Tele-Active Rehabilitation for Youth With Concussion: Evidence-Based and Theory-Informed Intervention Development
Bibliographic record
Abstract
BACKGROUND: Active rehabilitation involving subsymptom threshold exercise combined with education and support promotes recovery in youth with concussion but is typically delivered in person, which may limit accessibility for families because of a lack of services in their communities or logistical challenges to attending in-person sessions. OBJECTIVE: This paper describes the evidence-based and theory-informed development of the Tele-Active Rehabilitation (Tele-AR) intervention for pediatric concussion, which was specifically designed for remote service delivery. METHODS: The intervention was designed by clinician-researchers with experience in pediatric concussion rehabilitation following the Medical Research Council guidance for developing complex interventions. Development involved a critical review of the literature to identify existing evidence, the expansion of the theoretical basis for active rehabilitation, and the modeling of the intervention process and outcomes. RESULTS: Tele-AR is a 6-week home exercise and education and support program facilitated through weekly videoconferencing appointments with a clinician. Exercise consists of low- to moderate-intensity subsymptom threshold aerobic activity and coordination drills that are individualized to participant needs and interests (prescribed for 3 days per week). Education includes the evidence-supported Concussion & You self-management program, which covers topics related to energy management, nutrition, hydration, sleep hygiene, and return to activity. Elements of self-determination theory are incorporated to support motivation and engagement. We present a logic model describing predicted intervention effects using a biopsychosocial conceptualization of outcomes after concussion. CONCLUSIONS: The Tele-AR intervention may help to increase access to care that improves recovery and promotes a timely return to activity in youth with concussion. Future research is needed to evaluate the feasibility and efficacy of this approach.
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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 | 0.024 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".