Psychometric properties and factor structure of the suicidal narrative inventory in major depression: A multicentric evaluation.

BACKGROUND: The Suicidal Narrative Inventory (SNI) is a 38-item self-report measure developed to assess elements of the suicidal narrative, a subacute, predominantly cognitive, presuicidal construct. Our objectives were to assess the factor structure, validity, and reliability of the SNI-38 among adults with major depressive disorder (MDD). METHODS: Using a cross-sectional design, we administered the Hindi version of the SNI along with other self-report measures to adults with MDD, recruited from 24 tertiary care hospitals across India. Confirmatory factor analysis (CFA) was performed to assess the factor structure of SNI-38. Reliability (internal consistency) was assessed using Cronbach's alpha (α). Convergent, discriminant, and criterion validity of the SNI-38 were tested by comparing it against other appropriate measures. RESULTS: We collected usable responses from 654 Hindi-speaking participants (Mean age = 36.9 ± 11.9 years, 50.2% female). The eight-factor solution of the SNI showed good model fit indices (χ2[637] = 3345.58, p <.001, CFI =.98, and RMSEA =.08). Internal consistencies for the SNI subscale scores were good to excellent, α ranging from .73 to.92. While most subscales significantly converged with other measures, associations were comparatively weaker and inconsistent for the 'thwarted belongingness' and 'goal reengagement' subscales. CONCLUSION: Consistent with prior data, our study confirmed an eight-factor solution and demonstrated adequate psychometric properties for the Hindi version of the SNI-38 in our sample. These findings provide empirical support for the use of SNI to assess the suicidal narrative among Indian adults with MDD.

Cognitive impairment in 'non-user' first-degree relatives of persons with cannabis dependence syndrome: A pilot, endophenotype study.

INTRODUCTION: Cannabis use disorders are global emerging problem nowadays, with high prevalence and morbidity. Cognitive impairments, and also corresponding genetic vulnerability, has been fairly replicated in individuals with cannabis dependence. However, there are few studies that assess cognitive functioning as an endophenotype or a trait marker for cannabis dependence. While the primary objective of this study was to assess the endophenotype pattern of cognitive dysfunction in cannabis dependence, assessing the association between the degree of cognitive functioning, and their socio-demographic and clinical variables in the cannabis dependence patients and their first-degree relatives was the secondary objective. METHODOLOGY: We compared cognitive functioning across three groups- patients with cannabis dependence syndrome, their 'non-user' first-degree relatives and healthy controls, with 30 participants in each group. Five cognitive domains- attention and concentration, verbal fluency, memory, visuospatial ability and executive functions were assessed. We assessed for endophenotype pattern of statistical significance in pairwise analyses of Kruskal-Wallis test, which was corrected for multiple comparisons. Subsequently, correlation analysis to assess association of cognitive impairment with socio-demographic and clinical variables was conducted. RESULTS: Although impairment in attention and executive functions also was seen in patients with cannabis dependence, endophenotype pattern of statistical significance in pairwise analyses, with impairment in first-degree relatives too, was seen in all sub-scores of verbal fluency and verbal memory. None of the correlations were significant. CONCLUSION: 'Non-user' first-degree relatives of patients with cannabis dependence too show significant cognitive impairment. Verbal fluency and verbal memory are possible endophenotypes or trait markers for cannabis dependence syndrome.

External Ear Anomalies and Minor Physical Anomalies in Depressive Disorder Patients and Healthy Controls.

Objective: To determine if external ear anomalies (EEAs) and minor physical anomalies (MPAs) are more prevalent in patients with depressive disorder than in healthy controls.Methods: This cross-sectional study was conducted at a tertiary-level referral center between October 1, 2019, and September 30, 2020, and included 100 patients with depressive disorder (diagnosed per ICD-10 criteria) and 100 aged- and sex-matched healthy controls. The study participants were examined using the External Ear Anomalies Assessment Scale and the extended Waldrop Scale.Results: Independent samples Mann-Whitney U test showed a higher prevalence of mean EEAs and MPAs in patients with depressive disorder. Adherent ear lobe was the most common ear anomaly in both patients (52%) and controls (41%), followed by Darwinian tubercle (21% in the patient group and 19% in the control group).Conclusions: External ear anomalies are more prevalent in patients with depressive disorder, supporting the neurodevelopmental theory of depression. These EEAs need further description and attention for possible inclusion in scales that assess minor physical anomalies and may be used as an endophenotypic marker for depression in the future.Prim Care Companion CNS Disord. 2023;25(4):22m03416. Author affiliations are listed at the end of this article.

Indian Psychiatric Society multicentre study: Diagnostic patterns, comorbidity and prescription practices for patients with Dementia.

