title: Comparison of diagnostic performance of Two-Question Screen and 15 depression screening instruments for older adults: systematic review and meta-analysis.
abstract: BackgroundScreening for depression in older adults is recommended.AimsTo evaluate the diagnostic accuracy of the Two-Question Screen for older adults and compare it with other screening instruments for depression.MethodWe undertook a literature search for studies assessing the diagnostic performance of depression screening instruments in older adults. Combined diagnostic accuracy including sensitivity and specificity were the primary outcomes. Potential risks of bias and the quality of studies were also assessed.ResultsA total of 46 506 participants from 132 studies were identified evaluating 16 screening instruments. The majority of studies (63/132) used various versions of the Geriatric Depression Scale (GDS) and 6 used the Two-Question Screen. The combined sensitivity and specificity for the Two-Question Screen were 91.8% (95% CI 85.2-95.6) and 67.7% (95% CI 58.1-76.0), respectively; the diagnostic performance area under the curve (AUC) was 90%. The Two-Question Screen showed comparable performance with other instruments, including clinician-rated scales. The One-Question Screen showed the lowest diagnostic performance with an AUC of 78%. In subgroup analysis, the Two-Question Screen also had good diagnostic performance in screening for major depressive disorder.ConclusionsThe Two-Question Screen is a simple and short instrument for depression screening. Its diagnostic performance is comparable with other instruments and, therefore, it would be favourable to use it for older adult screening programmes.
authors.affiliation: Kelvin K. F. Tsoi, PhD, Jockey Club School of Public Health and Primary Care and Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Joyce Y. C. Chan, MPH, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong; Hoyee W. Hirai, MSc, Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Samuel Y. S. Wong, MPH, MD, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong.
authors.forename: Kelvin K F
authors.initials: KK
authors.lastname: Tsoi
authors.affiliation: Kelvin K. F. Tsoi, PhD, Jockey Club School of Public Health and Primary Care and Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Joyce Y. C. Chan, MPH, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong; Hoyee W. Hirai, MSc, Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Samuel Y. S. Wong, MPH, MD, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong.
authors.forename: Joyce Y C
authors.initials: JY
authors.lastname: Chan
authors.affiliation: Kelvin K. F. Tsoi, PhD, Jockey Club School of Public Health and Primary Care and Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Joyce Y. C. Chan, MPH, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong; Hoyee W. Hirai, MSc, Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Samuel Y. S. Wong, MPH, MD, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong.
authors.forename: Hoyee W
authors.initials: HW
authors.lastname: Hirai
authors.affiliation: Kelvin K. F. Tsoi, PhD, Jockey Club School of Public Health and Primary Care and Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Joyce Y. C. Chan, MPH, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong; Hoyee W. Hirai, MSc, Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong; Samuel Y. S. Wong, MPH, MD, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong yeungshanwong@cuhk.edu.hk.
authors.forename: Samuel Y S
authors.initials: SY
authors.lastname: Wong
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003863:Depression / Q000175:diagnosis*; D006801:Humans; D011569:Psychiatric Status Rating Scales / Q000592:standards*