteristics or teacher ratings of school culture or promotion of wellbeing were associated with baseline levels of student wellbeing or psychological distress.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults from baseline wellbeing and distress models.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"15\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDistress\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e\u003cem\u003eWellbeing\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u003cp\u003e\u003cem\u003eDistress (Covariates)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u003cp\u003e\u003cem\u003eWellbeing (Covariates)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLocation Characteristics\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIRSAD (Decile)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.29, 0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.21\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.08, 0.35\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.021\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e-0.20, 0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.20\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.08, 0.33\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u003cb\u003e.018\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetro vs. Rural Location\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.16, 1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.44, 1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.588\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e-0.71, 0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.30, 1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.371\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSchool Administrative Characteristics\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGovernment vs. Private School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.81, 1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.22, 0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-1.35, 0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.58, 0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoed vs. Single Gender School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.87, 0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.19, 2.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-1.67, -0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e0.26, 1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.062\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGross Income Per Student\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.09, 0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.09, 0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.06, 0.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.03, 0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudent/Teacher Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.27, 0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.31, 0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.33, 0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.14, 0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.607\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICSEA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-3.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-11.75, 3.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.68, 11.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-4.65, 5.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e4.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.00, 9.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.156\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStudent Body Characteristics\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCALD Percentage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.02, 0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.01, 0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.755\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.01, 0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.02, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.607\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndigenous Percentage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.07, 0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.07, 0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.05, 0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.08, 0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAttendance Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.23, 0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.03, 0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.19, 0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.01, 0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.820\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStudent Rated School Community\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Connectedness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.71\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e-0.79, -0.62\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.63\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.56, 0.69\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e-0.55\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e-0.62, -0.48\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.60\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.53, 0.68\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Climate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e-0.21\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e-0.30, -0.12\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.34\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.26, 0.41\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e-0.19\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cb\u003e-0.27, -0.10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.33\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.24, 0.41\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaff Rated School Community\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Promotion of Wellbeing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.15, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.09, 0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.683\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.09, 0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.11, 0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Culture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.18, 0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.15, 1.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-1.23, 0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.477\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.13, 1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.096\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"15\"\u003e\u003cem\u003eNote\u003c/em\u003e: \u003cem\u003eN\u003c/em\u003es vary due to missing data. Models including covariates are adjusted for history of mental health diagnosis and gender. IRSAD\u0026thinsp;=\u0026thinsp;Index of Relative Socioeconomic Advantage and Disadvantage, ICSEA\u0026thinsp;=\u0026thinsp;Index of Community Socio-educational Advantage, CALD\u0026thinsp;=\u0026thinsp;culturally and linguistically diverse.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eResults of all longitudinal models are reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Among all predictors, higher levels of student-rated school connectedness were significantly associated with higher levels of wellbeing at 24-month follow up (unstandardized \u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.17, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.035). No other significant relationships were detected.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults from models predicting psychological wellbeing and distress at 24-month follow up.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"15\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u003cem\u003eDistress\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003e\u003cem\u003eWellbeing\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u003cp\u003e\u003cem\u003eDistress (Covariates)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u003cp\u003e\u003cem\u003eWellbeing (Covariates)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLocation Characteristics\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIRSAD (Decile)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.02, 0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.426\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.10, 0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.683\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e-0.71, 0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.04, 0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetro vs. Rural Location\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.53, 0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.31, 0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.776\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e-0.05, 0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.37, 1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.401\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSchool Administrative Characteristics\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGovernment vs. Private School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.33, 2.