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Record W2131938224 · doi:10.1037/a0034006

Common dyadic coping is indirectly related to dietary and exercise adherence via patient and partner diabetes efficacy.

2013· article· en· W2131938224 on OpenAlexaff
Matthew D. Johnson, Jared R. Anderson, Ann F. Walker, Allison R. Wilcox, Virginia L. Lewis, David C. Robbins

Bibliographic record

VenueJournal of Family Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of Alberta
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesGeorgia Clinical and Translational Science Alliance
KeywordsSpouseCoping (psychology)Diabetes mellitusStructural equation modelingPsychologyType 2 diabetesClinical psychologyMediationSocial supportSelf-efficacyMedicinePsychotherapistEndocrinology

Abstract

fetched live from OpenAlex

Using cross-sectional data from 117 married couples in which one member is diagnosed with type 2 diabetes, the current study sought to explore a possible indirect association between common dyadic coping and dietary and exercise adherence via the mechanism of patient and spouse reports of diabetes efficacy. Results from the structural equation model analysis indicated common dyadic coping was associated with higher levels of diabetes efficacy for both patients and spouses which, in turn, was then associated with better dietary and exercise adherence for the patient. This model proved a better fit to the data than three plausible alternative models. The bootstrap test of mediation revealed common dyadic coping was indirectly associated with dietary adherence via both patient and spouse diabetes efficacy, but spouse diabetes efficacy was the only mechanism linking common dyadic coping and exercise adherence. This study highlights the importance of exploring the indirect pathways through which general intimate relationship functioning might be associated with type 2 diabetes 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 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)0.000
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 score0.202
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.037
GPT teacher head0.384
Teacher spread0.347 · 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

Citations68
Published2013
Admission routes1
Has abstractyes

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