Combined Treatment of Face-to-Face Physical Therapy and Telerehabilitation in Workers with Whiplash Syndrome
Bibliographic record
Abstract
Objective: Interventions through telerehabilitation have shown positive effects in various clinical conditions, facilitating the return to work of the working population. This study aimed to compare conventional, center-based physiotherapy versus an intervention combining home- and center-based treatment for whiplash syndrome in workers enrolled in a mutual insurance company, evaluating differences in the number of face-to-face sessions and the duration of sickness absence. The secondary aim was to assess the acceptability and usability of the telerehabilitation intervention. Methods: The study population ( n = 387) comprised workers aged 16 to 65 years who required physiotherapy due to whiplash (ICD-9 847.0). The main outcome variable was the number of face-to-face sessions. The duration of sickness absence was also calculated. A survey was also conducted to determine patient acceptance and usability of the platform. The analyses were adjusted for sex, age, occupation, and the center where the physiotherapy treatment was administered. Results: The number of face-to-face physiotherapy sessions dropped significantly, from 9 to 7, due to the implementation of telerehabilitation. This decrease was not associated with a longer duration of sickness absence. The difference in the median duration of sickness absence between patients who had not undergone telerehabilitation and those who had undergone telerehabilitation was −1 [95% CI= (−6 to 2)]. Conclusion: Telerehabilitation reduces the number of face-to-face physiotherapy sessions needed, which can reduce the care burden in physiotherapy centers and avoid the need for patients to travel (with a corresponding reduction in transportation costs), without increasing the duration of sickness absence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".