Effects of Social Isolation and Loneliness in Children with Neurodevelopmental Disabilities: A Scoping Review
Bibliographic record
Abstract
Loneliness and social isolation have negative consequences on physical and mental health in both adult and pediatric populations. Children with neurodevelopmental disabilities (NDD) are often excluded and experience more loneliness than their typically developing peers. This scoping review aims to identify the type of studies conducted in children with NDD to determine the effects of loneliness and/or social isolation. Three electronic databases (Ovid MEDLINE, EMBASE, PsychINFO) were searched from inception until 5 February 2019. Two independent reviewers screened the citations for inclusion and extracted data from the included articles. Quantitative (i.e., frequency analysis) and qualitative analyses (i.e., content analysis) were completed. From our search, 5768 citations were screened, 29 were read in full, and 12 were included. Ten were case-control comparisons with cross-sectional assessment of various outcomes, which limited inference. Autism spectrum disorder, attention-deficit/hyperactivity disorder, and learning disorder were the most commonly studied NDD. This review showed that loneliness among children with NDD was associated with negative consequences on mental health, behaviour, and psychosocial/emotional development, with a likely long-term impact in adulthood. Lack of research in this area suggests that loneliness is not yet considered a problem in children with NDD. More studies are warranted using prospective designs and a larger sample size with a focus on the dynamic aspect of loneliness development.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".