MATERIALS AND METHODS: A total of 480 students from different faculties in a Malaysian public university participated in this study. They were selected by simple random sampling method. They completed self-administered questionnaires including the Malay Version of Internet Addiction Test (MVIAT)) to measure internet addiction and Adult Self-Report Scale (ASRS) Symptom Checklist, Depression Anxiety Stress Scales (DASS) and UCLA Loneliness Scale (Version 3) to assess for ADHD symptoms, depression, anxiety, stress, and loneliness respectively.

RESULTS: The prevalence of IA among university students was 33.33% (n = 160). The respondents' mean age was 21.01 ± 1.29 years old and they were predominantly females (73.1%) and Malays (59.4%). Binary logistic regression showed that gender (p = 0.002; OR = 0.463, CI = 0.284-0.754), ADHD inattention (p = 0.003; OR = 2.063, CI = 1.273-3.345), ADHD hyperactivity (p<0.0001; OR = 2.427, CI = 1.495-3.939), stress (p = 0.048; OR = 1.795, CI = 1.004-3.210) and loneliness (p = 0.022; OR = 1.741, CI = 1.084-2.794) were significantly associated with IA.

METHODS: This was a cross-sectional study. All participants who fulfilled the requirements of the study according to the inclusion and exclusion criteria were enrolled. Study instruments included a demographic data questionnaire, Positive and Negative Symptom Scale (PANSS), Trail Making Tests, Rey's Auditory Verbal Learning Test (RAVLT) and Digit Span. Bivariate analyses were done using chi-square for categorical data and t-test for continuous data and multiple logistic regression analysis was done to identify predictors of employment status.

RESULTS: A total of 95 participants who fulfilled the inclusion criteria were enrolled into the study. Among the sociodemographic, clinical and cognitive variables studied marital status, educational level, mean scores of negative symptoms, Digit Span and RAVLT and Trail Making Tests were found to show significant association with employment status on bivariate analyses. However, when entered into a logistic regression model, only cognitive variables ie. Trail A and B, Digit Span and RAVLT were significant predictors of employment status.

Methods: A multidisciplinary group of experts from six ASEAN member states convened for two face-to-face meetings to discuss barriers and possible recommendations for optimizing NCD management, focused on cardiovascular diseases and mental disorders, in the region. Multiple approaches, ie, analysis of insights from the meetings and a review of existing literature on NCD programs in the ASEAN region were followed. The proposed recommendations were also based on selected successful interventions in ASEAN member states, thus providing actionable strategies.

Results: The gaps identified in NCD management for cardiovascular diseases and mental disorders in the ASEAN region were classified into gaps relating to policies and to clinical and public health practice. The proposed solutions addressing policy gaps include fostering multisectoral public-private partnerships, employing "whole-of-government" and "whole-of-society" approaches and promoting "health-in-all policies approach" to manage issues with financing, accessibility, efficiency and quality of health services. Whereas proposed solutions to bridge clinical and public health practice gaps entail strengthening primary care services, building the capacity of trained healthcare workers and employing collaborative care for holistic management of patients.