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.

BackgroundItem 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and PHQ-9.MethodsWe conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy.Results16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).ConclusionsPHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.

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The relationship between resilience and mental health was examined in three phases over 4 years in a sample of 314 college students in China. The present study aimed to gain insight into the reciprocal relationship of higher levels of resilience predicting lower levels of mental ill-being, and higher levels of positive mental health, and vice versa, and track changes in both resilience, mental ill-being and positive mental health over 4 years. We used the Depression Anxiety Stress, the Positive Mental Health, and the Resilience Scales. Results revealed that first-year students and senior year students experienced higher negative mental health levels and lower positive mental health levels than junior year students. Cross-lagged structural equation modeling analyses showed that resilience could significantly predict mental health status in the short term, namely within 1 year from junior to senior year. However, the predicting function of resilience for mental health is not significant in the long term, namely within 2 years from freshman to junior year. Additionally, the significant predicting function of individuals' mental health for resilience is fully verified for both the short and long term. These results indicate that college mental health education and interventions could be tailored based on students' year in college.

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.

Objective To evaluate the accuracy of the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) to screen for major depression among people with physical health problems. Design Systematic review and individual participant data meta-analysis. Data sources Medline, Medline In-Process and Other Non-Indexed Citations, PsycInfo, and Web of Science (from inception to 25 October 2018). Review methods Eligible datasets included HADS-D scores and major depression status based on a validated diagnostic interview. Primary study data and study level data extracted from primary reports were combined. For HADS-D cut-off thresholds of 5-15, a bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, in studies that used semi-structured diagnostic interviews (eg, Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders ), fully structured interviews (eg, Composite International Diagnostic Interview), and the Mini International Neuropsychiatric Interview. One stage meta-regression was used to examine whether accuracy was associated with reference standard categories and the characteristics of participants. Sensitivity analyses were done to assess whether including published results from studies that did not provide raw data influenced the results. Results Individual participant data were obtained from 101 of 168 eligible studies (60%; 25 574 participants (72% of eligible participants), 2549 with major depression). Combined sensitivity and specificity was maximised at a cut-off value of seven or higher for semi-structured interviews, fully structured interviews, and the Mini International Neuropsychiatric Interview. Among studies with a semi-structured interview (57 studies, 10 664 participants, 1048 with major depression), sensitivity and specificity were 0.82 (95% confidence interval 0.76 to 0.87) and 0.78 (0.74 to 0.81) for a cut-off value of seven or higher, 0.74 (0.68 to 0.79) and 0.84 (0.81 to 0.87) for a cut-off value of eight or higher, and 0.44 (0.38 to 0.51) and 0.95 (0.93 to 0.96) for a cut-off value of 11 or higher. Accuracy was similar across reference standards and subgroups and when published results from studies that did not contribute data were included. Conclusions When screening for major depression, a HADS-D cut-off value of seven or higher maximised combined sensitivity and specificity. A cut-off value of eight or higher generated similar combined sensitivity and specificity but was less sensitive and more specific. To identify medically ill patients with depression with the HADS-D, lower cut-off values could be used to avoid false negatives and higher cut-off values to reduce false positives and identify people with higher symptom levels. Trial registration PROSPERO CRD42015016761.

Objectives: The rapid pace, high volume, and limited quality of mental health evidence being generated during COVID-19 poses a barrier to effective decision-making. The objective of the present report is to compare mental health outcomes assessed during COVID-19 to outcomes prior to COVID-19 in the general population and other population groups. Design: Living systematic review. Data Sources: MEDLINE (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Web of Science Core Collection: Citation Indexes, China National Knowledge Infrastructure, Wanfang, medRxiv (preprints), and Open Science Framework Preprints (preprint server aggregator). The initial search was conducted on April 13, 2020 with ongoing weekly updates. Eligibility criteria for selecting studies: For this report, we included studies that compared general mental health, anxiety symptoms, or depression symptoms, assessed January 1, 2020 or later, to the same outcomes collected between January 1, 2018 and December 31, 2019. We required ≥ 90% of participants pre-COVID-19 and during COVID-19 to be the same or the use of statistical methods to address missing data. For population groups with continuous outcomes for at least three studies in an outcome domain, we conducted restricted maximum-likelihood random-effects meta-analyses. Results: As of March 22, 2021, we had identified 36 unique eligible studies with data from 33 cohorts. All reported COVID-19 outcomes between March and June 2020, and 3 studies also reported outcomes between September and November 2020. Estimates of changes in general mental health were close to zero in the general population (standardized mean difference [SMD] = 0.02, 95% CI -0.11 to 0.16, I2 = 94.6%; 4 studies, N = 19,707) and among older adults (SMD = 0.02, 95% CI -0.11 to 0.16, I2 = 90.4%; 4 studies, N = 5,520) and university students (SMD = -0.01, 95% CI -0.33 to 0.30, I2 = 92.0%; 3 studies, N = 3,372). Changes in anxiety symptoms were close to zero and not statistically significant in university students (SMD = 0.00, 95% CI -0.35 to 0.36, I2 = 95.4%; 5 studies, N = 1,537); women or females (SMD = 0.02, 95% CI -0.35 to 0.39, I2 = 92.3%; 3 studies, N = 2,778); and men or males (SMD = 0.07, 95% CI -0.01 to 0.15; I2 = 0.01%; 3 studies, N = 1,250); anxiety symptoms increased, however, among people with pre-existing medical conditions (SMD = 0.27, 95% CI 0.01 to 0.54, I2 = 91.0%; 3 studies, N = 2,053). Changes in depression symptoms were close to zero or small and not statistically significant among university students (SMD = 0.19, 95% CI -0.08 to 0.45, I2 = 91.8%; 5 studies, N = 1,537); people with pre-existing medical conditions (SMD = 0.01, 95% CI -0.15 to 0.17, I2 = 14.9%; 3 studies, N = 2,006); women or females (SMD = 0.21, 95% CI -0.14 to 0.55, I2 = 91.2%; 3 studies, N = 2,843); and men or males (SMD = 0.00, 95% CI -0.21 to 0.22; I2 = 92.3%; 4 studies, N = 3,661). In 3 studies with data from both March to June 2020 and September to November 2020, symptoms were unchanged from pre-COVID-19 at both time points or there were increases at the first assessment that had largely dissipated by the second assessment. Conclusions: Evidence does not suggest a widespread negative effect on mental health symptoms in COVID-19, although it is possible that gaps in data have not allowed identification of changes in some vulnerable groups. Continued updating is needed as evidence accrues.