Background: There are more than 5 million people with dementia in India. Multicentre studies looking at details of treatment for people with dementia In India are lacking. Clinical audit is a quality improvement process which aims to systematically assess, evaluate, and improve patient care. Evaluating current practice is the key to a clinical audit cycle. Aim: This study aimed to assess the diagnostic patterns and prescribing practices of psychiatrists for patients with dementia in India. Method: A retrospective case file study was conducted across several centers in India. Results: Information from the case records of 586 patients with dementia was obtained. Mean age of the patients was 71.14 years (standard deviation = 9.42). Three hundred twenty one (54.8%) were men. Alzheimer's disease (349; 59.6%) was the most frequent diagnosis followed by vascular dementia (117; 20%). Three hundred fifty five (60.6%) patients had medical disorders and 47.4% patients were taking medications for their medical conditions. Eighty one (69.2%) patients with vascular dementia had cardiovascular problems. Majority of the patients (524; 89.4%) were on medications for dementia. Most frequently prescribed treatment was Donepezil (230; 39.2%) followed by Donepezil-Memantine combination (225; 38.4%). Overall, 380 (64.8%) patients were on antipsychotics. Quetiapine (213, 36.3%) was the most frequently used antipsychotic. Overall, 113 (19.3%) patients were on antidepressants, 80 (13.7%) patients were on sedatives/hypnotics, and 16 (2.7%) patients were on mood stabilizers. Three hundred nineteen (55.4%) patients and caregivers of 374 (65%) patients were receiving psychosocial interventions. Conclusions: Diagnostic and prescription patterns in dementia which emerged from this study are comparable to other studies both nationally and internationally. Comparing current practices at individual and national levels against accepted guidelines, obtaining feedback, identifying gaps and instituting remedial measures help to improve the standard of care provided.

Prevalence of Psychiatric Disorders in Chhattisgarh: Findings from National Mental Health Survey.

Background: Psychiatric disorders are among the leading contributors to disability in India and worldwide. The pattern, prevalence, and distribution of psychiatric disorders in the country and its regions need to be assessed to facilitate early diagnosis and treatment. No study on the epidemiology of psychiatric disorders has been conducted in the Chhattisgarh state. This paper, as part of the National Mental Health Survey (NMHS), discusses the prevalence and pattern of psychiatric disorders in Chhattisgarh state. Methods: A stratified random cluster sampling technique and random selection based on probability proportional to size (PPS) at each stage were adopted. Participants were from three selected districts of Chhattisgarh, such as Janjgir-Champa, Kabirdham, and Raipur. Adults (aged ≥18 years) residing in selected households were interviewed using Mini International Neuropsychiatric Interview (version 6.0), the Fagerstrom test for nicotine dependence, the WHO-SEARO screening questionnaire for generalized tonic-clonic seizures, and screening tools for intellectual disability and autism spectrum disorders. Results: A total of 2841 individuals were interviewed. The state's lifetime and current prevalence of psychiatric disorders for adults were 14.06% [95% confidence interval (CI) = 13.83-14.29] and 11.66% (95% CI = 11.45-11.87), respectively. Prevalence of substance use disorders, tobacco use disorders, schizophrenia and related disorders, and mood disorders was 32.4% (95% CI = 32.09-32.71), 29.86% (95% CI = 29.56-30.16), 0.8% (95% CI = 0.75-0.86), and 4.44% (95% CI = 4.31-4.58), respectively. High risk for suicide was detected in 0.28% (95% CI = 0.25-0.31). Psychiatric disorders were twice more common in males than in females. Conclusions: The study gives authentic data on the prevalence of psychiatric disorders in Chhattisgarh. This shall pave the way for policymakers and planners to design state-specific plans for dealing with mental disorders and related issues.

Impact of COVID-19 lockdown on substance availability, accessibility, pricing, and quality: A multicenter study from India.

Background and Aim: Pandemic and consequent lockdowns are likely to affect the drug market by the sudden disruption of the supply chain. We explored the change in the availability, access, purity, and pricing during lockdown from respondents seeking treatment for drugs, alcohol, and tobacco dependence. Materials and Methods: A cross-sectional survey was conducted among 404 respondents from seven treatment centers across India. A structured questionnaire assessed the change in availability, access, quality, and price of substances used during the first phase (March 24-April 14) and the second phase (April 15-May 3) of lockdown. Results: A majority of the respondents in treatment used tobacco (63%) and alcohol (52%). Relatively few respondents used opioids (45%) or cannabis (5%). Heroin (44%) was the most common opioid the respondents were treated for. Seventy-five percent, 65%, and 60% of respondents treated for alcohol, tobacco, and opioid problems, respectively, reported a reduction in the availability and access during the first phase of the lockdown. In the second phase, respondents with alcohol and tobacco dependence reported greater availability than those with opioid and cannabis dependence. The reported price of all substances increased more than 50% during the first phase of lockdown and remained higher throughout the second phase. Deterioration in purity was reported by more than half of the people who used opioid. Conclusion: Lockdown could have affected both licit and illicit drug markets, albeit to a varying degree. The observed changes seemed short-lasting, as suggested by the recovering trends during the second phase of lockdown.

