Views of Service Users, Their Family or Carers, and Health Care Professionals on Telerehabilitation for People With Neurological Conditions in Ghana: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Up to 50% of people in low- and middle-income countries do not receive the rehabilitation they require. Telerehabilitation has the potential to improve access to neurorehabilitation services especially in low- and middle-income countries. Although there are reports of the barriers and facilitators to telerehabilitation in such settings, almost all are anecdotal. Furthermore, family or carers have a significant influence on the adoption and success of telerehabilitation, but their views have not been reported. OBJECTIVE: This study aimed to investigate the views of service users, their family or carers, and health care professionals (HCPs) on telerehabilitation for people with neurological conditions in Ghana. METHODS: Two focus groups were held at Komfo Anokye Hospital in Kumasi, Ghana: one in person for service users (n=11) and their family or carers (n=9), conducted in the Ghanaian language of Twi, and one hybrid for HCPs (n=18) conducted in English. The mean (SD) age of the service users was 59.8 (8.6) years; 5 users had a stroke and 6 had Parkinson disease. The HCP group consisted of 7 speech and language therapists, 3 physiotherapists, 3 occupational therapists, 3 medical staff, 1 nurse, and 1 industry representative. Focus groups were semi-structured and explored previous experiences of telerehabilitation, perceived benefits and challenges, and solutions to overcome these challenges. Focus groups were audio transcribed, and the service user transcript was translated into English. The resulting transcripts were analyzed using thematic analysis. RESULTS: Overall, participants were positive about the role of telerehabilitation but recommended hybrid delivery, with in-person rehabilitation in the early stages and telerehabilitation in the later stages. In relation to telerehabilitation in Ghana, there were 3 main themes: benefits, challenges or barriers, and implementation. Benefits included the convenience and lower cost for service users, the higher dose of therapy possible, and increased access for people in remote areas. However, challenges included lack of a stable internet connection, cost of phones and data packages, and low levels of literacy. Implementation issues included cultural relevance, information governance, and the platform used to deliver telerehabilitation, with most participants being familiar with WhatsApp. CONCLUSIONS: Telerehabilitation has the potential to be a useful method of delivering rehabilitation to people with neurological conditions in Ghana, especially in a hybrid rehabilitation model with telerehabilitation augmenting in-person sessions. However, many people were unaware of telerehabilitation, and challenges such as a reliable internet connection, cultural relevance, and costs need to be addressed. Clinical trials of low-cost telerehabilitation interventions contextualized to the specific user group are required.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".