Latent profile analysis of psychiatric symptoms and the Ability to Participate in Social Roles and Activities.

BACKGROUND

The objective of this study was to investigate latent response patterns in symptom severity, as measured by the Brief Symptom Inventory (BSI), and limitations in daily functioning, as assessed by the extended PROMIS item bank 'Ability to Participate in Social Roles and Activities' (APSRA), within a sample of psychiatric outpatients. In addition to identifying classes with converging test results, we hypothesized the existence of classes with divergent results: those exhibiting low symptom severity alongside severe functional limitations, and those demonstrating high symptom severity while maintaining high levels of functioning.

METHODS

A sample of 1,010 psychiatric outpatients from the Netherlands completed the Dutch BSI and APSRA. Latent Profile Analysis (LPA) was employed to group patients with similar patterns in symptom severity and daily functioning limitations. After identifying the LPA classes and class membership of all patients, we analyzed the distribution of suicidal ideation, participation level (i.e., employment), diagnosis, age, sex, living situation, and education level, across the LPA classes.

RESULTS

The correlation between APSRA and BSI scores (r = -.64) showed that higher APSRA scores were associated with lower psychopathology. LPA identified four distinct profiles of psychosocial dysfunction: minimal, mild, moderate, and severe. These profiles differed significantly in suicidal ideation and work participation but not in other demographic variables. While diagnosis had a statistically significant effect on class membership, the effect size was negligible. The hypothesized divergent classes were not observed.

CONCLUSION

The four profiles provide a clinically relevant framework for understanding self-reported psychosocial dysfunction, distinguishing patients on key outcomes such as suicidal ideation and work participation. This approach supports tailoring interventions, prioritizing treatment goals, and allocating resources based on shared patterns of characteristics. Future research should validate these profiles' temporal stability and predictive value for treatment outcomes while exploring the benefits of combining symptom and functioning assessments for clinical decision-making.