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Mood changes during pregnancy and the postpartum period: development of a biopsychosocial model

2004· article· en· W2068654225 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2004
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsHealth Sciences CentreWomen's College HospitalUniversity of TorontoSunnybrook Health Science Centre
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiopsychosocial modelPsychosocialMoodStructural equation modelingPregnancyPostpartum periodPsychologyClinical psychologyStressorAnxietyPostpartum depressionPsychiatryMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Women are vulnerable to mood changes during pregnancy and the postpartum period. We set out to empirically test the hypothesis that biological and psychosocial variables interact to result in this vulnerability. METHOD: Using structural equation modeling techniques, we developed an integrative model of perinatal mood changes from clinical, psychosocial, hormone and mood data collected from 150 women in late pregnancy and at 6-weeks postpartum. RESULTS: In the prenatal model, biological variables had no direct effect on depressive symptoms. However, they did act indirectly through their significant effects on psychosocial stressors and symptoms of anxiety. The same model did not fit the postpartum data, suggesting that different causal variables may be implicated in postpartum mood. CONCLUSION: This model demonstrates the importance of considering both biological and psychosocial variables in complex health conditions such as perinatal mood disorders.

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.

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)0.000
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 score0.447
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.278
Teacher spread0.263 · 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