Inclusion of currently diagnosed or treated individuals in studies of depression screening tool accuracy: a meta-research review of studies published in 2018-2021

Abstract

Objectives: Screening is done to improve health outcomes by identifying and effectively treating individuals with unrecognized conditions. Depression screening has been proposed to identify previously unrecognized depression cases. Including individuals already diagnosed or treated for depression in screening test accuracy studies could exaggerate accuracy and the yield of new cases from screening. The present study investigated (1) the proportion of depression screening tool accuracy primary studies published in 2018-2021 that excluded individuals with a confirmed depression diagnosis or who were already undergoing treatment; and (2) whether this has improved since the last review of studies published in 2013-2015, which found that five of 89 (5.6%) primary studies appropriately excluded such individuals.

Methods: MEDLINE was searched from January 1, 2018 through May 21, 2021 for primary studies on depression screening tool accuracy.

Results: Eighteen of 106 (17.0%; 95% Confidence Interval [CI], 11.0% to 25.3%) primary studies excluded currently diagnosed or treated individuals. This was 11.4% (95% CI, 2.8% to 20.0%) greater than in similar studies published in 2013-2015.

Conclusion: There has been an improvement since 2015, but the proportion of studies that exclude individuals already known to have depression remains low. This may bias research findings intended to inform clinical practice.

Keywords: Bias; Depression; Depression screening tools; Diagnostic test accuracy; Screening.