The extent to which member states transpose EU directives in a timely fashion is often argued to be strongly associated with the general effectiveness of national bureaucracies. But what kind of institutional solutions ensure better performance? This paper examines the patterns and effects of departmental oversight across 28 ministries in Estonia, Hungary, Poland and Slovenia. In mapping the strength of oversight, it relies on around 90 structured interviews regarding the rules-in-use on transposition planning, legal review and monitoring of deadlines. The analysis of the impact of departmental oversight is based on an original dataset of over 300 directives with transposition deadlines between January 2005 and December 2008.

On the european union

Background: Long-term conditions and their concomitant management place considerable pressure on patients, communities, and health care systems worldwide. International clinical guidelines on the majority of long-term conditions recommend the inclusion of self-management programs in routine management. Self-management programs have been associated with improved health outcomes; however, the successful and sustainable transfer of research programs into clinical practice has been inconsistent. Recent developments in mobile technology, such as mobile phone and tablet computer apps, could help in developing a platform for the delivery of self-management interventions that are adaptable, of low cost, and easily accessible. Objective: We conducted a systematic review to assess the effectiveness of mobile phone and tablet apps in self-management of key symptoms of long-term conditions. Methods: We searched PubMed, Embase, EBSCO databases, the Cochrane Library, and The Joanna Briggs Institute Library for randomized controlled trials that assessed the effectiveness of mobile phone and tablet apps in self-management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 2005–2016. We searched registers of current and ongoing trials, as well as the gray literature. We then checked the reference lists of all primary studies and review papers for additional references. The last search was run in February 2016. Results: Of the 9 papers we reviewed, 6 of the interventions demonstrated a statistically significant improvement in the primary measure of clinical outcome. Where the intervention comprised an app only, 3 studies demonstrated a statistically significant improvement. Interventions to address diabetes mellitus (5/9) were the most common, followed by chronic lung disease (3/9) and cardiovascular disease (1/9). A total of 3 studies included multiple intervention groups using permutations of an intervention involving an app. The duration of the intervention ranged from 6 weeks to 1 year, and final follow-up data ranged from 3 months to 1 year. Sample size ranged from 48 to 288 participants. Conclusions: The evidence indicates the potential of apps in improving symptom management through self-management interventions. The use of apps in mHealth has the potential to improve health outcomes among those living with chronic diseases through enhanced symptom control. Further innovation, optimization, and rigorous research around the potential of apps in mHealth technology will move the field toward the reality of improved health care delivery and outcomes. [J Med Internet Res 2016;18(5):e97]

/pdf/the-effectiveness-of-self-management-mobile-phone-and-tablet-4uliqye11l.pdf

The Effectiveness of Self-Management Mobile Phone and Tablet Apps in Long-term Condition Management: A Systematic Review

https://isiarticles.com/bundles/Article/pre/pdf/39621.pdf

Dissociating cognitive from affective theory of mind: A TMS study

https://research.birmingham.ac.uk/portal/files/24275827/Law_et_al_Levels_and_trends_Environment_International_Post_Print.pdf

Levels and trends of PBDEs and HBCDs in the global environment: Status at the end of 2012

How does transcranial magnetic stimulation modify neuronal activity in the brain? Implications for studies of cognition

With more than 1 billion users having access to mobile broadband Internet and a rapidly growing mobile app market, all stakeholders involved have high hopes that this technology may improve health care. Expectations range from overcoming structural barriers to access in low-income countries to more effective, interactive treatment of chronic conditions. Before medical health practice supported by mobile devices ("mHealth") can scale up, a number of challenges need to be adequately addressed. From a psychological perspective, high attrition rates, digital divide of society, and intellectual capabilities of the users are key issues when implementing such technologies. Furthermore, apps addressing behavior change often lack a comprehensive concept, which is essential for an ongoing impact. From a clinical point of view, there is insufficient evidence to allow scaling up of mHealth interventions. In addition, new concepts are required to assess the efficacy and efficiency of interventions. Regarding technology interoperability, open standards and low-energy wireless protocols appear to be vital for successful implementation. There is an ongoing discussion in how far health care-related apps require a conformity assessment and how to best communicate quality standards to consumers. "Apps Peer-Review" and standard reporting via an "App synopsis" appear to be promising approaches to increase transparency for end users. With respect to development, more emphasis must be placed on context analysis to identify what generic functions of mobile information technology best meet the needs of stakeholders involved. Hence, interdisciplinary alliances and collaborative strategies are vital to achieve sustainable growth for "mHealth 2.0," the next generation mobile technology to support patient care.

