Background and aimsThe aim of the study is to investigate (a) whether probable depression status assessed at baseline prospectively predicted new incidence of Internet addiction (IA) at the 12-month follow-up and (b) whether IA status assessed at baseline prospectively predicted new incidence of probable depression at follow-up.MethodsWe conducted a 12-month cohort study (n = 8,286) among Hong Kong secondary students, and derived two subsamples. The first subsample (n = 6,954) included students who were non-IA at baseline, using the Chen Internet Addiction Scale (≤63), and another included non-depressed cases at baseline (n = 3,589), using the Center for Epidemiological Studies Depression Scale (<16).ResultsIn the first subsample, 11.5% of the non-IA cases developed IA during follow-up, and probable depression status at baseline significantly predicted new incidence of IA [severe depression: adjusted odds ratio (ORa) = 2.50, 95% CI = 2.07, 3.01; moderate: ORa = 1.82, 95% CI = 1.45, 2.28; mild: ORa = 1.65, 95% CI = 1.32, 2.05; reference: non-depressed], after adjusting for sociodemographic factors. In the second subsample, 38.9% of those non-depressed participants developed probable depression during follow-up. Adjusted analysis showed that baseline IA status also significantly predicted new incidence of probable depression (ORa = 1.57, 95% CI = 1.18, 2.09).Discussion and conclusionsThe high incidence of probable depression is a concern that warrants interventions, as depression has lasting harmful effects in adolescents. Baseline probable depression predicted IA at follow-up and vice versa, among those who were free from IA/probable depression at baseline. Healthcare workers, teachers, and parents need to be made aware of this bidirectional finding. Interventions, both IA and depression prevention, should thus take both problems into consideration.

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This case control study included 74 Chinese schizophrenics (DSM-III criteria) who died of suicide and 74 age- and sex-matched nonsuicide schizophrenics. Sociodemographic variables were unrelated with suicide. Associations were found between suicide and severity of illness (more frequent admissions, higher dose of medication and earlier appointments), history of major depressive episodes and suicidal attempts, last admission for reasons other than schizophrenic symptoms alone, and suicidal ideas on mental state examination. The last 2 factors, together with the maintenance dose of medication, were identified as the most important risk factors by logistic regression analysis.

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Prevalence and incidence of IA conversion were high and need attention. Interventions should take into account risk predictors identified, such as those of the HBM, and time management skills should be enhanced. Screening is warranted to identify those at high risk (e.g. high CIAS score) and provide them with primary and secondary interventions.