359 research outputs found
Can we identify the poorest quality of life? Assessing the importance of quality of life using the WHOQOL-100
Assessing health and well-being among older people in rural South Africa
Background: The population in developing countries is ageing, which is likely to increase the burden of noncommunicable diseases and disability.
Objective: To describe factors associated with self-reported health, disability and quality of life (QoL) of older people in the rural northeast of South Africa.
Design: Cross-sectional survey of 6,206 individuals aged 50 and over. We used multivariate analysis to examine relationships between demographic variables and measures of self-reported health (Health Status), functional ability (WHODASi) and quality of life (WHOQoL).
Results: About 4,085 of 6,206 people eligible (65.8%) completed the interview. Women (Odds Ratio (OR)
1.30, 95% CI 1.09, 1.55), older age (OR2.59, 95% CI 1.97, 3.40), lower education (OR1.62, 95% CI 1.31,2.00), single status (OR1.18, 95% CI 1.01, 1.37) and not working at present (OR1.29, 95% CI 1.06, 1.59) were associated with a low health status. Women were also more likely to report a higher level of disability (OR1.38, 95% CI 1.14, 1.66), as were older people (OR2.92, 95% CI 2.25, 3.78), those with no education (OR1.57, 95% CI 1.26, 1.97), with single status (OR1.25, 95% CI 1.06, 1.46) and not working at present (OR1.33, 95% CI 1.06, 1.66). Older age (OR1.35, 95% CI 1.06, 1.74), no education (OR1.39, 95% CI
1.11, 1.73), single status (OR1.28, 95% CI 1.10, 1.49), a low household asset score (OR1.52, 95% CI 1.19,
1.94) and not working at present (OR1.32; 95% CI 1.07, 1.64) were all associated with lower quality of life.
Conclusions: This study presents the first population-based data from South Africa on health status, functional ability and quality of life among older people. Health and social services will need to be restructured to provide effective care for older people living in rural South Africa with impaired functionality and other health problems
BSRS-5 (5-item Brief Symptom Rating Scale) scores affect every aspect of quality of life measured by WHOQOL-BREF in healthy workers
This study aims to evaluate and quantify the possible effect of psychological symptoms on healthy workers' quality of life (QOL). The workers were recruited from a factory in south Taiwan. We assessed their psychological symptoms with a 5-item brief symptom rating scale (BSRS-5) and measured the QOL using the Taiwanese version of the World Health Organization Quality of Life (WHOQOL)-BREF. Multiple linear regression analysis was conducted to explore the association between the two tools after control of confounding by other predictors. A total of 1,080 workers , who attended a physical examination, completed questionnaires and informed consent forms. Scores on the BSRS-5 significantly predicted scores in each domain and items of the WHOQOL-BREF. The magnitude of psychological domain score seemed to be affected the most; every 1 point increase in BSRS-5 was associated with a 0.39 raw score (equivalent to 2. 44 percentile) decrease in QOL. The sleep facet of WHOQOL appeared to have the highest association, followed by items of negative feelings, energy, and concentration. The BSRS-5 score is predictive for scores of all four domains and 26 items of the Taiwanese version of the WHOQOL-BREF for regular factory workers
Health-related Quality of Life in Adult Patients with Morbid Obesity Coming for Bariatric Surgery
Healthcare in schizophrenia: effectiveness and progress of a redesigned care network
<p>Abstract</p> <p>Background</p> <p>The aim of this study was designed to investigate the care-effectiveness of different healthcare models for schizophrenic patients and the impact of it on caregivers.</p> <p>Methods</p> <p>Sample cases were randomly selected from southern Taiwan, 257 patients in redesigned care network, including a general hospital, a chronic ward, 10 outpatient clinics, and multialternative community programs, was compared to 247 patients in other traditional healthcare provider that were utilized as the control group. The quality of life (QOL) questionnaire and the Chinese health questionnaire (CHQ) were used.</p> <p>Results</p> <p>The controls had longer duration of illness (<it>p </it>= 0.001) and were older (<it>p </it>= 0.004). The average resource utilization in the study group (US 2041) (<it>t </it>= 7.91, <it>p </it>< 0.001). For the study group, the average length of stay was shorter, but the admission rate was higher. The QOL of the patients in the study group was better than that of the controls (<it>p </it>= 0.01). The family burden of the study group was lower (<it>p </it>= 0.035) and the score of general health questionnaire higher (<it>p </it>= 0.019).</p> <p>Conclusion</p> <p>We found that patients in the redesigned care network had a better QOL, lower family burden, decreased days of hospital stay, higher medical resource utilization and less frequent admission to a hospital, and the caregivers had better mental health. Although the costs were higher, the continued care network was more helpful in providing comprehensive mental illness services.</p
Development and validation of a WHOQOL-BREF Taiwanese audio player-assisted interview version for the elderly who use a spoken dialect
Profiles of physical, emotional and psychosocial wellbeing in the Lothian birth cohort 1936
