Keyword search (3,448 papers available)


Are MEDLINE searches sufficient for systematic reviews and meta-analyses of the diagnostic accuracy of depression screening tools? A review of meta-analyses

Author(s): Rice DB; Kloda LA; Levis B; Qi B; Kingsland E; Thombs BD;

Objective: Database searches for studies of diagnostic test accuracy are notoriously difficult to filter, highly resource-intensive, and a potential barrier to quality evidence synthesis. We examined published meta-analyses of depression screening tool accu...

Article GUID: 27411746

Effect of support group peer facilitator training programmes on peer facilitator and support group member outcomes: a systematic review

Author(s): Delisle VC; Gumuchian ST; Kloda LA; Boruff J; El-Baalbaki G; Körner A; Malcarne VL; Thombs BD;...

Objective: Peer facilitators play an important role in determining the success of many support groups for patients with medical illnesses. However, many facilitators do not receive...

Article GUID: 27856483

Reporting quality in abstracts of meta-analyses of depression screening tool accuracy: a review of systematic reviews and meta-analyses

Author(s): Rice DB; Kloda LA; Shrier I; Thombs BD;

Objective: Concerns have been raised regarding the quality and completeness of abstract reporting in evidence reviews, but this had not been evaluated in meta-analyses of diagnostic accuracy. Our objective was to evaluate reporting quality and completeness ...

Article GUID: 27864250

Depression Screening and Health Outcomes in Children and Adolescents: A Systematic Review

Author(s): Roseman M; Saadat N; Riehm KE; Kloda LA; Boruff J; Ickowicz A; Baltzer F; Katz LY; Patten SB; Rousseau C; Thombs BD;...

Objective: Depression screening among children and adolescents is controversial. In 2009, the United States Preventive Services Task Force first recommended routine depression screening for adolesc...

Article GUID: 28851234

Urban sprawl in Canada: Values in all 33 Census Metropolitan Areas and corresponding 469 Census Subdivisions between 1991 and 2011

Author(s): Pourali M; Townsend C; Kross A; Guindon A; Jaeger JAG;

The dataset presented here provides the degree of urban sprawl across 33 Census Metropolitan Areas (CMAs) in Canada of 2011 together with the 469 Census Subdivisions (CSDs) located within the 2011 boundaries of the CMAs, for the years 1991, 2001, and 2011. ...

Article GUID: 35242923

Overestimation of Postpartum Depression Prevalence Based on a 5-item Version of the EPDS: Systematic Review and Individual Participant Data Meta-analysis

Author(s): Thombs BD; Levis B; Lyubenova A; Neupane D; Negeri Z; Wu Y; Sun Y; He C; Krishnan A; Vigod SN; Bhandari PM; Imran M; Rice DB; Azar M; Chiovi...

Objective: The Maternal Mental Health in Canada, 2018/2019, survey reported that 18% of 7,085 mothers who recently gave birth reported "feelings consistent with postpartum depression" based on scor...

Article GUID: 33104415

Probability of Major Depression Classification Based on the SCID, CIDI, and MINI Diagnostic Interviews: A Synthesis of Three Individual Participant Data Meta-Analyses

Author(s): Wu Y; Levis B; Ioannidis JPA; Benedetti A; Thombs BD;

Introduction: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CID...

Article GUID: 32814337

A comparison of patient, intervention, comparison, outcome (PICO) to a new, alternative clinical question framework for search skills, search results, and self-efficacy: a randomized controlled trial.

Author(s): Kloda LA, Boruff JT, Cavalcante AS

J Med Libr Assoc. 2020 Apr;108(2):185-194 Authors: Kloda LA, Boruff JT, Cavalcante AS

Article GUID: 32256230

Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis

Author(s): Levis B; Benedetti A; Ioannidis JPA; Sun Y; Negeri Z; He C; Wu Y; Krishnan A; Bhandari PM; Neupane D; Imran M; Rice DB; Riehm KE; Saadat N; ...

Objectives: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores =10 are nonetheless often used to estimate depression prevalence. ...

