More and more seniors are using computers and smartphones on a regular basis. However, research shows that many seniors are only using a small number of the apps available to them, in contrast to younger adults. The current study aims to explore reasons for this selective use of apps by seniors.
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Welke beweeg-apps zijn bruikbaar bij het stimuleren van meer bewegen bij thuiswonende ouderen? In het project ‘Meer bewegen met uw Smartphone’ is kennis opgedaan over geschikte beweeg-apps voor ouderen. Tevens is onderzocht hoe een keuzewijzer beweeg-apps het beste gebruikt kan worden door zorgverleners in de eerstelijn.
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Results of an explorative study to gather experiences and identify barriers and facilitators for using e-health apps and wearables.
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De Nederlandse media-industrie merkt elke dag hoe groot de impact is van het voortschrijdende proces van digitalisering en dataficering. De transitie van analoge (broadcast) naar digitale (over-the top: OTT) netwerken zorgt er niet alleen voor dat mensen televisie kunnen kijken op ieder gewenst moment met het apparaat naar keuze, het maakt tevens interactie mogelijk met de kijker. Bij die interactie wordt allerhande data over de gebruiker verzameld. De kansen om hiermee nieuwe diensten te ontwikkelen blijven echter veelal onbenut. Vooral voor interactieve mediabedrijven ligt hier een kans omdat het hun apps zijn die grote hoeveelheden gebruikersdata verzamelen. Interactieve mediabedrijven hebben echter momenteel moeite om de gebruikersdata uit hun apps zodanig te analyseren dat nieuwe inzichten ontstaan waarop bestaande diensten (continue) verbeterd kunnen worden, nieuwe diensten voor hun klanten kunnen worden ontwikkeld én zijzelf diensten kunnen gaan vermarkten vanuit een zelfstandige positie. De terugkerende vraag is dan ook: Hoe kunnen nieuwe inzichten uit gebruikersdata systematisch worden verzameld, geanalyseerd en gevalideerd, en welke businessmodellen helpen om deze nieuwe inzichten te borgen in de strategie van de organisatie?
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Individual and unorganized sports with a health-related focus, such as recreational running, have grown extensively in the last decade. Consistent with this development, there has been an exponential increase in the availability and use of electronic monitoring devices such as smartphone applications (apps) and sports watches. These electronic devices could provide support and monitoring for unorganized runners, who have no access to professional trainers and coaches. The purpose of this paper is to gain insight into the characteristics of event runners who use running-related apps and sports watches. This knowledge is useful from research, design, and marketing perspectives to adequately address unorganized runners’ needs, and to support them in healthy and sustainable running through personalized technology. Data used in this study are drawn from the standardized online Eindhoven Running Survey 2014 (ERS14). In total, 2,172 participants in the Half Marathon Eindhoven 2014 completed the questionnaire (a response rate of 40.0%). Binary logistic regressions were used to analyze the impact of socio-demographic variables, running-related variables, and psychographic characteristics on the use of running-related apps and sports watches. Next, consumer profiles were identified. The results indicate that the use of monitoring devices is affected by socio-demographics as well as sports-related and psychographic variables, and this relationship depends on the type of monitoring device. Therefore, distinctive consumer profiles have been developed to provide a tool for designers and manufacturers of electronic running-related devices to better target (unorganized) runners’ needs through personalized and differentiated approaches. Apps are more likely to be used by younger, less experienced and involved runners. Hence, apps have the potential to target this group of novice, less trained, and unorganized runners. In contrast, sports watches are more likely to be used by a different group of runners, older and more experienced runners with higher involvement. Although apps and sports watches may potentially promote and stimulate sports participation, these electronic devices do require a more differentiated approach to target specific needs of runners. Considerable efforts in terms of personalization and tailoring have to be made to develop the full potential of these electronic devices as drivers for healthy and sustainable sports participation.
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In deze presentatie wordt in kaart gebracht, wat weten we over app gebruik en wat zijn de resultaten naar onderzoek van apps. Ook worden nieuwe projecten op het gebied van apps en bewegen toegelicht. Ten slotte wordt besproken wat we nog niet weten.
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Tijdens de expertmeeting Bewegingsstimulering door apps en online programma’s georganiseerd door het Kenniscentrum Sport heeft Joan Dallinga een presentatie gehouden over de huidige stand van zaken over app onderzoek en uitdagingen waar we voor staan.
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In deze presentatie komen de volgende onderwerpen aan bod: wie gebruiken apps en wearables, resultaten onderzoek apps en leefstijl/gezondheid, nieuwe projecten waarin technologie ingezet wordt om bewegen te stimuleren en ideeen voor de toekomst.
