Physiotherapists' perceptions and experiences of home-based rehabilitation in Libya: a qualitative study
Bibliographic record
Abstract
INTRODUCTION: home-based rehabilitation (HBR) is a rehabilitation model that aims to help people with disabilities to integrate into the community and be independent as much as possible. HBR is a promising alternative to institution-based rehabilitation, in which rehabilitation services are provided at patients' homes. However, challenges and barriers to HBR practice in Libya have never been researched before. This study explores physiotherapists' perceptions of home-based rehabilitation (HBR) in Libya and examines their views and the concerns they face. METHODS: eight physiotherapists (2 females, 6 males) with at least two years of work experience in the Libyan physiotherapy community participated in in-depth semi-structured interviews. The interviews were audio-recorded and transcribed verbatim, and the data were analyzed using framework method. RESULTS: three themes emerged from the data, namely: i) access problems, including lack of infrastructure; ii) lack of governmental policies, such as the absence of governmental support (e.g., lack of programs and resources); iii) poor awareness and misconception issues, including that of patients and families. CONCLUSION: although all the interviewed physiotherapists described HBR as an essential practice in Libya, they expressed concerns about several factors that hinder its development and may influence the quality of interventions provided in the community. Given the fact that this is the first qualitative study in this field in Libya, there is a need for future research to explore HBR from other perspectives, such as those of policymakers, healthcare planners, or patients and their families and/or caregivers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".