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Record W4401016946 · doi:10.3138/jcfs.54.4.05

Co-Rumination, Marital Satisfaction, and Depression: A Case of Married Men and Women in Pakistan

2024· article· en· W4401016946 on OpenAlexvenueno aff
Mohib Rehman, Ziarat Hossain

Bibliographic record

VenueJournal of Comparative Family Studies · 2024
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsRuminationPsychologyDepression (economics)DemographySociologyEconomicsPsychiatryCognition

Abstract

fetched live from OpenAlex

The current study examined co-rumination among married men and women and its influence on their reports of marital quality and depressive symptoms. Data were collected online through social media from 78 married men and 78 married women resulting in a total sample of 156 individuals residing in urban centers in Pakistan. Each participant had been married for at least one year, was at least 18 years old, and lived with their marital partner at the time of the survey. Although the results from multiple regression analyses revealed an increase in co-rumination was related to a decrease in the levels of depression, the moderating effect of the sex of participants indicated that the negative relationship between co-rumination and depression was only significant for married women. Furthermore, co-rumination was positively associated with marital relationship satisfaction. The findings suggest that that co-rumination with one’s spouse has implications for improved mental health and marital satisfaction among married men and women in Pakistani families.

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)0.002
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 score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.054
GPT teacher head0.478
Teacher spread0.424 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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