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Objective Patients with multiple long-term conditions visit various healthcare professionals and are exposed to medication information from various sources causing an increased risk of patients perceiving contradictory medication information. The aims of this study are to: (1) characterise conflicting medication information perceived by patients with long-term conditions, (2) better understand the related impact on patients’ medication self-management and healthcare system navigation and (3) explore ways in which such events could be prevented.Design This study was conducted through qualitative semistructured interviews. Data were analysed using thematic analysis.Setting Community pharmacies and medical centres in Geneva, Switzerland.Participants This study included outpatients from April 2019 to February 2020. Patients were included after participating in a quantitative survey of perceived conflicting information about medications for long-term diseases.Methods Semistructured audiotaped interviews of 20 to 60 min following a pre-established interview guide to explore participants’ perceptions of conflicting information. Interviews were transcribed verbatim, and a thematic analysis was conducted with inductive and deductive coding using MAXQDA (2018, Release 18.2.3).Results Twenty-two patients were interviewed, until data saturation, mentioning indication or need for a medication as the main topic of conflicting information between two healthcare professionals. Perceived conflicting information often resulted from insufficient information provided and poor communication leading to confusion, doubts and medication non-adherence. Patients expected more information and more interprofessional communication on their medications. As a result of conflicting information, most participants learnt or were learning to take an active role and become partners of the healthcare providers.Conclusion The need to strengthen and improve communication and interprofessional collaborative practice among healthcare professionals and with the patient is emerging to increase the quality and consistency of information about medications, and consequently, to ensure better use and experience of medications.

Objective The number of patients with chronic diseases and subsequent visits to various healthcare professionals has been rising over the past decades, exposing patients to potential risks of receiving conflicting medication information. This study aims to investigate the prevalence of conflicting information on medications perceived by chronic patients in Switzerland and to understand its impact on patients’ medication self-management and navigation in the healthcare system.Participants This cross-sectional study included adult patients taking at least one prescribed medication for at least 6 months, who had visited at least two physicians in the past 3 months.Main outcome measures Data on patients’ perceptions of conflicting information were collected in person through a 17-item questionnaire available on paper and electronically with four domains: (1) whether the patient had perceived any conflicting information, (2) categories of conflicting information, (3) impact and (4) sources involved in the conflicting information.Results Of the 405 included patients, 47% perceived conflicting information related to one or more medication topics including indication, schedule, dosage, risk, severity or duration of side effects. Patients who perceived conflicting information were prescribed more drugs than those perceiving no conflicting information (p

The effects of solar ultraviolet (UV) radiation on life on Earth differ greatly. While overexposure to UV rays is harmful, small amounts of exposure are necessary for the synthesis of Vitamin D and good health. To optimize individual exposure to solar UV, it is therefore crucial to use UV data sources representative for entire populations and realistically accounting for various influencing factors. A UV climatology for Switzerland based on satellite data has been developed to provide risk estimates at population level. An algorithm generating ground-based radiation estimate has been transformed from the visible to the UV wavelength domain by adapting both a clear-sky radiation transfer model and a cloud modification factor model using satellite imagery.The algorithm allows the computation of global UV erythemal irradiance at a spatial resolution of 1.5 – 2 km and an hourly temporal resolution over fifteen years. A validation, conducted with measurements from three meteorological stations over ten years, showed that the expanded uncertainty for low hourly UVI values (UVI 6) it can go up to ± 1.5. In clear-sky situation, the uncertainty is in the range of 10–15%.The climatology developed allows to visualise potential UV exposure at regional and national scale. National prevention intervention could use new strategies to better focus on populations at risk and better tailor available researches. The UV climatology allows a high versatility in adapting the data extraction to the goal of studies using it. Further tailored data extraction and analysis will be necessary to exploit this climatology in a wide range of environmental and occupational health applications. Its development was focused on Switzerland, but the techniques used can be extended globally.

