Evidence map›Paper›PMID 30518594›Full record

ArticleBMJ open2018

Diagnostic accuracy of the Geriatric Depression Scale-30, Geriatric Depression Scale-15, Geriatric Depression Scale-5 and Geriatric Depression Scale-4 for detecting major depression: protocol for a systematic review and individual participant data meta-analysis.

Andrea Benedetti, Yin Wu, Brooke Levis, Machelle Wilchesky, Jill Boruff, John P A Ioannidis, Scott B Patten, Pim Cuijpers, Ian Shrier, Simon Gilbody and 5 more

Abstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Excess mortality in depressive and anxiety disorders: The Lifelines Cohort Study.European psychiatry : the journal of the Association of European Psychiatrists · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Andrea BenedettiDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.
Yin WuDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.
Brooke LevisDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.
Machelle WilcheskyLady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada.
Jill BoruffSchulich Library of Science and Engineering, McGill University, Montreal, Quebec, Canada.
John P A IoannidisStanford Prevention Research Center, Department of Medicine, and Department of Health Research and Policy, Stanford School of Medicine, Stanford, California, USA.
Scott B PattenDepartment of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.
Pim CuijpersDepartment of Clinical, Neuro and Developmental Psychology and Amsterdam Public Health research institute, VU University Amsterdam, Amsterdam, The Netherlands.
Ian ShrierDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.
Simon GilbodyHull York Medical School and Department of Health Sciences, The University of York, York, UK.
Zahinoor IsmailDepartment of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.
Dean McMillanHull York Medical School and Department of Health Sciences, The University of York, York, UK.
Nicholas MitchellDepartment of Psychiatry, University of Alberta, Edmonton, Canada.
Roy C ZiegelsteinDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, USA.
Brett D ThombsDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.ORCID 0000-0002-5644-8432

Funding

CIHR
6 · The paper itself

Abstract

introductionThe 30-item Geriatric Depression Scale (GDS-30) and the shorter GDS-15, GDS-5 and GDS-4 are recommended as depression screening tools for elderly individuals. Existing meta-analyses on the diagnostic accuracy of the GDS have not been able to conduct subgroup analyses, have included patients already identified as depressed who would not be screened in practice and have not accounted for possible bias due to selective reporting of results from only better-performing cut-offs in primary studies. Individual participant data meta-analysis (IPDMA), which involves a standard systematic review, then a synthesis of individual participant data, rather than summary results, could address these limitations. The objective of our IPDMA is to generate accuracy estimates to detect major depression for all possible cut-offs of each version of the GDS among studies using different reference standards, separately and among participant subgroups based on age, sex, dementia diagnosis and care settings. In addition, we will use a modelling approach to generate individual participant probabilities for major depression based on GDS scores (rather than a dichotomous cut-off) and participant characteristics (eg, sex, age, dementia status, care setting). METHODS AND ANALYSIS: Individual participant data comparing GDS scores to a major depression diagnosis based on a validated structured or semistructured diagnostic interview will be sought via a systematic review. Data sources will include Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO and Web of Science. Bivariate random-effects models will be used to estimate diagnostic accuracy parameters for each cut-off of the different versions of the GDS. Prespecified subgroup analyses will be conducted. Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. ETHICS AND DISSEMINATION: The findings of this study will be of interest to stakeholders involved in research, clinical practice and policy. PROSPERO REGISTRATION NUMBER: CRD42018104329.

Indexed as

AgedAgingGeriatric AssessmentHumansMajor Depressive DisorderMeta-Analysis as TopicPsychiatric Status Rating ScalesSystematic Reviews as Topicdepressiongdsgeriatric depression scaleindividual participant data meta-analysis

Identifiers

PMID30518594
PMCPMC6286470

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.