Sociotechnical Adaptation of Telerehabilitation in Rehabilitation Practice: Survey Among Rehabilitation Professionals
Bibliographic record
Abstract
Background: Both rehabilitation practice and rehabilitation professionals' work have been transformed by the adoption of different technological solutions. Sociotechnical theory can be used to analyze the adoption of technologies in rehabilitation practice. Objective: This study aimed to enhance the understanding of the sociotechnical perspective of telerehabilitation (TR) in rehabilitation practice, as well as the understanding of how sociotechnical frameworks can be used to examine the implementation of telerehabilitation in outpatient rehabilitation. Methods: A survey of rehabilitation professionals (N=629) was conducted in a Finnish outpatient rehabilitation setting. Data from 5 open-ended questions were analyzed using inductive, deductive, and abductive qualitative content analysis. An analysis matrix formed from the Fit between Individuals, Tasks, and Technology (FITT) and the Fit between Individuals, Tasks, Technology, and Environment (FITTE) frameworks was used. Results: Deductive analysis revealed that in individual-task fit, professionals' and clients' adequate skills, support for participation, and a positive attitude were essential. The task-technology fit highlighted the need for the professionals' familiarization, changes in methods and materials, and collaboration with clients and their close associates and networks. The individual-task fit revealed that professionals found TR tasks to be more complex than those in in-person practice and that TR increased professionals' perceived workload and clients' need for personal contact, especially during the familiarization phase. Our findings suggest that certain dimensions of the FITTE framework need to be specified in order to better understand the sociotechnical adaptation of TR. Conclusions: We propose an extension to create the Fit between Individual, Task, Technology, Interactive Sociotechnical Environment, and Organizational and Sociopolitical Context (FITTIO) framework, which provides conceptual tools for making contextual interpretations of the adoption of TR in rehabilitation settings. This study increases understanding of the sociotechnical nature of TR, which can be used in the adoption of technological solutions in rehabilitation practice.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".