<p>Abstract</p> <p>Background</p> <p>Physical, emotional, and psychosocial wellbeing are important domains of function. The aims of this study were to explore the existence of separable groups among 70-year olds with scores representing physical function, perceived quality of life, and emotional wellbeing, and to characterise any resulting groups using demographic, personality, cognition, health and lifestyle variables.</p> <p>Methods</p> <p>We used latent class analysis (LCA) to identify possible groups.</p> <p>Results</p> <p>Results suggested there were 5 groups. These included High (n = 515, 47.2% of the sample), Average (n = 417, 38.3%), and Poor Wellbeing (n = 37, 3.4%) groups. The two other groups had contrasting patterns of wellbeing: one group scored relatively well on physical function, but low on emotional wellbeing (Good Fitness/ Low Spirits,n = 60, 5.5%), whereas the other group showed low physical function but relatively well emotional wellbeing (Low Fitness/Good Spirits, n = 62, 5.7%). Salient characteristics that distinguished all the groups included smoking and drinking behaviours, personality, and illness.</p> <p>Conclusions</p> <p>Despite there being some evidence of these groups, the results also support a largely one-dimensional construct of wellbeing in old age—for the domains assessed here—though with some evidence that some individuals have uneven profiles.</p
A pilot randomized controlled trial of a stepped care intervention package for depression in primary care in Nigeria
Background
Depression is common in primary care and is often unrecognized and untreated. Studies are needed to demonstrate the feasibility of implementing evidence-based depression care provided by primary health care workers (PHCWs) in sub-Saharan Africa. We carried out a pilot two-parallel arm cluster randomized controlled trial of a package of care for depression in primary care.
Methods
Six primary health care centers (PHCC) in two Local Government Areas of Oyo State, South West Nigeria were randomized into 3 intervention and 3 control clinics. Three PHCWs were selected for training from each of the participating clinics. The PHCWs from the intervention clinics were trained to deliver a manualized multicomponent stepped care intervention package for depression consisting of psychoeducation, activity scheduling, problem solving treatment and medication for severe depression. Providers from the control clinics delivered care as usual, enhanced by a refresher training on depression diagnosis and management. Outcome measures Patient’s Health Questionnaire (PHQ-9), WHO quality of Life instrument (WHOQOL-Bref) and the WHO disability assessment schedule (WHODAS) were administered in the participants’ home at baseline, 3 and 6 months.
Results
About 98% of the consecutive attendees to the clinics agreed to have the screening interview. Of those screened, 284 (22.7%) were positive (PHQ-9 score ≥ 8) and 234 gave consent for inclusion in the study: 165 from intervention and 69 from control clinics. The rates of eligible and consenting participants were similar in the control and intervention arms. In all 85.9% (92.8% in intervention and 83% in control) of the participants were successfully administered outcome assessments at 6 months. The PHCWs had little difficulty in delivering the intervention package. At 6 months follow up, depression symptoms had improved in 73.0% from the intervention arm compared to 51.6% control. Compared to the mean scores at baseline, there was improvement in the mean scores on all outcome measures in both arms at six months.
Conclusion
The results provide support for the feasibility of conducting a fully-powered randomized study in this setting and suggest that the instruments used may have the potential to detect differences between the arms
Psychosocial factors and health as determinants of quality of life in community-dwelling older adults.
PURPOSE: It is important to understand the determinants of differences in quality of life in old age and to include a wide range of possible predictors. The present study investigated the determinants of quality of life in two groups of older adults for whom there was an unusually informative set of possible predictor variables. METHOD: Participants were members of the Lothian Birth Cohorts of 1921 (n = 550) or 1936 (n = 1,091). Four facets of quality of life (QoL) and general QoL were measured using the WHOQOL-BREF. Possible determinants included personality traits, measured with the International Personality Item Pool (IPIP) scales; childhood and old age general cognitive ability, measured with the Moray House Test; minor psychological symptoms, measured with the Hospital Anxiety and Depression Scale (HADS); physical health, assessed by grip strength and cardiovascular disease history; and sociodemographic factors, assessed by interview. RESULTS: Linear regression analyses revealed that HADS depression had the greatest influence on quality of life. Personality traits, most notably Emotional Stability, also predicted quality of life to varying degrees, along with factors reflecting current life circumstances. There were differences between the two cohorts in the variables which predicted quality of life. There were different, conceptually relevant, contributions to the different QoL facets. CONCLUSIONS: Personality traits and minor depressive symptoms have an important influence on self-reported quality of life in old age. Quality of life may be influenced more by current than past circumstances, and this relationship may change with age
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