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Record W3048317652 · doi:10.3389/fpsyt.2020.00785

Network Analyses of Maternal Pre- and Post-Partum Symptoms of Depression and Anxiety

2020· article· en· W3048317652 on OpenAlexaff
Desiree Y. Phua, Helen Chen, Yap Seng Chong, Peter D. Gluckman, Birit F. P. Broekman, Michael J. Meaney

Bibliographic record

VenueFrontiers in Psychiatry · 2020
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersMedical Research CouncilJacobs FoundationNational University Health SystemSingapore Institute for Clinical SciencesNational Medical Research CouncilHope for Depression Research Foundation
KeywordsAnxietyPregnancyFeelingPost partumMental healthPsychologyPsychiatryDepression (economics)OffspringDepressive symptomsClinical psychologyChildbirthMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Maternal mental health problems often develop prenatally and predict post-partum mental health. However, the circumstances before and following childbirth differ considerably. We currently lack an understanding of dynamic variation in the profiles of depressive and anxiety symptoms over the perinatal period. METHODS: Depressive and anxiety symptoms were self-reported by 980 women at 26-week pregnancy and 3 months post-partum. We used network analysis of depressive and anxiety symptoms to investigate if the symptoms network changed during and after pregnancy. The pre- and post-partum depressive-anxiety symptom networks were assessed for changes in structure, unique symptom-symptom interactions, central and bridging symptoms. We also assessed if central symptoms had stronger predictive effect on offspring's developmental outcomes outcomes at birth and 24, 54, and 72 months old than non-central symptoms. Bridging symptoms between negative and positive mental health were also assessed. RESULTS: Though the depressive-anxiety network structures were stable during and after pregnancy, the post-partum network was more strongly connected. The central depressive-anxiety symptoms were also different between prenatal and post-partum networks. During pregnancy, central symptoms were mostly related to feeling worthless or useless; after pregnancy, central symptoms were mostly related to feeling overwhelmed or being punished. Central symptoms during pregnancy were associated with poorer developmental outcomes for the child. Anxiety symptoms were strongest bridging symptoms during and after pregnancy. The interactions between negative and positive mental health symptoms were also different during and after pregnancy. CONCLUSIONS: The differences between pre- and post-partum networks suggest that the presentation of maternal mental health problems varies over the peripartum period. This variation is not captured by traditional symptom scale scores. The bridging symptoms also suggest that anxiety symptoms may precede the development of maternal depression. Interventions and public health policies should thus be tailored to specific pre- and post-partum symptom profiles.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.365
Teacher spread0.340 · 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 designSimulation or modeling
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

Citations39
Published2020
Admission routes1
Has abstractyes

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