A Resiliency-Emotion Regulation Framework for Student Well-being

Thesis Abstract

This study addresses the growing concern that disruptions to academic routines and social environments undermine student well-being by impairing resilience and emotion regulation processes. Despite extensive research on individual resilience and emotion regulation, there is limited integration of these constructs into a cohesive framework that specifically predicts well-being outcomes in diverse student populations. The aim is to develop and validate a Resiliency-Emotion Regulation Framework (RERF) for predicting student well-being and to identify mechanisms by which resilience-promoting and emotion regulation strategies interact to buffer stressors inherent in higher education. The objectives are to (1) conceptualize a formal model that links resilience resources, emotion regulation strategies, and well-being indicators; (2) examine the mediating roles of adaptive emotion regulation and cognitive reappraisal in the resilience–well-being relationship; (3) test measurement invariance of the framework across undergraduate and graduate students; (4) evaluate the incremental validity of RERF beyond existing models such as the Ecological Model of Resilience and Gross’s Process Model of Emotion Regulation; and (5) provide contextually grounded recommendations for university mental health services. A correlational, cross-sectional design will be employed with a stratified random sample of 1,200 students (600 undergraduates and 600 postgraduate) drawn from three large public universities. In addition, a longitudinal subsample of 300 students will complete a three-month follow-up to assess temporal stability and predictive validity. Data will be collected using standardized instruments and purpose-built measures the Brief Resilience Scale, the Emotion Regulation Questionnaire, the Cognitive Emotion Regulation Questionnaire, the Warwick-Edinburgh Mental Well-being Scale, and the Perceived Stress Scale, supplemented by a Purposeful Engagement Inventory to capture domain-specific well-being indicators (academic satisfaction, social connectedness, and sleep quality). Structural equation modeling (SEM) will be used to test the hypothesized RERF, with multi-group SEM to evaluate invariance across student groups. Mediation analyses will probe indirect effects of resilience on well-being via adaptive emotion regulation (cognitive reappraisal, suppression attenuation) and emotional flexibility. In the longitudinal arm, cross-lagged panel modeling will assess reciprocal effects between resilience, emotion regulation, and well-being over time. The study will also deploy hierarchical multiple regression to ascertain the incremental validity of RERF components beyond demographic covariates and baseline well-being. Anticipated findings indicate that higher resilience resources predict greater well-being, with adaptive emotion regulation partially mediating this relationship. It is expected that cognitive reappraisal and emotional acceptance will show stronger mediating effects than suppression, particularly among the undergraduate cohort. Measurement invariance is anticipated to hold across student strata, supporting the framework’s generalizability. The longitudinal results are expected to demonstrate that baseline resilience and adaptive emotion regulation prospectively predict improvements in well-being and reductions in perceived stress over three months, with reciprocal influences suggesting feedback loops between regulatory processes and resilience. The study contributes to knowledge by delivering a theoretically informed, empirically testable framework that integrates resilience and emotion regulation into a unified model of student well-being. It clarifies the specific regulatory mechanisms that enhance well-being under academic adversity and provides a validated measurement model suitable for cross-sectional and longitudinal research. The practical implications include evidence-based guidance for university health promotion programs, indicating that interventions should simultaneously cultivate resilience resources (e.g., self-efficacy, social support) and train adaptive emotion regulation strategies (notably cognitive reappraisal and acceptance-based approaches) to maximize well-being outcomes. Limitations include the cross-sectional nature of most data (mitigated by the longitudinal subsample) and potential self-report bias, which will be addressed through methodological triangulation with a subset of behavioral indicators and academic performance records, subject to ethical approvals. The conclusion will emphasize the necessity of integrated resilience and emotion regulation training within student support services, advising iterative program evaluation and refinement in higher education settings.