Synchronous virtual care in children’s health care: a scoping review
Bibliographic record
Abstract
Objective: Synchronous virtual care comprises real-time, online-mediated healthcare. This approach has increasingly been used in pediatrics, largely implemented in the COVID-19 pandemic. Evidence is limited on the impacts of this mode of care delivery on patient and family experience and care quality. To our knowledge, this is the first scoping review to amalgamate existing knowledge about the perceived impact of synchronous virtual care as it is experienced by children and their families across multiple disciplines. Methods: Following guidance from the Joanna Briggs Institute, a search of the peer reviewed, published literature was conducted employing multiple databases: APA PsycInfo, CINAHL, EBSCO, Embase, and OVID. Reviewed articles were published in English from January 1, 2013 to December 31, 2023, and addressed virtual care for children and their families. The initial search generated 1,079 articles, which underwent abstract and then full-text screening. A total of 157 full text articles were screened, yielding 117 articles from which data was extracted. Results: Virtual care interventions, generally appearing in the last decade (2013-2023), have been largely studied using quantitative approaches. They tend to be positively viewed by youth and parents as indicated by identified benefits and general satisfaction. However, articles report both facilitating and hindering elements of virtual care, and barriers are reported that reflect inequities associated with social determinants of health. Such barriers are shown to impede the use of virtual care among some marginalized communities. The review indicates that effective virtual care approaches require (a) program/organizational infrastructure support, (b) training for both service providers and users, and (c) tailoring to clinical needs. Conclusion: Considering virtual care "fit" for target patients and families is important. Implications for clinical care as well as guidelines for future research are offered.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".