Human-AI collaborative decision-making tools are being increasingly applied in critical domains such as healthcare. However, these tools are often seen as closed and intransparent for human decision-makers. An essential requirement for their success is the ability to provide explanations about themselves that are understandable and meaningful to the users. While explanations generally have positive connotations, studies showed that the assumption behind users interacting and engaging with these explanations could introduce trust calibration errors such as facilitating irrational or less thoughtful agreement or disagreement with the AI recommendation. In this paper, we explore how to help trust calibration through explanation interaction design. Our research method included two main phases. We first conducted a think-aloud study with 16 participants aiming to reveal main trust calibration errors concerning explainability in AI-Human collaborative decision-making tools. Then, we conducted two co-design sessions with eight participants to identify design principles and techniques for explanations that help trust calibration. As a conclusion of our research, we provide five design principles: Design for engagement, challenging habitual actions, attention guidance, friction and support training and learning. Our findings are meant to pave the way towards a more integrated framework for designing explanations with trust calibration as a primary goal.

Today, social media play an important role in people’s daily lives. Many people use social media to satisfy their personal and social needs, such as enhancing self-image, acquiring self-esteem, and gaining popularity. However, when social media are used obsessively and excessively, behavioural addiction symptoms can occur, leading to negative impacts on one’s life, which is defined as a problematic attachment to social media. Research suggests that tools can be provided to assist the change of problematic attachment behaviour, but it remains unclear how such tools should be designed and personalised to meet individual needs and profiles. This study makes the first attempt to tackle this problem by developing five behavioural archetypes, characterising how social media users differ in their problematic attachments to them. The archetypes are meant to facilitate effective ideation, creativity, and communication during the design process and helping the elicitation and customisation of the variability in the requirements and design of behaviour change tools for combatting problematic usage of social media. This was achieved by using a four-phase qualitative study where the diary study method was considered at the initial stage, and also the refinement and confirmation stage, to enhance ecological validity.

Background: Social media addiction disorder has recently become a major concern and has been reported to have negative impacts on postgraduate studies, particularly addiction to Facebook. Although previous studies have investigated the effects of Facebook addiction disorder in learning settings, there still has been a lack of studies investigating the relationship between online intervention features for Facebook addiction focusing on postgraduate studies. Objective: In an attempt to understand this relationship, this study aimed to carry out an investigation on online intervention features for effective management of Facebook addiction in higher education. Methods: This study was conducted quantitatively using surveys and partial least square-structural equational modeling. The study involved 200 postgraduates in a Facebook support group for postgraduates. The Bergen Facebook Addiction test was used to assess postgraduates’ Facebook addiction level, whereas online intervention features were used to assess postgraduates’ perceptions of online intervention features for Facebook addiction, which are as follows: (1) self-monitoring features, (2) manual control features, (3) notification features, (4) automatic control features, and (5) reward features. Results: The study discovered six Facebook addiction factors (relapse, conflict, salience, tolerance, withdrawal, and mood modification) and five intervention features (notification, auto-control, reward, manual control, and self-monitoring) that could be used in the management of Facebook addiction in postgraduate education. The study also revealed that relapse is the most important factor and mood modification is the least important factor. Furthermore, findings indicated that notification was the most important intervention feature, whereas self-monitoring was the least important feature. Conclusions: The study’s findings (addiction factors and intervention features) could assist future developers and educators in the development of online intervention tools for Facebook addiction management in postgraduate education.

It is important to promote assistive technologies to improve quality of life. The proposed SmartAbility Android Application recommends assistive technologies for people with reduced physical abilit...

Background: As a result of the recent advancements in technology, the incorporation of digital interventions into the health care system has gained a lot of attention and adoption globally. However, these interventions have not been fully adopted, thereby limiting their impact on health care delivery in West Africa. Objective: This review primarily aims at evaluating the current digital interventions for medication and health care delivery in West Africa. Its secondary aim is to assess the impacts of digital interventions in managing medication and health care service delivery with the intent of providing vital recommendations that would contribute to an excellent adoption of digital intervention tools in the health care space in West Africa. Methods: In line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), a comprehensive search through various databases yielded 529 results. After a rigorous screening, 29 articles that provided information on 3 broad digital health intervention tools were found eligible for this review. Results: Out of 29 studies, 16 (55%) studies examined phone-based interventions, 9 (31%) studies focused on tele- and e-based interventions, and 4 (14%) studies evaluated digital interventions. These interventions were used for diverse purposes, some of which are monitoring adverse drug reactions, general health, sexual and reproductive health, and training of health care practitioners. The phone-based intervention appears to be the most known and impactful of all the interventions, followed by tele- and e-based, while digital interventions were scarcely used. Conclusions: Digital interventions have had a considerable level of impact on medication and health care delivery across West Africa. However, the overall impact is limited. Therefore, strategies must be developed to address the challenges limiting the use of digital intervention tools so that these tools can be fully incorporated into the health care space in West Africa.