Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of healthcare-and community-associated infections worldwide. Within the healthcare setting alone, MRSA infections are estimated to affect more than 150,000 patients annually in the European Union (EU), resulting in attributable extra in-hospital costs of EUR 380 million for EU healthcare systems. Pan-European surveillance data on bloodstream infections show marked variability among EU Member States in the proportion of S. aureus that are methicillin-resistant, ranging from less than 1% to more than 50%. In the past five years, the MRSA bacteraemia rates have decreased significantly in 10 EU countries with higher endemic rates of MRSA infections. In addition to healthcare-associated infections, new MRSA strains have recently emerged as communityand livestock-associated human pathogens in most EU Member States. The prevention and control of MRSA have therefore been identified as public health priorities in the EU. In this review, we describe the current burden of MRSA infections in healthcare and community settings across Europe and outline the main threats caused by recent changes in the epidemiology of MRSA. Thereby, we aim at identifying unmet needs of surveillance, prevention and control of MRSA in Europe.

Blended care, a combination of online and face-to-face therapy, is increasingly being applied in mental health care to obtain optimal benefit from the advantages these two treatment modalities have. Promising results have been reported, but a variety in descriptions and ways of operationalizing blended care exists. Currently, what type of “blend” works for whom, and why, is unclear. Furthermore, a rationale for setting up blended care is often lacking. In this viewpoint paper, we describe postulates for blended care and provide an instrument (Fit for Blended Care) that aims to assist therapists and patients whether and how to set up blended care treatment. A review of the literature, two focus groups (n=5 and n=5), interviews with therapists (n=14), and interviews with clients (n=2) were conducted to develop postulates of eHealth and blended care and an instrument to assist therapists and clients in setting up optimal blended care. Important postulates for blended care are the notion that both treatment modalities should complement each other and that set up of blended treatment should be based on shared decision making between patient and therapist. The “Fit for Blended Care” instrument is presented which addresses the following relevant themes: possible barriers to receiving blended treatment such as the risk of crisis, issues in communication (at a distance), as well as possible facilitators such as social support. More research into the reasons why and for whom blended care works is needed. To benefit from blended care, face-to-face and online care should be combined in such way that the potentials of both treatment modalities are used optimally, depending on patient abilities, needs, and preferences. To facilitate the process of setting up a personalized blended treatment, the Fit for Blended Care instrument can be used. By applying this approach in research and practice, more insight into the working mechanisms and optimal (personal) “blends” of online and face-to-face therapy becomes within reach.

BackgroundBlending online modules into face-to-face therapy offers perspectives to enhance patient self-management and to increase the (cost-)effectiveness of therapy, while still providing the support patients need. The aim of this study was to outline optimal usage of blended care for depression, according to patients and therapists.MethodsA Delphi method was used to find consensus on suitable blended protocols (content, sequence and ratio). Phase 1 was an explorative phase, conducted in two rounds of online questionnaires, in which patients’ and therapists’ preferences and opinions about online psychotherapy were surveyed. In phase 2, data from phase 1 was used in face-to-face interviews with therapists to investigate how blended therapy protocols could be set up and what essential preconditions would be.ResultsTwelve therapists and nine patients completed the surveys. Blended therapy was positively perceived among all respondents, especially to enhance the self-management of patients. According to most respondents, practical therapy components (assignments, diaries and psycho-education) may be provided via online modules, while process-related components (introduction, evaluation and discussing thoughts and feelings), should be supported face-to-face. The preferred blend of online and face-to-face sessions differs between therapists and patients; most therapists prefer 75% face-to-face sessions, most patients 50 to 60%. The interviews showed that tailoring treatment to individual patients is essential in secondary mental health care, due to the complexity of their problems. The amount and ratio of online modules needs to be adjusted according to the patient’s problems, skills and characteristics. Therapists themselves should also develop skills to integrate online and face-to-face sessions.ConclusionsBlending online and face-to-face sessions in an integrated depression therapy is viewed as a positive innovation by patients and therapists. Following a standard blended protocol, however, would be difficult in secondary mental health care. A database of online modules could provide flexibility to tailor treatment to individual patients, which asks motivation and skills of both patients and therapists. Further research is necessary to determine the (cost-)effectiveness of blended care, but this study provides starting points and preconditions to blend online and face-to-face sessions and create a treatment combining the best of both worlds.

