The Most Bothersome Aspects of <i>Off</i> Periods Reported by Individuals with Parkinson's Disease
Bibliographic record
Abstract
ABSTRACT Introduction The off periods in Parkinson's disease have a significantly negative impact on quality of life. What the most bothersome aspects of off periods are from the patient's perspective are not well studied, nor is the degree to which screening tools for wearing off such as the Wearing Off Questionnaires (WOQs) capture what bothers patients most. Methods A questionnaire was deployed to eligible participants of Fox Insight, an online study of individuals with self‐reported Parkinson's disease. Inclusion criteria were the use of ≥1 dopaminergic medications and an affirmative response to a question on experiencing off periods. Participants provided free‐text responses regarding the top 3 most bothersome symptoms they experience when off. A determination was made regarding whether each response would have been captured by the 32‐item, 19‐item, and 9‐item WOQs. Results The final sample had 2106 participants, a mean age of 66.6 years, 52.3% were men, and had a disease duration of 4.9 years. The WOQ‐32 items covered all of the most bothersome symptoms for 53.2% of respondents. Among bothersome aspects of off not captured by the WOQs, 597 (66.2%) were specific symptoms, with freezing of gait, apathy, and memory problems being the most common. The functional consequences of off periods were most bothersome to 232 (25.7%), with walking problems being the most common. The emotional response to off periods was the most bothersome aspect to 169 respondents (18.7%). Discussion This study emphasizes the value of narrative data in understanding patient experiences, and what bothers patients most about off periods. The WOQs, although of established utility in the screening for wearing off, may not capture those symptoms most bothersome to patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".