Development of a Questionnaire to Investigate Study Design Factors Influencing Participation in Gait Rehabilitation Research by People with Stroke: A Brief Report
Bibliographic record
Abstract
PURPOSE: The main objective of this study was to evaluate the feasibility of a newly developed questionnaire to assess the influence of study design on participation in gait rehabilitation research in a pilot test with individuals with stroke. A secondary objective was to investigate the relationship between participation in gait rehabilitation research and social and clinical factors of interest after stroke. METHODS: A questionnaire was developed with expert opinion and guidance from related previous research. The questionnaire was pilot tested in a group of 21 people with stroke, and social and clinical factors (including gait function) were collected. Gait function was assessed using a pressure-sensitive mat; social and clinical characteristics were extracted from patient charts. Correlations were performed to investigate relationships between questionnaire responses and gait function, motor impairment, and chronicity; t-tests were used to examine response differences between people with a caregiver at home and those without. RESULTS: A total of 21 people with stroke completed the questionnaire without difficulty; mean completion time was 7.2 (SD 3.5) minutes, with a range of responses across participants. Borderline significant associations were found between gait function and the number of studies in which a person would participate and between stroke chronicity and the location of studies in which a person would participate. CONCLUSIONS: A questionnaire to investigate the influence of study design factors on participation in rehabilitation research is feasible for administration in the post-stroke population and has potential to inform the design of future studies.
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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 | 0.037 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".