Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Heritability and polygenic predictionIn the EUR sample, the SNP-based heritability (h 2 SNP ) (that is, the proportion of variance in liability attributable to all measured SNPs)

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Two dimensions of temperament, namely, (high levels of) novelty seeking and (low levels of) harm avoidance are related to substance addictions. However, their implications for smartphone addiction remain unexplored. Medical students are heavy smartphone users. Accordingly, screening for the risk of smartphone addiction based on individual differences in temperament can facilitate the identification of the best possible prevention strategy. Therefore, the present study aimed to examine the relationship between temperament and the vulnerability to smartphone addiction among medical students in Jakarta, Indonesia. The research study adopted a cross-sectional research design and used a simple random sampling technique. The Indonesian versions of the Temperament and Character Inventory and the Smartphone Addiction Scale were used to measure the study variables. Logistic regression analysis was conducted to examine the relationships between demographic factors, patterns of smartphone use, temperament, and vulnerability to smartphone addiction. A majority of the 185 participants were found to have the following temperament profile: low levels of novelty seeking and high levels of reward dependence and harm avoidance. The average duration of daily smartphone use was 7.83 hours (SD = 4.03) and the age at first smartphone use was 7.62 years (SD = 2.60). The respondents used smartphone to communicate with other people and access social media. A high level of harm avoidance was significantly associated with the risk of smartphone addiction (Odds Ratio [OR] = 2.04, 95% Confidence Interval [CI] = 1.12, 3.70). The findings suggest that smartphone addiction is comparable to other addictive behaviors. Further, harm avoidance increases the risk of smartphone addiction. Therefore, the risk of smartphone addiction among medical students must be ascertained based on their temperament profiles.

Background Depression and anxiety are prevalent mental health issues among medical students due to the various challenges during medical education. These issues affect not only their quality of life, but also their academic and professional development. Coping strategy and resilience are two factors that may influence students’ mental health outcomes. Data of medical student mental health in Indonesia is scarce, hampering efforts to systematically address the problem. Hence, this study aims to estimate the prevalence of depressive and anxiety symptoms in Indonesian medical students, and their association with coping strategy and resilience. Methods Undergraduate medical students from each year of study (Preclinical Year 1 to 4, Clinical Year 1 and 2) in the Faculty of Medicine Universitas Indonesia were randomly selected to participate in this cross-sectional study. The study questionnaire included sociodemographic characteristics, Depression Anxiety Stress Scale (DASS) to measure symptoms of depression and anxiety, Brief COPE to measure coping strategy, and Connor-Davidson Resilience Scale (CD-RISC) to measure resilience. Scores of depression and anxiety symptoms were analyzed by comparing them between different sociodemographic groups and by measuring their correlation with coping strategies and resilience. Multiple regression analyses were conducted to identify predictors of depression and anxiety symptoms. Results Among 532 respondents, 22.2% reported symptoms of depression and 48,1% reported anxiety, including 3.0% and 8.1% with extremely severe depression and anxiety, respectively. Students not living with immediate family had higher depression score; female students and those in Preclinical Year 1 and Clinical Year 1 showed higher anxiety scores. Dysfunctional coping strategies and lower resilience are predictors of higher depression and anxiety symptoms. Conclusions Students show different levels of depressive and anxiety symptoms, signifying different levels of mental health support needs from universal mental health promotion to psychiatric treatment. Prevention programs can be targeted towards students with risk factors, such as not living with immediate family, undergoing first year of preclinical studies or clinical rotations, coping with dysfunctional strategies, and having low resilience. Additionally, medical educators must be aware of other, non-student factors that may impact student mental health, such as curriculum design and learning experience.