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Record W2021494948 · doi:10.1016/j.jmwh.2008.07.003

Postpartum Depression and Help‐Seeking Behavior

2008· article· en· W2021494948 on OpenAlexaff
Joanne McGarry, Han Kim, Xiaoming Sheng, Marlene J. Egger, Laurie Baksh

Bibliographic record

VenueJournal of Midwifery & Women s Health · 2008
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of Alberta
FundersNational Center for Chronic Disease Prevention and Health Promotion
KeywordsMedicineOdds ratioDepression (economics)Psychological interventionPregnancyPostpartum depressionConfidence intervalOddsDemographyDomestic violenceHelp-seekingPsychiatrySuicide preventionPoison controlMental healthLogistic regressionEnvironmental health

Abstract

fetched live from OpenAlex

The objective of this analysis was to investigate the demographic differences between women who report postpartum depression symptoms (PPDS) and seek help versus those who report symptoms but who do not seek help, using data from the Utah Pregnancy Risk Assessment Monitoring System (PRAMS) 2004 dataset. Overall, 14.7% of Utah women reported experiencing PPDS in 2004. Sixty percent of the women who reported having PPDS did not seek help. Seeking help for depression during pregnancy was associated with help-seeking behavior postpartum (adjusted odds ratio [aOR] = 0.1; 95% confidence interval [CI], 0.04-0.2). Other factors associated with seeking help included having an infant admitted to the intensive care unit (aOR = 0.4; 95% CI, 0.2-0.9) and rural residency (aOR = 0.3; 95% CI, 0.2-0.7). Nonwhite women were 12.1 times (95% CI, 3.0-48.5) more likely to not seek help for depression compared to white women. Further, Hispanic women (aOR = 3.2; 95% CI, 1.3-8.1) and women who experienced emotional abuse had increased odds of not seeking help (aOR = 2.9; 95% CI, 1.3-6.2). Nearly 15% of Utah women in this study reported PPDS, yet fewer than half sought help. Target populations, such as nonwhite, Hispanic, emotionally abused, and urban women, have been identified for public health interventions.

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 score0.020
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.028
GPT teacher head0.313
Teacher spread0.284 · 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

Citations126
Published2008
Admission routes1
Has abstractyes

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