Personal Projects Analysis in occupational therapy research: A scoping review
Bibliographic record
Abstract
Introduction Personal Projects Analysis has been used in occupational therapy research to better understand occupation. The purpose of this scoping review is to describe Personal Projects Analysis and examine how it has been used in occupational therapy research. Method Occupational therapy studies using Personal Projects Analysis were identified and described in terms of sample, research question, design, use of Personal Projects Analysis, and results. Findings Fifteen studies in which Personal Projects Analysis was used in occupational therapy research were retrieved. Three of the four Personal Projects Analysis modules have been used in occupational therapy research on project characteristics and subjective well-being, types of projects affected by health problems, and occupational balance. Only one paper described a clinical use of Personal Projects Analysis in occupational therapy. Conclusion Personal Projects Analysis is a useful evaluation for occupational therapy research and a potential tool for practice.
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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 | 0.036 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.034 | 0.033 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".