This study examines children's flow experiences in an interactive social game environment. A total of 33 children aged from 7 to 9 years participated in the study for 6 weeks. Data were collected through observations and interviews. In order to measure the flow experiences of the children, items of a flow scale were administered to the children through interviews. Results revealed that flow experiences occur more among boys than girls during gameplay. While ludology had more effect on the flow experiences of boys when compared with the narratology of computer games, narratology had more effect among girls. Challenge and complexity elements of games had more effect on the flow experiences of the children than clear feedback.
Background Many mobile health (mHealth) apps for mental health have been made available in recent years. Although there is reason to be optimistic about their effect on improving health and increasing access to care, there is a call for more knowledge concerning how mHealth apps are used in practice. Objective This study aimed to review the literature on how usability is being addressed and measured in mHealth interventions for mental health problems. Methods We conducted a systematic literature review through a search for peer-reviewed studies published between 2001 and 2018 in the following electronic databases: EMBASE, CINAHL, PsycINFO, PubMed, and Web of Science. Two reviewers independently assessed all abstracts against the inclusion and exclusion criteria, following the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Results A total of 299 studies were initially identified based on the inclusion keywords. Following a review of the title, abstract, and full text, 42 studies were found that fulfilled the criteria, most of which evaluated usability with patients (n=29) and health care providers (n=11) as opposed to healthy users (n=8) and were directed at a wide variety of mental health problems (n=24). Half of the studies set out to evaluate usability (n=21), and the remainder focused on feasibility (n=10) or acceptability (n=10). Regarding the maturity of the evaluated systems, most were either prototypes or previously tested versions of the technology, and the studies included few accounts of sketching and participatory design processes. The most common reason referred to for developing mobile mental health apps was the availability of mobile devices to users, their popularity, and how people in general became accustomed to using them for various purposes. Conclusions This study provides a detailed account of how evidence of usability of mHealth apps is gathered in the form of usability evaluations from the perspective of computer science and human-computer interaction, including how users feature in the evaluation, how the study objectives and outcomes are stated, which research methods and techniques are used, and what the notion of mobility features is for mHealth apps. Most studies described their methods as trials, gathered data from a small sample size, and carried out a summative evaluation using a single questionnaire, which indicates that usability evaluation was not the main focus. As many studies described using an adapted version of a standard usability questionnaire, there may be a need for developing a standardized mHealth usability questionnaire.
Internet-Delivered Psychological Treatments (IDPT) are based on evidence-based psychological treatment models adjusted for interaction through the Internet. The use of Internet technologies has the potential to increase the availability of evidence-based mental health services for a far-reaching population with the use of fewer resources. Despite evidence that Internet Interventions can be effective means in mental health morbidities, most current IDPT systems are tunnel-based, inflexible, and non-interoperable. Hence it becomes essential to understand which elements of an Internet intervention contribute to effectiveness and treatment outcomes. By analogy, adaptation is a central aspect of successful face-to-face mental health therapy. Adaptability to patient needs can be regarded as an essential outcome factor in online systems for mental health interventions as well. While some aspects of rule-based and machine-learning-based adaptation have attracted attention in recent IDPT development, systematic reporting of core components, dimensions of adaptiveness, information architecture, and strategies for adaptation in the IDPT system are still lacking. To bridge this gap, we propose a model that shows how adaptive systems are represented in classical control theory and discuss how the model can be used to specify adaptive IDPT systems. Concerning the reference model, we outline the core components of adaptive IDPT systems, the main adaptive elements, dimensions of adaptiveness, information architecture applied to adaptive systems, and strategies used in the adaptation process. We also provide comprehensive guidelines on how to develop an adaptive IDPT system based on the Person-Based Approach.
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