Evaluation of telephone and virtual visits for routine pediatric diabetes care during the COVID-19 pandemic
Bibliographic record
Abstract
To evaluate pediatric type 1 diabetes telehealth visits during the COVID-19 pandemic, with a focus on assessing the usability of these visits and gathering patient perspectives. An online survey, which included a validated telehealth usability questionnaire, was offered via email to families with a telephone or virtual visit since the COVID-19-related cancellation of routine in-person care. Survey data was linked with the British Columbia (BC) Clinical Diabetes Registry. Outcomes between groups were assessed using Welch’s t-test. Associations with type of visit as well as with desire to return to in-person care were assessed with logistic regression models. The response rate was 47%. Of 141 survey respondents, 87 had clinical data available in the BC Clinical Diabetes Registry, and thus were included in our analysis. Overall, telephone and virtual visits were rated highly for usability. Telephone visits were easier to learn to use, and simpler to understand; however, telephone and virtual visits were similar across multiple areas. No factors associated with choosing one type of visit over the other, or with desire to return to in-person care, could be identified. 72% of participants want future telehealth care; however, some would like all future care to be in-person. Telephone and virtual visits had impressive usability. Many families want telehealth to play a significant part in their future care.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".