Medication adherence is crucial for success in the management of patients with chronic conditions. This study analyzes whether a mobile application on a tablet aimed at supporting drug intake and vital sign parameter documentation affects adherence in elderly patients.Patients with coronary heart disease and no prior knowledge of tablet computers were recruited. They received a personal introduction to the mobile application Medication Plan, installed on an Apple iPad. The study was conducted using a crossover design with 3 sequences: initial phase, interventional phase (28 days of using the app system), and comparative phase (28 days of using a paper diary). Users experienced the interventional and comparative phases alternately.A total of 24 patients (12 males; mean age 73.8 years) were enrolled in the study. The mean for subjectively assessed adherence (A14-scale; 5-point Likert scale, from “never” to “very often” which results in a score from 0 to 56) before the study was 50.0 (SD = 3.44). After both interventions there was a significant increase, which was more pronounced after the interventional phase (54.0; SD = 2.01) than after the comparative phase (52.6; SD = 2.49) (for all pairs after both interventions, P <0.001). Neither medical conditions nor the number of drug intake (amount and frequency of drug taking) per day affected subjective adherence. Logging data showed a significantly stronger adherence for the medication app than the paper system for both blood pressure recordings (P <0.001) and medication intake (P = 0.033). The majority of participants (n = 22) stated that they would like to use the medication app in their daily lives and would not need further assistance with the app.A mobile app for medication adherence increased objectively and subjectively measured adherence in elderly users undergoing rehabilitation. The findings have promising clinical implications: digital tools can assist chronic disease patients achieve adherence to medication and to blood pressure measurement. Although this requires initial offline training, it can reduce complications and clinical overload because of nonadherence.

The use of robots in the national economy-especially in industrialized countries-is growing. At the same time, the interdependency between humans and robots is getting increasingly closer: they are engaging in direct contact with each other as more and more organizations let robots and humans work hand-in-hand. One factor that predicts successful human-robot interdependency is the acceptance of the robot by the human. Generally, only when an innovative assistive working system covers human needs and expectations, it is perceived to be useful and hence accepted. Furthermore, it has been found that cultural context has an impact on human-robot interaction, as people feel more comfortable interacting with a robot in a culturally normative way. Therefore this paper aims at presenting a human-robot collaboration acceptance model (HRCAM) with regard to the collaboration between humans and robots that is based on prior acceptance models, while also considering technology affinity and ethical, legal and social implications. Additionally, similarities and differences in robot acceptance are shown for four selected countries-both in comparison to the overall human-robot collaboration acceptance model and between the countries. The HRCAM additionally shows which variables influence perceived usefulness and perceived ease of use, and thus behavioral intention to use and use behavior. A further distinction is made between anchor variables, which can be influenced in the long term, and adjustment variables, which can be influenced in the short to medium term. The model therefore offers practitioners in the field of human-robot collaboration recommendations to increase the acceptance of robots. Keywords Technology acceptance • Human-robot interaction • Human-robot cooperation • Human-machine interaction • Cross-cultural differences • TAM

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PurposeA wealth of mobile applications are designed to support users in their drug intake. When developing software for patients, it is important to understand the differences between individuals who have, who will or who might never adopt mobile interventions. This study analyzes demographic and health-related factors associated with real-life “longer usage” and the “usage-intensity per day” of the mobile application “Medication Plan”.MethodsBetween 2010-2012, the mobile application “Medication Plan” could be downloaded free of charge from the Apple-App-Store. It was aimed at supporting the regular and correct intake of medication. Demographic and health-related data were collected via an online questionnaire. This study analyzed captured data.ResultsApp-related activities of 1799 users (1708 complete data sets) were recorded. 69% (1183/1708) applied “Medication Plan” for more than a day. 74% were male (872/1183), the median age 45 years. Variance analysis showed a significant effect of the users´ age with respect to duration of usage (p = 0.025). While the mean duration of use was only 23.3 days for users younger than 21 years, for older users, there was a substantial increase over all age cohorts up to users of 60 years and above (103.9 days). Sex and educational status had no effect. “Daily usage intensity” was directly associated with an increasing number of prescribed medications and increased from an average of 1.87 uses per day and 1 drug per day to on average 3.71 uses per day for users stating to be taking more than 7 different drugs a day (p<0.001). Demographic predictors (sex, age and educational attainment) did not affect usage intensity.ConclusionUsers aged 60+ as well as those with complicated therapeutic drug regimens relied on the service we provided for more than three months on average. Mobile applications may be a promising approach to support the treatment of patients with chronic conditions.

BackgroundProhibiting falls and fall-related injuries is a major challenge for health care systems worldwide, as a substantial proportion of falls occur in older adults who are previously known to be either frail or at high risk for falls. Hence, preventive measures are needed to educate and minimize the risk for falls rather than just minimize older adults’ fall risk. Health apps have the potential to address this problem, as they enable users to self-assess their individual fall risk.ObjectiveThe objective of this study was to identify product features of a fall prevention smartphone app, which increase or decrease users’ satisfaction. In addition, willingness to pay (WTP) was assessed to explore how much revenue such an app could generate.MethodsA total of 96 participants completed an open self-selected Web-based survey. Participants answered various questions regarding health status, subjective and objective fall risk, and technical readiness. Seventeen predefined product features of a fall prevention smartphone app were evaluated twice: first, according to a functional (product feature is implemented in the app), and subsequently by a dysfunctional (product feature is not implemented in the app) question. On the basis of the combination of answers from these 2 questions, the product feature was assigned to a certain category (must-be, attractive, one-dimensional, indifferent, or questionable product feature). This method is widely used in user-oriented product development and captures users’ expectations of a product and how their satisfaction is influenced by the availability of individual product features.ResultsFive product features were identified to increase users’ acceptance, including (1) a checklist of typical tripping hazards, (2) an emergency guideline in case of a fall, (3) description of exercises and integrated workout plans that decrease the risk of falling, (4) inclusion of a continuous workout program, and (5) cost coverage by health insurer. Participants’ WTP was assessed after all 17 product features were rated and revealed a median monthly payment WTP rate of €5.00 (interquartile range 10.00).ConclusionsThe results show various motivating product features that should be incorporated into a fall prevention smartphone app. Results reveal aspects that fall prevention and intervention designers should keep in mind to encourage individuals to start joining their program and facilitate long-term user engagement, resulting in a greater interest in fall risk prevention.