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Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis
Brooke Levis, Andrea Benedetti, John P. A. Ioannidis, Ying Sun, Zelalem Negeri, Chen He, Yin Wu, Ankur Krishnan, Parash Mani Bhandari, Dipika Neupane, Mahrukh Imran, Danielle B. Rice, Kira E. Riehm, Nazanin Saadat, Marleine Azar, Jill Boruff, Pim Cuijpers, Simon Gilbody, Lorie A. Kloda, Dean McMillan, Scott B. Patten, Ian Shrier, Roy C. Ziegelstein, Sultan H. Alamri, Dagmar Amtmann, Liat Ayalon, Hamid Reza Baradaran, Anna Beraldi, Çharles N. Bernstein, Arvin Bhana, Charles H. Bombardier, Gregory Carter, Marcos Hortes Nisihara Chagas, Dixon Chibanda, Kerrie Clover, Yeates Conwell, Crisanto Díez, Jesse R. Fann, Felix Fischer, Leila Gholizadeh, Lorna J. Gibson, Eric Green, Catherine G. Greeno, Brian J. Hall, Emily E. Haroz, Khalida Ismail, Nathalie Jetté, Mohammad E. Khamseh, Yunxin Kwan, Ma. Asunción Lara, Shen-Ing Liu, Sônia Regina Loureiro, Bernd Löwe, Ruth Ann Marrie, Laura Marsh, Anthony McGuire, Kumiko Muramatsu, Laura Navarrete, Flávia de Lima Osório, Inge Petersen, Angelo Picardi, Stephanie L. Pugh, Terence J. Quinn, Alasdair G Rooney, Eileen H. Shinn, Abbey Sidebottom, Lena Spangenberg, Pei Lin Lynnette Tan, Martin Taylor‐Rowan, Alyna Turner, Henk van Weert, Paul A. Vöhringer, Lynne I. Wagner, Jennifer White, Kirsty Winkley, Brett D. Thombs
Bibliographic record
VenueJournal of Clinical Epidemiology · 2020
Typereview
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of ManitobaMcGill UniversityUniversity of CalgaryConcordia UniversityMcGill University Health CentreOntario Brain InstituteJewish General Hospital
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteMedical Research CouncilFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchH. Lundbeck A/SMinisterio de Economía, Fomento y Turismo, ChileAlberta Health ServicesCrohn's and Colitis CanadaMultiple Sclerosis SocietyUniversidade de São PauloNational Health Research InstitutesUniversidade de MacauUniversiteit StellenboschMcGill UniversityConselho Nacional de Desenvolvimento Científico e TecnológicoAgency for Healthcare Research and QualityMinistero della SaluteAlberta Innovates - Health SolutionsHealth Resources and Services AdministrationDepartment for International DevelopmentBundesministerium für Bildung und ForschungPennsylvania Department of HealthCumming School of Medicine, University of CalgaryUniversity of Technology SydneyAlberta InnovatesNational Institute for Health and Care ResearchHotchkiss Brain InstituteUniversiteit van AmsterdamUniversität HeidelbergNational Center for Research ResourcesNational Institute of General Medical SciencesDuke Global Health Institute, Duke UniversityCenters for Disease Control and PreventionNational Center for Medical Rehabilitation ResearchUnited States Agency for International DevelopmentGrand Challenges CanadaAcademisch Medisch CentrumBanco SantanderTehran University of Medical Sciences and Health ServicesResearch ManitobaNational Institute on Disability and Rehabilitation ResearchUniversity of WashingtonPfizerFaculty of Medicine, McGill UniversityMcGill University Health CentreLance Armstrong FoundationGovernment of the United KingdomWilliamsUniversity of MichiganEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentU.S. Department of Health and Human ServicesNational Institute of Mental HealthHunter Medical Research InstituteProgramme Grants for Applied ResearchHealth ResearchConsejo Nacional de Ciencia y TecnologíaZonMwNational Multiple Sclerosis Society
KeywordsPatient Health QuestionnaireMedicineConfidence intervalDepression (economics)Meta-analysisPrevalenceEpidemiologyInternal medicinePsychiatryDepressive symptomsAnxiety
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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)0.040
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
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 score0.981
Threshold uncertainty score0.213
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.079 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 head0.886
GPT teacher head0.699
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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
Citations208
Published2020
Admission routes2
Has abstractno