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Record W2925151916 · doi:10.1111/dmcn.14206

Health coaching for parents of children with developmental disabilities: a systematic review

2019· review· en· W2925151916 on OpenAlexafffund
Tatiana Ogourtsova, Maureen O’Donnell, Annette Majnemer

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2019
Typereview
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMontreal Children's HospitalMcGill UniversityUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsCoachingIntervention (counseling)AutismPsychologyHealth coachingAutism spectrum disorderPopulationMedicineRandomized controlled trialClinical psychologyDevelopmental psychologyPsychiatryPsychotherapistEnvironmental health

Abstract

fetched live from OpenAlex

AIM: To determine the level of evidence on the effectiveness of health coaching for parents of children with disabilities. METHOD: A systematic review approach, comprised of a comprehensive, librarian-guided literature search; transparent study selection and data extraction; quality assessment; and synthesis of sufficiently similar data (per population, intervention nature, and overall level of evidence for each outcome using standard definitions) was undertaken. RESULTS: Twenty-eight studies (13 randomized clinical trials) were included. Three health coaching approaches were identified: child-targeted (most commonly applied), parent-targeted, and a mixed approach. Overall, there is an insufficient-to-limited level of evidence regarding the effectiveness of these approaches. INTERPRETATION: High-quality clinical trials using the parent-targeted coaching approach are warranted. WHAT THIS PAPER ADDS: Health coaching parents of children with disabilities is an emergent practice. Child-targeted, parent-targeted, or mixed health coaching approaches exist. The child-targeted health coaching approach is currently most applied. Parents of children with autism spectrum disorder are the most common recipients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.099
GPT teacher head0.408
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations43
Published2019
Admission routes2
Has abstractyes

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