E-coaching Systems Research Articles

E-coaching systems and social justice: ethical concerns about inequality, coercion, and stigmatization

AbstractPoor self-regulation has been linked to various behaviors that contribute to pressing societal issues, including rising household debt, inefficient use of sustainable resources, and increasing healthcare demands. In light of this observation, the prospect of individuals receiving automated, tailored support by “e-coaching systems” to scaffold and improve their self-regulation is thought to hold promise for making society-wide progress in addressing such issues. Though there may be legitimate reasons for promoting the use of such systems, and individuals might welcome the support, our aim in the present article is to contribute to the ethics of e-coaching by showing how societal pressures towards the widespread adoption of automated e-coaching systems raise concerns in relation to three distinct aspects of social justice. We argue that societal inequalities may be introduced or exacerbated by (1) unequal access to the technologies, (2) unequally distributed restrictions to liberty and subjection to coercion, and (3) the potentially disparate impact of the use of e-coaching technologies on (self-)stigmatizing perceptions of competence. The article offers a research agenda for studying and addressing these concerns.

Fair performance-based user recommendation in eCoaching systems

Offering timely support to users in eCoaching systems is a key factor to keep them engaged. However, coaches usually follow a lot of users, so it is hard for them to prioritize those with whom they should interact first. Timeliness is especially needed when health implications might be the consequence of a lack of support. In this paper, we focus on this last scenario, by considering an eCoaching platform for runners. Our goal is to provide a coach with a ranked list of users, according to the support they need. Moreover, we want to guarantee a fair exposure in the ranking, to make sure that users of different groups have equal opportunities to get supported. In order to do so, we first model their performance and running behavior and then present a ranking algorithm to recommend users to coaches, according to their performance in the last running session and the quality of the previous ones. We provide measures of fairness that allow us to assess the exposure of users of different groups in the ranking and propose a re-ranking algorithm to guarantee a fair exposure. Experiments on data coming from the previously mentioned platform for runners show the effectiveness of our approach on standard metrics for ranking quality assessment and its capability to provide a fair exposure to users. The source code and the preprocessed datasets are available at: https://github.com/wiguider/Fair-Performance-based-User-Recommendation-in-eCoaching-Systems.

Virtual Avatar-Based Life Coaching for Children With Autism Spectrum Disorder

The rapid development of computer and sensing technologies enables e-coaching systems for individuals with various physical health and mental health challenges. In this article, we review recent research efforts on using virtual avatar-based computer technologies to improve social and communication skills of children with autism spectrum disorder (ASD) and outline the research needed for building the next generation virtual avatar-based life coaching system for children with ASD.

Virtual Coaches for Older Adults’ Wellbeing: A Systematic Review

Virtual Coaches, also known as e-coaches, are a disruptive technology in healthcare. Indeed, among other usages, they might provide cost-effective solutions for increasing human wellbeing in different domains, such as physical, nutritional, cognitive, social, and emotional. This paper presents a systematic review of virtual coaches specifically aimed at improving or maintaining older adults' health in the aforementioned domains. Such digital systems assume various forms, from classic apps, to more advanced conversational agents or robots. Fifty-six articles describing a virtual coach for older adults and aimed at improving their wellbeing were identified and further analyzed. In particular, we presented how previous studies defined their virtual coaches, which behavioral change models and techniques they adopted and the overall system architecture, in terms of monitoring solutions, processing methods and modalities for intervention delivery. Our results show that few thorough evaluations of e-coaching systems have been conducted, especially regarding multi-domain coaching approaches. Through our analysis, we identified the wellbeing domains that should be addressed in future studies as well as the most promising behavior change models and techniques and coaching interfaces. Previous work illustrates that older adults often appreciate conversational agents and robots. However, the lack of a multidomain intervention approach in the current literature motivates us to seek to define future solutions.

Architecting E-Coaching Systems: A First Step for Dealing with Their Intrinsic Design Complexity

E-coaching systems are a highly valuable asset for promoting healthier lifestyles. However, the design of these systems is intrinsically complex. This article proposes a loosely coupled architecture to support the modeling of e-coaching solutions, reducing design complexity and enhancing the flexibility required for the e-coaching process.

What technological features are used in smartphone apps that promote physical activity? A review and content analysis

Despite the well-known health benefits of physical activity, a large proportion of the population does not meet the guidelines. Hence, effective and widely accessible interventions to increase levels of physical activity are needed. Over the recent years, the number of health and fitness apps has grown rapidly, and they might form part of the solution to the widespread physical inactivity. However, it remains unclear to which extent they make use of the possibilities of mobile technology and form real e-coaching systems. This study aims to investigate the current landscape of smartphone apps that promote physical activity for healthy adults. Therefore, we present a framework to rate the extent to which such apps incorporate technological features. And, we show that the physical activity promotion apps included in the review implemented an average of approximately eight techniques and functions. The features that were implemented most often were user input, textual/numerical overviews of the user’s behavior and progress, sharing achievements or workouts in social networks, and general advice on physical activity. The features that were present least often were adaptation, integration with external sources, and encouragement through gamification, some form of punishment or the possibility to contact an expert. Overall, the results indicate that apps can be improved substantially in terms of their utilization of the possibilities that current mobile technology offers.

