on behalf of the SMILe study team, Clinicians and patients perspectives on follow-up care and eHealth support after allogeneic hematopoietic stem cell transplantation: A mixed-methods contextual analysis as part of the SMILe study,

Background: Medication adherence to immunosuppressants in allogeneic stem cell transplantation (alloSCT) is essential to achieve favorable clinical outcomes (e.g. control of Graft-versus-Host Disease). Over 600 apps supporting medication adherence exist, yet they lack successful implementation and sustainable use likely because of lack of end-user involvement and theoretical underpinnings in their development and insufficient attention to implementation methods to support their use in real-life settings. Medication adherence has three phases: initiation, implementation and persistence. We report the theory-driven development of an intervention module to support medication adherence (implementation and persistence phase) in alloSCT outpatients as a first step for future digitization and implementation in clinical setting within the SMILe project (Development, implementation and testing of an integrated care model in allogeneic SteM cell transplantatIon faciLitated by eHealth). Methods: We applied Michie's Behavior Change Wheel (BCW) and the Capability-Opportunity-Motivation and Behavior (COM-B) model using three suggested stages followed by one stage added by our team regarding preparation for digitization of the intervention: (I) Defining the problem in behavioral terms; (II) Identifying intervention options; (III) Identifying content and implementation options; (IV) SMILe Care Model Prototype Development. Scientific evidence, data from a contextual analysis and patients'/caregivers' and clinical experts' inputs were compiled to work through these steps.

Purpose Allogeneic stem cell transplantation would benefit from re-engineering care towards an integrated eHealth-facilitated care model. With this paper we aim to: (1) describe the development of an integrated care model (ICM) in allogeneic SteM-cell-transplantatIon faciLitated by eHealth (SMILe) by combining implementation, behavioral, and computer science methods (e.g., contextual analysis, Behavior Change Wheel, and user-centered design combined with agile software development); and (2) describe that model’s characteristics and its application in clinical practice. Methods The SMILe intervention’s development consisted of four steps, with implementation science methods informing each: (1) planning its set-up within a theoretical foundation; (2) using behavioral science methods to develop the content; (3) choosing and developing its delivery method (human/technology) using behavioral and computer science methods; and (4) describing its characteristics and application in clinical practice. Results The SMILe intervention is embedded within the eHealth enhanced Chronic Care Model, entailing four self-management intervention modules, targeting monitoring and follow-up of important medical and symptom-related parameters, infection prevention, medication adherence, and physical activity. Interventions are delivered partly face-to-face by a care coordinator embedded within the transplant team, and partly via the SMILeApp that connects patients to the transplant team, who can monitor and rapidly respond to any relevant changes within 1 year post-transplant. Conclusion This paper provides stepwise guidance on how implementation, behavioral, and computer science methods can be used to develop interventions aiming to improve care for stem cell transplant patients in real-world clinical settings. This new care model is currently being tested in a hybrid I effectiveness-implementation trial.

PurposeTo describe a process of creating eHealth components for an integrated care model using an agile software development approach, user‐centered design and, via the Behavior Change Wheel, behavior theory‐guided content development. Following the principles of implementation science and using the SMILe project (integrated care model for allogeneic stem cell transplantation facilitated by eHealth) as an example, this study demonstrates how to narrow the research‐to‐practice gap often encountered in eHealth projects.MethodsWe followed a four‐step process: (a) formation of an interdisciplinary team; (b) a contextual analysis to drive the development process via behavioral theory; (c) transfer of content to software following agile software development principles; and (d) frequent stakeholder and end user involvement following user‐centered design principles.FindingsOur newly developed comprehensive development approach allowed us to create a running eHealth component and embed it in an integrated care model. An interdisciplinary team’s collaboration at specified interaction points supported clear, timely communication and interactions between the specialists. Because behavioral theory drove the content development process, we formulated user stories to define the software features, which were prioritized and iteratively developed using agile software development principles. A prototype intervention module has now been developed and received high ratings on the System Usability Scale after two rounds of usability testing.ConclusionsFollowing an agile software development process, structured collaboration between nursing scientists and software specialists allowed our interdisciplinary team to develop meaningful, theory‐based eHealth components adapted to context‐specific needs.Clinical RelevanceThe creation of high‐quality, accurately fitting eHealth components specifically to be embedded in integrated care models should increase the chances of uptake, adoption, and sustainable implementation in clinical practice.

OrCaSS is a promising intervention to delay and reduce OM. These results can serve to plan a larger RCT.