Article GUID: 32105798

Probability of major depression diagnostic classification based on the SCID, CIDI and MINI diagnostic interviews controlling for Hospital Anxiety and Depression Scale - Depression subscale scores: An individual participant data meta-analysis of 73 primary studies

Author(s): Wu Y; Levis B; Sun Y; Krishnan A; He C; Riehm KE; Rice DB; Azar M; Yan XW; Neupane D; Bhandari PM; Imran M; Chiovitti MJ; Saadat N; Boruff J...

Objective: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or ...

Article GUID: 31911325

Group sample sizes in nonregulated health care intervention trials described as randomized controlled trials were overly similar

Author(s): Thombs BD; Levis AW; Azar M; Saadat N; Riehm KE; Sanchez TA; Chiovitti MJ; Rice DB; Levis B; Fedoruk C; Lyubenova A; Malo Vázquez de Lara AL...

Objectives: We evaluated whether sample sizes in different arms of two-arm parallel group randomized controlled trials of nonregulated interventions were systematically closer in size than would pl...

Article GUID: 31866472

Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta-analysis

Author(s): Levis B; McMillan D; Sun Y; He C; Rice DB; Krishnan A; Wu Y; Azar M; Sanchez TA; Chiovitti MJ; Bhandari PM; Neupane D; Saadat N; Riehm KE; I...

Objectives: A previous individual participant data meta-analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for dep...

Article GUID: 31568624

Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis

Author(s): Wu Y; Levis B; Riehm KE; Saadat N; Levis AW; Azar M; Rice DB; Boruff J; Cuijpers P; Gilbody S; Ioannidis JPA; Kloda LA; McMillan D; Patten S...

Background: Item 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most posit...

Article GUID: 31298180

Diagnostic accuracy of the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) for detecting major depression: protocol for a systematic review and individual patient data meta-analyses.

Author(s): Thombs BD, Benedetti A, Kloda LA, Levis B, Azar M, Riehm KE, Saadat N, Cuijpers P, Gilbody S, Ioannidis JP, McMillan D, Patten SB, Shrier I,...

BMJ Open. 2016 Apr 13;6(4):e011913 Authors: Thombs BD, Benedetti A, Kloda LA, Levis B, Azar M, Riehm KE, Saadat N, Cuijpers P, Gilbody S, Ioannidis JP, McMillan D, Patten SB, Shrier I, Steele RJ, ...

Article GUID: 27075844

Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews

Author(s): Levis B; Benedetti A; Riehm KE; Saadat N; Levis AW; Azar M; Rice DB; Chiovitti MJ; Sanchez TA; Cuijpers P; Gilbody S; Ioannidis JPA; Kloda L...

Background: Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully str...

Article GUID: 29717691

Shortening self-report mental health symptom measures through optimal test assembly methods: Development and validation of the Patient Health Questionnaire-Depression-4

Author(s): Ishihara M; Harel D; Levis B; Levis AW; Riehm KE; Saadat N; Azar M; Rice DB; Sanchez TA; Chiovitti MJ; Cuijpers P; Gilbody S; Ioannidis JPA;...

Background: The objective of this study was to develop and validate a short form of the Patient Health Questionnaire-9 (PHQ-9), a self-report questionnaire for assessing depressive symptomatology, ...

Article GUID: 30238571

Evaluation of Journal Registration Policies and Prospective Registration of Randomized Clinical Trials of Nonregulated Health Care Interventions

Author(s): Azar M; Riehm KE; Saadat N; Sanchez T; Chiovitti M; Qi L; Rice DB; Levis B; Fedoruk C; Levis AW; Kloda LA; Kimmelman J; Benedetti A; Thombs ...

Importance: Many interventions that are important to the health care of patients are not subject to regulation by the US Food and Drug Administration (FDA) or comparable regulatory bodies in other ...

