A study of a rural community's readiness for telehealth
Bibliographic record
Abstract
A qualitative approach was used to explore the readiness of a rural community for the implementation of telehealth services. There were four domains of interest: patient, practitioner, public and organization. Sixteen semistructured telephone interviews (three to five in each domain) were carried out with key informants and recorded on audio-tape. Two community awareness sessions were held, which were followed by five audio-taped focus groups (with five to eight people in each) in the practitioner, patient and public domains. In addition, two in-depth interviews were conducted with community physicians. Analysis of the data suggested that there were four types of community readiness: core, engagement, structural and non-readiness. The level of readiness varied across domains. There were six main themes: core readiness; structural readiness; projection of benefits; assessment of risk; awareness and education; and intra-group and inter-group dynamics. The results of the study can be used to investigate the readiness of rural and remote communities for telehealth, which should improve the chance of successful implementation.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".