Protocol for a remote home-based upper extremity self-training program for community-dwelling individuals after stroke
Why this work is in the frame
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Bibliographic record
Abstract
Background: Half of all stroke survivors experience hemiparesis on the contralateral side, resulting in chronic upper extremity (UE) impairment. Remote rehabilitation is a promising approach to optimize the gains made in the clinic to maximize function and promote UE use at home. This paper describes the study protocol for a remote home-based UE self-training program. Design: This was a feasibility study that used a convergent mixed methods approach. Methods: We collected data on 15 community-dwelling individuals with UE hemiparesis after stroke. The study used motivational interviewing (MI) and ecological momentary assessments (EMA) to maximize engagement in a 4-week personalized UE self-training program. The study consisted of three phases: 1) training in MI for the interventionists 2) creating customized treatment plans using shared decision making, and 3) four weeks of UE self-training. Measures and analysis: To evaluate feasibility, we will summarize recruitment and retention rates, intervention delivery, acceptance, adherence, and safety. Quantitative UE outcomes will measure change in UE status after the intervention (Fugl-Meyer Assessment, Motor Activity Log, Canadian Occupational Performance Measure, and bilateral magnitude ratio). Qualitative data (1:1 semi-structured interviews) will capture participants' perceptions and experience with the intervention. Quantitative and qualitative data will be integrated to gain a deeper understanding of the facilitators and barriers for engagement and adherence to UE self-training. Conclusion: The results of this study will advance the scientific knowledge for use of MI and EMA as methods for enhancing adherence and engagement in UE self-training in stroke rehabilitation. The ultimate impact of this research will be to improve UE recovery for individuals with stroke transitioning back into community. Clinical trials registration: NCT05032638.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it