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Associations and costs of parental symptoms of psychiatric distress in a multi-diagnosis group of children with special needs

2011· article· en· W1952927524 on OpenAlexaff
Sandy Thurston, Louise Paul, Patricia Loney, C. Ye, Marian Y. L. Wong, Gina Browne

Bibliographic record

VenueJournal of Intellectual Disability Research · 2011
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcMaster UniversityOntario HIV Treatment Network
Fundersnot available
KeywordsPsychosocialDistressPsychiatryDisadvantagedMental healthMedicineSocial supportPsychologyClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Families supporting children with complex needs are significantly more distressed and economically disadvantaged than families of children without disability and delay. What is not known is the associations and costs of parental psychiatric distress within a multi-diagnosis group of special needs children. METHODS: In this cross-sectional survey, families were identified from the Children's Treatment Network. Families were eligible if the child was aged 0-19 years, resided in Simcoe/York, and if there were multiple family needs (n = 429). RESULTS: Some 42% of surveyed parents exhibited symptoms (mild to severe) of psychiatric distress. The presence of these symptoms was associated with reports of poorer social support, family dysfunction, greater adverse impact of the child's situation on the family, poorer child behaviour, unfavourable parenting styles and poorer child psychosocial functioning. The severity of the child's physical dysfunction was not related to parents/guardians most knowledgeable symptoms of psychiatric distress. Total parent costs were higher and children's uses of primary care services were higher in parents with symptoms of psychiatric distress. CONCLUSION: Parent symptoms of psychiatric distress are a significant societal concern in families with complex needs children. Children's rehabilitation efforts need to incorporate parental mental health assessment and treatment into existing programmes. This could lead to decreases in direct and indirect healthcare utilisation costs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.389
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), 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

Citations42
Published2011
Admission routes1
Has abstractyes

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