Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review

Abstract Background Depression symptom questionnaires are commonly used to assess symptom severity and as screening tools to identify patients who may have depression. They are not designed to ascertain diagnostic status and, based on published sensitivity and specificity estimates, would theoretica...

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Main Authors: Brooke Levis, Xin Wei Yan, Chen He, Ying Sun, Andrea Benedetti, Brett D. Thombs
Format: Article
Language:English
Published: BMC 2019-03-01
Series:BMC Medicine
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12916-019-1297-6
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spelling doaj-79297e3eb46942d9a70bda4e01aaa6ab2020-11-25T01:39:23ZengBMCBMC Medicine1741-70152019-03-0117111010.1186/s12916-019-1297-6Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research reviewBrooke Levis0Xin Wei Yan1Chen He2Ying Sun3Andrea Benedetti4Brett D. Thombs5Lady Davis Institute for Medical Research, Jewish General HospitalLady Davis Institute for Medical Research, Jewish General HospitalLady Davis Institute for Medical Research, Jewish General HospitalLady Davis Institute for Medical Research, Jewish General HospitalDepartment of Epidemiology, Biostatistics and Occupational Health, McGill UniversityLady Davis Institute for Medical Research, Jewish General HospitalAbstract Background Depression symptom questionnaires are commonly used to assess symptom severity and as screening tools to identify patients who may have depression. They are not designed to ascertain diagnostic status and, based on published sensitivity and specificity estimates, would theoretically be expected to overestimate prevalence. Meta-analyses sometimes estimate depression prevalence based on primary studies that used screening tools or rating scales rather than validated diagnostic interviews. Our objectives were to determine classification methods used in primary studies included in depression prevalence meta-analyses, if pooled prevalence differs by primary study classification methods as would be predicted, whether meta-analysis abstracts accurately describe primary study classification methods, and how meta-analyses describe prevalence estimates in abstracts. Methods We searched PubMed (January 2008–December 2017) for meta-analyses that reported pooled depression prevalence in the abstract. For each meta-analysis, we included up to one pooled prevalence for each of three depression classification method categories: (1) diagnostic interviews only, (2) screening or rating tools, and (3) a combination of methods. Results In 69 included meta-analyses (81 prevalence estimates), eight prevalence estimates (10%) were based on diagnostic interviews, 36 (44%) on screening or rating tools, and 37 (46%) on combinations. Prevalence was 31% based on screening or rating tools, 22% for combinations, and 17% for diagnostic interviews. Among 2094 primary studies in 81 pooled prevalence estimates, 277 (13%) used validated diagnostic interviews, 1604 (77%) used screening or rating tools, and 213 (10%) used other methods (e.g., unstructured interviews, medical records). Classification methods pooled were accurately described in meta-analysis abstracts for 17 of 81 (21%) prevalence estimates. In 73 meta-analyses based on screening or rating tools or on combined methods, 52 (71%) described the prevalence as being for “depression” or “depressive disorders.” Results were similar for meta-analyses in journals with impact factor ≥ 10. Conclusions Most meta-analyses combined estimates from studies that used screening tools or rating scales instead of diagnostic interviews, did not disclose this in abstracts, and described the prevalence as being for “depression” or “depressive disorders ” even though disorders were not assessed. Users of meta-analyses of depression prevalence should be cautious when interpreting results because reported prevalence may exceed actual prevalence.http://link.springer.com/article/10.1186/s12916-019-1297-6DepressionPrevalenceMeta-analysisClassification methodsTransparency
collection DOAJ
language English
format Article
sources DOAJ
author Brooke Levis
Xin Wei Yan
Chen He
Ying Sun
Andrea Benedetti
Brett D. Thombs
spellingShingle Brooke Levis
Xin Wei Yan
Chen He
Ying Sun
Andrea Benedetti
Brett D. Thombs
Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review
BMC Medicine
Depression
Prevalence
Meta-analysis
Classification methods
Transparency
author_facet Brooke Levis
Xin Wei Yan
Chen He
Ying Sun
Andrea Benedetti
Brett D. Thombs
author_sort Brooke Levis
title Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review
title_short Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review
title_full Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review
title_fullStr Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review
title_full_unstemmed Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review
title_sort comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review
publisher BMC
series BMC Medicine
issn 1741-7015
publishDate 2019-03-01
description Abstract Background Depression symptom questionnaires are commonly used to assess symptom severity and as screening tools to identify patients who may have depression. They are not designed to ascertain diagnostic status and, based on published sensitivity and specificity estimates, would theoretically be expected to overestimate prevalence. Meta-analyses sometimes estimate depression prevalence based on primary studies that used screening tools or rating scales rather than validated diagnostic interviews. Our objectives were to determine classification methods used in primary studies included in depression prevalence meta-analyses, if pooled prevalence differs by primary study classification methods as would be predicted, whether meta-analysis abstracts accurately describe primary study classification methods, and how meta-analyses describe prevalence estimates in abstracts. Methods We searched PubMed (January 2008–December 2017) for meta-analyses that reported pooled depression prevalence in the abstract. For each meta-analysis, we included up to one pooled prevalence for each of three depression classification method categories: (1) diagnostic interviews only, (2) screening or rating tools, and (3) a combination of methods. Results In 69 included meta-analyses (81 prevalence estimates), eight prevalence estimates (10%) were based on diagnostic interviews, 36 (44%) on screening or rating tools, and 37 (46%) on combinations. Prevalence was 31% based on screening or rating tools, 22% for combinations, and 17% for diagnostic interviews. Among 2094 primary studies in 81 pooled prevalence estimates, 277 (13%) used validated diagnostic interviews, 1604 (77%) used screening or rating tools, and 213 (10%) used other methods (e.g., unstructured interviews, medical records). Classification methods pooled were accurately described in meta-analysis abstracts for 17 of 81 (21%) prevalence estimates. In 73 meta-analyses based on screening or rating tools or on combined methods, 52 (71%) described the prevalence as being for “depression” or “depressive disorders.” Results were similar for meta-analyses in journals with impact factor ≥ 10. Conclusions Most meta-analyses combined estimates from studies that used screening tools or rating scales instead of diagnostic interviews, did not disclose this in abstracts, and described the prevalence as being for “depression” or “depressive disorders ” even though disorders were not assessed. Users of meta-analyses of depression prevalence should be cautious when interpreting results because reported prevalence may exceed actual prevalence.
topic Depression
Prevalence
Meta-analysis
Classification methods
Transparency
url http://link.springer.com/article/10.1186/s12916-019-1297-6
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