BackgroundIn electronic health (eHealth) evaluations, there is increasing attention for studying the actual usage of a technology in relation to the outcomes found, often by studying the adherence to the technology. On the basis of the definition of adherence, we suggest that the following three elements are necessary to determine adherence to eHealth technology: (1) the ability to measure the usage behavior of individuals; (2) an operationalization of intended use; and (3) an empirical, theoretical, or rational justification of the intended use. However, to date, little is known on how to operationalize the intended usage of and the adherence to different types of eHealth technology.ObjectiveThe study aimed to improve eHealth evaluations by gaining insight into when, how, and by whom the concept of adherence has been used in previous eHealth evaluations and finding a concise way to operationalize adherence to and intended use of different eHealth technologies.MethodsA systematic review of eHealth evaluations was conducted to gain insight into how the use of the technology was measured, how adherence to different types of technologies was operationalized, and if and how the intended use of the technology was justified. Differences in variables between the use of the technology and the operationalization of adherence were calculated using a chi-square test of independence.ResultsIn total, 62 studies were included in this review. In 34 studies, adherence was operationalized as “the more use, the better,” whereas 28 studies described a threshold for intended use of the technology as well. Out of these 28, only 6 reported a justification for the intended use. The proportion of evaluations of mental health technologies reporting a justified operationalization of intended use is lagging behind compared with evaluations of lifestyle and chronic care technologies. The results indicated that a justification of intended use does not require extra measurements to determine adherence to the technology.ConclusionsThe results of this review showed that to date, justifications for intended use are often missing in evaluations of adherence. Evidently, it is not always possible to estimate the intended use of a technology. However, such measures do not meet the definition of adherence and should therefore be referred to as the actual usage of the technology. Therefore, it can be concluded that adherence to eHealth technology is an underdeveloped and often improperly used concept in the existing body of literature. When defining the intended use of a technology and selecting valid measures for adherence, the goal or the assumed working mechanisms should be leading. Adherence can then be standardized, which will improve the comparison of adherence rates to different technologies with the same goal and will provide insight into how adherence to different elements contributed to the outcomes.

BackgroundThe combination of self-tracking and persuasive eCoaching in automated interventions is a new and promising approach for healthy lifestyle management.ObjectiveThe aim of this study was to identify key components of self-tracking and persuasive eCoaching in automated healthy lifestyle interventions that contribute to their effectiveness on health outcomes, usability, and adherence. A secondary aim was to identify the way in which these key components should be designed to contribute to improved health outcomes, usability, and adherence.MethodsThe scoping review methodology proposed by Arskey and O’Malley was applied. Scopus, EMBASE, PsycINFO, and PubMed were searched for publications dated from January 1, 2013 to January 31, 2016 that included (1) self-tracking, (2) persuasive eCoaching, and (3) healthy lifestyle intervention.ResultsThe search resulted in 32 publications, 17 of which provided results regarding the effect on health outcomes, 27 of which provided results regarding usability, and 13 of which provided results regarding adherence. Among the 32 publications, 27 described an intervention. The most commonly applied persuasive eCoaching components in the described interventions were personalization (n=24), suggestion (n=19), goal-setting (n=17), simulation (n=17), and reminders (n=15). As for self-tracking components, most interventions utilized an accelerometer to measure steps (n=11). Furthermore, the medium through which the user could access the intervention was usually a mobile phone (n=10). The following key components and their specific design seem to influence both health outcomes and usability in a positive way: reduction by setting short-term goals to eventually reach long-term goals, personalization of goals, praise messages, reminders to input self-tracking data into the technology, use of validity-tested devices, integration of self-tracking and persuasive eCoaching, and provision of face-to-face instructions during implementation. In addition, health outcomes or usability were not negatively affected when more effort was requested from participants to input data into the technology. The data extracted from the included publications provided limited ability to identify key components for adherence. However, one key component was identified for both usability and adherence, namely the provision of personalized content.ConclusionsThis scoping review provides a first overview of the key components in automated healthy lifestyle interventions combining self-tracking and persuasive eCoaching that can be utilized during the development of such interventions. Future studies should focus on the identification of key components for effects on adherence, as adherence is a prerequisite for an intervention to be effective.