Industrial Psychiatry Journal最新文献

Background: Obsessive-compulsive disorder (OCD) is a chronic psychiatric disorder characterized by persistent, distressing obsessive thoughts and compulsive behaviors. In OCD, the level of insight is classified as good, poor, or absent. Poorer insight is associated with a more complex clinical presentation and a poorer prognosis.

Aim: The aim of our research was to investigate the relationship between the level of insight in individuals with OCD and various neuropsychological and psychopathological factors.

Materials and methods: This cross-sectional study recruited a total of 100 participants diagnosed with OCD. The Brown assessment of beliefs scale (BABS) was used to evaluate the insight of the patients. Psychopathology was assessed using the Yale-Brown obsessive compulsive scale (YBOCS) and Hamilton depression rating scale (HDRS). Neuropsychological assessments included the Stroop test, digit span test, controlled oral word association (COWA) test, trail making test, and Wisconsin card sorting test.

Results: The majority of the patients had good insight (54%), mild depression (48%), and moderate symptom severity (47%). Patients with poor insight had significantly higher scores on the YBOCS and HAM-D. They also performed significantly worse on the WCST and TMT-A. Patients with comorbid depression (mild/moderate) showed significantly poor performance on the WCST compared to those without depression.

Conclusion: The findings of our study indicate that patients with poor insight exhibit more severe forms of OCD, display greater psychopathology, and show more pronounced neuropsychological dysfunction.

Background: Sleep is essential for promoting physical and mental wellbeing. Short sleep duration and poor sleep quality are becoming more common among Informational Technology (IT) professionals; many IT workers seem to be using caffeine as a coping mechanism to alleviate the negative effects of insufficient sleep. Caffeine reduces sleep quality, prolongs sleep latency, and shortens sleep duration. Information on the sleep quality of young IT professionals is required to determine whether there may be a link between sleep quality, excessive daytime sleep, and caffeine usage.

Aim: This cross-sectional study examined sleep quality in IT professionals and the associations between sleep quality, excessive daytime sleep, and caffeine consumption.

Materials and methods: Caffeine Consumption, Epworth Sleepiness Scale, and Pittsburgh Sleep Quality Index questionnaires were administered to 200 IT professionals aged 23-40 years via the online survey.

Results: The average daily caffeine intake was 156.2 (98.7-252.5) mg per day, with coffee and tea being the primary contributor. A high prevalence of poor sleep quality (70%) was observed in the study population. Daily caffeine consumption was associated with poor sleep quality (r = 0.510, P > 0.01), and excessive day time sleep was associated with increased caffeine consumption (r = 0.363, P > 0.01). Excessive caffeine intake tends to be a predictive factor of poor sleep quality with an odd's ratio of OR 3.15, CI 2.34-4.25), P < 0.01.

Conclusion: These findings reveal that poor sleep quality is prevalent among IT professionals. More research is required to determine the methods to improve sleep issues. Additionally, health education should be provided regarding the quantity of caffeine in products to avoid excess caffeine consumption and to improve sleep quality.

Psychiatric disorders like depression and anxiety represent significant global health challenges, affecting individuals of all ages and contributing to a substantial disability burden worldwide. Despite advancements in mental health care, barriers such as cost, geographical limits, and social stigma may prevent individuals from receiving early psychological interventions. In recent years, artificial intelligence (AI) has emerged as a prominent tool to address these issues by facilitating early detection, personalized treatment, and intervention delivery for individuals experiencing depression and anxiety. Hence, the present systematic review focused on AI-enabled conversational chatbots for the identification and management of depression and anxiety. The current systematic review yielded a total of ten studies after a thorough analysis. The majority of studies were randomized controlled trials. The most frequently utilized AI method was conversational AI agents which are chatbots available through online software accessible via computers or smartphones. The investigations revealed significant outcomes by using AI for the enhancement of psychotherapy. The majority of studies showed a low risk (71.67%), indicating their reliability, while unclear studies (15%) exhibited some ambiguity without invalidating results. Conversely, studies classified as high risk (13.33%) indicated significant bias and potential errors. Chatbots have emerged as an effective medium for self-help depression and anxiety management. Studies have revealed significant positive outcomes, showing the potential of AI augmentation in psychotherapy to reduce clinical symptomatology. Notably, chatbot-delivered therapies have proven to be more successful than limited bibliotherapy, demonstrating their ability to effectively reduce the symptoms of depression and anxiety while encouraging a stronger therapeutic alliance among participants.

Background: Lawyers are exposed to a multitude of stressors; hence, a high proportion of them experience mental health issues and dissatisfaction with their jobs. However, no data compare these parameters in private and public sector lawyers from India.

Aim: To compare mental health status, perceived stress, and job satisfaction in public versus private sector lawyers.