http://evs.ehealth-syte.com/wp-content/uploads/2015/09/MHealth-Experiences-Possibilities-and-Perspectives.pdf

mHealth 2.0: Experiences, Possibilities, and Perspectives

Background: By adding new levels of experience, mobile Augmented Reality (mAR) can significantly increase the attractiveness of mobile learning applications in medical education. Objective: To compare the impact of the heightened realism of a self-developed mAR blended learning environment (mARble) on learners to textbook material, especially for ethically sensitive subjects such as forensic medicine, while taking into account basic psychological aspects (usability and higher level of emotional involvement) as well as learning outcomes (increased learning efficiency). Methods: A prestudy was conducted based on a convenience sample of 10 third-year medical students. The initial emotional status was captured using the “Profile of Mood States” questionnaire (POMS, German variation); previous knowledge about forensic medicine was determined using a 10-item single-choice (SC) test. During the 30-minute learning period, the students were randomized into two groups: the first group consisted of pairs of students, each equipped with one iPhone with a preinstalled copy of mARble, while the second group was provided with textbook material. Subsequently, both groups were asked to once again complete the POMS questionnaire and SC test to measure changes in emotional state and knowledge gain. Usability as well as pragmatic and hedonic qualities of the learning material was captured using AttrakDiff2 questionnaires. Data evaluation was conducted anonymously. Descriptive statistics for the score in total and the subgroups were calculated before and after the intervention. The scores of both groups were tested against each other using paired and unpaired signed-rank tests. An item analysis was performed for the SC test to objectify difficulty and selectivity. Results: Statistically significant, the mARble group (6/10) showed greater knowledge gain than the control group (4/10) (Wilcoxon z=2.232, P=.03). The item analysis of the SC test showed a difficulty of P=0.768 (s=0.09) and a selectivity of RPB=0.2. For mARble, fatigue (z=2.214, P=.03) and numbness (z=2.07, P=.04) decreased with statistical significance when comparing pre- and post-tests. Vigor rose slightly, while irritability did not increase significantly. Changes in the control group were insignificant. Regarding hedonic quality (identification, stimulation, attractiveness), there were significant differences between mARble (mean 1.179, CI −0.440 to 0.440) and the book chapter (mean −0.982, CI −0.959 to 0.959); the pragmatic quality mean only differed slightly. Conclusions: The mARble group performed considerably better regarding learning efficiency; there are hints for activating components of the mAR concept that may serve to fascinate the participants and possibly boost interest in the topic for the remainder of the class. While the small sample size reduces our study’s conclusiveness, its design seems appropriate for determining

/pdf/effects-of-mobile-augmented-reality-learning-compared-to-1wv7m4k6g4.pdf

Effects of mobile augmented reality learning compared to textbook learning on medical students: randomized controlled pilot study.

Background: Google Glass is a promising premarket device that includes an optical head-mounted display. Several proof of concept reports exist, but there is little scientific evidence regarding its use in a medical setting. Objective: The objective of this study was to empirically determine the feasibility of deploying Glass in a forensics setting. Methods: Glass was used in combination with a self-developed app that allowed for hands-free operation during autopsy and postmortem examinations of 4 decedents performed by 2 physicians. A digital single-lens reflex (DSLR) camera was used for image comparison. In addition, 6 forensic examiners (3 male, 3 female; age range 23-48 years, age mean 32.8 years, SD 9.6; mean work experience 6.2 years, SD 8.5) were asked to evaluate 159 images for image quality on a 5-point Likert scale, specifically color discrimination, brightness, sharpness, and their satisfaction with the acquired region of interest. Statistical evaluations were performed to determine how Glass compares with conventionally acquired digital images. Results: All images received good (median 4) and very good ratings (median 5) for all 4 categories. Autopsy images taken by Glass (n=32) received significantly lower ratings than those acquired by DSLR camera (n=17) (region of interest: z =–5.154, P <.001; sharpness: z =–7.898, P <.001; color: z =–4.407, P <.001, brightness: z =–3.187, P =.001). For 110 images of postmortem examinations (Glass: n=54, DSLR camera: n=56), ratings for region of interest ( z =–8.390, P <.001) and brightness ( z =–540, P =.007) were significantly lower. For interrater reliability, intraclass correlation (ICC) values were good for autopsy (ICC=.723, 95% CI .667-.771, P <.001) and postmortem examination (ICC=.758, 95% CI .727-.787, P <.001). Postmortem examinations performed using Glass took 42.6 seconds longer than those done with the DSLR camera ( z =–2.100, P =.04 using Wilcoxon signed rank test). The battery charge of Glass quickly decreased; an average 5.5% (SD 1.85) of its battery capacity was spent per postmortem examination (0.81% per minute or 0.79% per picture). Conclusions: Glass was efficient for acquiring images for documentation in forensic medicine, but the image quality was inferior compared to a DSLR camera. Images taken with Glass received significantly lower ratings for all 4 categories in an autopsy setting and for region of interest and brightness in postmortem examination. The effort necessary for achieving the objectives was higher when using the device compared to the DSLR camera thus extending the postmortem examination duration. Its relative high power consumption and low battery capacity is also a disadvantage. At the current stage of development, Glass may be an adequate tool for education. For deployment in clinical care, issues such as hygiene, data protection, and privacy need to be addressed and are currently limiting chances for professional use. [J Med Internet Res 2014;16(2):e53]

Google Glass for Documentation of Medical Findings: Evaluation in Forensic Medicine

Smart devices such as smartphones and tablet PCs have become an integral part of everyday life as well as for professional applications. This is also true for medicine [1]. To enhance patient safety for medical apps or health apps that are to be used successfully in today’s medical settings, a good information policy should always be part of the marketing strategy. Patients and doctors that are well informed about the benefits, limits, and risks of an app are in a better position to give more reasoning to their decisions whether they want to use it in a medical context or not.

