Psychosocial support and care for children with special healthcare needs and their families: A scoping review for enhancing the care system
Bibliographic record
Abstract
BACKGROUND: Advances in medical technology have increased the identification of children with special healthcare needs (CSHCN), indicating the need to strengthen care systems. However, existing systematic reviews are outdated, over a decade old, and narrowly focused-primarily on hospital-based comprehensive care programs and family-centered care. This scoping review aimed to organize and integrate existing findings on care and support for CSHCN and their families from the available literature. METHODS: We employed an extensive search in December 2023, utilizing databases such as PubMed, Web of Science, CINAHL, ERIC, and The Cochrane Library. Selected articles were thoroughly reviewed, categorized, and organized by the type of care and support addressed. The findings of the included studies were organized and integrated descriptively. RESULTS: Following a comprehensive search and screening process, 49 articles were selected and categorized into 5 themes: care systems based on hospitals and other specialized institutions, specialized personnel or programs for care coordination/integrated care, support using telehealth technology to enhance and facilitate care, care aimed at reducing the psychological burden on the child and family, and peer and group support emphasizing the role of family and community. Publication years ranged from 1998 to 2023. The studies were conducted in 7 countries, predominantly in the United States, with additional studies from Canada, Australia, the United Kingdom, Japan, India, and Belgium. CONCLUSIONS: This study underscores the importance of establishing effective care systems that ensure continuous and smooth care coordination from multiple perspectives for the well-being of CSHCN and their families. To enhance support systems for the well-being of CSHCN and their families, it is necessary to pursue a multi-faceted approach that facilitates continuous and smooth care coordination from various perspectives.
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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 | 0.023 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.025 | 0.019 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 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".