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)

Following the onset of a First Episode of Psychosis (FEP), the rate of individuals Not in Education, Employment, or Training (NEET) appears to drastically increase. Sociodemographic and clinical factors were reported to be associated with NEET status in FEP patients. This study examined how these sociodemographic and clinical factors were linked to NEET status in FEP patients independently and from an intersectional perspective. It was hypothesized that NEET status in FEP patients would be described by the intersection between at least two predictor variables. Secondary analyses were conducted on files of participants recruited from a local FEP clinic. Univariate logistic regression and Chi-squared Automatic Interaction Detection (CHAID) analyses were performed on a total of 440 participants with FEP. Univariate logistic regressions indicated that age (p = .03), socioeconomic status (p < .001), and negative symptom severity (p < .001) were significant independent predictors of NEET. CHAID analyses suggested an intersectional pattern of negative symptom severity and socioeconomic status in differentiating between FEP patients with NEET versus non-NEET status. The applicability and generalizability of results from this study were enhanced by the large and representative sample as well as the use of benchmark quantitative intersectionality research methods. Future intersectionality research on NEET with a clinical population is needed to validate and expand the current results by including more sociodemographic variables.