Wim Van Biesen

The population‐attributable fraction (PAF) is commonly interpreted as the proportion of events that can be ascribed to a certain exposure in a certain population. Its estimation is sensitive to common forms of time‐dependent bias in the face of a time‐dependent exposure. Predominant estimation approaches based on multistate modeling fail to fully eliminate such bias and, as a result, do not permit a causal interpretation, even in the absence of confounding. While recently proposed multistate modeling approaches can successfully eliminate residual time‐dependent bias, and moreover succeed to adjust for time‐dependent confounding by means of inverse probability of censoring weighting, inadequate application, and misinterpretation prevails in the medical literature. In this paper, we therefore revisit recent work on previously proposed PAF estimands and estimators in settings with time‐dependent exposures and competing events and extend this work in several ways. First, we critically revisit the interpretation and applied terminology of these estimands. Second, we further formalize the assumptions under which a causally interpretable PAF estimand can be identified and provide analogous weighting‐based representations of the identifying functionals of other proposed estimands. This representation aims to enhance the applied statistician's understanding of different sources of bias that may arise when the aim is to obtain a valid estimate of a causally interpretable PAF. To illustrate and compare these representations, we present a real‐life application to observational data from the Ghent University Hospital ICUs to estimate the fraction of ICU deaths attributable to hospital‐acquired infections.

Background For persons with kidney failure, life participation is a critically important outcome, strongly linked to quality of life and mortality. To support patients' self-management abilities, three domains are typically emphasized: medical management, emotional management, and management of everyday life ( i.e. , role management). Although role management is strongly linked to life participation, there is currently limited research on interventions designed to support it. We explored existing self-management interventions that aim to support everyday life functioning, rather than only medical management. Methods In this systematic review and qualitative meta-synthesis, we searched MEDLINE, Embase, CINAHL, PsycINFO, Web of Science, and CENTRAL up to April 2022 for interventional studies involving self-management interventions designed, at least partly, to support management of everyday life. The guidelines by Sandelowski and Barosso were used to analyze and synthesize the results. A taxonomy of everyday self-management strategies was used to further explore intervention content. Study quality was assessed using the Cochrane Collaboration risk-of-bias tools. Evidence of effectiveness was summarized, and a meta-analysis of eligible outcomes was conducted. Results Of 22,667 records, 53 studies were included in the meta-synthesis. Most self-management interventions focused on medical management. Included interventions involved strategies to support eight domains: Activities of daily living, Work and school life, Meaningful occupations, Leisure activities, Mobility and travel, Interpersonal relationships, Role functioning, and Social participation. Major interventions focused on providing education, skill training, counseling, and cognitive behavioral therapy. Evidence of effectiveness was reported across a wide range of patient-reported outcomes, including (health-related) quality of life, depression, and self-efficacy. Studies were geographically concentrated and were of moderate to low quality. Conclusions Despite its well-recognized importance, research on interventions to improve life participation mostly consisted of pilot and feasibility studies and studies of low quality. Interventions were reported heterogeneously, limiting comparability, and were restricted to specific regions and cultures, limiting generalizability.