A multicentric survey among patients with substance use disorders during the COVID-19 lockdown in India.

Background: The unprecedented first wave of the COVID-19 pandemic severely impacted mental health services globally. However, the negative impact of such disruptions on people with substance use disorders (SUD) seeking treatment remains unclear. We aim to explore the behaviors adopted by these individuals to overcome the service disruptions. Materials and Methods: We explored the changes related to substance use behavior (quit attempts, withdrawal experienced, treatment-seeking, and risky behaviors), and behavioral changes in response to COVID-19 lockdown. A cross-sectional survey was conducted among 404 people with SUD seeking treatment from seven centers across India. They were assessed by a specially designed structured questionnaire during the first wave (June-September) of the pandemic. Results: An overwhelming majority experienced withdrawal symptoms, with close to half making quit attempts and seeking treatment during the lockdown. Three-fourth of the sample reported difficulty in accessing treatment services and medications. Patients with opioid use were significantly more likely to think about quitting (χ2 = 20.408, P = 0.000), make attempts (χ2 = 12.436, P = 0.000), seek treatment (χ 2 = 7.536, P = 0.006), and self-medicate for withdrawal symptoms (χ2 = 5.885, P = 0.015). In turn, those with alcohol use were more likely to use telepsychiatry services (χ2 = 35.143, P = 0.000) and experience stigma by family members (χ2 = 29.951, P = 0.000) and neighbors (χ2 = 17.725, P = 0.000). Among COVID-19 safety precautions, majority practised wearing masks and social distancing but not others. Conclusion: COVID-19 lockdown led a significant proportion of substance users, especially opioid users, to make quit attempts and seek help. However, these could not be sustained due to difficulty in accessing treatment services. Further, significant proportion failed to adhere to COVID-19 safety precautions.

Exploratory Factor Analysis of Young's Internet Addiction Test Among Professionals from India: An Online Survey.

BACKGROUND: Internet use has spread across the world due to easy accessibility and affordability. However, it has been creating many problems at several levels. So, there is a need to identify the suitability of psychometric properties and the factor structure of the widely used Internet Addiction Test (IAT) in the Indian settings. Our objective was to perform an exploratory factor analysis on the IAT and to test the reliability of the scale. METHODS: It was a cross-sectional study that included various professional groups. We used an online questionnaire that included sociodemographic details and Young's IAT. Exploratory factor analysis was used to identify the factor structure of Young's IAT in the Indian setup. RESULTS: The mean age of the sample (N = 1,782) was 27.7 years (SD = 8.74) with a predominantly male population 1040 (58.4%). In total, 1.0% (17) of the sample had significant problems with internet usage, whereas 13% (232) were in the range of frequent/occasional problems, and the mean score on IAT was 32 (SD = 16.42). Exploratory factor analysis revealed two factors that explained 49% of the variance (Kaiser-Meyer-Olkin measure of sampling adequacy: 0.95, Bartlett's test of sphericity: P = 0.000). They were "mood and relationship issues" and "duration and productivity." Cronbach's α was 0.92, which indicates a high level of internal consistency. CONCLUSION: In Indian settings, IAT can be understood based on the two-factor structure. The scale has excellent reliability. Further studies are needed to replicate these results, by using confirmatory factor analysis and validity testing.

Quality of life after coronary artery bypass graft & percutaneous transluminal coronary angioplasty: A follow up study from India.

Coronary artery bypass graft (CABG) and percutaneous transluminal coronary angioplasty (PTCA) are treatments of choice for coronary artery disease. Quality of life (QoL) is an important factor in determining optimum treatment. This study was aimed to compare changes in QoL, six months post procedure, between CABG and PTCA, and to understand the confounding effect of various contributing factors. Thirty stable angina patients each in CABG and PTCA groups, were followed up for six months. QoL was assessed with WHO-QoL-BREF. Depression was rated on the Hamilton Depression Rating Scale. Changes in QoL and depression within and between CABG and PTCA groups were compared. Multinomial logistic regression was used to measure the predictive strength of treatment type (CABG and PTCA) on QoL, controlling for significant confounders. Although scores of QoL and depression significantly changed over time in both the groups, time×group interaction did not reach to a significance. Significant confounding effects of diabetes (P<0.01), hypertension (P<0.05) and diet restriction (P<0.05) were found. Controlling for confounding effects of these factors, group distribution to PTCA, compared to CABG, significantly predicted greater improvements in QoL (P<0.01).

Artificial intelligence-based classification of schizophrenia: A high density electroencephalographic and support vector machine study.

