Designing personalised mHealth solutions: An overview

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

Designing Personalised mHealth solutions: An overview

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

Empowering vulnerable people with serious games and gamification

Although many people will associate games with entertainment and leisure, games can also aim more serious purposes, such as training or education. Games with such goals are called serious games. In addition, gamification means that a (serious) task is enhanced with game elements. Examples of serious games and gamification can be seen in many aspects of daily life. Loyalty programs of stores, educational games in schools, fitness wearables and their gamified applications, rehabilitation games, and so on. In this dissertation, the focus is on a specific domain in which serious games and gamification can create societal benefit, namely by using them to empower vulnerable target groups. In the first part of this dissertation, a literature review is performed to understand the domain of serious games and gamification for vulnerable target groups. Based on this review, research gaps can be identified. Moreover, the review resulted in a taxonomy that is used throughout the dissertation to classify different games and applications. In the following parts of the dissertation, projects addressing two different target groups and in total three vulnerabilities are discussed. The first target group is older adults, who are vulnerable in different ways. In this dissertation, safety risks for doorstep scams and health risks through malnutrition are addressed. The first vulnerability is addressed by a serious game using interactive scenarios of doorstep scams. A diet tracking system that was used to support participants in a diet trial addressed the latter vulnerability. The second target group is young adults, which is an age group with a vulnerable mental well-being. The last part of this dissertation aims to study how gamification can be used to enhance self-compassion among young adults via an online 6-weeks training program, to increase their resilience in the face of mental well-being difficulties. Artificial Intelligence (AI) technologies can be used to personalize and adapt the experience of a game to users. Tone of voice analysis was used to influence the progression in scenarios of the serious game about doorstep scams, and it gave players the possibility to assess the assertiveness of their voice. Machine learning algorithms were used to create personalized meal recommendations that can be used to improve the user experience of the diet tracking system for older adults. These algorithms base their recommendations on information about the historical intake of users to suggest meals and to additional items during meal editing. This makes the process of registering a meal less time-consuming. Sentiment analysis is used to adapt responses of the system in an exercise from the self-compassion training program. In addition, a topic detection algorithm was designed to assign one topic from a predefined set of topics to a note by a user of the training program. With this information, users can choose different types of situations to use in the exercises: frequently or rarely discussed topics. Aside from those techniques, knowledge representation is used in all projects, which is important for serious games/gamified applications since they are often based on expert and/or domain knowledge. This dissertation contributes to understanding the domain of serious games and gamification to empower vulnerable groups. The work also contributes to the research on the development of applications within that domain. On top of that, it contributes to understanding how AI techniques can be used to offer (personalized) features that enrich serious games or gamified applications. Finally, for each of the project centered parts, the results that are found in those parts contribute to the research in those specific fields

Game-Based Learning, Gamification in Education and Serious Games

The aim of this book is to present and discuss new advances in serious games to show how they could enhance the effectiveness and outreach of education, advertising, social awareness, health, policies, etc. We present their use in structured learning activities, not only with a focus on game-based learning, but also on the use of game elements and game design techniques to gamify the learning process. The published contributions really demonstrate the wide scope of application of game-based approaches in terms of purpose, target groups, technologies and domains and one aspect they have in common is that they provide evidence of how effective serious games, game-based learning and gamification can be

The evaluation of social media to increase engagement rate, reach and health education: the case for WoW!

Introduction: In 2021, South Africans had a 51.9 percent chance of dying from an NCD. The Western Cape on Wellness (WoW!) program advocates for wellness, through partnership, innovation and policy, including health in communities, worksites and schools. Increasing knowledge and awareness regarding health behaviors and NCD risk factors is an important pathway in preventing and mitigating the problem at hand through a combination of structural and social policy change. Social media provides an unprecedented opportunity and innovative way to provide a solution to the problem. The internet has increasingly become a popular source of health information by connecting individuals with health content, experts, and support. Aim & Objective: To use a social media campaign with expert knowledge to change healthy lifestyle actions and increase health knowledge and engagement in a para-social western cape on wellness social media group. Methods: A mixed methods quantitative and qualitative analysis was undertaken to assess key messages, which were publicly available on the WoW! Facebook group. 60 lifestyle messages were posted on the WoW! Facebook group 5 times a week from Monday through to Friday. Each message was disseminated by a moderator and followed a theme for the day. Three icons were used to measure levels of participant engagement likes, shares, comments. Associated comments were extracted and coded using a codebook based on items from the supportive accountability model and peer social support analysis. The identified search material was reviewed allowing removal of any personally identifying or geographical material in order that that the comments were rendered anonymous. One –way ANOVA was performed to determine whether level of likes, shares and comments differed between posts. One-way ANOVA was performed to determine whether level of engagement differed between post types, with Tukey–Kramer test used to determine post hoc differences. An independent samples t-test was conducted to determine whether total engagement differed between moderator initiated posts and Facebook user-initiated posts. Results: The most common form of engagement was "likes," and engagement was higher for moderator initiated rather than participant-initiated posts. Overall traffic to the page increased over the 3 month period from 1083 WoW! Facebook users to 1300. Likes were the most common and easiest form of engagement (M=7.6, SD 9.8) with comments being the lowest (m=0.81, SD 2.3). The most engaged with and resonative messages were the #transformationthursday posts. Empirically physical activity behaviour and change in eating patterns did increase over time. The 7 main themes that were identified constituted 53.3% (112/210) of all comments in the pre and during campaign analyses. The most prevalent theme was social cohesion and connectedness at 29% (33/112). The least common theme was developing professional communication and organisational support at 4.5% (5/112). Overall, there were more comments before the campaign (n=63), than during (n=49). In terms of Geographical proximity most of the comments and posts came from participants in the Metro (58.3%) and rural districts Paarl (48.3%) and George (40%). A proximal or virtual tie to a place adds connection and thus value to the information. Conclusion: The favourable results of the WoW! Facebook campaign shows promise for future social media-driven health campaigns to educate and prevent lifestyle related chronic conditions. Social media content for knowledge sharing should be created through a well-intentioned process with the support of moderators to facilitate the conversation and drive engagement