Paving the Road for More Ethical and Equitable Policies and Practices in Telerehabilitation in Psychology and Neuropsychology: Protocol for a Rapid Review (Preprint)
Bibliographic record
Abstract
BACKGROUND Virtual rehabilitation, or telerehabilitation (TR), has exponentially evolved in the last few years, gaining particular momentum since the COVID-19 pandemic. In response to a new reality of strict restrictions of physical contact necessitating the shift from in-person health services to tele-health visits, TR has seen widespread adoption. In this context, ensuring ethical and equitable TR services is crucial for establishing sustainable TR models for psychology and neuropsychology into health care systems. This requires complete and consistent guidance for clinicians and patients involved. OBJECTIVE The objective of this study is to synthesize existing evidence to provide timely insights on potential ethical and equitable benefits and pitfalls associated with the use of TR in a psychological and neuropsychological framework. METHODS A rapid review of TR practices will be conducted specifically within the context of neuropsychology and psychology rehabilitation. We will include review articles published between 2010 and 2020 as well as original articles published between 2020 and 2023, all addressing TR issues with a main focus on neuropsychological and/or psychological rehabilitation activities. This research protocol describes the methodology, including search strategy, screening process, data extraction, and analysis methods. RESULTS Guided by an experienced librarian, the search strategy was designed and performed in 3 relevant databases. Articles were screened in accordance with the inclusion and exclusion criteria, and data were collected by 2 independent reviewers. Data extraction is underway, and we expect to complete the rapid review in January 2025. CONCLUSIONS This study is part of a broader cross-Canadian initiative aimed at informing policy development and clinical practices in TR. By evaluating the ethical and equitable considerations specific to psychology and neuropsychology, this review aims to contribute to help shape future TR practices to ensure access to high-quality, accessible TR services supporting diverse patient needs in psychology and neuropsychology. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/66639
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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 | 0.119 | 0.215 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.106 | 0.026 |
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".