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Record W4292457537 · doi:10.21203/rs.3.rs-1897587/v1

Individual participant data meta-analysis to compare EPDS accuracy to detect major depression with and without the self-harm item

2022· preprint· en· W4292457537 on OpenAlexafffund
Xia Qiu, Yin Wu, Ying Sun, Brooke Levis, Jizhou Tian, Jill Boruff, Pim Cuijpers, John P. A. Ioannidis, Sarah Markham, Roy C. Ziegelstein, Simone N. Vigod, Andrea Benedetti, Brett D. Thombs

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsMcGill UniversityUniversity of TorontoJewish General Hospital
FundersFondo Nacional de Desarrollo Científico y TecnológicoNational Institute of Child Health and Human DevelopmentProgramme Grants for Applied ResearchFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchDuke Global Health Institute, Duke UniversityWerner Otto StiftungNational Center of Neurology and PsychiatryTrygFondenChina Medical UniversityMinistério da SaúdeChina Scholarship CouncilHarry Crossley FoundationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungDepartment of Families, Housing, Community Services and Indigenous AffairsJapan Society for the Promotion of ScienceConselho Nacional de Desenvolvimento Científico e TecnológicoUniversity of ConnecticutChulalongkorn UniversityPatrick and Catherine Weldon Donaghue Medical Research FoundationNational Research FoundationMyer FoundationUniversity of OxfordMedical Research CouncilDepartment of Health and Social CareFundação de Amparo à Pesquisa do Estado de Minas GeraisWellcome TrustUniversity of SouthamptonVetenskapsrådetAustralian GovernmentNational Health and Medical Research CouncilFundação de Amparo à Pesquisa do Estado de São PauloForskningsrådet för Arbetsliv och SocialvetenskapDivision of Materials ResearchNational Institute for Health and Care ResearchSvenska LäkaresällskapetAmerican Psychological AssociationNational Science Foundation
KeywordsEdinburgh Postnatal Depression ScalePsycINFOClinical psychologyMeta-analysisConfidence intervalMedicineBivariate analysisSuicidal ideationMEDLINEPsychologyPoison controlPsychiatryInjury preventionStatisticsDepressive symptomsMedical emergencyInternal medicineAnxiety

Abstract

fetched live from OpenAlex

Abstract Item 10 of the Edinburgh Postnatal Depression Scale (EPDS) is intended to assess thoughts of intentional self-harm but may also elicit concerns about accidental self-harm. It does not specifically address suicide ideation but, nonetheless, is sometimes used as an indicator of suicidality. The 9-item version of the EPDS (EPDS-9), which omits item 10, is sometimes used in research due to concern about positive endorsements of item 10 and necessary follow-up. We assessed the equivalence of total score correlations and screening accuracy to detect major depression using the EPDS-9 versus full EPDS among pregnant and postpartum women. A medical librarian searched Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science from database inception to October 3, 2018 for studies that administered the EPDS and conducted diagnostic classification for major depression based on a validated semi-structured or fully structured interview among women aged 18 or older during pregnancy or within 12 months of giving birth. We conducted an individual participant data meta-analysis. We calculated Pearson correlations with 95% prediction interval (PI) between EPDS-9 and full EPDS total scores using a random effects model. Bivariate random-effects models were fitted to assess screening accuracy. Equivalence tests were done by comparing the confidence intervals (CIs) around the pooled sensitivity and specificity differences to the equivalence margin of δ = 0.05. Individual participant data were obtained from 41 eligible studies (10,906 participants, 1,407 major depression cases). The correlation between EPDS-9 and full EPDS scores was 0.998 (95% PI 0.991, 0.999). For sensitivity, the EPDS-9 and full EPDS were equivalent for cut-offs 7 to 12 (difference range − 0.02, 0.01) and the equivalence was indeterminate for cut-offs 13 to 15 (all differences − 0.04). For specificity, the EPDS-9 and full EPDS were equivalent for all cut-offs (difference range 0.00, 0.01). The EPDS-9 performs similarly to the full EPDS.

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)0.042
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.082
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.062
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.388
GPT teacher head0.506
Teacher spread0.118 · 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.

Study designMeta-analysis
DomainMethods
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

Citations1
Published2022
Admission routes2
Has abstractyes

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