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Record W4402905998 · doi:10.1016/j.jad.2024.09.144

The relationship of childhood maltreatment, adult sexual victimization, depressed mood and symptoms of trauma with fear of childbirth

2024· article· en· W4402905998 on OpenAlexafffundabout
Nichole Fairbrother, Cora Keeney, Yue Mao, Quincy M. Beck

Bibliographic record

VenueJournal of Affective Disorders · 2024
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsPsychologyMoodSexual abuseClinical psychologyChildbirthPsychiatryPoison controlInjury preventionMedicinePregnancyMedical emergency

Abstract

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Background: Fear of childbirth (FoB) is experienced to some degree by most pregnant people and can be intense enough to merit treatment. Despite significant research on the topic of FoB, studies investigating various forms of maltreatment and mental health symptoms in relation to FoB are very limited. In particular, studies including multiple forms of maltreatment along with mental health symptoms as predictors of FoB are extremely limited. We sought to fill this gap and clarify the relative contributions of these variables to the prediction of FoB. Methods: This was a secondary analysis of data from pregnant people in Canada. Participants ( N = 881) provided demographic and reproductive history information, completed self-report measures of FoB, childhood maltreatment (multiple forms), adult sexual victimization, depressed mood and symptoms of posttraumatic stress disorder (PTSD). They were also administered a diagnostic interview to assess for specific phobia, FoB. Analyses included descriptive information, Wilcoxon rank sum tests, linear and logistic regression, and path analysis. Results: Most forms of maltreatment showed some association with increased FoB. However, when assessed together, only emotional maltreatment remained a significant predictor of FoB. Both depressed mood and symptoms of PTSD contributed more to FoB than maltreatment, and mediated the relationship of emotional maltreatment with FoB. The only direct effects of childhood emotional maltreatment on FoB were for fears of medical interventions and feelings of embarrassment during labour and delivery. Limitations: Study findings fill significant gaps in our understanding of the relationship between maltreatment, mental health symptoms and FoB. However, the study sample was limited to Canadian participants, most of whom were socio-economically advantaged, cis-gender women of European descent, thus limiting the generalizability of the findings. Further, as childhood maltreatment and sexual assault experiences in adulthood were reported retrospectively, study findings are also vulnerable to recall bias. Conclusions: Findings contribute to our understanding of the relationship between childhood maltreatment, adult sexual victimization, mental health and FoB. These findings can facilitate future research and improved care via a focus on depressed mood, symptoms of PTSD, emotional maltreatment and specific fears of medical interventions and social discomfort as significant contributors to one's experience of FoB. • Fear of childbirth (FoB) can be clinically significant and interfere with functioning • We examined the associations between prior trauma, mental health, and FoB among pregnant people • Childhood motional maltreatment significantly predicted FoB, specifically fear of medical intervention and embarrassment during labour • Symptoms of depression and post-traumatic stress disorder mediated the relationship between emotional maltreatment and FoB • Depression and parity remained the strongest predictors of FoB from among study variables

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)0.005
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 score0.238
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.277
Teacher spread0.270 · 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".

Quick stats

Citations4
Published2024
Admission routes3
Has abstractyes

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