To address the current shortcomings concerning the way information about apps is provided to potential users of apps, Lewis, in a recent letter to JMIR, proposed a set of standard criteria [2] analogous to those published by the Health on the Net foundation [3] to be used for assessing the utility of medical apps based on a systematic self-certification model. He suggested using a central platform for this purpose, for example, the United Kingdom National Health Service App Store, to allow registered developers of mobile medical apps to highlight the fact that they conform to these criteria. This would probably also give developers and distributors of such apps an advantage over their competitors.

While this certainly is a promising approach, I would like to add a few points. For one, in an international setting with users coming from various (and in many cases non-professional) backgrounds, it may be difficult to lead them to a separate platform that is not the standard app distribution platform that users are accustomed to. This is especially the case for casual users who probably tend to use information that is readily available on the app stores or to simply read what other users have to say about an app.

In my opinion, the users themselves should not be disregarded in the overall process since they play an important role by applying the information they have at hand to the product they are interested in and evaluating whether it meets their needs. In contrast to other medical products (eg, for clinical use), where many professional users are confronted with already chosen products that have been labeled as appropriate by experts, many professionals or laypersons have to decide on the appropriateness of the medical app themselves. Therefore, especially for apps, ensuring patient safety also has to include the identification of the right product, in this case an app, that matches the desired setting and indication. Every piece of information covering the necessary aspects helps decision makers and/or end users in professional settings as well as for private use to determine whether an app can be trusted and safe. Thus, to ensure high impact, it would probably make sense to provide users with the appropriate information at places where they expect it (ie, directly in an app’s description on the respective app store and/or on the manufacturer’s homepage and/or marketing material). This should be done following a standardized structure that includes criteria with a clear rationale (Table 1), for example, in the form of a clearly structured app synopsis (Table 2) [4]. A basis for this was proposed in [5], which also included the aspects mentioned in [2] with more detail.



Table 1

Criteria for assessing health apps and medical apps.





Table 2

Detailed description of items of the App-Synopsis for health apps and medical apps.



There are already a number of existing initiatives and projects that use almost identical criteria to those suggested by Lewis, for example, the “Apps Peer-Review” by the Journal of Medical Internet Research (JMIR) launched in 2013 [6]. The JMIR mHealth disclosure form [7] also covers many of the concerns mentioned in the proposed app synopsis. Mostly, these projects reach this goal by installing certification and/or (third party) review processes and publishing the corresponding evaluation results using specific channels (eg, their own webpage or scientific journals). The app synopsis could be seen as a “first level” approach according to criteria already specified by previous projects dealing with quality assurance for Web-based information sources [8], though its focus is slightly different. At first, it could serve to provide all interested parties with sufficient information that, in addition to providing customers with basic information about an app, can then also be used as a starting point for building tests (eg, to identify the appropriate reviewers and testing methods, independent of the business model or revenue strategy that is employed by each respective initiative). The current market players come from different backgrounds and thus also have different interests in mind. In Germany, for example, there are some initiatives focusing mainly on a single disease while others target health apps in general. Also, their funding strategies differ significantly, ranging from privately funded initiatives or publicly financed institutions to companies that are being paid on a case-by-case basis.

If manufacturers were to publish the necessary information following this app synopsis, both they as well as the users would clearly benefit. Users would receive a complete and easily comprehensible set of information that would support them in their decision making process while manufacturers would be able to follow the simple structure of the synopsis to compile the necessary information without expending too much effort since they only have to compile information that should already be available to them. Although this is not equivalent to an officially sanctioned certification process, information published according to the synopsis could nevertheless serve as a reference if there are any disputes between both sides.

Transparency of health-apps for trust and decision making

Background: Despite their increasing popularity, little is known about how users perceive mobile devices such as smartphones and tablet PCs in medical contexts. Available studies are often restricted to evaluating the success of specific interventions and do not adequately cover the users’ basic attitudes, for example, their expectations or concerns toward using mobile devices in medical settings. Objective: The objective of the study was to obtain a comprehensive picture, both from the perspective of the patients, as well as the doctors, regarding the use and acceptance of mobile devices within medical contexts in general well as the perceived challenges when introducing the technology.

https://serwiss.bib.hs-hannover.de/files/861/Mobile Technologies Expectancy, Usage, and Acceptance of Clinical Staff and Patients at a University Medical Center.pdf

Urs-Vito Albrecht

Papers

mHealth 2.0: Experiences, Possibilities, and Perspectives

Effects of mobile augmented reality learning compared to textbook learning on medical students: randomized controlled pilot study.

Google Glass for Documentation of Medical Findings: Evaluation in Forensic Medicine

Transparency of health-apps for trust and decision making

Mobile Technologies: Expectancy, Usage, and Acceptance of Clinical Staff and Patients at a University Medical Center