A Review of Instruments for Measuring Functional Recovery in Those Diagnosed With Psychosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The task of judging an individual's functional recovery is not an easy one for healthcare professionals. Indeed, increasing one's accuracy in predicting one's ability to self-maintain would be of great value for determining if functional recovery has or is occurring. The purpose of this review is to examine existing measures for assessing remission/normalization of functional status among people with psychosis. Our review evaluates 8 measures of functional ability encompassing self-report, clinical, and performance-based measures. We elected to utilize a grading system to aid readers in understanding the merit of a scale for use in assessing functional recovery. In this approach, a letter grade (A, B, or C) was assigned to each of 4 domains we deemed important to professionals in electing to use specific assessments: (1) Ease of Administration, (2) Reliability, (3) Validity/Relationship to Real-World Outcomes, and (4) Sensitivity to Change/Use in Clinical Trials. Results indicated that no "gold standard" measure has been developed to date, but performance-based measures appear to have the most evidence for predicting concurrent self-maintenance abilities (eg, residing independently or maintaining work). More research on existing measures is needed, and greater funding for developing new measures of functional recovery is strongly recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it