Objective: To study the pattern of psychotropic prescription among Thai bipolar outpatients by using cross sectional study. Methods: This is a cross-section study of bipolar outpatients treated in 4 general and psychiatric hospitals during January to March 2005. Results: Two hundred eighty-four outpatients with the age of 15 year olds or more were enrolled. The psychotropic prescribing pattern in Thai bipolar patients is similar to those found in US and UK studies. Valproate was the most frequently prescribed medication followed closely by lithium. Aypical antipsychotics were the third. The only exceptions are the smaller number of antidepressant uses and the more frequent use of typical antipsychotics in Thai patients. Conclusions: The study shows the similar psychotropic prescribing pattern given to Thai bipolar outpatients as compare to those in US and UK. The major differences are that Thai clinicians prescribed more typical antipsychotics and less antidepressants.

Objective: To study the pattern of psychotropic prescription among Thai bipolar outpatients by using cross sectional study. Methods: This is a cross-section study of bipolar outpatients treated in 4 general and psychiatric hospitals during January to March 2005. Results: Two hundred eighty-four outpatients with the age of 15 year olds or more were enrolled. The psychotropic prescribing pattern in Thai bipolar patients is similar to those found in US and UK studies. Valproate was the most frequently prescribed medication followed closely by lithium. Aypical antipsychotics were the third. The only exceptions are the smaller number of antidepressant uses and the more frequent use of typical antipsychotics in Thai patients. Conclusions: The study shows the similar psychotropic prescribing pattern given to Thai bipolar outpatients as compare to those in US and UK. The major differences are that Thai clinicians prescribed more typical antipsychotics and less antidepressants.

Objective: To determine the cost of treatment for schizophrenic patients in Social Security scheme, Thailand. Methods: The paper reviewed available evidence in Thailand on the cost of schizophrenia treatment in different hospital settings and data of health service utilization obtained from various sources. The sensitivity analysis of direct health care cost of schizophrenia was conducted in social security system, both in outpatient and inpatient services. The cost for schizophrenia coverage per individual social security applicant was estimated in different contexts. Results: The total cost of treatment depends on the service utilization rate and unit cost of treatment. The annual direct health care cost of schizophrenic outpatients in Thai social security scheme was averagely estimated at about 171 million Baht. (Range: 28.5 million to 372 million Baht in sensitivity analysis). The annual direct health care cost of schizophrenic inpatients in Thai social security scheme was averagely estimated about 265.3 million Baht (Range; 22.7 million to 531 million Baht in sensitivity analysis). Aggregation the outpatient and inpatient treatment for schizophrenic employees accounted for 436.5 million Baht/year (Range from 436.5 million to 903 million Baht). The cost for schizophrenia coverage per individual social security applicant was about 48 Baht/year. (Range 5.63 Baht to 99.22 Baht). Conclusion: This study illustrated the cost of schizophrenia treatment in Thai social security scheme in various contexts, which might be useful in planning, preparing, budgeting and decision making. However, the huge societal impacts of schizophrenia should be carefully considered for policy makers.

Introduction: Domestic violence, now a national health concern, has pervasive effects at both individual and social levels. The objective of this study was to survey the prevalence of DV, the characteristics and the impact of the violence among married women living in the slum communities of metropolitan Bangkok, Thailand. Methods: A cross-sectional survey was carried out. A total of 580 married women aged 15 years and above were randomly sampled from seven slum communities in Bangkok. Information on age, education, occupation, income, family size, alcohol use, and experience of DV were collected. Results: The prevalence of DV was 27.2%. Most of the violent episodes were triggered either by factors related to personal characteristic of the couples, such as bad temper (89.9%) and being grumpy (83.5%), or circumstantial factors, such as financial problems (74.7%) and suspicion of adultery (28.5%). Twelve per cent of the abuse episodes were moderate violence, and 34.2% was severe violence. The impacts of victims of violence included mental, family, and social problems. The mental impacts, e.g., anxiety, stress and nervousness were found in 79.1%. Others were sad, unhappy, and depressed at 68.4%. Of those, 50.3% could not control their emotion, got angry easily, and threw things. Other important mental episodes were that they wanted to harm others or revenge at 19% and injured themselves or committed suicide at 17.1%. The last was negative attitude about sex at 12.2%. Conclusion: DV is common in slum communities and highly related to socioeconomic status, personality characteristics, and alcohol consumption of the couples.

Introduction: Domestic violence, now a national health concern, has pervasive effects at both individual and social levels. The objective of this study was to survey the prevalence of DV, the characteristics and the impact of the violence among married women living in the slum communities of metropolitan Bangkok, Thailand. Methods: A cross-sectional survey was carried out. A total of 580 married women aged 15 years and above were randomly sampled from seven slum communities in Bangkok. Information on age, education, occupation, income, family size, alcohol use, and experience of DV were collected. Results: The prevalence of DV was 27.2%. Most of the violent episodes were triggered either by factors related to personal characteristic of the couples, such as bad temper (89.9%) and being grumpy (83.5%), or circumstantial factors, such as financial problems (74.7%) and suspicion of adultery (28.5%). Twelve per cent of the abuse episodes were moderate violence, and 34.2% was severe violence. The impacts of victims of violence included mental, family, and social problems. The mental impacts, e.g., anxiety, stress and nervousness were found in 79.1%. Others were sad, unhappy, and depressed at 68.4%. Of those, 50.3% could not control their emotion, got angry easily, and threw things. Other important mental episodes were that they wanted to harm others or revenge at 19% and injured themselves or committed suicide at 17.1%. The last was negative attitude about sex at 12.2%. Conclusion: DV is common in slum communities and highly related to socioeconomic status, personality characteristics, and alcohol consumption of the couples.

Background: The Medical Outcomes Study 36-item Short Form (SF-36) is a widely used measure of health-related quality of life. Normative data are the key to determine whether a group or an individual score above or below the average for their country, age or sex. Published norms for the SF-36 exist for other countries but have not been previously published for Thailand. Methods: The multi-site studies of Thai Quality of Health were the cross- sectional study involving 1,148 randomly selected Thai men and women aged 15 years or more living in Bangkok metropolitan. The information collected included the SF-36, a measure of healthrelated quality of life. These provided a unique opportunity to develop age- and sex-adjusted normative data for the Thai population. Results: Thai women scored substantially higher than men on role physical, bodily pain, role emotional and physical component summary, whereas men scored higher than women on social functioning. Conclusion: The scores of Bangkok people are lower than their US counterparts on all SF-36 domains, although many of the differences were not large. The differences in the SF-36 scores between age groups, sexes and countries confirm that these Thai norms are necessary for comparative purposes. The data will be useful for assessing the health status of the general population and patient populations, and the effect of interventions on health-related quality of life.