The experience of off periods: Qualitative analysis of interviews with persons with Parkinson's and carepartners
Bibliographic record
Abstract
Introduction Off period research in Parkinson's disease commonly relies on questionnaires. We aimed to investigate the breadth of off period experiences by interviewing persons with Parkinson's disease (PwP) and carepartners. Methods Investigators performed PwP and carepartner dyad interviews using a semi-structured questionnaire to describe off period experiences. Investigators analyzed interview transcripts using a qualitative descriptive approach to identify and compare themes between groups. Results Twenty PwP and their carepartners participated in interviews. PwP were on average 65.1 years-old (SD 8.3) and 7.8 years (SD 4.7) after their Parkinson's disease diagnosis. PwP and carepartners identified 13 motor symptoms, 5 of which (immobility, gait changes, freezing, trouble swallowing, and having to concentrate on movements) were not in the wearing off questionnaires recommended by the International Parkinson and Movement Disorders Society. PwP and carepartners identified 15 non-motor symptoms, 8 of which (behavior changes, irritability, fatigue, language difficulties, dizziness, dry mouth, urinary symptoms, and swollen feet) were not in recommended questionnaires. Certain symptoms were reported only by PwP (e.g. dizziness, urinary symptoms) or carepartners (e.g. behavioral changes), or were reported by dyad members to different degrees (e.g. fatigue, anxiety). Conclusion Wearing off questionnaires capture the presence of fluctuations and can facilitate patient-physician communication regarding off periods. However, they may miss the breadth of individual PwP experiences. PwP and carepartners also report different PwP experiences during off periods. To fully appreciate an individual's off experiences, clinicians likely need to use multiple approaches to gathering information including questionnaires and both PwP and carepartner report.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".