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Record W3181316824 · doi:10.1186/s12889-021-11385-5

Testing the effects of a prenatal depression preventive intervention on parenting and young children’s self-regulation and functioning (EPIC): protocol for a longitudinal observational study

2021· article· en· W3181316824 on OpenAlexaff
Alicia Diebold, Jessica K. Johnson, Marianne Brennan, Jody D. Ciolino, Amélie Petitclerc, Lauren S. Wakschlag, Craig F. Garfield, Chen Yeh, Aiko E. Lovejoy, Dana Zakieh, S. Darius Tandon

Bibliographic record

VenueBMC Public Health · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversité Laval
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Institutes of HealthNorthwestern University
KeywordsObservational studyMedicinePsychological interventionPublic healthBiostatisticsIntervention (counseling)Postpartum depressionMental healthDepression (economics)Longitudinal studyRandomized controlled trialPsychiatryClinical psychologyPregnancyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Perinatal depression is a pervasive public health concern that disproportionately affects low-income women and can have negative impacts on parenting and child developmental outcomes. Few interventions focus on preventing perinatal depression. Previous studies suggest that Mothers and Babies is efficacious in preventing the worsening of depressive symptoms and the onset of postpartum depression. This manuscript presents the protocol of the EPIC study (Effects of a Prenatal Depression Preventive Intervention on parenting and young children's Self-Regulation and Functioning) to test the effects of Mothers and Babies on parenting and child developmental outcomes through 54 months postpartum. EPIC is an observational study that builds on a completed cluster-randomized trial (CRT). Innovations of this study are direct observations of a subsample of mother-child dyads and the inclusion of fathers/caregivers' variables as moderators of maternal mental health. METHODS: For this study, we plan to enroll 738 women with children under 30 months old, ≥18 years old, and who speak English or Spanish. Additionally, 429 fathers, partners, or other adult caregivers will be recruited through women participating in the study. Women will be recruited through the parent study (intervention and control participants) or through one of 10 home visiting programs in Illinois (control participants). Data collection will take place through maternal self-report at five time points (when the child is 30, 36, 42, 48, and 54 months), paternal self-report at three time points (when the child is 30, 42, and 54 months), and through mother-child observations at three time points (when the child is 36, 42, and 48 months). Outcome domains include maternal mental health, cognitive-behavioral and parenting skills, and child self-regulation and functioning. Moderators include the contributions of fathers/caregivers, race-ethnicity, and socioeconomic disadvantage. Power and sample size were calculated assuming a two-sided 5% type I error rate and assumed analyses on the individual level. DISCUSSION: This study has several key strengths and innovations, as well as great potential significance to influence the long-term trajectories of parenting and child development via prenatal intervention. TRIAL REGISTRATION: The study was retrospectively registered at ClinicalTrials.gov (Identifier: NCT04296734 ) on March 5, 2020.

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)0.038
metaresearch head score (Gemma)0.035
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.038
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.035
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0020.003
Science and technology studies0.0060.002
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0340.008

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 head0.092
GPT teacher head0.377
Teacher spread0.285 · 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
GenreProtocol

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
Published2021
Admission routes1
Has abstractyes

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