RESUMO
BACKGROUND: Multi-dimensional behavioral rating scales like the CBCL and YSR are available for diagnosing psychosocial maladjustment in adolescents, but these are unsuitable for large-scale usage since they are time-consuming and their many sensitive questions often lead to missing data. This research applies multiple imputation to tackle the effects of missing data in order to develop a simple questionnaire-based predictive instrument for psychosocial maladjustment. METHODS: Questionnaires from 2919 Chinese sixth graders in 21 schools were collected, but 86% of the students were missing one or more of the variables for analysis. Fifteen (10 training, 5 validation) samples were imputed using multivariate imputation chain equations. A ten-variable instrument was constructed by applying stepwise variable selection algorithms to the training samples, and its predictive performance was evaluated on the validation samples. RESULTS: The instrument had an AUC of 0.75 (95% CI: 0.73 to 0.78) and a calibration slope of 0.98 (95% CI: 0.86 to 1.09). The prevalence of psychosocial maladjustment was 18%. If a score of > 1 was used to define a negative test, then 80% of the students would be classified as negative. The resulting test had a diagnostic odds ratio of 5.64 (95% CI: 4.39 to 7.24), with negative and positive predictive values of 88% and 43%, and negative and positive likelihood ratios of 0.61 and 3.41, respectively. CONCLUSIONS: Multiple imputation together with internal validation provided a simple method for deriving a predictive instrument in the presence of missing data. The instrument's high negative predictive value implies that in populations with similar prevalences of psychosocial maladjustment test-negative students can be confidently excluded as being normal, thus saving 80% of the resources for confirmatory psychological testing.
Assuntos
Saúde Mental/estatística & dados numéricos , Psicologia da Criança , Área Sob a Curva , Povo Asiático , Calibragem , Criança , Estudos de Coortes , Feminino , Humanos , Funções Verossimilhança , Masculino , Modelos Psicológicos , Curva ROC , Projetos de Pesquisa , Inquéritos e QuestionáriosRESUMO
Stigma of mental illness is a major obstacle to its diagnosis and treatment and may be worse among Asians than Caucasians. This study compared the stigma of depression in 50 Chinese Americans (CA) and 50 Caucasian Americans (WA). Subjects were asked to read 5 case vignettes in the following order: diabetes mellitus (DB), major depressive disorder (MDD), somatoform depression (SD), psychotic depression (PD), and fever of unknown origin (HA). Diagnosis of each case was not revealed. Subjects then rated their response to each case, on a Likert scale from "strongly disagree" to "strongly agree," to 25 statements that contained 6 stigma factors: fear, shame, cognitive distortion, social consensus, discrimination, and sanction. Composite scores constructed from ratings of each factor were used to calculate the severity of stigma. Stigma of all 5 cases was worse in CA than WA. Both groups ranked DB and HA to be least and PD to be most stigmatizing. CA rated SD to be less stigmatizing than MDD but not WA. We concluded that stigma formation and severity were determined by fear, shame, cognitive distortion, social communication, consensus, and sanction. Mental symptoms, particularly psychotic symptoms, were more stigmatizing than physical symptoms, especially for CA. Belief that depression was like a physical illness did not diminish its stigma.