User-perceived utility of the Daily Experiences of Pleasure, Productivity, and Restoration Profile
Bibliographic record
Abstract
BACKGROUND: Awareness of the relationship between everyday occupations and subjective experience could help clients make changes that promote health. PURPOSE: This study evaluated user-perceived utility of the Daily Experiences of Pleasure, Productivity, and Restoration Profile (PPR Profile), a time-use survey designed to uncover users' experiences of pleasure, productivity, and restoration and to promote awareness of how these experiences are related to daily occupations. METHOD: Eighteen participants completed the PPR Profile on 2 days within I week and were subsequently interviewed. Content analysis was used to uncover themes. FINDINGS: Analysis revealed that completion of the PPR Profile requires time and energy, completion more than once is useful, and the PPR Profile contributes to awareness. Four subthemes of awareness were identified: awareness of the here and now, insights into one's occupations, context matters, and what is and what might be. IMPLICATIONS: Results support the utility of the PPR Profile to promote users' awareness of their occupations and related subjective experiences. This awareness may encourage positive change. Further research is recommended to continue to evaluate the PPR Profile's clinical utility.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".