The Impact of Virtual Care on Health-Related Quality of Life in Pediatric Diabetes Mellitus: A Systematic Review
Bibliographic record
Abstract
Background: The COVID-19 pandemic has escalated the utilization of virtual care platforms in pediatric diabetes mellitus. The impact of these interventions on the health-related quality of life (HRQOL) is unclear. Objective: This systematic review evaluated the impact of virtual care, including eHealth and mHealth modalities, when compared to in-person care, on HRQOL in children with diabetes. Methods: , 2023. Randomized and non-randomized comparative studies were eligible for inclusion. Results: Thirteen studies were identified (12 randomized controlled trials, 1 cross-sectional study) involving 1566 children with type 1 diabetes mellitus (T1DM). The supplemental virtual care interventions utilized either web- or mobile-based platforms for intervention implementation. No interventions were detrimental to HRQOL, and a few improved the short-term HRQOL. No interventions worsened glycemic control. Patients and family's satisfaction with virtual care was high, perceiving it to be equal to or better than in-person care. There was no evidence for the use of virtual care and its effect on HRQOL in pediatric type 2 diabetes mellitus patients. Conclusion: Virtual care is associated with a stable or improved HRQOL and patient and family satisfaction in pediatric T1DM. Decision makers need to consider expanding virtual access to pediatric diabetes care that can improve equitable access to quality care across healthcare systems globally.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".