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Record W2312183341 · doi:10.1111/fare.12183

The Impact of Formal and Informal Support on Health in the Context of Caregiving Stress

2016· article· en· W2312183341 on OpenAlexaff
Jean‐Philippe Gouin, Chelsea da Estrela, Kim Desmarais, Erin T. Barker

Bibliographic record

VenueFamily Relations · 2016
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsSocial supportContext (archaeology)PsychologyAutism spectrum disorderAutismClinical psychologyGerontologyMedicineDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Caregiving stress increases risk for poor health. The overproduction of inflammatory markers is a core process contributing to this effect. In this study the authors investigated whether formal and informal social support act as protective factors against stress‐induced immune dysregulation. Fifty‐six parents of children with an autism spectrum disorder completed questionnaires on formal support services, informal social support, self‐rated health, and daily somatic symptoms, and they provided a blood sample for analysis of C‐reactive protein (CRP), a biomarker of inflammation. The results indicated that greater informal social support was associated with lower CRP and that a higher number of formal support services received by the family was related to better self‐rated health, fewer daily somatic symptoms, and lower CRP. Moreover, the impact of support services on the parents' CRP levels increased with child age. These findings highlight the role of formal and informal support in protecting the health of individuals facing caregiving stress across the life course.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.046
GPT teacher head0.384
Teacher spread0.339 · 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

Citations59
Published2016
Admission routes1
Has abstractyes

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