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Record W4416736273 · doi:10.1186/s12884-025-07933-1

Associated factors of barriers to help-seeking among postpartum women with and without (childbirth-related) posttraumatic stress disorder: results from the cross-sectional study INVITE

2025· article· en· W4416736273 on OpenAlexaff
Lara Seefeld, Julia Schellong, Susan Garthus‐Niegel

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsDalhousie University
FundersDeutsche Forschungsgemeinschaft
KeywordsPsychoeducationShamePosttraumatic stressEmpathyReproductive medicineMental healthSocial supportPostpartum periodCompassion fatigue

Abstract

fetched live from OpenAlex

BACKGROUND: Mental health disorders are widespread during the postpartum period, yet only a minority of affected women seek professional help for their symptoms. While prior studies have explored barriers to help-seeking, certain factors yielded inconsistent results. Our study aimed to investigate whether these factors do not serve as barriers themselves, but rather as predictors of barrier formation. Given the limited previous research on postpartum women affected by posttraumatic stress disorder (PTSD), we examined those affected by childbirth-related PTSD (CB-PTSD) and general PTSD (gPTSD). METHODS: We used data from the cross-sectional study INVITE (INtimate partner VIolence care and Treatment prEferences in postpartum women). For this study, a total of N = 3,874 postpartum women were inquired about their mental health status and barriers keeping them from seeking help. We categorized these women into three distinct groups: (1) women affected by CB-PTSD, (2) women affected by gPTSD, and (3) non-affected women. For each group, we conducted multiple linear regression analyses to examine whether certain factors (self-report of PTSD, knowledge of healthcare services, previous help-seeking, social support, severity of symptoms, and household net income) are associated with previously identified barriers to help-seeking. RESULTS: Our findings revealed that higher social support predicted lower barriers to help-seeking, particularly among women with gPTSD. Self-reporting PTSD predicted lower barriers among women with CB-PTSD. Previous help-seeking predicted lower barriers among women with CB-PTSD, but higher barriers among those with gPTSD. Greater knowledge of healthcare services predicted lower barriers for non-affected women, but higher barriers for women with CB-PTSD. A higher household net income predicted lower barriers only among non-affected women. We found no association between symptom severity and barriers to help-seeking. CONCLUSIONS: High levels of social support and self-report of postpartum PTSD emerge as crucial elements in reducing women's barriers to help-seeking. Strengthening these factors can be achieved by providing psychoeducation to women and their social surroundings, equipping them to identify symptoms and respond accordingly. Moreover, implementing PTSD screenings for all postpartum women may facilitate symptom recognition, thereby reducing barriers to help-seeking. Additionally, educational campaigns could help to reduce stigmatization and shame associated with postpartum mental health disorders within the society, fostering greater understanding and empathy for affected women.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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 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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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