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Record W2944559381 · doi:10.1080/01494929.2019.1610136

Marital quality and depression: a review

2019· review· en· W2944559381 on OpenAlexafffund
M.R. Goldfarb, Gilles Trudel

Bibliographic record

VenueMarriage & Family Review · 2019
Typereview
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversité du Québec à Montréal
FundersCanadian Institutes of Health Research
KeywordsModerationPsychologyDepression (economics)Association (psychology)Marital statusClinical psychologyLongitudinal studyDevelopmental psychologyGerontologyDemographySocial psychologyMedicinePopulationPsychotherapistSociology

Abstract

fetched live from OpenAlex

The present review examines (a) the published literature on the association between marital quality and depression in mixed-age groups, and (b) the association between these variables during later life. With regards to both issues, target studies were grouped into three categories: cross-sectional research, longitudinal research, and research on mediator and moderator variables. The main theoretical models that account for the relation between marital quality and depression are briefly presented. Whereas the evidence for a cross-sectional association between marital quality and depression seems robust, longitudinal research as well as research on mediator/moderator variables is less conclusive. This is particularly so vis-a-vis older adults, where studies are scarce. We conclude with suggestions for future research and the clinical implications of work in this area.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.203
GPT teacher head0.532
Teacher spread0.329 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations105
Published2019
Admission routes2
Has abstractyes

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