Materials and methods: Thity participants, each from lawyers working in the public and private sectors in Chandigarh, were recruited and administered a sociodemographic scale, General Health Questionnaire 12, Cohen's Perceived Stress Scale, and Generic Job Satisfaction Scale.

Results: 73% and 60% of participants scored more than two on GHQ in the public and private sector groups, respectively. A significantly higher (90%) proportion of lawyers working in the public sector experienced high levels of stress when compared with lawyers working in the private sector (63%). A negative correlation between stress levels and job satisfaction was observed in both groups.

Conclusion: Lawyers experience high levels of stress and mental health issues, with stress being more prevalent in public sector lawyers. There is a negative correlation between stress levels and job satisfaction in private and public sector lawyers.

Background: Modified electroconvulsive therapy (mECT) is the treatment of choice in suicidality and resistant psychiatric disorders like treatment resistant depression and schizophrenia. A handful of studies with modest sample sizes have shown some effect of mECT on glycemic control and cholesterol levels; however, not a single study has explored the association between mECT and metabolic syndrome.

Aim: To find out the prevalence and clinical corelates of metabolic syndrome in patients receiving mECT.

Materials and methods: This was a cross-sectional exploratory study in which 89 patients receiving mECT were recruited via systematic random sampling and evaluated for metabolic syndrome by using modified National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP-III) criteria.

Results: The prevalence of metabolic syndrome in patients receiving mECT was 55.06%. The most common metabolic abnormality noted was elevated blood pressure, with increased diastolic blood pressure in 71.9% and elevated systolic blood pressure in 67.42%. We found a significant association between age (P < 0.001) and gender of patients on ECT with metabolic syndrome. (P = 0.019). Having received mECT's in past (P < 0.001) and a higher number of mECTs (P < 0.001) were both significantly associated with metabolic syndrome. Multivariate logistic regression metabolic syndrome was significantly predicted by the number of mECTs [{(unadjusted odds ratio 1.57), (adjusted odds ratio 1.52)}(P value < 0.001)}].

Conclusion: Our findings revealed an increased prevalence of metabolic syndrome in mECT population; this emphasizes the importance of screening for metabolic syndrome to reduce the risk of cardiovascular disease and premature death.

Background: Tobacco use is the largest preventable risk of non-communicable diseases (NCDs). Moreover, tobacco use interferes with glycaemic control, and there is a proven link between smoking and diabetes complications.

Aim: This cross-sectional study investigates the prevalence of tobacco use and the effect of advice about quitting and its impact at one-month and one-year follow-ups in outpatient type 2 diabetics.

Materials and methods: Type 2 diabetes patients attending physician OPD in tertiary care hospitals were interviewed using a questionnaire based on Global Adult Tobacco Survey (GATS) 2, India. They also received the National Toll-Free Quitline Number 1800112356 and the M Cessation no. 011-22901701. The free tobacco cessation clinic details at the government hospital in Pune were also shared, in case patients wanted to attend these facilities.

Results: The prevalence of tobacco use was 19% (present and former tobacco usage), wherein smoking contributed 9.0%, smokeless tobacco (SLT) contributed 7.5%, and dual use contributed 2.5%. The highest use was observed in the seventh decade. More women than men used smokeless tobacco. Poly SLT use and dual tobacco use - smoking and smokeless tobacco products, use of areca nut with SLT was also observed. Following brief physician advice, 27.2% quit tobacco usage at one-year follow-up.

Conclusion: A history of tobacco use needs to be asked to all type 2 diabetes mellitus (DM) patients in each visit, documenting it, explaining the importance of quitting tobacco in the context of diabetes, and advising to quit tobacco, even to elderly patients. If all the physicians in the health system offer quit advice to all the tobacco users, many patients are likely to quit tobacco.

Background: Shopping addiction refers to excessive, unnecessary shopping and is characterized by an inclination to acquire unnecessary items to feel pleasure and escape negative emotions. It is a type of behavioral addiction where the person finds the behavior rewarding psychologically while getting engaged in the activity but may later feel guilt, remorse, or even overwhelmed by the consequences.

Aim: To understand the prevalence and to assess the relation between shopping addiction and psychopathology, self-esteem, impulsivity, and personality traits.

Materials and methods: A total sample of 250 was taken for the study through purposive sampling, and responses were collected in both offline and online modes. The tools used were sociodemographic sheet, self-structured shopping behavior questionnaire, Bergen Shopping Addiction Scale (BSAS), Symptom Checklist-90-Revised (SCL-90-R), Barratt Impulsivity Scale Abbreviated (BIS-A), and Big Five Inventory-10 (BFI-10).

Results: A total of 122 individuals have been scored a cutoff score of 3 or more, indicating the presence of shopping addiction in them. Further analysis of these individuals suggests a relationship between impulsivity and extraversion personality trait and dimensions of shopping addiction.

Conclusion: Shopping addiction is a growing concern which needs to be explored more for treatment planning.