Knowledge, perceived benefits, perceived concerns, and predisposition to use telehealth services in Bangladesh: a cross-sectional survey
Bibliographic record
Abstract
Abstract Background Telehealth services are essential to expand healthcare coverage for all in the era of modern technology. Knowledge, willingness, and involvement with the service are also significantly important in the utilization of the service. This study investigated factors associated with knowledge, perceived benefits, perceived concerns, and predisposition to use telehealth services in Bangladesh. This web-based survey was conducted among 1266 adults in Bangladesh. Respondents were enrolled by following a convenience sampling technique. Results Demographic, telehealth service, and perceived health related information were significantly associated with respondents’ knowledge, perceived benefits, perceived concerns, and predispositions. The knowledge was significantly positively correlated with the perceived benefit ( p <0.05) and predisposition of telehealth ( p <0.05). Albeit, knowledge was significantly negatively correlated with perceived concerns of telehealth ( p <0.05). Conclusion The findings of the study may assist policymakers in implementing telehealth services by addressing the associated factors of knowledge, perceived benefits, perceived concerns, and predispositions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".