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Record W4295270132 · doi:10.1002/nur.22250

Parenting styles and dimensions in parents of children with developmental disabilities

2022· article· en· W4295270132 on OpenAlexaff
Emma Marston, Chi C. Cho, Karen F. Pridham, Amy C. McPherson, Michele Polfuss

Bibliographic record

VenueResearch in Nursing & Health · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalToronto Rehabilitation InstituteUniversity of Toronto
FundersSpina Bifida Association
KeywordsParenting stylesPermissivePsychologyDevelopmental psychologyStyle (visual arts)AutismAutism spectrum disorderChild rearingSpina bifidaClinical psychologyMedicinePediatrics

Abstract

fetched live from OpenAlex

Parenting influences child development. There is limited research, however, related to parenting children who have developmental disabilities. The aims of this study were to: (1) describe the parenting styles and dimensions of parents of children with developmental disabilities and (2) assess differences in parenting styles and dimensions among parents of children with autism spectrum disorder (ASD), Down syndrome (DS), and spina bifida (SB). Secondary data analysis was conducted from a nationwide cross-sectional study of 496 parents of children aged 5-16 years with ASD (n = 180), DS (n = 156), or SB (n = 160). Parent scores indicated high use of the authoritative parenting style and associated parenting dimensions, mid-to-low use of the permissive parenting style, and low use of the authoritarian parenting style and associated dimensions. Variation in parenting styles and dimensions among parents was primarily related to the child's diagnosis and family income. An unanticipated but positive finding was that parents with lower family incomes had significantly higher scores for the authoritative parenting style. Results from this study can inform future research that might inform clinical practice.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.128
GPT teacher head0.473
Teacher spread0.346 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2022
Admission routes1
Has abstractyes

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