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Record W4286221866 · doi:10.3138/jmvfh-2022-0110

Mediating role of dyadic satisfaction on social support and health outcomes in a sample of military family caregivers

2022· article· en· W4286221866 on OpenAlexvenueno aff
Sherrie L. Wilcox

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2022
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSpousePsychologyMental healthAnxietySocial supportSample (material)Clinical psychologyDepressive symptomsSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

LAY SUMMARY Military family caregivers (MFCs) can experience many health-related challenges associated with caregiving responsibilities. Perceived support from a spouse or partner can influence dyadic satisfaction and health outcomes among those who care for a spouse or partner. This study examined the relations among social support, dyadic satisfaction, and mental (i.e., depressive and anxiety symptoms) and physical (i.e., somatic symptoms) health outcomes in a sample of MFCs. This sample consisted of 104 MFCs who were the spouse or partner of their care recipient. The findings indicate that more support predicted greater dyadic satisfaction and greater dyadic satisfaction predicted fewer anxiety symptoms. This study highlights the importance of considering relationship-focused contributors to mental health outcomes.

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)0.004
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 score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.046
GPT teacher head0.386
Teacher spread0.340 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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