18 resultados para Quality of information


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This study examined if a person’s quality of life could be predicted by six relevant factors in a sample of 114 individuals with intellectual disability who had moved from institutional settings to community living settings within Ontario. Further, two aspects of self-efficacy were tested to see if they moderated the relationship between the possible predictors and the quality of life indicator. The initial multiple regression model accounted for a very small amount of the variance in the outcome (r2 = .08). The second analysis included decision-making as a predictor (r2 = .35) but did not find it to be moderator. The third analysis used opportunities for change as a predictor (r2 = .28), and as a moderator with two significant interaction terms, health and years in an institutional setting (r2 = .35). These findings support the often-theorized influence of self-efficacy on quality of life for individuals with intellectual disability.

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As the dementia spectrum lacks any viable cure, quality of life is typically regarded as an essential measure of assessing the clinical course and evaluating interventions. With caregivers typically providing this rating to health professionals, the literature has noted inconsistencies between caregiver and person with dementia (PwD) ratings of quality of life and suggested several factors may moderate the rating relationship. To investigate this, an intraclass correlation coefficient was calculated to observe rating agreement and moderator regression analysis was conducted to explore potential moderators. Potential moderators of caregiver burden, caregiver age, caregiver income, PwD IADLs/ADLs, PwD education, PwD cognitive impairment, PwD depressive symptom severity, PwD behavioural symptom severity, as well as relationship between caregiver and PwD. Utilizing secondary data from 107 recruited dyads, analyses conducted found fair agreement between caregivers and those with dementia while none of the hypothesized factors were found to moderate the rating relationship.

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Objective: To determine which socio-demographic, exposure, morbidity and symptom variables are associated with health-related quality of life among former and current heavy smokers. Methods: Cross sectional data from 2537 participants were studied. All participants were at ≥2% risk of developing lung cancer within 6 years. Linear and logistic regression models utilizing a multivariable fractional polynomial selection process identified variables associated with health-related quality of life, measured by the EQ-5D. Results: Upstream and downstream associations between smoking cessation and higher health-related quality of life were evident. Significant upstream associations, such as education level and current working status and were explained by the addition of morbidities and symptoms to regression models. Having arthritis, decreased forced expiratory volume in one second, fatigue, poor appetite or dyspnea were most highly and commonly associated with decreased HRQoL. Discussion: Upstream factors such as educational attainment, employment status and smoking cessation should be targeted to prevent decreased health-related quality of life. Practitioners should focus treatment on downstream factors, especially symptoms, to improve health-related quality of life.