BackgroundEarly identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increase the opportunity for early intervention.ObjectiveThe aim of this study was to explore whether computerized language analysis methods can be utilized to assess one’s suicide risk and emotional distress in Chinese social media.MethodsA Web-based survey of Chinese social media (ie, Weibo) users was conducted to measure their suicide risk factors including suicide probability, Weibo suicide communication (WSC), depression, anxiety, and stress levels. Participants’ Weibo posts published in the public domain were also downloaded with their consent. The Weibo posts were parsed and fitted into Simplified Chinese-Linguistic Inquiry and Word Count (SC-LIWC) categories. The associations between SC-LIWC features and the 5 suicide risk factors were examined by logistic regression. Furthermore, the support vector machine (SVM) model was applied based on the language features to automatically classify whether a Weibo user exhibited any of the 5 risk factors.ResultsA total of 974 Weibo users participated in the survey. Those with high suicide probability were marked by a higher usage of pronoun (odds ratio, OR=1.18, P=.001), prepend words (OR=1.49, P=.02), multifunction words (OR=1.12, P=.04), a lower usage of verb (OR=0.78, P<.001), and a greater total word count (OR=1.007, P=.008). Second-person plural was positively associated with severe depression (OR=8.36, P=.01) and stress (OR=11, P=.005), whereas work-related words were negatively associated with WSC (OR=0.71, P=.008), severe depression (OR=0.56, P=.005), and anxiety (OR=0.77, P=.02). Inconsistently, third-person plural was found to be negatively associated with WSC (OR=0.02, P=.047) but positively with severe stress (OR=41.3, P=.04). Achievement-related words were positively associated with depression (OR=1.68, P=.003), whereas health- (OR=2.36, P=.004) and death-related (OR=2.60, P=.01) words positively associated with stress. The machine classifiers did not achieve satisfying performance in the full sample set but could classify high suicide probability (area under the curve, AUC=0.61, P=.04) and severe anxiety (AUC=0.75, P<.001) among those who have exhibited WSC.ConclusionsSC-LIWC is useful to examine language markers of suicide risk and emotional distress in Chinese social media and can identify characteristics different from previous findings in the English literature. Some findings are leading to new hypotheses for future verification. Machine classifiers based on SC-LIWC features are promising but still require further optimization for application in real life.

BackgroundA pilot study about the effectiveness of a universal school-based programme, “The Little Prince is Depressed”, for preventing depression in Chinese adolescents in Hong Kong was conducted and reported previously. This study used a larger sample to examine the effectiveness and sustainability of the programme.MethodsThis study used quasi-experimental design. Twelve schools enrolled in “The Little Prince is Depressed” programme either as an intervention or a control condition. The intervention schools carried out the 12-session programme in two phases: the professional-led first phase and the teacher-led second phase. All participants were required to complete a questionnaire at three time points measuring their (1) depressive, anxiety, and stress levels; (2) knowledge of mental health; (3) attitudes towards mental illness; (4) perceived social support; and (5) help-seeking behaviours.ResultsA total of 3,391 students participated in the study. The level of depressive symptoms did not reduce significantly at post-intervention; however, a delayed effect was observed at follow-up assessment for the participants of the teacher-led group in reducing anxiety and stress levels. Also, the knowledge of mental health and attitudes towards mental illness of the intervention-group participants significantly improved at post-test, and the outcomes were maintained at 4 to 5 months after the intervention in both the professional-led and the teacher-led conditions (p<.05). A preference among schoolchildren for whom to seek help from was identified.ConclusionsThe universal depression prevention programme was effective in enhancing knowledge of mental health and promoting a more positive attitude towards mental illness among adolescents in Hong Kong. In particular, the teacher-led group showed better outcomes than the professional-led group in reducing students’ anxiety and stress at follow-up period. The programme can achieve sustainability in schools if teachers are provided with adequate support.

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