1,232 research outputs found

    Gamification of Older Adults’ Physical Activity: An Eight-Week Study

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    Designing fitness programs to combat a sedentary lifestyle and foster older adults’ motivation and goal-setting is not yet well-understood beyond point-based systems. To improve older adults’ (over 50 years) health and wellness, we studied a gamified physical activity intervention over eight weeks in an experiment (N=30) with three conditions (gamified, non-gamified, control). Our qualitative analysis showed the gamified group exhibited more engagement and interest in performing physical activity facilitated by technology. Results from our quantitative analysis indicated significance in the perceived competence dimension compared to the non-gamified and the control group. Perceived autonomy was significant for the non-gamified group against the control group. The findings from qualitative and quantitative analysis show motivation, enjoyment, and engagement were higher in the gam-ified group. This provides support for successfully facilitating older adults’ physical activity through gamified technology, which helped us create guide-lines for older adults’ adaptive engagement

    THERAPEUTIC STRATEGY IN GAMIFICATION AND GAME BASED LEARNING FOR ELDERLY PEOPLE IN THAILAND

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    Purpose: This study aims to review the literature of the therapeutic strategies in gamification and a game-based learning for elderly people. During the increasing of the aging city in Thailand, how to prepare and how to live up the society are challenged. Gamification as a Game-based learning is a key issue in terms of conception. The conception of the game focuses on establishing trust with players and finding the right way to motivate the players to care for their health and to encourage the players to set goals. Methodology:A survey of healthcare for aging people was conducted in regard to technology-driven gamification.Gamified training appears to be highly engaging and does boost participant motivation.The survey attempts to examine Thai culture in terms of game technology and family networks and supports the influence the health-promoting behaviors among older persons. Main Findings:The reviews illustrate the role of game-based learning in therapeutic strategies. In accordance with the Gamification Concept, the concepts of games are broad in scope,encompassing various contexts, such as training. The results of this findings may influence Thai elderly to care their healthy by using gamification. The game design shows the Health Care Training Game and Gamification prototype. Implications:Gamification strategies may contribute to sustainable healthcare in Thailand.The designing game examines the therapeutic strategy game by establishing a technology-driven trust relationship with players, and then determining the best way to motivate the players to care for their health. Originality:Knowledge and skills can be improved by using game-based learning. A learning game is a self-contained unit with start, game play and ending activities. The games are based on a combination of well-known game-design principles and principles of task-oriented training and involve the manipulation of everyday physical objects

    Use of a smartphone app combined with gamification to increase the level of physical activity of adults and older adults: protocol of a sequential multiple assignment randomized trial

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    Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP: 2016/50249–3FAPESP: 2018/11817–1Background There is scientific evidence suggesting that app-based interventions targeted to increase the level of physical activity might be effective, although multicomponent interventions appear to be more effective than app-based interventions alone. Despite the motivating results, it remains unclear whether or not app-based interventions can increase the level of physical activity and cardiovascular health. Our study aims to investigate the effect of a smartphone app combined with gamification on the level of physical activity of adults and older adults. The specific aims are (1) to verify the effects of the intervention on cardiometabolic and cardiovascular health, lung function, and cardiorespiratory fitness; and (2) to verify the relationship between age group and the response rate. Methods/design We will conduct a sequential multiple assignment randomized trial (SMART). The adaptive intervention protocol will last 6 months. After baseline assessments, participants will be randomized into one of three groups (group 1: app + tailored messages; group 2: app + tailored messages + gamification I; control group: physical activity counseling). For 12 weeks, we will record the average number of steps per day of participants from groups 1 and 2. At 6 weeks from initiation of recording, participants will be classified into responders and non-responders according to their increase in the average number of daily steps; all those considered as non-responders will be re-randomized, with the chance to participate in a third group – group 3: app + tailored messages + gamification II. Finally, at 12 weeks, participants will continue using the app but will no longer receive direct intervention from investigators. All participants will be reassessed at 3 and 6 months from baseline. Our pilot SMART will require 42 participants (14 per arm). Following the SMART pilot, we will calculate the sample size for the trial based on the variation of the average number of steps/day, including an up to 40% loss to follow-up and a less optimistic nonresponse rate of 65%. Discussion To our knowledge, this will be the first trial with adaptive intervention to test the effectiveness of using a smartphone app to increase the level of physical activity of adults and older adults

    Evaluating the impact of physical activity apps and wearables: interdisciplinary review

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    Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines

    Autonomy in Video Games and Gamification

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    In the past decade, gamification (using game elements in non-gaming tasks to enhance motivation and engagement) has become a popular concept in many industries, but few studies have explored the principles under which it works. Self-determination theory suggests three psychological needs that gamification fulfills: competence, relatedness, and autonomy. Autonomy, a person\u27s perception that they have the ability to act however they choose, has emerged as an important, yet less-studied aspect in gamification. Inclusion of autonomy in gamification should foster engagement, enjoyment, and better performance. An experiment inspired by the above was carried out in which a sample of college students (N = 57) played a video game called Super Mario Bros. Crossover with either the choice to customize the aesthetics of their character and background (autonomy-supportive) or no choice of aesthetics (non-supportive). It was hypothesized that conditions involving more choice would lead to higher perceived autonomy and performance, and that perceived autonomy would be positively correlated with engagement, enjoyment, and performance. The manipulation resulted in no significant difference in perceived autonomy or performance, and perceived autonomy was only significantly positively correlated with enjoyment. Prior Super Mario Bros. experience was also found to positively correlate with perceived autonomy in the autonomy-supportive condition. The choice of aesthetics does not appear to have been sufficiently strong enough to increase perceived autonomy in this context

    Exploring virtual rewards in real life: A gimmick or a motivational tool for promoting physical activity?

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    Virtual rewards, digital badges or points, are often awarded to extrinsically reinforce desirable user behaviors. Acknowledging their motivational power for increased user engagement and enhanced playfulness, virtual reward systems are widely employed in contemporary activity tracking devices and services. While the characteristics of the current virtual reward systems vary and previous studies point to mixed outcomes around the effectiveness of virtual rewards for encouraging physical activity, there is little empirical research on the actual use and impact of virtual rewards provided from activity tracking tools in a real-life environment. To address the knowledge gaps on the use and effects of virtual rewards, I investigate the lived experiences of users with the virtual reward system of the activity tracking tool and their effects and value in the physical activity practices of individuals. To understand this both qualitatively and quantitatively, I conduct user experience research using mixed methods. Diary-based autoethnography research is preceded using three popular activity trackers, thereby having and documenting situated experiences with two different digital badge systems and one points-based system. My autoethnographic exploration is followed by an online survey with 113 existing users of activity tracking devices. The collected data is analysed through content and statistical analyses. By interpreting the findings from both studies and the reviewed literature, this thesis illustrates in great detail how virtual rewards interact with users and other system features in real-life practices. In addition, it provides a clearer picture of the effects of virtual rewards on people’s engagement in physical exercise and what makes some of them more valuable. Finally, it offers a set of considerations for the design of virtual reward systems that can lead to more user-centric, multi-layered, and meaningful virtual reward experience

    Games for health & mHealth apps for police & blue light personnel: A research review

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    Previous research has reported adverse health outcomes for emergency services personnel (ESP), outcomes that research more broadly has shown can be improved using a gamification and mobile health (mhealth) apps approach. We conducted a review of research on gamification and mhealth apps for ESP that had been published in the last 19 years using 6 major research databases. The results demonstrated that virtually no relevant research has been published, suggesting a significant gap in the evidence base of an approach that could potentially have significant benefits for the health of ESP

    14 Years of Self-Tracking Technology for mHealth -- Literature Review: Lessons Learnt and the PAST SELF Framework

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    In today's connected society, many people rely on mHealth and self-tracking (ST) technology to help them adopt healthier habits with a focus on breaking their sedentary lifestyle and staying fit. However, there is scarce evidence of such technological interventions' effectiveness, and there are no standardized methods to evaluate their impact on people's physical activity (PA) and health. This work aims to help ST practitioners and researchers by empowering them with systematic guidelines and a framework for designing and evaluating technological interventions to facilitate health behavior change (HBC) and user engagement (UE), focusing on increasing PA and decreasing sedentariness. To this end, we conduct a literature review of 129 papers between 2008 and 2022, which identifies the core ST HCI design methods and their efficacy, as well as the most comprehensive list to date of UE evaluation metrics for ST. Based on the review's findings, we propose PAST SELF, a framework to guide the design and evaluation of ST technology that has potential applications in industrial and scientific settings. Finally, to facilitate researchers and practitioners, we complement this paper with an open corpus and an online, adaptive exploration tool for the PAST SELF data.Comment: 40 pages, 10 figure

    Designing Personalised mHealth solutions: An overview

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    Introduction Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation. Materials and Methods We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques. Results Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis. Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease self-management and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed. Discussion Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it. Conclusions Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques
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