Special issue on supporting a healthier lifestyle with e-coaching systems

Special issue on supporting a healthier lifestyle with e-coaching systems

Contributing or receiving-the role of social interaction styles in persuasion over a social networking platform

In this paper, the use of the network platform Twitter is explored in relation to behavior change (BC) for health. We studied the effect of participation style (tweeters vs. non-tweeters) on perceived health behavior change through the constructs social influence, efficacy, and pre-test health In the experiment (N = 30), participants were given a basic health message, and the tweeters were then asked to actively search, think up, and share tips and guidance with non-tweeters. Results indicate that for both tweeters and non-tweeters, efficacy and influence were positively related, but that efficacy and perceived health behavior change are only positively related for non-tweeters. From this, we concluded that participation style can impact the effect of efficacy on target behavior. To understand the information processing in the two groups in terms of higher or lower need for cognition, we also studied the participants' thought elaboration. We found that tweeters were more distracted from elaboration on the health message, in particular those tweeters presenting a higher need for cognition. From this, we concluded that taking an active content creating role in peer-to-peer e-coaching systems may lead (a) to higher efficacy appraisal without a positive impact on BC and (b) to reduced attention on the intended behavior change message. In other words, the position of producing content may not translate into better intake of that content. In conclusion, there is a need for investigating strategies for overcoming the distracting nature of an active sharing role in e-coaching systems presented by a network platform.

E-coaching systems

The ongoing digitalization and automation of coaching practices is rapidly changing the landscape of coaching and (health-related) self-improvement. The introduction of a new class of support technologies— “e-coaching systems”—promises to deliver highly personalized, timely, around-the-clock coaching in a wide variety of domains and to a broad audience. At the same time, the introduction of these systems raises a number of practical and ethical concerns regarding, for example, privacy and personal autonomy, that deserve careful consideration. Unfortunately, constructive conversations about these technologies are hindered by the lack of a precise understanding of what constitutes an e-coaching system and how e-coaching systems differ from other types of behavior change interventions. The broad and inclusive definitions that have been offered in the recent literature facilitate a systematic underestimation of the impact that the introduction of e-coaching systems will have, by allowing discussions to include examples of systems with which people are familiar but which lack the level of sophistication and independence needed for a genuine process of coaching. As a consequence, specific concerns that arise with sophisticated, adaptive systems that form their own perspective on a user’s health and behavior and from that perspective shape persuasive interactions, remain out of focus. This paper aims to remedy this situation by proposing a more narrowly construed definition of e-coaching systems.

An e-coaching ecosystem: design and effectiveness analysis of the engagement of remote coaching on athletes

Nowadays, the use of mobile applications and wearable technologies to support and encourage an active lifestyle has become widespread. Several studies put in evidence that the usage of these kinds of support has to be monitored by high-qualified figures, to favor a safe and a long-term adherence to training routines. In order to investigate the impact of these professionals, this work sets out to provide an overview and an evaluation of an e-coaching ecosystem specifically designed for runners. The platform supports and guides people towards an active lifestyle by stimulating their motivation to exercise through the engagement provided by the interactions between users and human trainers. In this study, we investigate the effectiveness of the support offered by the human trainers and the engagement of the users. The results show that the support of human qualified trainers is crucial. Users tend to be more engaged to train when their trainings are developed and remotely supervised by a human coach. This has resulted in more workout sessions performed with respect to users exercising by following standard or self-made routines without direct professional supervision. Our findings show that e-coaching systems should develop their coaching protocols always taking into account the effectiveness of the support of qualified professionals over completely automated approaches.

Why option generation matters for the design of autonomous e-coaching systems

Autonomous e-coaching systems offer their users suggestions for action, thereby affecting the user's decision-making process. More specifically, the suggestions that these systems make influence the options for action that people actually consider. Surprisingly though, options and the corresponding process of option generation--a decision-making stage preceding intention formation and action selection--have received very little attention in the various disciplines studying decision making. We argue that this neglect is unjustified and that it is important, particularly for designers of autonomous e-coaching systems, to understand how human option generation works. The aims of this paper are threefold. The first aim is to generate awareness with designers of autonomous e-coaching systems that these systems do in fact influence their users' options. The second is to show that understanding the interplay between a person's options and the e-coaching system's suggestions is important for improving the effectiveness of the system. The third is that the very same interplay is also crucial for designing e-coaching systems that respect people's autonomy.

E-coaching systems: Convenient, anytime, anywhere, and nonhuman

Technologies continue to evolve to provide more compelling and interactive learning opportunities. Coaching has traditionally been face-to-face or by email. By combining the new technologies with coaching, learning developers now have the opportunity to develop an asynchronous, online, nonhuman coaching system, or e-coaching system. An e-coaching system can alleviate much of the coaching labor while making it more conducive to the coachee.