Aims:The study aims to assess the prevalence of smartphone addiction and its effects on sleep quality among medical students.Study Setting and Design:A cross-sectional study was carried out by convenience sampling of medical students at a tertiary care hospital in South India.Materials and Methods:Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision axis I disorders research version was used for screening past and current psychiatric illness. A semi-structured pro forma was used to obtain demographic details. Smartphone Addiction Scale-Short Version was used to assess smartphone addiction in the participants. Sleep quality was assessed using Pittsburgh's Sleep Quality Index (PSQI).Results:Among 150 medical students, 67 (44.7%) were addicted to smartphone usage. Despite the preponderance of male students (31 [50%]) being addicted, there was no statistically significant gender difference in smartphone addiction (P = 0.270). The PSQI revealed poor sleep quality in 77 (51.3%) which amounts to half of the participants. Smartphone addiction was found to be statistically significantly associated with poor sleep quality (odds ratio: 2.34 with P < 0.046).Conclusions:The prevalence of smartphone addiction among younger population is higher compared to those of contemporary studies. No gender difference in smartphone addiction could be made out in the current study. Smartphone addiction was found to be associated with poor sleep quality. The findings support screening for smartphone addiction which will be helpful in early identification and prompt management.
Background Suicide is the leading contributor to mortality in bipolar disorder (BD). A history of suicidal attempt is a robust predictive marker for future suicide attempts. Personality profiles and coping strategies are the areas of contemporary research in bipolar suicides apart from clinical and demographic risk factors. However, similar research in developing countries is rarer. Objectives The present study aimed to identify the risk factors associated with suicidal attempts in BD type I (BD-I). Materials and Methods Patients with BD-I currently in clinical remission (N = 102) were recruited. Sociodemographic details and the clinical data were collected using a semistructured pro forma. The psychiatric diagnoses were confirmed using the Mini-International Neuropsychiatric Interview 5.0. The National Institute of Mental Health–Life Chart Methodology Clinician Retrospective Chart was used to chart the illness course. Presumptive Stressful Life Events Scale, Coping Strategies Inventory Short Form, Buss–Perry aggression questionnaire, Past Feelings and Acts of Violence, and Barratt Impulsivity scale were used to assess the patient’s stress scores, coping skills, aggression, violence, and impulsivity, respectively. Statistical Analysis Descriptive statistics were used for demographic details and characteristics of the illness course. Binary logistic regression analyses were performed to identify the predictors for lifetime suicide attempt in BD-I. Results A total of 102 patients (males = 49 and females = 53) with BD-I were included. Thirty-seven subjects (36.3%) had a history of suicide attempt. The illness course in suicide attempters more frequently had an index episode of depression, was encumbered with frequent mood episodes, especially in depression, and had a higher propensity for psychiatric comorbidities. On binary logistic regression analysis, the odds ratios (ORs) for predicting a suicide attempt were highest for positive family history of suicide (OR: 13.65, 95% confidence interval [CI]: 1.28–145.38, p = 0.030), followed by the presence of an index depressive episode (OR: 6.88, 95% CI: 1.70–27.91, p = 0.007), and lower scores on problem-focused disengagement (OR: 0.72, 95% CI: 0.56–0.92, p = 0.009). Conclusion BD-I patients with lifetime suicide attempt differ from non-attempters on various course-related and temperamental factors. However, an index episode depression, family history of suicide, and lower problem-focused engagement can predict lifetime suicide attempt in patients with BD-I.
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