Indian Journal of Psychological Medicine最新文献

Background: Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) is a health insurance scheme launched by the Government of India (GOI) in 2018 to cover the in-patient (IP) treatment expenditures, including mental illness treatment expenditures, for 500 million Indians. AB-PMJAY pays 100% of treatment expenditures for persons below the poverty line (BPL) and 30% for people above the poverty line (APL). Ayushman Bharat Arogya Karnataka (ABAK) trust implements this scheme in Karnataka, a southern Indian state.

Methods: Data of persons with mental illness (PMI) admitted under AB-PMJAY at a tertiary care neuropsychiatric hospital between 2018 and 2021 was analyzed to understand the socio-demographic and clinical variables, the average length of stay (LOS), and the amount claimed by the hospital.

Results: Median LOS for PMI with any clinical diagnoses was 18 days (range 2-145),14 for those with substance use or mood disorders, and 24 days for those with schizophrenia and other psychotic disorders. The hospital claimed an amount of Indian Rupees (INR) 15,291,349 for treating 868 PMI under AB-PMJAY.

Conclusions: The minimum and maximum LOS varied 70-fold, and there was a significant difference between different PMIs based on their clinical diagnosis. ABAK paid ₹3,488-12,750 per PMI for their treatment. Further research is needed to determine the variables influencing the LOS and the cost to the implementing agency.

Background: Depression among the elderly is a growing public health concern, especially in India. This study aimed to investigate the predictive validity of physiological, psychological, and functional health factors in classifying the level of depressive symptoms among the elderly using the extreme gradient boosting (XGBoost) technique. Additionally, we compared the performance of models trained on original and resampled data.

Methods: This study is entirely based on secondary data analysis of the Longitudinal Aging Study in India wave 1 data. We classified the observations into "high depressive symptom" and "low/no depressive symptom" groups based on the predictors, including physiological, psychological, and functional health factors, along with socio-demographic factors. We developed three models (Models 1, 2, and 3) trained on original, over-sampled, and under-sampled data, respectively. Model performance was evaluated using the metrics of balanced accuracy, sensitivity, specificity, and area under the receiver operating characteristics curve (AUC).

Results: The study included 26,065 individuals aged 60 and above. Model 3, trained on under-sampled data, demonstrated the best overall performance. It achieved a balanced accuracy of 64%, with a sensitivity of 62.8% and specificity of 65.2%. The AUC for Model 3 was 0.692. Feature importance analysis revealed that life satisfaction, instrumental activities of daily living, mobility, caste, and monthly per capita expenditure quintiles were among the most influential factors in predicting the level of depressive symptoms.

Conclusion: The XGBoost models demonstrate promise in predicting depressive symptoms among the elderly. These findings suggest that machine learning models can be envisaged for early detection and management of depression, especially in primary care.

Purpose of the review: Accidental autoerotic death, more commonly known as "autoerotic asphyxia," is an extreme paraphilic behavior wherein individuals induce cerebral hypoxia during self-stimulated sexual activities, often by constricting the neck or obstructing respiratory passages. Data on accidental deaths caused by autoerotic play is very low because of the non-disclosure of the mode/circumstances of death or non-paralleled forensic systems in many countries. There is a high likelihood of coexisting mental disorders with such behavior. This review identifies the association of any comorbid mental disorder with accidental autoerotic deaths.

Collection and analysis of data: On August 23, 2023, a systematic literature search was carried out through Cochrane, PubMed, ScienceDirect, and SCOPUS, and studies identified in the English language were screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review (PRISMA-ScR) guideline. Eighteen studies identified specific mental disorders with autoerotic deaths, including paraphilia, vaginismus, gender dysphoria, multiplex paraphilia, alcohol dependence, bipolar disorder, borderline personality disorder, and substance use disorder. Inhalant use like chloroform, toluene, and xylene was implicated during autoerotic fantasies.

Conclusions: Prospective clinical screening and comprehensive multicentric psychological autopsy studies are needed to clarify the prevalence of accidental autoerotic death and related mental health conditions in the future. Given the possibility of accidental death, it remains to be seen whether paraphilia involving a single harmful event could be classified as a specifier within the impulsive-compulsive-reward spectrum, similar to how newer diagnostic systems address substance use disorders.

Background: Depression not only fosters the development of metabolic syndrome through behavioral, physiological, genetic, and treatment-related factors, but it also doubles the risk of experiencing metabolic syndrome. The objectives were to assess the sociodemographic and clinical profile of patients with depressive disorder, to assess the various metabolic parameters of metabolic syndrome in patients with depressive disorder, and to study the association between the severity of depression and metabolic syndrome.

Methods: A cross-sectional study was conducted among patients diagnosed with depression (n = 160) attending the Psychiatry outpatient department of a tertiary healthcare facility in Puducherry. The Hamilton Depression Rating Scale (HAM-D) and modified National Cholesterol Education Program-Adult Treatment Panel-III (NCEP ATP-III) criteria were used to assess the severity of depression and diagnose metabolic syndrome, respectively.

Results: The mean age at onset of depression was 31.4 years (+11.3); the duration of depression was 41.2 months (+32.5); and the severity of depression as assessed using the HAM-D was 17.9 (+6.3). The results showed that 27.5% of patients had metabolic syndrome. Factors associated with higher rates of metabolic syndrome included increasing age, female gender (79.5%), being single (25.0%), belonging to upper socioeconomic class (65.9%), non-Hindu religion (20.5%), and urban residence (72.7%) (P < .05). Patients with metabolic syndrome had later onset (36.4 years) and longer duration (51.6 months) of depression, more severe symptoms (18.2), and were more likely to have recurrent depressive disorder or dysthymia (88.6%) (P < .05). Furthermore, the current use of psychotropic medications (59.1%) and obesity (93.2%) were significantly associated with metabolic syndrome (P < .05).

Conclusion: This study reveals a high prevalence of metabolic syndrome among patients with depressive disorders linked to factors such as age, gender, marital status, socioeconomic status, religion, and urban residence. Integrated care approaches, including comprehensive screening and targeted interventions, are crucial for improving both mental and metabolic health outcomes.