Background: The World Health Organization (WHO) and the International Labour Organization (ILO) are developing joint estimates of the work-related burden of disease and injury (WHO/ILO Joint Estimates). For this, systematic reviews of studies estimating the prevalence of exposure to selected occupational risk factors will be conducted to provide input data for estimations of the number of exposed workers. A critical part of systematic review methods is to assess risk of bias (RoB) of individual studies. In this article, we present and describe the development of such a tool, called the Risk of Bias in Studies estimating Prevalence of Exposure to Occupational risk factors (RoB-SPEO) tool; report results from RoB-SPEO's pilot testing; note RoB-SPEO's limitations; and suggest how the tool might be tested and developed further. Methods: Selected existing RoB tools used in environmental and occupational health systematic reviews were reviewed and analysed. From existing tools, we identified domains for the new tool and, if necessary, added new domains. For each domain, we then identified and integrated components from the existing tools (i.e. instructions, domains, guiding questions, considerations, ratings and rating criteria), and, if necessary, we developed new components. Finally, we elicited feedback from other systematic review methodologists and exposure scientists and agreed upon RoB-SPEO. Nine experts pilot tested RoB-SPEO, and we calculated a raw measure of inter-rater agreement (Pi) for each of its domain, rating Pi 0.80 as almost perfect agreement. Results: Our review found no standard tool for assessing RoB in prevalence studies of exposure to occupational risk factors. We identified six existing tools for environmental and occupational health systematic reviews and found that their components for assessing RoB differ considerably. With the new RoB-SPEO tool, assessors judge RoB for each of eight domains: (1) bias in selection of participants into the study; (2) bias due to a lack of blinding of study personnel; (3) bias due to exposure misclassification; (4) bias due to incomplete exposure data; (5) bias due to conflict of interest; (6) bias due to selective reporting of exposures; (7) bias due to difference in numerator and denominator; and (8) other bias. The RoB-SPEO's ratings are low, probably low, probably high, high or no information. Pilot testing of the RoB-SPEO tool found substantial inter-rater agreement for six domains (range of Pi for these domains: 0.51–0.80), but poor agreement for two domains (i.e. Pi of 0.31 and 0.33 for biases due to incomplete exposure data and in selection of participants into the study, respectively). Limitations of RoB-SPEO include that it has not yet been fully performance-tested. Conclusions: We developed the RoB-SPEO tool for assessing RoB in prevalence studies of exposure to occupational risk factors. The tool will be applied and its performance tested in the ongoing systematic reviews for the WHO/ILO Joint Estimates.

Purpose: This study aims to describe a 12-month medication adherence with oral anticancer medications (OAMs) in a routine care medication adherence program, and to better characterize non-persistence.Patients and methods:In this observational, one-centered, longitudinal study, medication adherence was monitored electronically while patients were taking part in a medication adherence program for 12 months or until treatment stop. Patients were >18 years and starting or taking one of the following OAMs: letrozole, exemestane, imatinib, sunitinib, capecitabine, or temozolomide. Non-persistence was defined as any premature treatment interruption due to patient's unilateral decision or to a medical decision because of adverse effects. The Kaplan Meier survival function estimate was used to characterize persistence, and Generalized Estimating Equations (GEE) were adopted to fit implementation. Statistical analyses were performed using the R software package.Results: Forty-three outpatients with various tumor entities were enrolled. Reasons for quitting the medication adherence program and/or OAM medication were characterized as OAM discontinuation due to adverse effects or toxicity (n = 5), planned OAM completion time (n = 10), OAM failure (cancer relapse) (n = 5) and non-compliance to the adherence program (n = 3). In persistent patients, the implementation rates were high (from 98% at baseline to 97% at 12 months). The probability of being persistent at 12 months was estimated at 85%.Conclusion: A better characterization of both persistence and implementation to OAMs in real life settings is crucial for understanding and optimizing medication adherence to OAMs. The complex identification of non-persistence underlines the need to carefully and prospectively assess OAM interruption or treatment switch reasons. The GEE analysis for describing implementation to OAMs will allow researchers and professionals to take advantage of the richness of longitudinal real-time data, to avoid reducing such data through thresholds and to put them into perspective with OAM blood levels.

Epidemiology and public health research relating to solar ultraviolet (UV) exposure usually relies on dosimetry to measure UV doses received by individuals. However, measurement errors affect each dosimetry measurement by unknown amounts, complicating the analysis of such measurements and their relationship to the underlying population exposure and the associated health outcomes. This paper presents a new approach to estimate UV doses without the use of dosimeters. By combining new satellite-derived UV data to account for environmental factors and simulation-based exposure ratio (ER) modelling to account for individual factors, we are able to estimate doses for specific exposure periods. This is a significant step forward for alternative dosimetry techniques which have previously been limited to annual dose estimation. We compare our dose estimates with dosimeter measurements from skiers and builders in Switzerland. The dosimetry measurements are expected to be slightly below the true doses due to a variety of dosimeter-related measurement errors, mostly explaining why our estimates are greater than or equal to the corresponding dosimetry measurements. Our approach holds much promise as a low-cost way to either complement or substitute traditional dosimetry. It can be applied in a research context, but is also fundamentally well-suited to be used as the basis for a dose-estimating mobile app that does not require an external device.