Family‐centred care interventions for children with chronic conditions: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Children with chronic conditions have greater health care needs than the general paediatric population but may not receive care that centres their needs and preferences as identified by their families. Clinicians and researchers are interested in developing interventions to improve family-centred care need information about the characteristics of existing interventions, their development and the domains of family-centred care that they address. We conducted a scoping review that aimed to identify and characterize recent family-centred interventions designed to improve experiences with care for children with chronic conditions. METHODS: We searched Medline, Embase, PsycInfo and Cochrane databases, and grey literature sources for relevant articles or documents published between 1 January 2019 and 11 August 2020 (databases) or 7-20 October 2020 (grey literature). Primary studies with ≥10 participants, clinical practice guidelines and theoretical articles describing family-centred interventions that aimed to improve experiences with care for children with chronic conditions were eligible. Following citation and full-text screening by two reviewers working independently, we charted data covering study characteristics and interventions from eligible reports and synthesized interventions by domains of family-centred care. RESULTS: Our search identified 2882 citations, from which 63 articles describing 61 unique interventions met the eligibility criteria and were included in this review. The most common study designs were quasiexperimental studies (n = 18), randomized controlled trials (n = 11) and qualitative and mixed-methods studies (n = 9 each). The most frequently addressed domains of family-centred care were communication and information provision (n = 45), family involvement in care (n = 37) and access to care (n = 30). CONCLUSION: This review, which identified 61 unique interventions aimed at improving family-centred care for children with chronic conditions across a range of settings, is a concrete resource for researchers, health care providers and administrators interested in improving care for this high-needs population. PATIENT OR PUBLIC CONTRIBUTION: This study was co-developed with three patient partner co-investigators, all of whom are individuals with lived experiences of rare chronic diseases as parents and/or patients and have prior experience in patient engagement in research (I. J., N. P., M. S.). These patient partner co-investigators contributed to this study at all stages, from conceptualization to dissemination.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 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".