Exploring routine use of telemedicine through a case study in rehabilitation.
Bibliographic record
Abstract
OBJECTIVE: This study examines how telerehabilitation becomes part of existing and new clinical routines and identifies factors that enable or constrain its routine use. METHODS: An in-depth case study of a telemedicine program in rehabilitation implemented between an urban specialized rehabilitation center and a rural regional rehabilitation center was conducted. Using a conceptual framework based on Giddens' theory of structuration, a qualitative analysis was carried out using four data sources: focus groups and phone interviews (with health professionals, managers, and patients and their family members); telerehabilitation video recordings; and project documents (e.g., proposals, requests for funding, summaries, agendas of meetings, operating procedures, patient handouts, and tools for clinicians). RESULTS: In two rehabilitation programs for 1) patients who sustained a traumatic brain injury and 2) those who sustained a spinal cord injury, telerehabilitation was successfully incorporated into routine clinical practices for activities such as interdisciplinary care plans. However, for specialized clinical consultations or long-term patient follow-up, telerehabilitation was not successfully incorporated. Factors that facilitated or prevented the integration of telerehabilitation in routine practices stemmed from both the structure (norms, rules, resources, and values) and the agent (e.g., users of telerehabilitation, including clinicians, managers, and patients and their families) and include 1) shared beliefs and assumptions held by patient care team members regarding the nature of the clinical activities, and the perceptions of patients and their family members; 2) clinical and organizational leadership; 3) extent and type of telerehabilitation use; 4) available resources; and 5) collaborations already in place or needing to be developed. CONCLUSIONS: This study provides empirical evidence of how telerehabilitation activities may become integrated into routine day-to-day clinical activities.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".