Client Perceptions of the Individual Packer Managing Fatigue Program: A Mixed-Method Evaluation
Bibliographic record
Abstract
Fatigue is common, but under-recognized in Parkinson’s disease (PD), with limited treatment options. The aim of this study is to explore the experience of people with PD (PwPD) regarding content and delivery of the individual Packer Managing Fatigue program. This mixed-method study ( n = 12) was conducted concurrently with a pilot randomized controlled trial. Data were collected using questionnaires, interviews, and focus groups. Five themes emerged: the program is helpful; the program has strengths; areas for improvement; individual online delivery is feasible; and more support from occupational therapist would be helpful. Quantitative findings confirmed feasibility with high ratings on questionnaires and confidence to use learned strategies. The findings inform future implementation of the Packer Managing Fatigue program and contribute to understanding the needs of PwPD. Future studies might explore program’s effectiveness as stand-alone treatment or in combination with other approaches. Tailoring fatigue programs to PwPD’s unique needs and characteristics of PD fatigue is suggested.
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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 | 0.030 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".