Mindfulness-based lifestyle programs for the self-management of Parkinson’s disease in Australia
Bibliographic record
Abstract
Despite emerging evidence suggesting positive outcomes of mindfulness training for the self-management of other neurodegenerative diseases, limited research has explored its effect on the self-management of Parkinson's disease (PD). We aimed to characterize the experiences of individuals participating in a facilitated, group mindfulness-based lifestyle program for community living adults with Stage 2 PD and explore how the program influenced beliefs about self-management of their disease. Our longitudinal qualitative study was embedded within a randomized controlled trial exploring the impact of a 6-week mindfulness-based lifestyle program on patient-reported function. The study was set in Melbourne, Australia in 2012-2013. We conducted semi-structured interviews with participants before, immediately after, and 6 months following participation in the program. Sixteen participants were interviewed prior to commencing the program. Of these, 12 were interviewed shortly after its conclusion, and 9 interviewed at 6 months. Prior to the program, participants felt a lack of control over their illness. A desire for control and a need for alternative tools for managing the progression of PD motivated many to engage with the program. Following the program, where participants experienced an increase in mindfulness, many became more accepting of disease progression and reported improved social relationships and self-confidence in managing their disease. Mindfulness-based lifestyle programs have the potential for increasing both participants' sense of control over their reactions to disease symptoms as well as social connectedness. Community-based mindfulness training may provide participants with tools for self-managing a number of the consequences of Stage 2 PD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".