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Record W4284972564 · doi:10.1177/0192513x221113850

Predictors of Relationship Satisfaction Across the Transition to Parenthood: Results from the Norwegian Mother, Father, and Child Cohort Study (MoBa)

2022· article· en· W4284972564 on OpenAlexafffund
Mila Kingsbury, Zahra M. Clayborne, Wendy Nilsen, Fartein Ask Torvik, Kristin Gustavson, Ian Colman

Bibliographic record

VenueJournal of Family Issues · 2022
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of Ottawa
FundersNorges ForskningsrådHelse- og OmsorgsdepartementetCanada Research Chairs
KeywordsPsychologyNorwegianMultinomial logistic regressionPsychological interventionCohortSocial supportLogistic regressionClinical psychologyDevelopmental psychologyDemographyMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

The purpose of the study was to describe trajectories of relationship satisfaction across the transition to parenthood, and identify predictors of these trajectories. This study is based on the Norwegian Mother, Father, and Child Cohort Study (MoBa). Mothers (N = 43,517) reported on their relationship satisfaction at five timepoints from 17 weeks gestation to 5 years postpartum, as well as sociodemographic, psychological, and behavioral covariates. Latent Trajectory Modeling revealed 5 trajectories of relationship satisfaction: “stable very high” (18.05%), “stable high” (43.47%); “stable moderate” (17.21%); “high falling” (3.38%); and “low falling” (4.02%). Predictors of group membership were identified using multinomial logistic regression. Significant predictors included unplanned pregnancy, maternal social support, maternal history of depression, maternal history of abuse, postnatal depression, financial stress, sexual satisfaction, and child negative emotionality. These results may help identify families at risk of declining relationship satisfaction, and aid in targeting interventions aimed at improving satisfaction during this vulnerable transition.

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 score0.023
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.030
GPT teacher head0.324
Teacher spread0.295 · 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

Citations9
Published2022
Admission routes2
Has abstractyes

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