The beliefs of Senegal’s physicians toward the use of telemedicine
Bibliographic record
Abstract
INTRODUCTION: Telemedicine is seen as a potential solution to improve access to specialist services in underserved areas, but using telemedicine depends on physicians' beliefs regarding its use. Applying the theory of planned behaviour, there are three kinds of beliefs of relevance: behavioural, normative and control beliefs. This study aimed to determine the behavioural, normative and control beliefs of Senegal's physicians regarding the use of telemedicine. METHODS: A qualitative descriptive study involving individual interviews with physicians was conducted between January and June 2014. It included 32 physicians working in public hospitals and 37 physicians working in district health centres. Interviews were taped, transcribed and their content coded thematically using the NVivo 10 software. RESULTS: The most significant positive behavioural belief was that telemedicine makes experts' opinions accessible despite distance; the most important negative behavioural belief was that telemedicine can lead to medical errors. The positive normative belief mentioned most was that patients approve the use of telemedicine, but the negative normative belief mentioned most was that the patients would not approve it. The prevailing positive control belief was that physicians will use telemedicine if it is easy to use and the most cited negative control belief was that physicians will not use telemedicine if they have insufficient time. CONCLUSION: The results of this study provide a better understanding of the beliefs of Senegal's physicians regarding telemedicine, which can help in designing interventions to promote its use. Such interventions may help improve access to healthcare in rural areas.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".