Abstract
Aim: The fluctuating symptoms of clinical high risk for psychosis hamper conversion prediction models. Exploring specific symptoms using machine-learning has proven fruitful in accommodating this challenge. The aim of this study is to explore specific predictors and generate atheoretical hypotheses of onset using a close-monitoring, machine-learning approach. Methods: Study participants, N = 96, mean age 16.55 years, male to female ratio 46:54%, were recruited from the Prevention of Psychosis Study in Rogaland, Norway. Participants were assessed using the Structured Interview for Psychosis Risk Syndromes (SIPS) at 13 separate assessment time points across 2 years, yielding 247 specific scores. A machine-learning decision-tree analysis (i) examined potential SIPS predictors of psychosis conversion and (ii) hierarchically ranked predictors of psychosis conversion. Results: Four out of 247 specific SIPS symptom scores were significant: (i) reduced expression of emotion at baseline, (ii) experience of emotions and self at 5 months, (iii) perceptual abnormalities/hallucinations at 3 months and (iv) ideational richness at 6 months. No SIPS symptom scores obtained after 6 months of follow-up predicted psychosis. Conclusions: Study findings suggest that early negative symptoms, particularly those observable by peers and arguably a risk factor for social exclusion, were predictive of psychosis. Self-expression and social behaviour might prove relevant entry points for early intervention in psychosis and psychosis risk. Testing study results in larger samples and at other sites is warranted.
RAS ID
38910
Document Type
Journal Article
Date of Publication
2022
Funding Information
Health West Foundation Norwegian Extra Foundation for Health and Rehabilitation through EXTRA funds
School
School of Arts and Humanities
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Publisher
Wiley
Comments
Bjornestad, J., Tjora, T., Langeveld, J. H., Stain, H. J., Joa, I., Johannessen, J. O., . . . ten Velden Hegelstad, W. (2022). Exploring specific predictors of psychosis onset over a 2‐year period: A decision‐tree model. Early Intervention in Psychiatry, 16(4), 363-370. https://doi.org/10.1111/eip.13175