Ecological determinants of school absenteeism in Australia: Multilevel models using LSAC

Background and rationale School absenteeism is not solely an individual behaviour; it reflects developmental change over time and multiple, partially independent systems of influence (family, school, neighbourhood, and broader policy/service contexts). Consistent with an ecological systems perspective, this project treats these influences as interacting layers that shape how attendance is sustained or disrupted across development. Using the Longitudinal Study of Australian Children (LSAC), we will quantify how absenteeism varies within individuals over time and between individuals and contexts, estimating the extent to which contextual environments (e.g., school-level and area-level conditions) predict absenteeism above and beyond individual and family characteristics. Aims: (i) Estimate developmental change in absenteeism across repeated LSAC waves (within-person change). (ii) Identify individual and family predictors of absenteeism (between-person differences). (iii) Quantify contextual effects (school and neighbourhood/area influences) and test cross-level moderation (e.g., whether supportive school contexts buffer individual vulnerability), aligned with a Bronfenbrenner framework. Research questions: (i) How does absenteeism change across time within children/adolescents in LSAC? (ii) Which individual factors (e.g., self-regulation, health, internalising/externalising difficulties) predict absenteeism? (iii) Which family factors (e.g., SES, family functioning, parenting stress) predict absenteeism? (iv) Which school/area contexts predict absenteeism net of individual/family factors? (v) Do contexts moderate individual risk (cross-level interactions), indicating “for whom” and “under what conditions” absenteeism risk is amplified or buffered? Hypotheses: H1. Absenteeism will show meaningful within-person change over time (non-zero growth and variance in growth). H2. Lower baseline self-regulation and higher psychosocial difficulties will predict higher absenteeism (between-person effects). H3. Disadvantaged contexts (e.g., lower area SES; adverse school climate proxies where available) will predict higher absenteeism above individual/family factors (context effects). H4. Contextual supports will buffer individual vulnerability (cross-level moderation): individual risks will be more strongly associated with absenteeism in less supportive contexts.