Baduanjin Qigong Intervention by Telerehabilitation (TeleParkinson): A Proof-of-Concept Study in Parkinson’s Disease
Bibliographic record
Abstract
Many people living with Parkinson's Disease (PD) face issues with healthcare services, including delays in diagnosis and treatment, as well as limited access to specialized care, including rehabilitation programs. Non-motor and motor signs and symptoms typically observed in people with PD, such as tremor, rigidity, postural instability, bradykinesia, and freezing are particularly disabling and have been associated with falls, fractures, hospitalizations, and a worse quality of life. Baduanjin Qigong (BDJ) programs have been proven potentially effective in improving physical outcomes and reducing the incidence of falls in PD. The aim of this case report, proof-of-concept, study was to explore the adherence, feasibility, acceptability, and potential efficacy of a BDJ program offered via telerehabilitation in people with PD living in the community. Two participants performed semi-supervised exercise sessions at home, twice a week (over eight weeks) using the TeraPlus platform. Adherence, adverse events, and feasibility (technical implementability), acceptability (patient satisfaction), patient-reported, self-reported, and performance outcomes were measured. Results were based on single-subject descriptive data, minimal detectable change, and anchor-based minimally important difference. Our findings suggest that the intervention seems feasible with no major technical issues or adverse events, and high adherence; acceptable (patient satisfaction); and potentially effective to improve markers of walking performance (gait speed, balance), and quality of life (activities of daily living, mobility).
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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 | 0.003 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".