Screening for colorectal cancer (CRC) is associated with reduced CRC mortality, but low screening rates have been reported in several settings. The aim of the study was to assess predictors of low CRC screening in Switzerland. A retrospective cohort of a random sample of 940 patients aged 50-80 years followed for 2 years from four Swiss University primary care settings was used. Patients with illegal residency status and a history of CRC or colorectal polyps were excluded. We abstracted sociodemographic data of patients and physicians, patient health status, and indicators derived from RAND's Quality Assessment Tools from medical charts. We defined CRC screening as colonoscopy in the last 10 years, flexible sigmoidoscopy in the last 5 years, or fecal occult blood testing in the last 2 years. We used bivariate and multivariate logistic regression analyses. Of 940 patients (mean age 63.9 years, 42.7% women), 316 (33.6%) had undergone CRC screening. In multivariate analysis, birthplace in a country outside of Western Europe and North America [odds ratio (OR) 0.65, 95% confidence interval (CI) 0.45-0.97], male sex of the physician in charge (OR 0.67, 95% CI 0.50-0.91), BMI 25.0-29.9 kg/m2 (OR 0.66, CI 0.46-0.96) and at least 30.0 kg/m2 (OR 0.61, CI 0.40-0.90) were associated with lower CRC screening rates. Obesity, overweight, birthplace outside of Western Europe and North America, and male sex of the physician in charge were associated with lower CRC screening rates in Swiss University primary care settings. Physician perception of obesity and its impact on their recommendation for CRC screening might be a target for further research.
One in 12 young Swiss men use nasal dry snuff and 3% use snus. Consumption of smokeless tobacco is associated with a cluster of other risky behaviours, especially binge drinking.
BackgroundShared Decision Making (SDM) is increasingly advocated as a model for medical decision making. However, there is still low use of SDM in clinical practice. High impact factor journals might represent an efficient way for its dissemination. We aimed to identify and characterize publication trends of SDM in 15 high impact medical journals.MethodsWe selected the 15 general and internal medicine journals with the highest impact factor publishing original articles, letters and editorials. We retrieved publications from 1996 to 2011 through the full-text search function on each journal website and abstracted bibliometric data. We included publications of any type containing the phrase “shared decision making” or five other variants in their abstract or full text. These were referred to as SDM publications. A polynomial Poisson regression model with logarithmic link function was used to assess the evolution across the period of the number of SDM publications according to publication characteristics.ResultsWe identified 1285 SDM publications out of 229,179 publications in 15 journals from 1996 to 2011. The absolute number of SDM publications by journal ranged from 2 to 273 over 16 years. SDM publications increased both in absolute and relative numbers per year, from 46 (0.32% relative to all publications from the 15 journals) in 1996 to 165 (1.17%) in 2011. This growth was exponential (P < 0.01). We found fewer research publications (465, 36.2% of all SDM publications) than non-research publications, which included non-systematic reviews, letters, and editorials. The increase of research publications across time was linear. Full-text search retrieved ten times more SDM publications than a similar PubMed search (1285 vs. 119 respectively).ConclusionThis review in full-text showed that SDM publications increased exponentially in major medical journals from 1996 to 2011. This growth might reflect an increased dissemination of the SDM concept to the medical community.
The study aimed at assessing the link between physical activity (PA), sports activity and snus use among young men in Switzerland. Data from the Cohort Study on Substance Use Risk Factors (C-SURF) were used to measure PA with the International Physical Activity Questionnaire and sports activity with a single item. Multivariate logistic regression analysis was conducted to measure the association between snus use, PA and sports activity. Similar models were run for smoking and snuff use. Snus use increased in a dose-response association with PA (high level: OR = 1.72; 95% CI 1.16–2.55) and with individuals exercising once a week or more often (OR = 1.65; 95% CI 1.26–2.16; p < 0.001) or almost every day (OR = 2.27; 95% CI 1.72–3.01; p < 0.001) in separate models. Entered simultaneously, only sports and exercise maintained a basically unchanged significant dose-response relationship, whereas PA became non-significant. A non-significant dose-response relation was found for cigarette smoking and snuff use, indicating that the association with sport is specific to snus and not to tobacco use in general or smokeless tobacco in particular. This study showed that the association between snus use and sports is not specific to Nordic countries.
Introduction The persistent fragmentation of home healthcare reflects inadequate coordination between care providers. Still, while factors at the system (e.g., regulations) and organisational (e.g., work environment) levels crucially influence homecare organisation, coordination and ultimately quality, knowledge of these factors and their relationships in homecare settings remains limited. Objectives This study has three aims: [1] to explore how system-level regulations lead to disparities between homecare agencies’ structures, processes and work environments; [2] to explore how system- and organisation-level factors affect agency-level homecare coordination; and [3] to explore how agency-level care coordination is related to patient-level quality of care. Design and methods This study focuses on a national multi-center cross-sectional survey in Swiss homecare settings. It will target 100 homecare agencies, their employees and clients for recruitment, with data collection period planned from January to June 2021. We will assess regulations and financing mechanisms (via public records), agency characteristics (via agency questionnaire data) and homecare employees’ working environments and coordination activities, as well as staff- and patient-level perceptions of coordination and quality of care (via questionnaires for homecare employees, clients and informal caregivers). All collected data will be subjected to descriptive and multi-level analyses. Discussion The first results are expected by December 2021. Knowledge of factors linked to quality of care is essential to plan and implement quality improvement strategies. This study will help to identify modifiable factors at multiple health system levels that might serve as access points to improve coordination and quality of care.
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