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BackgroundDo DSM-IV diagnostic criteria for major depression (MD) in Chinese and Western women perform in a similar manner?MethodThe CONVERGE study included interview-based assessments of women of Han Chinese descent with treated recurrent MD. Using Mplus software, we investigated the overall degree of between-sample measurement invariance (MI) for DSM-IV diagnostic criteria for MD in the CONVERGE sample and samples selected from four major Western studies from the USA and Europe matched to the inclusion criteria of CONVERGE. These analyses were performed one pair at a time. We then compared the results from CONVERGE paired with Western samples to those obtained when examining levels of MI between pairs of the Western samples.ResultsAssuming a single factor model for the nine diagnostic criteria for MD, the level of MI based on global fit indexes observed between the CONVERGE and the four Western samples was very similar to that seen between the Western samples. Comparable results were obtained when using a two-factor structure for MI testing when applied to the 14 diagnostic criteria for MD disaggregated for weight, appetite, sleep, and psychomotor changes.ConclusionsDespite differences in language, ethnicity and culture, DSM criteria for MD perform similarly in Chinese women with recurrent MD and comparable subjects from the USA and Europe. The DSM criteria for MD may assess depressive symptoms that are relatively insensitive to cultural and ethnic differences. These results support efforts to compare findings from depressed patients in China and Western countries. [ABSTRACT FROM AUTHOR]

BackgroundThere are no risk models for the prediction of anxiety that may help in prevention. We aimed to develop a risk algorithm for the onset of generalized anxiety and panic syndromes.MethodFamily practice attendees were recruited between April 2003 and February 2005 and followed over 24 months in the UK, Spain, Portugal and Slovenia (Europe4 countries) and over 6 months in The Netherlands, Estonia and Chile. Our main outcome was generalized anxiety and panic syndromes as measured by the Patient Health Questionnaire. We entered 38 variables into a risk model using stepwise logistic regression in Europe4 data, corrected for over-fitting and tested it in The Netherlands, Estonia and Chile.ResultsThere were 4905 attendees in Europe4, 1094 in Estonia, 1221 in The Netherlands and 2825 in Chile. In the algorithm four variables were fixed characteristics (sex, age, lifetime depression screen, family history of psychological difficulties); three current status (Short Form 12 physical health subscale and mental health subscale scores, and unsupported difficulties in paid and/or unpaid work); one concerned country; and one time of follow-up. The overall C-index in Europe4 was 0.752 [95% confidence interval (CI) 0.724–0.780]. The effect size for difference in predicted log odds between developing and not developing anxiety was 0.972 (95% CI 0.837–1.107). The validation of predictA resulted in C-indices of 0.731 (95% CI 0.654–0.809) in Estonia, 0.811 (95% CI 0.736–0.886) in The Netherlands and 0.707 (95% CI 0.671–0.742) in Chile.ConclusionsPredictA accurately predicts the risk of anxiety syndromes. The algorithm is strikingly similar to the predictD algorithm for major depression, suggesting considerable overlap in the concepts of anxiety and depression. [ABSTRACT FROM PUBLISHER]