Implementation of Home-Based Telerehabilitation of Patients With Stroke in the United States: Protocol for a Realist Review
Bibliographic record
Abstract
BACKGROUND: Stroke is a common cause of mortality and morbidity. Insufficient and untimely rehabilitation has been associated with inadequate recovery. Telerehabilitation provides an opportunity for timely and accessible services for individuals with stroke, especially in remote areas. Telerehabilitation is defined as a health care team's use of a communication mode (eg, videoconferencing) to remotely provide rehabilitation services. Telerehabilitation is as effective as facility-based rehabilitation; however, it is infrequently used due to implementation barriers. OBJECTIVE: The aim of the study is to explore the interaction between the implementation strategies, context, and outcomes of telerehabilitation of patients with stroke. METHODS: This review will follow four steps: (1) defining the review scope, (2) literature search and quality appraisal, (3) data extraction and evidence synthesis, and (4) narrative development. PubMed via MEDLINE, the PEDro database, and CINAHL will be queried till June 2023 and supplemented with citation tracking and a gray literature search. The relevance and rigor of papers will be appraised using the TAPUPAS (Transparency, Accuracy, Purposivity, Utility, Propriety, Accessibility, and Specificity) and Weight of Evidence frameworks. The reviewers will extract and synthesize data iteratively and develop explanatory links between contexts, mechanisms, and outcomes. The results will be reported according to the Realist Synthesis publication standards set by Wong and colleagues in 2013. RESULTS: The literature search and screening will be completed in July 2023. Data extraction and analysis will be completed in August 2023, and findings will be synthesized and reported in October 2023. CONCLUSIONS: This will be the first realist synthesis, uncovering the causal mechanisms to explain how, why, and to what extent implementation strategies impact telerehabilitation adoption and implementation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/47009.
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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 | 0.092 | 0.096 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.018 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.059 | 0.008 |
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".