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Record W4200521789 · doi:10.1002/imhj.21959

When the Bough Breaks: A systematic review and meta‐analysis of mental health symptoms in mothers of young children during the COVID‐19 pandemic

2021· review· en· W4200521789 on OpenAlexaff
Nicole Racine, Rachel Eirich, Jessica E. Cooke, Jenney Zhu, Paolo Pador, Nicole Dunnewold, Sheri Madigan

Bibliographic record

VenueInfant Mental Health Journal · 2021
Typereview
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsAnxietyDepression (economics)Mental healthPandemicMeta-analysisMedicineCoronavirus disease 2019 (COVID-19)Depressive symptomsDemographyPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

Parents have experienced considerable challenges and stress during the COVID-19 pandemic, which may impact their well-being. This meta-analysis sought to identify: (1) the prevalence of depression and anxiety in parents of young children (

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)0.020
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.051
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.038
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0030.002
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 head0.050
GPT teacher head0.386
Teacher spread0.336 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations107
Published2021
Admission routes1
Has abstractyes

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