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Record W2417734622 · doi:10.1037/a0039580

Relationship education and marital satisfaction in newlywed couples: A propensity score analysis.

2015· article· en· W2417734622 on OpenAlexafffund
Rebecca J. Cobb, Kieran T. Sullivan

Bibliographic record

VenueJournal of Family Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyRelationship educationDistressMultilevel modelPropensity score matchingMarital statusClinical psychologyDemographyDevelopmental psychologyMedicinePopulation

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate whether premarital relationship education and characteristics of relationship education in a community sample of newlywed couples predicted marital trajectories over 27 months. Newlywed couples (N = 191) completed measures of marital satisfaction 9 times over 27 months, and prior to marriage they provided information about relationship education and demographic, personal, and relationship risk factors for marital distress. Propensity scores (i.e., the probability of receiving relationship education) were estimated using the marital distress risk factors, and used to derive a matched sample of 72 couples who participated in relationship education and 86 couples who did not. Multilevel analyses of the propensity score matched sample (n = 158) indicated that wives who participated in relationship education had declines in marital satisfaction while wives who did not receive relationship education maintained satisfaction over time. Furthermore, the more hours of relationship education the couple participated in, the less steeply their marital satisfaction declined. Findings indicate that participation in community-based relationship education may not prevent declines in marital satisfaction for newlywed couples. A possible explanation is that the quality of relationship education available to couples is generally poor and could be greatly improved by inclusion of empirically based relationship information and skills training that are known to lead to stronger marriages.

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)0.001
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 score0.015
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.151
GPT teacher head0.445
Teacher spread0.294 · 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

Citations20
Published2015
Admission routes2
Has abstractyes

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