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Record W2969171571 · doi:10.1111/jftr.12341

Paternal Depressive Symptoms and Marital Quality: A Meta‐Analysis of Cross‐Sectional Studies

2019· article· en· W2969171571 on OpenAlexafffund
Kristene Cheung, Jennifer Theule, Diane Hiebert‐Murphy, Caroline C. Piotrowski

Bibliographic record

VenueJournal of Family Theory & Review · 2019
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDepression (economics)Meta-analysisDepressive symptomsPsychologyClinical psychologyMarital relationshipCross-sectional studyQuality (philosophy)Marital statusAssociation (psychology)MedicinePsychiatryCognitionPopulationEnvironmental health

Abstract

fetched live from OpenAlex

Paternal depression is typically negatively associated with marital quality; however, the magnitude of the relationship varies across studies. The objectives of this study were to clarify the strength of the association and explore whether study‐specific factors moderate the strength of the relationship. The present meta‐analysis consisted of 42 studies that included a quantitative comparison between concurrent paternal depressive symptoms and marital quality. Overall, the relationship between paternal depressive symptoms and father ratings of marital quality and mother ratings of marital quality were significant. None of the explored moderators were significant. The findings of this study suggested that clinicians should be mindful of the link between paternal depression and marital quality. Clinical implications and future research directions are discussed.

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)0.013
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.019
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.135
GPT teacher head0.506
Teacher spread0.371 · 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 designMeta-analysis
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

Citations15
Published2019
Admission routes2
Has abstractyes

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