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.93, 0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.92, 0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-1.51, 0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.349\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoed vs. Single Gender School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.53, 1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.40, 0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.683\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.36, 0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-1.21, 0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.689\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGross Income Per Student\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.16, 0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.952\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.03, 0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.13, 0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e0.01, 0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.112\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudent/Teacher Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.20, 0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.16, 0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.567\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.21, 0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-0.09, 0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICSEA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-7.42, 5.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.50, 8.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-4.68, 5.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e3.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e\u003cp\u003e-1.23, 7.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.342\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStudent Body Characteristics\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCALD Percentage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.03, -0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.01, 0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.01, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.01, 0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.689\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndigenous Percentage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.12, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.426\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.03, 0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.567\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.13, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.02, 0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.349\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAttendance Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.11, 0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.07, 0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.643\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.16, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.04, 0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.349\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStudent Rated School Community\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Connectedness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.24, -0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.20\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.08, 0.31\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.23, -0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u003cb\u003e0.17\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cb\u003e0.05, 0.28\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e\u003cb\u003e.035\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Climate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.16, 0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.08, 0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.617\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.16, 0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.06, 0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.371\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaff Rated School Community\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Promotion of Wellbeing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.15, 0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.10, 0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.05, 0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-0.12, 0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.369\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSchool Culture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.18, 0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.37, 1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.510\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-0.74, 0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.14, 1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003e.084\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"15\"\u003e\u003cem\u003eNote\u003c/em\u003e: \u003cem\u003eN\u003c/em\u003es vary due to missing data. Models including covariates are adjusted for history of mental health diagnosis, gender, and baseline levels of the outcome variable (wellbeing or distress). Key: IRSAD\u0026thinsp;=\u0026thinsp;Index of Relative Socioeconomic Advantage and Disadvantage, ICSEA\u0026thinsp;=\u0026thinsp;Index of Community Socio-educational Advantage, CALD\u0026thinsp;=\u0026thinsp;culturally and linguistically diverse.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe purpose of this study was to explore school-, staff-, and student-level factors associated with student psychological distress and mental wellbeing, both cross-sectionally and longitudinally in a national sample of Australian secondary school students. Results showed that higher student home area-level socioeconomic advantage was associated with higher wellbeing, and greater student-rated school climate and school connectedness were associated with both lower psychological distress and higher wellbeing at baseline. Longitudinally, greater student-rated school connectedness was associated with greater student wellbeing two years later, consistent with prior studies \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. This suggests that finding ways to augment students\u0026rsquo; connectedness throughout high school may positively impact their wellbeing over time.\u003c/p\u003e\u003cp\u003eOur finding that higher student home area-level socioeconomic advantage is associated with higher wellbeing cross-sectionally is in line with previous recent research \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. As the socioeconomic advantage of the area an adolescent is raised in has the potential to influence so many domains of their life, including safety, access to educational support, and access to both physical and mental health care \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, there are many ways that socioeconomic advantage is likely to be associated with wellbeing. While there has been increasing attention given to the identification of the most salient social determinants of mental health \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, socioeconomic advantage remains a multifaceted construct requiring more nuanced investigation to determine what aspects of advantage play the largest role in terms of promoting mental wellbeing. Our cross-sectional findings contribute to the growing evidence suggesting a need to determine how best to reduce and mitigate the effects of socioeconomic disadvantage through changes in social and health policy.\u003c/p\u003e\u003cp\u003eNotably, no relationships between school-level factors and students\u0026rsquo; wellbeing and psychological distress were observed cross-sectionally or longitudinally. This is somewhat surprising, given that the conceptual groupings and factors were drawn from literature showing relevance to overall school efficacy, academic achievement, and student mental health \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Despite these factors supporting important aspects of school functioning and academic achievement as shown in previous research, school-level characteristics related to the regionality, administration, and student body of the school were not associated with wellbeing or distress in this sample. Our longitudinal findings are in line with the only other study to take a comprehensive approach to exploring the influence of many levels of factors in one sample \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e; however, further research taking this approach in school-based national samples is needed to replicate these findings both cross-sectionally and over time.\u003c/p\u003e\u003cp\u003eOur findings relating to staff- and student- rated perspectives of the school community found that student-rated school climate and student-rated school connectedness were both associated with lower psychological distress and higher wellbeing cross-sectionally. This finding contributes to a growing literature demonstrating that supportive and connected school communities play an important role in supporting the mental health and wellbeing of students. Notably, no significant associations were found between teacher-rated school culture and either student wellbeing or psychological distress. Although previous studies have found relationships between teacher-rated school culture and adolescent mental health both cross-sectionally \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e and longitudinally \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, concordance has not consistently been observed between teacher and student\u0026rsquo;s perceptions \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. It is possible that our findings may be indicative of a potential disconnect between staff and students\u0026rsquo; perceptions of their school community. Further research assessing underlying contributors to concordance and discordance between staff and student ratings of these factors over time would aid researchers to better understand the broader social dynamics of the school community, as well as potentially identify areas to target for those looking to improve school culture in both staff and students.