An intersectional perspective on the sociodemographic and clinical factors influencing the status of not in Education, Employment, or training (NEET) in patients with first-episode psychosis (FEP).

Purpose: High rates of Not in Education, Employment or Training (NEET) are seen in people with first episode of psychosis (FEP). Sociodemographic and clinical factors were reported to be associated with NEET status in FEP patients. This study follows Intersectionality to examine the independent and additive effects, and most importantly the intersections of sociodemographic and clinical variables concerning NEET status in FEP patients. It was hypothesized that NEET status in FEP patients would be described by the intersection between at least two predictor variables.

Methods: Secondary analyses with chi-square tests, multiple logistic regression and Chi-squared Automatic Interaction Detection (CHAID) analyses were performed on 440 participants with FEP.

Results: Chi-square tests indicated that patient socioeconomic status and negative symptom severity were significantly and independently associated with their NEET status. Multiple logistic regression suggested additive effects of age (odds ratio = 1.61), patient socioeconomic status (odds ratio = 1.55) and negative symptom severity (odds ratio = 1.75) in predicting patients' NEET status. CHAID detected an intersection between patients' negative symptom severity and socioeconomic status in shaping their NEET status.

Conclusion: This study explored how the NEET status of patients with FEP was explained not only by the separate effects of negative symptom severity and socioeconomic status but also by the unique intersections of their clinical and social identities. Findings indicated that functional outcomes of patients appear co-constructed by the intersections of multiple identities. Crucial clinical implications of complementing care for negative symptom severity with vocational resources to improve functional outcomes of patients are discussed.