An integrative process model of resilience in an academic context: Resilience resources, coping strategies, and positive adaptation.

Tertiary study presents students with a number of pressures and challenges. Thus, mental resilience plays a key role in students' well-being and performance. Resilience research has moved away from conceptualising resilience as a trait and towards studying resilience as a process by which resources protect against the negative impact of stressors to produce positive outcomes. However, there is a lack of research in the academic domain examining the mechanisms underlying this process. This study addressed this gap by examining a range of personal resilience resources and their interaction with coping responses to produce positive adaptation outcomes, in a sample of 306 undergraduate students. Firstly, individual differences in resilience were examined, whereby factor analysis resulted in self-report measures of resilience-related attributes converging onto an overarching factor. The extracted factor was then validated against markers of positive adaptation (mental well-being, university adjustment, and somatic health symptoms), and the mediating roles of coping strategies were investigated through structural equation modelling. The resilience resources factor directly predicted mental well-being and adjustment; and indirectly predicted adjustment and somatic health symptoms through support-seeking and avoidant coping, respectively. These findings have theoretical implications for how resilience is conceptualised, as well as practical implications for improving student well-being and adjustment through promoting social support and reducing disengaged and avoidant coping strategies.

To comply or not comply? A latent profile analysis of behaviours and attitudes during the COVID-19 pandemic.

How and why do people comply with protective behaviours during COVID-19? The emerging literature employs a variable-centered approach, typically using a narrow selection of constructs within a study. This study is the first to adopt a person-centred approach to identify complex patterns of compliance, and holistically examine underlying psychological differences, integrating multiple psychology paradigms and epidemiology. 1575 participants from Australia, US, UK, and Canada indicated their behaviours, attitudes, personality, cognitive/decision-making ability, resilience, adaptability, coping, political and cultural factors, and information consumption during the pandemic's first wave. Using Latent Profile Analysis, two broad groups were identified. The compliant group (90%) reported greater worries, and perceived protective measures as effective, whilst the non-compliant group (about 10%) perceived them as problematic. The non-compliant group were lower on agreeableness and cultural tightness-looseness, but more extraverted, and reactant. They utilised more maladaptive coping strategies, checked/trusted the news less, and used official sources less. Females showed greater compliance than males. By promoting greater appreciation of the complexity of behaviour during COVID-19, this research provides a critical platform to inform future studies, public health policy, and targeted behaviour change interventions during pandemics. The results also challenge age-related stereotypes and assumptions.

Applying Evidence-Centered Design to Measure Psychological Resilience: The Development and Preliminary Validation of a Novel Simulation-Based Assessment Methodology.

Modern technologies have enabled the development of dynamic game- and simulation-based assessments to measure psychological constructs. This has highlighted their potential for supplementing other assessment modalities, such as self-report. This study describes the development, design, and preliminary validation of a simulation-based assessment methodology to measure psychological resilience-an important construct for multiple life domains. The design was guided by theories of resilience, and principles of evidence-centered design and stealth assessment. The system analyzed log files from a simulated task to derive individual trajectories in response to stressors. Using slope analyses, these trajectories were indicative of four types of responses to stressors: thriving, recovery, surviving, and succumbing. Using Machine Learning, the trajectories were predictive of self-reported resilience (Connor-Davidson Resilience Scale) with high accuracy, supporting construct validity of the simulation-based assessment. These findings add to the growing evidence supporting the utility of gamified assessment of psychological constructs. Importantly, these findings address theoretical debates about the construct of resilience, adding to its theory, supporting the combination of the "trait" and "process" approaches to its operationalization.