Background:Premenstrual dysphoric disorder (PMDD) is a severe form of premenstrual syndrome (PMS) characterized by mood changes, anxiety, and somatic symptoms experienced during the specific time of menstrual cycle. Prevalence data of PMS and PMDD is sparse among college girls in India.Aims:The aim of this study is to study the prevalence of PMS and PMDD among college students of Bhavnagar (Gujarat), its associated demographic and menstrual factors, to rank common symptoms and compare premenstrual symptom screening tool (PSST) with Structured Clinical Interview for DSM-IV-TR defined PMDD (SCID-PMDD) for sensitivity and specificity.Materials and Methods:A cross-sectional survey was done in five colleges of Bhavnagar. Of 529 subjects approached, 489 college girls were finally analyzed for sociodemographic data, menstrual history, and PSST. SCID-PMDD was applied among those who were positive on PSST and 20% of those who were negative. The data were analyzed using OpenEpi Version 2. Chi-square test was done for qualitative variables and analysis of variance for quantitative variables. Sensitivity, specificity, and predictive values were calculated for PSST.Results:The prevalence of PMS was 18.4%. Moderate to severe PMS was 14.7% and PMDD was 3.7% according to DSM IV-TR and 91% according to International Classification of Diseases, 10th edition criteria. The symptoms commonly reported were “fatigue/lack of energy,” “decrease interest in work,” and “anger/irritability.” The most common functional impairment item was “school/work efficiency and productivity.” PSST has 90.9% sensitivity, 57.01% specificity, and 97.01% predictive value of negative test.Conclusion:Prevalence of PMS among college students is similar to other studies from Asia. PSST is a useful screening tool for PMS, and it should be confirmed by more specific tool as by SCID-PMDD. Routine screening with PSST can identify college girls who can improve with treatment.

BackgroundCaregivers play a pivotal role in providing care for mentally ill patients. Increase in caregiver burden can make them vulnerable to mental illness themselves.AimsWe assessed the severity of burden of care and its association with depression, anxiety and quality of life among caregivers of patients with alcohol use disorder (AUD) and schizophrenia.MethodsThis was an observational, cross-sectional, single-centred study of 50 consecutive caregivers of patients with AUD and schizophrenia. Participants were recruited from the psychiatry outpatient department of a tertiary care hospital between January and June 2017. The caregivers were further assessed by demographic details, Hospital Anxiety Depression Scale for assessment of depression and anxiety, Zarit Burden Interview for assessment of caregiver burden and WHO Quality Of Life-BREF for assessment of quality of life. Statistical data were analysed using GraphPad InStat V.3.06 (California). Multiple linear regression analysis was applied to identify the predictors of caregiver burden.ResultsBurden of care experienced by caregivers of patients with AUD is as high as that of caregivers of patients with schizophrenia (U=1142.5, p=0.46). Caregivers experiencing high burden of care are likely to have symptoms of anxiety (U=22, p<0.001), depression (U=32, p<0.001) and poor quality of life (U=84.5, p<0.001). Female caregivers are likely to experience higher burden of care (U=819.5, p=0.006). For caregivers of patients with schizophrenia, anxiety, environmental health, socioeconomic status and patients’ occupation can predict burden of care, while for caregivers of patients with AUD, depression and environmental health can predict burden of care.ConclusionOur study suggests that caregivers of patients with AUD experience burden of care as high as that of caregivers of patients with schizophrenia. Caregivers with high burden of care are more likely to have depression, anxiety and poor quality of life.Trial registration numberCTRI/2017/03/008224.

Background: Problematic Internet use (PIU) is the inability of individuals to control their Internet use, resulting in marked distress and/or functional impairment in daily life. Aim/Objective: We assessed the frequency of PIU and predictors of PIU, including social anxiety disorder (SAD), quality of sleep, quality of life and Internet-related demographic variables among school going adolescents. Methods: This was an observational, single-centered, cross-sectional, questionnaire-based study of 1,312 school going adolescents studying in Grades 10, 11 and 12 in Bhavnagar, India. Every participant was assessed by a pro forma containing demographic details, questionnaires of Internet Addiction Test (IAT), Social Phobia Inventory (SPIN), Pittsburgh Sleep Quality Index (PSQI) and Satisfaction With Life Scale (SWLS) for PIU severity, SAD severity, Quality of Sleep assessment and Quality of Life assessment, respectively. The statistical analysis was done with SPSS Version 23 (IBM Corporation) using chi-square test, Student’s t test and Pearson’s correlation. Multiple linear regression analysis was applied to find the predictors of PIU. Results: We found frequency of PIUs as 16.7% and Internet addiction as 3.0% among school going adolescents. Participants with PIU are more likely to experience SAD ( p < .0001), poor quality of sleep ( p < .0001) and poor quality of life ( p < .0001). There is positive correlation between severity of PIU and SAD ( r = .411, p < .0001). Linear regression analysis shows PIU can be predicted by SAD, sleep quality, quality of life, English medium, male gender, total duration of Internet use, monthly cost of Internet use, education, social networking, gaming, online shopping and entertainment as purpose of Internet use. Conclusion: Participants with PIU are more likely to experience SAD, poor quality of sleep and poor quality of life.