Total Metacognitive Capacity Predicts Competitive Employment Acquisition Across 6 Months in Adults With Serious Mental Illness Receiving Psychiatric Rehabilitation Services
Bibliographic record
Abstract
ABSTRACT: Deficits in metacognitive capacity are common among people with serious mental illness (SMI), although there is a gap in knowledge regarding how these impairments predict later functioning, especially employment. This study aimed to prospectively examine the relationship between metacognitive capacity and 6-month competitive employment attainment in adults with SMI who were participating in a study testing a cognitive behavioral therapy intervention added to supported employment services. Sixty-seven participants with complete data at baseline and the 6-month follow-up comprised the sample. Data were analyzed using stepwise logistic regression covarying for work history and study assignment. Results indicate that total metacognitive capacity at baseline significantly predicted employment acquisition at 6 months; the final model correctly classified 83.3% of participants who obtained work. In conclusion, these findings suggest that better overall metacognitive capacity may be key for future work functioning. Thus, interventions that target metacognitive capacity may lead to enhancements in community outcomes.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".