Background Designing intervention and implementation strategies with careful consideration of context is essential for successful implementation science projects. Although the importance of context has been emphasized and methodology for its analysis is emerging, researchers have little guidance on how to plan, perform, and report contextual analysis. Therefore, our aim was to describe the Basel Approach for coNtextual ANAlysis (BANANA) and to demonstrate its application on an ongoing multi-site, multiphase implementation science project to develop/adapt, implement, and evaluate an integrated care model in allogeneic SteM cell transplantatIon facILitated by eHealth (the SMILe project). Methods BANANA builds on guidance for assessing context by Stange and Glasgow (Contextual factors: the importance of considering and reporting on context in research on the patient-centered medical home, 2013). Based on a literature review, BANANA was developed in ten discussion sessions with implementation science experts and a medical anthropologist to guide the SMILe project’s contextual analysis. BANANA’s theoretical basis is the Context and Implementation of Complex Interventions (CICI) framework. Working from an ecological perspective, CICI acknowledges contextual dynamics and distinguishes between context and setting (the implementation’s physical location). Results BANANA entails six components: (1) choose a theory, model, or framework (TMF) to guide the contextual analysis; (2) use empirical evidence derived from primary and/or secondary data to identify relevant contextual factors; (3) involve stakeholders throughout contextual analysis; (4) choose a study design to assess context; (5) determine contextual factors’ relevance to implementation strategies/outcomes and intervention co-design; and (6) report findings of contextual analysis following appropriate reporting guidelines. Partly run simultaneously, the first three components form a basis both for the identification of relevant contextual factors and for the next components of the BANANA approach. Discussion Understanding of context is indispensable for a successful implementation science project. BANANA provides much-needed methodological guidance for contextual analysis. In subsequent phases, it helps researchers apply the results to intervention development/adaption and choices of contextually tailored implementation strategies. For future implementation science projects, BANANA’s principles will guide researchers first to gather relevant information on their target context, then to inform all subsequent phases of their implementation science project to strengthen every part of their work and fulfill their implementation goals.

This study aimed to investigate the levels of burnout and work engagement among home care workers in Switzerland and to test their association with job demands and job resources. We conducted a multi-centre, cross-sectional survey in the Germanspeaking part of Switzerland with a convenience sample of seven home care agencies. Data were collected between September 2017 and January 2018. We assessed burnout with the Maslach Burnout Inventory (MBI) and work engagement with the Utrecht Work Engagement Scale (UWES) as well as job demands (overtime, workfamily conflicts, experienced aggression and work stressors) and job resources (predictability, staffing, teamwork, leadership, collaboration, social support, sense of community, feedback). To investigate the levels of burnout and work engagement, we applied descriptive statistics. Based on Bakker and colleagues' Job Demands-Resources model, we used a path analysis to test the associations of job demands and job resources with burnout and work engagement. We analysed data from 448 home care workers (response rate 61.8%, mean age 44 years (SD 13.2), 96% female). The frequency of burnout in our sample was low, while that of work engagement was high. Job demands correlated positively with emotional exhaustion (β = .54, p < .001) and negatively with work engagement (β = −.25, p < .001). Job resources correlated negatively with emotional exhaustion (β = −.28, p < .001) and positively with work engagement (β = .41, p < .001). Work-family conflicts and work stressors correlated strongest with emotional exhaustion, whereas social support and feedback were found to correlate strongest with work engagement. Improvements to the home care work environment might enhance work engagement and reduce burnout. Corrective interventions could focus on reducing specific aspects of job demands, such as workfamily conflicts and work stressors, as well as on increasing aspects of job resources, especially social support and feedback.

Purpose:Little is known about allogeneic stem cell transplant (alloSCT) patients' medication adherence strategies. Acceptability and preferences regarding electronic monitoring (EM) systems to assess all three phases of medication adherence (ie, initiation, implementation, persistence) are crucial to allow their successful implementation in clinical or research settings but have not yet been evaluated. We therefore aimed to explore: 1) alloSCT patients' medication adherence and self-management strategies; and 2) their acceptability and preferences of three different EM systems (MEMS Cap, Helping Hand, Button) as part of the Swiss SMILe study. Patients and Methods: Respecting anti-pandemic measures, we used a purposive sample of six adult alloSCT patients from the University Hospital Basel, Switzerland (USB)-6 weeks to 2 years post-alloSCT-to conduct three focus group sessions with two patients each. Using a semistructured outline, we explored 1) patients' medication adherence strategies and medication selfmanagement; and 2) their acceptance and preferences regarding EM use. The three tested EM systems were available for testing during each session. Discussions were audio-recorded, visualized using mind-mapping and analyzed using Mayring's qualitative content analysis. Results: Patients (33% females; mean age 54.6±16.3 years; 10.4±8.4 months post-alloSCT) used medication adherence enhancing strategies (eg, preparing pillbox, linking intake to a habit). Still, they indicated that post-alloSCT medication management was challenging (eg, frequent schedule changes). All participants preferred the MEMS Button. Participants said its small size and the possibility to combine it with existing pillboxes (eg, putting it into/next to them) made them more confident about implementing it in their daily lives. Conclusion: Regarding EM systems for medication adherence, end-user preferences and acceptability influence adoption and fidelity. Of the three systems tested, our sample found the MEMS Button most acceptable and most preferable. Therefore, we will use it for our USB SMILe study.