Postsecondary academic achievement and first-episode psychosis: A mixed-methods study
Bibliographic record
Abstract
BACKGROUND: Postsecondary academic achievement as an area of functional recovery for young adults living with mental illness has received little research attention. PURPOSE: This study had three purposes: to compare rates of participation, performance, and satisfaction in postsecondary education between young adults with first-episode psychosis and closely matched young adults; to identify characteristics associated with academic participation; and to explore the processes associated with educational experiences. METHOD: One hundred young adults ages 18 to 30 participated in the study. Quantitative data on academic engagement, performance, and satisfaction, and qualitative data (n = 52) on academic experiences were integrated through pattern analyzes. FINDINGS: Young adults with psychosis were significantly less likely to be engaged in postsecondary education. No difference appeared for the extent of engagement, but performance and satisfaction were lower among participants with psychosis. Participants engaged in reflexive decision making to access postsecondary education and to maintain adequate academic performance. Strategies used by successful students with mental illness were identified. IMPLICATIONS: Assessment and intervention focused on educational needs and skills should become landmark practices for psychiatric rehabilitation practitioners, including occupational therapists.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".