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Objectives: Selectively reported results from only well-performing cutoffs in diagnostic accuracy studies may bias estimates in meta-analyses. We investigated cutoff reporting patterns for the Patient Health Questionnaire-9 (PHQ-9; standard cutoff 10) and Edinburgh Postnatal Depression Scale (EPDS; no standard cutoff, commonly used 10–13) and compared accuracy estimates based on published cutoffs versus all cutoffs. Methods: We conducted bivariate random effects meta-analyses using individual participant data to compare accuracy from published versus all cutoffs. Results: For the PHQ-9 (30 studies, N = 11,773), published results underestimated sensitivity for cutoffs below 10 (median difference: −0.06) and overestimated for cutoffs above 10 (median difference: 0.07). EPDS (19 studies, N = 3637) sensitivity estimates from published results were similar for cutoffs below 10 (median difference: 0.00) but higher for cutoffs above 13 (median difference: 0.14). Specificity estimates from published and all cutoffs were similar for both tools. The mean cutoff of all reported cutoffs in PHQ-9 studies with optimal cutoff below 10 was 8.8 compared to 11.8 for those with optimal cutoffs above 10. Mean for EPDS studies with optimal cutoffs below 10 was 9.9 compared to 11.8 for those with optimal cutoffs greater than 10. Conclusion: Selective cutoff reporting was more pronounced for the PHQ-9 than EPDS.

BACKGROUND: Several countries have implemented 'lockdown' measures to curb the spread of the coronavirus disease 2019 (COVID-19). AIMS: To examine the psychological, physical activity (PA), and financial impact of a 2-month COVID-19 lockdown on older adults aged ≥60 years in Singapore, and to identify factors associated with adverse lockdown-related outcomes. METHOD: We interviewed 496 community-dwelling adults (mean age [standard deviation]: 73.8 [7.6] years; 54.8% female) during the lockdown who had previously participated in a population-based epidemiological study. Validated questionnaires were utilised to assess loneliness and depressive symptoms at both timepoints, while inhouse questionnaires were used to assess PA and financial difficulty during lockdown. Multivariable regression models determined the lockdown-related change in loneliness and depression scores, and the factors associated with adverse outcomes. RESULTS: Loneliness increased significantly during the lockdown period (p < 0.001) while depressive symptoms decreased (p = 0.022). Decreased PA, greater financial problems, male gender, Indian ethnicity, living alone, having a greater body mass index and perceived susceptibility to COVID-19 were all associated with worsening loneliness scores. A total of 36.9% and 19.6% participants reported decreased PA and had financial problems during the lockdown, respectively. Unemployment was associated with decreased PA, while self-employed individuals, cleaners, retail workers and smokers had greater odds of experiencing financial difficulty. CONCLUSION: Despite a decrease in depressive symptoms, our population of older Asians reported a significant increase in loneliness and decreased PA, with one-fifth experiencing financial problems during lockdown. Our data suggest that more targeted public health efforts are needed to reduce repercussions of future lockdowns.

INTRODUCTION: We investigated knowledge, attitudes, and practice (KAP) about COVID-19 and related preventive measures in Singaporeans aged ≥ 60 years. METHODS: This was a population-based, cross-sectional, mixed-methods study (13 May 2020-9 June 2020) of participants aged ≥60 years. Self-reported KAP about ten COVID-19 symptoms and six government-endorsed preventive measures were evaluated. Multivariable regression models identified sociodemographic and health-related factors associated with knowledge, attitudes and practices in our sample. Associations between knowledge/attitude scores, and practice categories were determined using logistic regression. 78 participants were interviewed qualitatively about practice of additional preventive measures and data were analysed thematically. RESULTS: Mean awareness score of the symptoms was 7.2/10. Fever (93.0%) and diarrhoea (33.5%) were the most- and least-known symptoms, respectively. Most knew all six preventive measures (90.4%), perceived them as effective (78.7%), and practiced 'wear a mask' (97.2%). Indians, Malays, and those in smaller housing had poorer mean knowledge of COVID-19 symptoms scores. Older participants had poorer attitudes towards preventive measures. Compared to Chinese, Indians had lower odds of practicing 3/6 recommendations. A one-point increase in knowledge of and attitudes towards preventive measures score had higher odds of always practicing 3/6 and 2/6 measures, respectively. Qualitative interviews revealed use of other preventive measures, e.g. maintaining a healthy lifestyle. CONCLUSION: Elderly Singaporeans displayed high levels of KAP about COVID-19 and related preventive measures, with a positive association between levels of knowledge/attitude, and practice. However, important ethnic and socioeconomic disparities were evident, suggesting key vulnerabilities remain, requiring immediate attention.

Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data.