Background: Normal personality development, gone awry due to genetic or environmental factors, results in personality disorders (PD). These often coexist with other psychiatric disorders, affecting their outcome adversely. Considering the heterogeneity of data, more research is warranted. Methods: This was a cross-sectional study on personality traits in psychiatric patients of a tertiary hospital, over 1 year. Five hundred and twenty-five subjects, aged 18–45 years, with substance, psychotic, mood, or neurotic disorders were selected by convenience sampling. They were evaluated for illness-related variables using psychiatric pro forma; diagnostic confirmation and severity assessment were done using ICD-10 criteria and suitable scales. Personality assessment was done using the International Personality Disorder Examination after achieving remission. Results: Prevalence of PD traits and PDs was 56.3% and 4.2%, respectively. While mood disorders were the diagnostic group with the highest prevalence of PD traits, it was neurotic disorders for PDs. Patients with PD traits had a past psychiatric history and upper middle socioeconomic status (SES); patients with PDs were urban and unmarried. Both had a lower age of onset of psychiatric illness. Psychotic patients with PD traits had higher and lower PANSS positive and negative scores, respectively. The severity of personality pathology was highest for mixed cluster and among neurotic patients. Clusterwise prevalence was cluster C > B > mixed > A (47.1%, 25.2%, 16.7%, and 11.4%). Among subtypes, anankastic (18.1%) and mixed (16.7%) had the highest prevalence. Those in the cluster A group were the least educated and with lower SES than others. Conclusions: PD traits were present among 56.3% of the patients, and they had many significant sociodemographic and illness-related differences from those without PD traits. Cluster C had the highest prevalence. Among patients with psychotic disorders, those with PD traits had higher severity of psychotic symptoms.

Background: Duration of untreated psychosis (DUP) is an important modifiable factor affecting schizophrenia outcomes. A dearth of research in India on untreated versus treated schizophrenia warrants further research. Methods: This was a longitudinal study in a tertiary hospital over 2 years. Inpatients diagnosed with schizophrenia ( N = 116), aged 18–45, were divided into untreated and treated groups. Diagnostic confirmation, severity assessment, and clinical outcome were done using ICD-10 criteria, Positive and Negative Syndrome Scale (PANSS), and Clinical Global Impression (CGI) scale. Follow-up was done at 12 and 24 weeks. DUP was measured, and its association with the outcome was assessed. Results: Final analysis included 100 patients, 50 each of previously untreated and treated. Untreated patients had lower age and duration of illness (DOI), but higher DUP ( p < .001). Treated patients showed much improvement on CGI-I at 12 weeks ( p = .029), with no difference at 24 weeks. PANSS severity comparison showed no difference, and both groups followed a declining trend. In untreated patients, age of onset (AoO) was negatively correlated with severity (except general symptoms at baseline) at all follow-ups (‘ r’ range = −0.32 to –0.49, p < .05), while DOI showed a positive correlation with negative and general symptoms at 12 weeks ( r ~ 0.3, p < .05). Treated patients showed inconsistent and lower negative correlation between AoO and PANSS, with no correlation between severity and DOI. The mean sample DUP was 17.9 ± 31.6 weeks; it negatively correlated with education ( r = –0.25, p = .01) and positively with PANSS severity (‘ r’ range = 0.22 to 0.30, p < .05) at all follow-ups, especially negative symptoms. Patients with no or minimal improvement on CGI at 24 weeks had higher DUP (Quade’s ANOVA F[1,98] = 6.24, p = .014). Conclusion: Illness variables in untreated schizophrenia affect severity, which has delayed improvement than treated schizophrenia. Higher DUP is associated with negative symptoms of schizophrenia.

Introduction: Migraine is the most common cause of vascular headache with a one-year prevalence as high as 6-14.3%. Having various pathophysiological theories, it occurs in much co-morbidity with several medical as well as psychiatric disorders like mood disorders, phobia, anxiety spectrum, etc. Migraine, especially when co-morbid with psychiatric illness stands markedly burdensome economically, diagnostically, therapeutically and prognostically. Hence, needs even further research. Aim: To study patients with migraine versus other types of headache and to study psychiatric co-morbidity among patients with migraine. Materials and Methods: This cross-sectional study was conducted on total 100 patients presenting with headache, meeting the criteria were taken up for the study and divided into two groups. Patients meeting International Headache Society (IHS) criteria for migraine were enrolled under group A and patients suffering from headache other than migraine under group B. Having subjected to detailed history and evaluation, patients were subjected to Symptom checklist-80, Hamilton’s Anxiety Rating Scale (HARS) and Montgomery Asberg Depression Rating Scale (MADRS), International Classification of Diseases (ICD)-10 criteria. The data so collected was subjected to statistical analysis and association of psychiatric morbidity with migraine patients was assessed. Results: Patients with migraine (group A) and among those too, patients having psychiatric morbidity had significantly (p<0.01) longer duration of illness (≥8 years), more frequent attacks ≥5 attacks per month and had longer duration of each attack >24 hours compared to the other groups. Patients having migraine had significantly (p<0.01) higher psychiatric morbidity, more SCL-80 symptoms (mean score 83.05); more depressive symptoms (mean MADRS score was 31.9±9.2) and more anxiety with the mean Hamilton Anxiety score was 23.3 than in patients without psychiatric morbidity. Conclusion: A thorough evaluation of psychiatric disorders in migraine is important so as to propose a non segregated model of care to direct the burden and deterioration associated with psychiatric co-morbidity in migraine.

Introduction: Adherence to drug regimen is a very important factor for improvement. Dropping out may affect the treatment outcome and also is as indication of poor clinical performance. Patient who left the treatment in between can lead to a deterioration in clinical condition, resulting in the need for more intensive therapy that significantly incurs higher social and economic loss. Therefore, improving medication compliance potentially reduces morbidity and suffering of patients and their families, and the cost of rehospitalisation. Aim: To study the pattern of follow-up among patients of various psychiatric disorders and also to study the therapist factors contributing in adherence to treatment and the sociodemographic profile of patients who drop out from study. Materials and Methods: This was a prospective analytical study conducted in the Department of Psychiatry, GGSMCH Faridkot, Punjab, India over one year. A total of 500 psychiatric patients were selected by the convenient non probability sampling technique in the age group between 18-45 years who met the inclusion criteria. These patients were evaluated for illness related variables using psychiatric proforma and Charleston Psychiatric Outpatient Satisfaction Scale (CPOSS) was applied. After this all the patients were assessed for a period of one year, the factors affecting the pattern of follow-up, relating to the treatment and its side effects, disease progression as well as therapist-related factors using a semi-structured questionnaire. The data, thus generated, was subjected to appropriate statistical analysis. Results: In the socio-demographic profile among drop out education status, occupation, and duration of illness, statistically significant difference was found among different disorders (p<0.05). CPOSS scale was applied among three follow-up groups in which highest mean was 53.03±10.05 in regular follow-up group followed by 49.49±9.06 in intermittent and 44.80±10.70 in drop out follow-up group. Total CPOSS mean was 49.19±10.66. Overall results were statistically significant (p=0.0001). Also in the medication, disease and physician related factors among followup groups, statistically significant results were found (p<0.05). Conclusion: The study showed that various socio-demographic factors, medication, disease and physician related factors affect the follow-up patterns. So, it is very important to diagnose all these factors to improve adherence among various psychiatric patients.