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The diagnostic accuracy of the Patient Health Questionnaire-2 (PHQ-2), Patient Health Questionnaire-8 (PHQ-8), and Patient Health Questionnaire-9 (PHQ-9) for detecting major depression: protocol for…

Overview of attention for article published in Systematic Reviews, October 2014
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Title
The diagnostic accuracy of the Patient Health Questionnaire-2 (PHQ-2), Patient Health Questionnaire-8 (PHQ-8), and Patient Health Questionnaire-9 (PHQ-9) for detecting major depression: protocol for a systematic review and individual patient data meta-analyses
Published in
Systematic Reviews, October 2014
DOI 10.1186/2046-4053-3-124
Pubmed ID
Authors

Brett D Thombs, Andrea Benedetti, Lorie A Kloda, Brooke Levis, Ioana Nicolau, Pim Cuijpers, Simon Gilbody, John P A Ioannidis, Dean McMillan, Scott B Patten, Ian Shrier, Russell J Steele, Roy C Ziegelstein

Abstract

Major depressive disorder (MDD) may be present in 10%-20% of patients in medical settings. Routine depression screening is sometimes recommended to improve depression management. However, studies of the diagnostic accuracy of depression screening tools have typically used data-driven, exploratory methods to select optimal cutoffs. Often, these studies report results from a small range of cutoff points around whatever cutoff score is most accurate in that given study. When published data are combined in meta-analyses, estimates of accuracy for different cutoff points may be based on data from different studies, rather than data from all studies for each possible cutoff point. As a result, traditional meta-analyses may generate exaggerated estimates of accuracy. Individual patient data (IPD) meta-analyses can address this problem by synthesizing data from all studies for each cutoff score to obtain diagnostic accuracy estimates. The nine-item Patient Health Questionnaire-9 (PHQ-9) and the shorter PHQ-2 and PHQ-8 are commonly recommended for depression screening. Thus, the primary objectives of our IPD meta-analyses are to determine the diagnostic accuracy of the PHQ-9, PHQ-8, and PHQ-2 to detect MDD among adults across all potentially relevant cutoff scores. Secondary analyses involve assessing accuracy accounting for patient factors that may influence accuracy (age, sex, medical comorbidity).

X Demographics

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 138 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 16%
Researcher 17 12%
Student > Bachelor 16 12%
Student > Doctoral Student 14 10%
Student > Postgraduate 8 6%
Other 32 23%
Unknown 29 21%
Readers by discipline Count As %
Medicine and Dentistry 36 26%
Psychology 24 17%
Nursing and Health Professions 10 7%
Mathematics 5 4%
Engineering 4 3%
Other 20 14%
Unknown 39 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 November 2014.
All research outputs
#15,749,963
of 23,393,453 outputs
Outputs from Systematic Reviews
#1,625
of 2,032 outputs
Outputs of similar age
#153,400
of 261,868 outputs
Outputs of similar age from Systematic Reviews
#29
of 35 outputs
Altmetric has tracked 23,393,453 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,032 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.9. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 261,868 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.