9 research outputs found
Environmental Factors Influencing Arab Qatari Women’s Breast Cancer Screening: Health Care Practitioners’ Perspective
Breast cancer, the most common cancer among Arab women in Qatar, significantly affects the morbidity and mortality of Arab women largely because of delayed diagnosis related to low participation rates in breast cancer screening (BCS). To understand the reasons for the low participation rates, a critical ethnographic study was conducted with 15 health care practitioners in Qatar. Thematic analysis of the interview data resulted in identification of environmental factors influencing participation in BCS: (a) gender friendly health care services, (b) lack of a national BCS protocol, (c) time constraints, (d) deficiencies in the patient health records system, (e) cost for mammograms, and (f) transportation. A recurring theme across the factors was that, from the perspective of health care practitioners, Arab women’s health cannot be understood in isolation from the environment in which they live. Interventions that promote BCS practices must address the contextual factors that impact health of the population. 
Responsiveness of the Eating Disorders Quality of Life Scale (EDQLS) in a longitudinal multi-site sample
<p>Abstract</p> <p>Background</p> <p>In eating disorders (EDs), treatment outcome measurement has traditionally focused on symptom reduction rather than functioning or quality of life (QoL). The Eating Disorders Quality of Life Scale (EDQLS) was recently developed to allow for measurement of broader outcomes. We examined responsiveness of the EDQLS in a longitudinal multi-site study.</p> <p>Methods</p> <p>The EDQLS and comparator generic QoL scales were collected in person at baseline, and 3 and 6 months from 130 participants (mean age 25.6 years; range 14-60) in 12 treatment programs in four Canadian provinces. Total score differences across the time points and responsiveness were examined using both anchor- and distribution-based methods.</p> <p>Results</p> <p>98 (75%) and 85 (65%) responses were received at 3 and 6 months respectively. No statistically significant differences were found between the baseline sample and those lost to follow-up on any measured characteristic. Mean EDQLS total scores increased from 110 (SD = 24) to 124.5 (SD = 29) at 3 months and 129 (SD = 28) at 6 months, and the difference by time was tested using a general linear model (GLM) to account for repeated measurement (p < .001). Responsiveness was good overall (Cohen's d = .61 and .80), and confirmed using anchor methods across 5 levels of self-reported improvement in health status (p < .001). Effect sizes across time were moderate or large for for all age groups. Internal consistency (Chronbach's alpha=.96) held across measurement points and patterns of responsiveness held across subscales. EDQLS responsiveness exceeded that of the Quality of Life Inventory, the Short Form-12 (mental and physical subscales) and was similar to the 16-dimension quality of life scale.</p> <p>Conclusions</p> <p>The EDQLS is responsive to change in geographically diverse and clinically heterogeneous programs over a relatively short time period in adolescents and adults. It shows promise as an outcome measure for both research and clinical practice.</p
Situating power and knowledge in adolescent (mental) health promotion
Bibliography : p. 242-260Copyright Clearance Form: yUAR
"Situating power and knowledge in ' adolescent (mental) health promotion'"
Bibliography: p. 242-26
Responsiveness of the Eating Disorders Quality of Life Scale (EDQLS) in a longitudinal multi-site sample
Abstract
Background
In eating disorders (EDs), treatment outcome measurement has traditionally focused on symptom reduction rather than functioning or quality of life (QoL). The Eating Disorders Quality of Life Scale (EDQLS) was recently developed to allow for measurement of broader outcomes. We examined responsiveness of the EDQLS in a longitudinal multi-site study.
Methods
The EDQLS and comparator generic QoL scales were collected in person at baseline, and 3 and 6 months from 130 participants (mean age 25.6 years; range 14-60) in 12 treatment programs in four Canadian provinces. Total score differences across the time points and responsiveness were examined using both anchor- and distribution-based methods.
Results
98 (75%) and 85 (65%) responses were received at 3 and 6 months respectively. No statistically significant differences were found between the baseline sample and those lost to follow-up on any measured characteristic. Mean EDQLS total scores increased from 110 (SD = 24) to 124.5 (SD = 29) at 3 months and 129 (SD = 28) at 6 months, and the difference by time was tested using a general linear model (GLM) to account for repeated measurement (p < .001). Responsiveness was good overall (Cohen's d = .61 and .80), and confirmed using anchor methods across 5 levels of self-reported improvement in health status (p < .001). Effect sizes across time were moderate or large for for all age groups. Internal consistency (Chronbach's alpha=.96) held across measurement points and patterns of responsiveness held across subscales. EDQLS responsiveness exceeded that of the Quality of Life Inventory, the Short Form-12 (mental and physical subscales) and was similar to the 16-dimension quality of life scale.
Conclusions
The EDQLS is responsive to change in geographically diverse and clinically heterogeneous programs over a relatively short time period in adolescents and adults. It shows promise as an outcome measure for both research and clinical practice