All’s well that ends well: an early-phase study testing lower end-session exercise intensity to promote physical activity in patients with Parkinson’s disease
Bibliographic record
Abstract
Decreasing the intensity of exercise at the end of a session has been associated with greater post-exercise pleasure and enjoyment. Here, we investigated whether this manipulation can enhance affective attitudes toward physical activity (PA) and promotes PA in patients with Parkinson’s disease (PD). Seven patients (72.9±5.6 years, 3 women) were included in an eight-week within-subject study consisting of weekly exercise sessions. The first four weeks were used as a control condition. In the last four weeks, ten minutes of lower-intensity exercise were added at the end of each session (experimental condition). Results of the linear mixed-effects models showed that the addition of lower-intensity exercise increased the explicit affective attitudes toward PA (b = 1.00, 95% Confidence Interval = .36 to 1.64, p = .022). We found no evidence of an effect on implicit affective attitudes (p = .564), accelerometer-based PA (p = .417) and self-reported PA (p = .122) measures of PA. Although not significant, self-reported physical activity per day was 36 minutes longer in the intervention than in the control condition. These findings suggest that consistently reducing the intensity of an exercise at the end of the sessions enhances explicit affective attitudes toward PA in patients with PD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".