The Impact of Virtual Care on Health-Related Quality of Life in Pediatric Diabetes Mellitus: A Systematic Review
Bibliographic record
Abstract
Raeesha Rajan,1– 4 Roman Dovbenyuk,1,2 Maya Kshatriya,1,2 Sezgi Yanikomeroglu,1,2,4 Laura Banfield,5 Uma Athale,1,6 Lehana Thabane,3,7– 9 M Constantine Samaan1,2,10,11 1Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada; 2Division of Pediatric Endocrinology, McMaster Children’s Hospital, Hamilton, Ontario, Canada; 3Department of Health Research Methodology, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada; 4Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; 5Health Sciences Library, McMaster University, Hamilton, Ontario, Canada; 6Division of Hematology Oncology, McMaster Children’s Hospital, Hamilton, Ontario, Canada; 7Department of Anesthesia, McMaster University, Hamilton, Ontario, Canada; 8Centre for Evaluation of Medicines, Hamilton, Ontario, Canada; 9Biostatistics Unit, St Joseph’s Healthcare-Hamilton, Hamilton, Ontario, Canada; 10Department of Pediatrics, Queen’s University, Kingston, Ontario, Canada; 11Division of Pediatric Endocrinology, Kingston Health Sciences Center, Kingston, Ontario, CanadaCorrespondence: M Constantine Samaan, Department of Pediatrics, Queen’s University, Kingston, Ontario, K7L 2V7, Canada, Tel +001-613-548-3232, Fax + 001-613-548-2453, Email constantine.samaan@queensu.caBackground: 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: MEDLINE, EMBASE, EMCare, PsycInfo, and Web of Science, ProQuest Dissertations and Theses A&I, and ClinicalTrials.gov databases and registries were searched from database inception to October 2nd, 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.Keywords: pediatric diabetes, health-related quality of life, virtual care
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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 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".