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1.
AIDS Care ; 21(4): 473-81, 2009 Apr.
Article in English | MEDLINE | ID: mdl-19283642

ABSTRACT

This study examines psycho-social impact of HIV and quality of life of 646 HIV-infected persons from a major government sexually transmitted disease (STD) clinic in South India. In this cross-sectional study, data was collected using interview schedule and scales. Nearly 70% had problems in parenting their children after acquiring the infection. Most (88%) of the respondents reported of seeking help from their family members, relatives or close friends at the time of their illness. Among the four categories of stigma, most of them (96%) reported perceived stigma whereas actual stigma was mentioned by only 33%. All four categories of stigma were experienced on a higher proportion by females than males (p<0.05). Each type of stigma was significantly associated with each domain of quality of life of the respondents (p<0.005). Respondents who reported of actual stigma (33%) had significantly good quality of life in their physical domain (49%), psychological domain (48%) and environmental domain (44%). Multivariate analysis showed that gender and marital status had significant association with quality of life. The findings of the study underscore the need for enabling environment through "human force" to uplift their social status and to have a better quality of life.


Subject(s)
HIV Infections/psychology , Quality of Life/psychology , Stereotyping , Adaptation, Psychological , Adult , Cross-Sectional Studies , Female , Humans , India , Male , Middle Aged , Prejudice , Social Support , Socioeconomic Factors , Young Adult
2.
Indian Pediatr ; 36(6): 555-9, 1999 Jun.
Article in English | MEDLINE | ID: mdl-10736582

ABSTRACT

OBJECTIVE: To explore the usefulness of Lot Quality Assurance Sampling (LQAS) to identify divisions in a city that had immunization coverage levels of 80% for any of the four EPI vaccines. METHODS: Only 43 divisions were considered for the study, the stratification factor being the death rate. The hypothesis that 80% coverage is 'unacceptable' was stipulated. Critical value (the number of unimmunized children) was chosen as 3. A simple random sample of 36 children in the age-group 12-23 months was taken from each selected division. Since sampling frames of children were not available, a simple random sample of 36 households was selected. Immunization status of each child was assessed by interviewing the child's mother/guardian. If the number of unimmunized children exceeded 3, then the division was regarded having coverage level 80% and rejected. RESULTS: The coverage was classified as unacceptable(i. e., below 80%) in 19 divisions for Polio and DPT vaccines, in 26 divisions for Measles vaccine and in 4 divisions for BCG vaccine. The average time spent for undertaking the LQAS survey was 6 man-days per division. CONCLUSION: This study demonstrated the utility of the LQAS technique in identifying 'unsatisfactory' pockets in Madras City, when the overall coverage was satisfactory. The technique will have greater application with an increase in the number of large units (cities/districts) having an overall coverage of 90% or more.


Subject(s)
Immunization Programs/standards , Quality Assurance, Health Care/methods , Health Care Surveys , Health Services Accessibility/statistics & numerical data , Humans , India , Infant , Quality Control , Sampling Studies
3.
Indian Pediatr ; 32(3): 383-90, 1995 Mar.
Article in English | MEDLINE | ID: mdl-8613305

ABSTRACT

A concurrent comparison of the WHO 30-cluster sample survey method for estimating immunization coverages (DPT, Polio, BCG, Measles) and an Indian modification of (GOI) was undertaken in five districts in South India. The essential difference between the two methods is the manner in which the first household is selected in the chosen clusters. With the WHO method, it is chosen clusters. With the WHO method, it is chosen at random, whereas with the GOI method it is often close to the village centre. Estimates with the required degree of precision, i.e., 95% confidence limits of +/- 10 percentage points, were provided in 18 (90%) of 20 instances by the WHO method and in 19 (95%) by the GOI method, findings which are in accordance with expectation. The estimated coverages were, however, higher by the GOI method than by the WHO method in two districts, lower in one district, and in the remaining two districts there was no clear pattern. On the average, there was a suggestion that the GOI method yielded slightly higher coverages, but the differences were not statistically significant.


Subject(s)
Health Surveys , Immunization/statistics & numerical data , Research Design , Humans , India , Infant , Selection Bias , World Health Organization
4.
Indian Pediatr ; 32(1): 129-35, 1995 Jan.
Article in English | MEDLINE | ID: mdl-8617527

ABSTRACT

A 30-cluster survey method that is employed for estimating immunization coverages by the Government of India (GOI) was compared with a Purposive method, to investigate whether the likely omission of SC/ST and backward classes in the former would lead to the reporting of higher coverages. The essential difference between the two methods is in the manner in which the first household is selected in the chosen first stage sampling units (villages). With the GOI method, it is often close to the village centre, whereas with the Purposive method it is always in the periphery or in a pocket consisting of SC/ST or backward classes. A concurrent comparison of the two methods in three districts in Tamil Nadu showed no real differences in the coverage with DPT and BCG vaccines. However, the coverage was consistently higher by the GOI method in the case of the Polio vaccine (by 1.5%, 3.1% and 5.3% in the 3 districts), and the Measles vaccine (by 4.8%, 13.3% and 13.9%); the average difference was 3.3% for Polio vaccine (p = 0.08) and 7.3% for Measles vaccine (p = 0.01).


Subject(s)
Immunization/statistics & numerical data , Population Surveillance/methods , Research Design , Selection Bias , Analysis of Variance , Humans , India , Infant , Socioeconomic Factors
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