for the Depression Screening Data (DEPRESSD) PHQ Collaboration IMPORTANCE The Patient Health Questionnaire depression module (PHQ-9) is a 9-item self-administered instrument used for detecting depression and assessing severity of depression. The Patient Health Questionnaire-2 (PHQ-2) consists of the first 2 items of the PHQ-9 (which assess the frequency of depressed mood and anhedonia) and can be used as a first step to identify patients for evaluation with the full PHQ-9.OBJECTIVE To estimate PHQ-2 accuracy alone and combined with the PHQ-9 for detecting major depression.

BackgroundEvidence on the burden of depression, internet addiction and poor sleep quality in undergraduate students from Nepal is virtually non-existent. While the interaction between sleep quality, internet addiction and depressive symptoms is frequently assessed in studies, it is not well explored if sleep quality or internet addiction statistically mediates the association between the other two variables.MethodsWe enrolled 984 students from 27 undergraduate campuses of Chitwan and Kathmandu, Nepal. We assessed sleep quality, internet addiction and depressive symptoms in these students using Pittsburgh Sleep Quality Index, Young’s Internet Addiction Test and Patient Health Questionnaire-9 respectively. We included responses from 937 students in the data analysis after removing questionnaires with five percent or more fields missing. Via bootstrap approach, we assessed the mediating role of internet addiction in the association between sleep quality and depressive symptoms, and that of sleep quality in the association between internet addiction and depressive symptoms.ResultsOverall, 35.4%, 35.4% and 21.2% of students scored above validated cutoff scores for poor sleep quality, internet addiction and depression respectively. Poorer sleep quality was associated with having lower age, not being alcohol user, being a Hindu, being sexually active and having failed in previous year’s board examination. Higher internet addiction was associated with having lower age, being sexually inactive and having failed in previous year’s board examination. Depressive symptoms were higher for students having higher age, being sexually inactive, having failed in previous year’s board examination and lower years of study. Internet addiction statistically mediated 16.5% of the indirect effect of sleep quality on depressive symptoms. Sleep quality, on the other hand, statistically mediated 30.9% of the indirect effect of internet addiction on depressive symptoms.ConclusionsIn the current study, a great proportion of students met criteria for poor sleep quality, internet addiction and depression. Internet addiction and sleep quality both mediated a significant proportion of the indirect effect on depressive symptoms. However, the cross-sectional nature of this study limits causal interpretation of the findings. Future longitudinal study, where the measurement of internet addiction or sleep quality precedes that of depressive symptoms, are necessary to build upon our understanding of the development of depressive symptoms in students.

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Objective To update a previous individual participant data meta-analysis and determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9), the most commonly used depression screening tool in general practice, for detecting major depression overall and by study or participant subgroups. Design Systematic review and individual participant data meta-analysis. Data sources Medline, Medline In-Process, and Other Non-Indexed Citations via Ovid, PsycINFO, Web of Science searched through 9 May 2018. Review methods Eligible studies administered the PHQ-9 and classified current major depression status using a validated semistructured diagnostic interview (designed for clinician administration), fully structured interview (designed for lay administration), or the Mini International Neuropsychiatric Interview (MINI; a brief interview designed for lay administration). A bivariate random effects meta-analytic model was used to obtain point and interval estimates of pooled PHQ-9 sensitivity and specificity at cut-off values 5-15, separately, among studies that used semistructured diagnostic interviews (eg, Structured Clinical Interview for Diagnostic and Statistical Manual), fully structured interviews (eg, Composite International Diagnostic Interview), and the MINI. Meta-regression was used to investigate whether PHQ-9 accuracy correlated with reference standard categories and participant characteristics. Results Data from 44 503 total participants (27 146 additional from the update) were obtained from 100 of 127 eligible studies (42 additional studies; 79% eligible studies; 86% eligible participants). Among studies with a semistructured interview reference standard, pooled PHQ-9 sensitivity and specificity (95% confidence interval) at the standard cut-off value of ≥10, which maximised combined sensitivity and specificity, were 0.85 (0.79 to 0.89) and 0.85 (0.82 to 0.87), respectively. Specificity was similar across reference standards, but sensitivity in studies with semistructured interviews was 7-24% (median 21%) higher than with fully structured reference standards and 2-14% (median 11%) higher than with the MINI across cut-off values. Across reference standards and cut-off values, specificity was 0-10% (median 3%) higher for men and 0-12 (median 5%) higher for people aged 60 or older. Conclusions Researchers and clinicians could use results to determine outcomes, such as total number of positive screens and false positive screens, at different PHQ-9 cut-off values for different clinical settings using the knowledge translation tool at www.depressionscreening100.com/phq . Study registration PROSPERO CRD42014010673.