\u003c/p\u003e\u003cp\u003eOur findings also identified student-rated school connectedness as being associated with higher levels of wellbeing cross-sectionally and two years later. This finding demonstrates not only how impactful a supportive school community may be on adolescent wellbeing above and beyond other school-level factors but provides important longitudinal evidence that feeling connected to one\u0026rsquo;s school and peers at school is likely to be key factor in sustaining and improving student wellbeing over time. Improving school connectedness is a rising area of importance to policy makers \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, and emerging intervention research provides some evidence that school-based programs designed to improve school connectedness may also be useful in improving student mental health and wellbeing \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Notably, we did not find an association between school connectedness and psychological distress two years later. In evidence-supported psychological theories such as the Dual Continuum Model of Mental Health \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e, distress and wellbeing are posited to be related but distinct psychological dimensions contributing to an individual\u0026rsquo;s mental health, with distress encompassing a broad range of emotional symptoms, and wellbeing capturing feelings related to life satisfaction and sense of purpose \u003csup\u003e\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Our findings suggest that students\u0026rsquo; feelings of connectedness with their school community may promote their mental health through improving their sense of positivity and ability to find meaning even when experiencing periods of emotional difficulty.\u003c/p\u003e\u003cp\u003eOur study has several important limitations to consider when interpreting these findings. First, although it can be considered a strength that our student sample is broadly representative of the Australian adolescent population \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, it was beyond the scope of this study to assess whether these relationships differed among subgroups known to be more vulnerable to psychopathology. Future research should consider whether certain school-level factors may be more important in supporting groups at greater risk. Second, results from our attrition analyses showed that our longitudinal sample significantly differed from our baseline sample on mental health history, baseline school climate, and baseline wellbeing. While these effects were either found to be of negligible size or included as covariates in our longitudinal models, these factors may have influenced our longitudinal findings. Additionally, the sample of teachers and school staff who completed our measures of school culture and promotion of student wellbeing was small (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;55) relative to the student sample, and the number of representatives from each of our 35 schools varied between 1\u0026ndash;4 members from each school. This may have contributed to the discordance in staff and student assessments of school community characteristics, at least in part. Future research should include larger staff samples to both ensure a more representative measurement of staff-rated school culture as well as enable further examinations of the concordance between staff- and student-level data. Finally, while our study included many school-, staff-, and student-level factors across several theoretical domains, it cannot be said that our list of potential factors was exhaustive of all potential school-related factors that may influence student mental health. Other school characteristics (such as uniform policy, access to green space, class size) found to be associated with student academic outcomes \u003csup\u003e\u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e may be worthy of examination in regard to their associations with student mental health, particularly as student mental health and academic achievement are associated outcomes \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eResults from this study highlight that among multiple dimensions of school-related factors, students\u0026rsquo; sense of connectedness with their school\u0026rsquo;s community is the most robust predictor of their wellbeing over time. This has important implications for both policy and future research, as school connectedness is a modifiable factor which emerging evidence shows can be improved through intervention \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Future research should examine the relationship between fluctuations in school connectedness and student mental health with greater nuance, investigating the potential bidirectional influence of these factors on one another, as well as assessments of what aspects of student connectedness are most important to student wellbeing, to further inform targeted interventions. Our findings also demonstrate that difficult to change, systemic factors such as socioeconomic advantage are associated with student mental health, representing an important consideration for social policy. However, targeting modifiable factors such as school connectedness may have the potential to improve student mental health more swiftly, while systemic factors are slower to address. Our findings demonstrate that school connectedness may be a promising candidate for intervention and policy initiatives designed to support student mental health and wellbeing at school.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the students and school communities who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData and code from this study are available upon reasonable request to the corresponding author, subject to ethical approval and governance processes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by a NHMRC Project Grant awarded to Helen Christensen (GNT1138405), a NHMRC Emerging Leader Fellowship awarded to Aliza Werner‐Seidler (GNT1197074) and Alison L. Calear (GNT1173146), SPRF NHMRC Fellowship to Helen Christensen (GNT 1155614), and a NHMRC Fellowship (GNT1158707) to Philip J. Batterham. The funders had no role in any aspect of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK.M., A.W-S., and S.K.S. conceived the study. S.K.S. conducted the analyses and wrote the original manuscript draft. P.B. provided statistical oversight. A.W-S, H.C., A.L.C, M.T., B.O.D. and P.B. conceived the trial and were awarded the funding, and J.R.B. supported data collection. All authors reviewed the manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKessler, R. 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This study assessed whether school-level (regional, administrative, and student characteristics), staff-level (school culture and promotion of wellbeing), and student-level factors (school climate and connectedness) were associated with students\u0026rsquo; distress and wellbeing cross-sectionally, and two years later. The sample consisted of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1548 adolescents in Year 8 (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e=13.9) from 35 schools in Australia. Results showed that greater student-level socioeconomic advantage was associated with better wellbeing cross-sectionally. Higher levels of student-rated school connectedness and climate were associated with greater wellbeing and lower distress cross-sectionally. Longitudinally, only higher student-rated school connectedness was associated with higher wellbeing two years later. No school-level factors were associated with student wellbeing or distress, cross-sectionally or two years later. Findings highlight the importance of students\u0026rsquo; sense of connectedness with their school community on wellbeing over time.\u003c/p\u003e","manuscriptTitle":"Longitudinal Associations Between School-, Staff-, and Student-Level Factors with Student Mental Health and Wellbeing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 13:05:43","doi":"10.21203/rs.3.rs-7341749/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-13T10:48:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93959184288309705223517281845355467515","date":"2026-04-13T16:37:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136337916436945193480146978463312912329","date":"2025-12-19T17:13:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-09T13:51:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3763034414716244944993144595007732879","date":"2025-10-09T05:40:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128004314172509444243991105953552309745","date":"2025-09-15T14:55:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-05T10:29:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-11T19:07:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-11T18:56:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Mental Health Research","date":"2025-08-11T02:43:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-mental-health-research","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjmentalhealth","sideBox":"Learn more about [npj Mental Health Research](https://www.nature.com/npjmentalhealth/)","snPcode":"44184","submissionUrl":"https://mts-npjmentalhealth.nature.com/cgi-bin/main.p...","title":"npj Mental Health Research","twitterHandle":"@npjmentalhealth\n","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"npj","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"337825a4-0563-4f64-b95e-255af44d1862","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-13T10:48:51+00:00","index":121,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":54515320,"name":"Health sciences/Health care"},{"id":54515321,"name":"Biological sciences/Psychology"},{"id":54515322,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2025-09-11T13:05:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 13:05:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7341749","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7341749","identity":"rs-7341749","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}