Bibliographic record
Abstract
Telehealth coordinators practising in Canada were invited to respond to an online survey and participate in a telephone interview. For the present study, the definition of 'telehealth' was limited to the use of videoconferencing. The coordinators were recruited with the assistance of the Ontario Telemedicine Network (OTN) and the Canadian Telehealth Forum (CTF). The response rate to the online survey from the OTN cohort was 4% (n = 13) and from the CTF cohort was 36% (n = 34). Of the 47 people who completed the survey, 16 also participated in a telephone interview. Most respondents were female; their mean age was 40 years. Most telehealth coordinators had some form of post-secondary education. Most, 66% (n = 31) coordinated both clinical and educational videoconferences. About half of the telehealth coordinators (55%, n = 26) indicated that their job was dedicated solely to telehealth, although 32% (n = 15) reported that their jobs involved responsibilities outside telehealth. About half of the respondents worked full-time (51%, n = 24). Most respondents either strongly agreed or agreed with the statement that 'If a telehealth coordinator's role involves patient care then that individual should be a member of a regulated health profession'. The need for organizations to more clearly define the role, better recognize and support telehealth coordinators and develop mechanisms for continuing professional education and certification were recurrent themes in the interviews.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".