Remote supervision of rehabilitation interventions for survivors of moderate or severe traumatic brain injury: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Individuals with moderate or severe traumatic brain injury (TBI) often have persistent impairments upon discharge home. In rural communities, specialized rehabilitation services to address impairments can be difficult to access. The purpose of this scoping review is to examine how remote supervision is currently being used in TBI rehabilitation to identify gaps in knowledge that need to be addressed to facilitate access to and implementation of these services. METHODS: The main objective for this review is to identify the methods being used to deliver remote supervision for rehabilitation in a moderate or severe TBI population. The aim of this review was to document the implementation characteristics of remote supervision used including: (1) type of supervision such as synchronous, asynchronous supervision or mixed; (2) frequency and intensity of remote supervision; and (3) outcomes used to measure intervention delivery as well as effectiveness within this population. This scoping review follows EQUATOR Network recommendations for screening and extracting data. RESULTS: Twenty-six studies using a variety of remote supervision technology and outcome measures were included. Supervision frequency and intensity are poorly reported with no standardization. One hundred and six outcome measures were reported in this review showing large diversity in the areas being explored. DISCUSSION: Different types of remote supervision have been used with this population; however, there are no clear guidelines on clinical implementation. Future studies must better define implementation parameters of remote supervision. Benefit on physical activity, balance and mobility outcomes also need to be further explored.
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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 | 0.010 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".