Applying self-regulated learning to anxiety and stress management in severe mental disorders: A qualitative study.

Severe mental disorders (SMDs), such as schizophrenia, bipolar disorder, and personality disorders, present significant challenges for stress and anxiety management due to cognitive vulnerabilities. Self-regulated learning (SRL) models offer a structured framework for analyzing self-management strategies, yet their application in mental health contexts remains underexplored. This study applies Pintrich's (2000) SRL model to examine how individuals with SMDs manage stress and anxiety, identifying strengths and gaps across the forethought, monitoring, control, and reaction/reflection phases. A qualitative approach was employed, analyzing focus group discussions with 28 adults diagnosed with SMDs. Thematic analysis, conducted using NVivo, combined inductive coding and theory-driven interpretation based on the SRL framework. Results show that the forethought phase was most frequently represented, emphasizing participants' cognitive preparation and anticipation of stressors. The control phase followed, highlighting behavioral and contextual coping strategies such as relaxation, problem-solving, and support-seeking. However, the monitoring and reaction/reflection phases were less developed, with limited focus on real-time awareness and evaluation. These findings point to the need for tailored interventions and highlight theoretical adaptations required to extend SRL to clinical contexts. We discuss how integrating SRL with recovery-oriented frameworks could support more adaptive, person-centered strategies for managing stress and anxiety in SMDs.