SU60. Risk and Protective Factors Associated With Psychotic Symptom Profiles of Marginally Housed Adults
Bibliographic record
Abstract
Background: This study examined the characteristics and associated risk and protective factors of distinct psychotic symptom profiles exhibited by marginally housed adults. Methods: The Hotel Study is a longitudinal observational study of adults living in marginalized housing. Five psychosis symptoms (delusions, conceptual disorganization, hallucinations, suspiciousness, and unusual thought content) from the Positive and Negative Syndrome Scale (PANSS) were assessed monthly. Sociodemographic, psychiatric, medical, developmental, social, and substance use factors were also assessed. Two-step cluster analysis was employed to identify groups of people that shared similar symptom profiles at the time of their maximum (MaxTime) and minimum (MinTime) total symptom severity (PANSS) in 1 year. Multinomial logistic regression analysis was used to estimate the associations between factors and cluster membership. Paired Wilcoxon and McNemar’s tests were used to compare substance use at MaxTime and MinTime within each cluster. Results: In the first year of study, 404 participants had at least three 5-item PANSS assessments. Cluster analysis of the PANSS scores identified 3 clusters at MaxTime. The Severe Cluster (n = 74) endorsed severe psychosis symptoms, while the Variable Cluster (n = 147) endorsed supra-threshold delusions and hallucinations only. The Low Cluster (n = 183) did not endorse psychosis at MaxTime. Variable Cluster membership was associated with methamphetamine (OR, 95% CI: 2.28, 1.26–4.10) and cannabis use in the past week (OR, 95% CI: 2.69, 1.39–5.24), a history of traumatic brain injury (OR, 95% CI: 3.14, 1.41–7.01), and low social support at study entry (OR, 95% CI: 0.79, 0.63–0.99). The Variable Cluster experienced frequent transitions between psychotic and nonpsychotic states (median, IQR: 3, 1–5; P < .001), possibly exacerbated by methamphetamine (X2 = 6.86; P = .009) and alcohol use (X2 = 7.90; P = .005). Severe Cluster membership was associated with antipsychotic treatment (OR, 95% CI: 7.34, 3.21–16.81), methamphetamine (OR, 95% CI: 2.84, 1.36–5.90) and cannabis use in the past week (OR, 95% CI: 2.69, 1.39–5.24), and low social support at study entry (OR, 95% CI: 0.73, 0.53–0.99). The Severe Cluster had high rates of primary psychosis diagnosis (P < .001) and poorer psychosocial functioning (P < .001) than the Low Cluster. Symptoms may be exacerbated by recent cannabis (X2 = 5.06; P = .024), opioid (X2 = 4.00; P = .046), or alcohol use (X2 = 4.65; P = .031), but may be unaffected by methamphetamine (X2 = 0.44; P = .505) and antipsychotic use (X2 = 0.00; P = 1.000) in the Severe Cluster. Conclusion: A subset of marginally housed adults living with complex multimorbid illness experience severe psychotic symptoms that may be unresponsive to both antipsychotic treatment and methamphetamine use. These individuals may need alternative or additional forms of mental health care and rehabilitation support.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".