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In recent years, there has been an exponential increase in the use of health and sports-related smartphone applications (apps). This is also reflected in App-stores, which are stacked with thousands of health- and sports-apps, with new apps launched each day. These apps have great potential to monitor and support people’s physical activity and health. For users, however, it is difficult to know which app suits their needs. In this paper, we present an online tool that supports the decision-making process for choosing an appropriate app. We constructed and validated a screening instrument to assess app content quality, together with the assessment of users’ needs. Both served as input for building the tool through various iterations with prototypes and user tests. This resulted in an online tool which relies on app content quality scores to match the users’ needs with apps that score high in the screening instrument on those particular needs. Users can add new apps to the database via the screening instrument, making the tool self-supportive and future proof. A feedback loop allows users to give feedback on the recommended app and how well it meets their needs. This feedback is added to the database and used in future filtering and recommendations. The principles used can be applied to other areas of sports, physical activity and health to help users to select an app that suits their needs. Potentially increasing the long-term use of apps to monitor and to support physical activity and health.
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Which factors are important for effectiveness of sport- and health-related apps? Results of focus groups with experts.Dallinga, J, van der Werf, J , Janssen, M, Vos, S, Deutekom-Baart de la Faille, M.A huge amount of sport- and health-related smartphone applications (apps) is available in the app stores [1]. These apps are often used by individual recreational athletes participating in running, walking or cycling [2]. Exercise apps ideally should support athletes and encourage them to be physical active in a frequent and healthy way. In order to reach these goals, more insight into the value of different app features is necessary. With this knowledge the health enhancing effects of apps can be improved. Therefore the aim of this study was to identify which features in sport- and health-related apps are important for stimulating and maintaining physical activity. Two focus groups (n=4 & n=3) were organized to identify and rank app features relevant for increasing and maintaining physical activity. These groups were facilitated by two of the authors (JD and JvdW). A nominal group technique was used. Seven behavioral and sport scientists participated in the focus groups consisting of three consultation rounds. In the first round these experts were asked to individually list all factors that they found necessary for increasing and maintaining physical activity. After that, all factors were collected, explained and listed on a white board. In the second round the experts were asked to individually rank the ten most important features. Subsequently, these rankings were discussed groupwise. In the last round, the experts individually made a final ranking of the ten most important features. In addition, they were also asked to appoint a score to each feature (0-100), to indicate the importance.The participants in the focus groups generated 28 and 24 features respectively in round one. After combining these features and checking for duplicates, we reduced the number of features to 25. Factors with highest frequency in the top 10 most important factors were ‘usability’ (n=7), ‘monitoring’ (n=5), ‘fun’ (n=5), ‘anticipating/context awareness’ (n=5) and ‘motivational feedback’ (n=4). Factors with highest importance scores were ‘instructional feedback’ (95.0), ‘motivating/challenging’ (95.0), ‘monitoring’ (92.5), ‘peer rating and peer use’ (92.0) and ‘motivational feedback’ (91.3). In conclusion, based on opinions of behavioral and sport scientists several app features were extracted related to physical activity, with instructional feedback and features that motivate or challenge the athlete as most important. A smart and tailored app may need to be developed that can provide feedback and anticipate on the environment. A feature for monitoring and a fun element may need to be included as well. Interestingly, usability was mentioned by all experts, this seems to be a premise for effectiveness of the app. Based on the results of this study, currently available exercise app rating scales could be revised [3, 4].This research is cofinanced by ‘Regieorgaan SIA’, part of the Netherlands Organisation for Scientific Research (NWO) and by the Dutch national program COMMIT.References[1] Yuan S, Ma W, Kanthawala S, Peng W. Keep Using My Health Apps: Discover Users' Perception of Health and Fitness Apps with the UTAUT2 Model. Telemed J E Health. 2015 Sep;21(9):735-41. doi: 10.1089/tmj.2014.0148.[2] Dallinga JM., Janssen M, van der Bie J, Nibbeling N, Krose B, Goudsmit J, Megens C, Baart de la Faille-Deutekom M en Vos S. De rol van innovatieve technologie in het stimuleren van sport en bewegen in de steden Amsterdam en Eindhoven. Vrijtijdstudies. 2016, 34 (2): 43-57.[3] Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol. 2008 May;27(3):379-87. doi: 10.1037/0278-6133.27.3.379.[4] Stoyanov SR, Hides L, Kavanagh DJ, Zelenko O, Tjondronegoro D, Mani M. Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR Mhealth Uhealth. 2015 Mar 11;3(1):e27. doi: 10.2196/mhealth.3422
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