Article GUID: 30855655


Title:Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis
Authors:Levis BBenedetti AIoannidis JPASun YNegeri ZHe CWu YKrishnan ABhandari PMNeupane DImran MRice DBRiehm KESaadat NAzar MBoruff JCuijpers PGilbody SKloda LAMcMillan DPatten SBShrier IZiegelstein RCAlamri SHAmtmann DAyalon LBaradaran HRBeraldi ABernstein CNBhana ABombardier CHCarter GChagas MHChibanda DClover KConwell YDiez-Quevedo CFann JRFischer FHGholizadeh LGibson LJGreen EPGreeno CGHall BJHaroz EEIsmail KJetté NKhamseh MEKwan YLara MALiu SILoureiro SRLöwe BMarrie RAMarsh LMcGuire AMuramatsu KNavarrete LOsório FLPetersen IPicardi APugh SLQuinn TJRooney AGShinn EHSidebottom ASpangenberg LTan PLLTaylor-Rowan MTurner Avan Weert HCVöhringer PAWagner LIWhite JWinkley KThombs BD
Link:https://pubmed.ncbi.nlm.nih.gov/32105798/
DOI:10.1016/j.jclinepi.2020.02.002
Category:J Clin Epidemiol
PMID:32105798
Dept Affiliation: LIBRARY
1 Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.
2 Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada; Respiratory Epidemiology and Clinical Research Unit, McGill University Health Centre, Montréal, Québec, Canada; Department of Medicine, McGill University, Montréal, Québec, Canada.
3 Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA; Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA; Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, CA, USA.
4 Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada.
5 Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada; Department of Psychiatry, McGill University, Montréal, Québec, Canada.
6 Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada; Department of Psychology, McGill University, Montréal, Québec, Canada.
7 Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada; Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
8 Schulich Library of Physical Sciences, Life Sciences, and Engineering, McGill University, Montréal, Québec, Canada.
9 Department of Clinical, Neuro and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
10 Hull York Medical School and the Department of Health Sciences, University of York, Heslington, NY, UK.
11 Library, Concordia University, Montréal, Québec, Canada.
12 Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
13 Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute and O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada.
14 Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada; Department of Family Medicine, McGill University, Montréal, Québec, Canada.
15 Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
16 Faculty of Medicine, King Abdulaziz University, Jeddah, Makkah, Saudi Arabia.
17 Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA.
18 Louis and Gabi Weisfeld School of Social Work, Bar Ilan University, Ramat Gan, Israel.
19 Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran; Ageing Clinical & Experimental Research Team, Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Scotland, UK.
20 Kbo-Lech-Mangfall-Klinik Garmisch-Partenkirchen, Klinik für Psychiatrie, Psychotherapie & Psychosomatik, Lehrkrankenhaus der Technischen Universität München, Munich, Germany.

Description:

Objectives: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores =10 are nonetheless often used to estimate depression prevalence. We compared PHQ-9 =10 prevalence to Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID) major depression prevalence and assessed whether an alternative PHQ-9 cutoff could more accurately estimate prevalence.

Study design and setting: Individual participant data meta-analysis of datasets comparing PHQ-9 scores to SCID major depression status.

Results: A total of 9,242 participants (1,389 SCID major depression cases) from 44 primary studies were included. Pooled PHQ-9 =10 prevalence was 24.6% (95% confidence interval [CI]: 20.8%, 28.9%); pooled SCID major depression prevalence was 12.1% (95% CI: 9.6%, 15.2%); and pooled difference was 11.9% (95% CI: 9.3%, 14.6%). The mean study-level PHQ-9 =10 to SCID-based prevalence ratio was 2.5 times. PHQ-9 =14 and the PHQ-9 diagnostic algorithm provided prevalence closest to SCID major depression prevalence, but study-level prevalence differed from SCID-based prevalence by an average absolute difference of 4.8% for PHQ-9 =14 (95% prediction interval: -13.6%, 14.5%) and 5.6% for the PHQ-9 diagnostic algorithm (95% prediction interval: -16.4%, 15.0%).

Conclusion: PHQ-9 =10 substantially overestimates depression prevalence. There is too much heterogeneity to correct statistically in individual studies.