A systematic review of online parent-implemented interventions for children with neurodevelopmental disorders
Bibliographic record
Abstract
Kim M. Tan-MacNeilla, Isabel M. Smithabc, Shannon A. Johnsona, Jill Chorneyde & Penny Corkuma* a Department of Psychology & Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canadab Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canadac IWK Health Centre, Halifax, Nova Scotia, Canadad Paediatric Anaesthesia, IWK Health Centre, Halifax, New Brunswick, Canadae Anesthesia, Pain Management, and Perioperative Medicine, Dalhousie University, Nova Scotia, Halifax, CanadaCONTACT Penny Corkum penny.corkum@dal.ca Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada.ABSTRACTOnline parent-implemented interventions may increase treatment accessibility and reduce health care services burden by enabling parents of children with neurodevelopmental disorders (NDD) to implement treatments at home. This systematic review identified and evaluated the quality of evidence for the efficacy of online parent-implemented interventions for children with Autism Spectrum Disorder (ASD), Attention-Deficit/Hyperactivity Disorder (ADHD), Cerebral Palsy (CP), and Fetal Alcohol Spectrum Disorder (FASD). Twelve interventions were identified targeting a range of behaviors (ASD = 8, ADHD = 3, FASD = 1). Preliminary evidence suggests that online parent-implemented interventions are promising for children with these diagnoses, but require more rigorous, large-scale research as study quality was poor overall.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".