BACKGROUND: Interview-based schizophrenia (SCZ) diagnostic methods are not completely valid. Moreover, SCZ-the disease entity is very heterogeneous. Supervised-Machine-Learning (sML) application of Artificial-Intelligence holds a tremendous promise in solving these issues. AIMS: To sML-based discriminating validity of resting-state electroencephalographic (EEG) quantitative features in classifying SCZ from healthy and, positive (PS) and negative symptom (NS) subgroups, using a high-density recording. SETTINGS AND DESIGN: Data collected at a tertiary care mental-health institute using a cross-sectional study design and analyzed at a premier Engineering Institute. MATERIALS AND METHODS: Data of 38-SCZ patients and 20-healthy controls were retrieved. The positive-negative subgroup classification was done using Positive and Negative Syndrome Scale operational-criteria. EEG was recorded using 256-channel high-density equipment. Eight priori regions-of-interest were selected. Six-level wavelet decomposition and Kernel-Support Vector Machine (SVM) method were used for feature extraction and data classification. STATISTICAL ANALYSIS: Mann-Whitney test was used for comparison of machine learning-features. Accuracy, sensitivity, specificity, and area under receiver operating characteristics-curve were measured as discriminatory indices of classifications. RESULTS: Accuracy of classifying SCZ from healthy and PS from NS SCZ, were 78.95% and 89.29%, respectively. While beta and gamma frequency related features most accurately classified SCZ from healthy controls, delta and theta frequency related features most accurately classified positive from negative SCZ. Inferior frontal gyrus features most accurately contributed to both the classificatory instances. CONCLUSIONS: SVM-based classification and sub-classification of SCZ using EEG data is optimal and might help in improving the "validity" and reducing the "heterogeneity" in the diagnosis of SCZ. These results might only be generalized to acute and moderately ill male SCZ patients.

The National Mental Health Survey of India (2016): Prevalence, socio-demographic correlates and treatment gap of mental morbidity.

BACKGROUND: Recognizing the need for good quality, scientific and reliable information for strengthening mental health policies and programmes, the National Mental Health Survey (NMHS) of India was implemented by National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, in the year 2015-2016. AIM: To estimate the prevalence, socio-demographic correlates and treatment gap of mental morbidity in a representative population of India. METHODS: NMHS was conducted across 12 Indian states where trained field investigators completed 34,802 interviews using tablet-assisted personal interviews. Eligible study subjects (18+ years) in households were selected by a multi-stage, stratified, random cluster sampling technique. Mental morbidity was assessed using MINI 6. Three-tier data monitoring system was adopted for quality assurance. Weighted and specific prevalence estimates were derived (current and lifetime) for different mental disorders. Mental morbidity was defined as those disorders as per the International Statistical Classification of Diseases, Tenth Revision Diagnostic Criteria for Research (ICD-10 DCR). Multivariate logistic regression was conducted to examine risk for mental morbidity by different socio-demographic factors. Survey was approved by central and state-level institutional ethical committees. RESULTS: The weighted lifetime prevalence of 'any mental morbidity' was estimated at 13.67% (95% confidence interval (CI) = 13.61, 13.73) and current prevalence was 10.56% (95% CI = 10.51, 10.61). Mental and behavioural problems due to psychoactive substance use (F10-F19; 22.44%), mood disorders (F30-F39; 5.61%) and neurotic and stress-related disorders (F40-F48; 3.70%) were the most commonly prevalent mental morbidity in India. The overall prevalence was estimated to be higher among males, middle-aged individuals, in urban-metros, among less educated and in households with lower income. Treatment gap for overall mental morbidity was 84.5%. CONCLUSION: NMHS is the largest reported survey of mental morbidity in India. Survey estimated that nearly 150 million individuals suffer from one or the other mental morbidity in India. This information is to be used for planning, delivery and evaluating mental health programming in the country.

Management of a pathological fracture in a rare case of Gorham Stout disease of the hip with a mega prosthesis.

Gorham-Stout disease (GSD) is a rare bone disease of unknown etiology, characterized by spontaneous and progressive resorption of bones. This disease occurs most commonly in males of the age group of fewer than 40 years and has no genetic predisposition. It most commonly affects the skull, spine, pelvis and shoulder girdle. The diagnosis of GSD is established based on the combination of clinical, radiologic, and histological features, after excluding other diseases. There is no standard treatment for it so far, and the therapy depends on patient's clinical condition and may include surgery, radiotherapy, and drugs, with varying degrees of success. To the best of our knowledge such involvement of hip and its treatment by a megaprosthesis, in an elderly lady by GSD has not been reported. This case report describes an unusual presentation of the disease of the hip in an elderly female successfully treated with replacement of the deficient proximal femur by using a bipolar hip mega prosthesis of the hip (XLO, India).