Exploring user experience and technology acceptance for a fall prevention system: results from a randomized clinical trial and a living lab

Background: Falls are common in older adults and can result in serious injuries. Due to demographic changes, falls and related healthcare costs are likely to increase over the next years. Participation and motivation of older adults in fall prevention measures remain a challenge. The iStoppFalls project developed an information and communication technology (ICT)-based system for older adults to use at home in order to reduce common fall risk factors such as impaired balance and muscle weakness. The system aims at increasing older adults’ motivation to participate in ICT-based fall prevention measures. This article reports on usability, user-experience and user-acceptance aspects affecting the use of the iStoppFalls system by older adults. Methods: In the course of a 16-week international multicenter study, 153 community-dwelling older adults aged 65+ participated in the iStoppFalls randomized controlled trial, of which half used the system in their home to exercise and assess their risk of falling. During the study, 60 participants completed questionnaires regarding the usability, user experience and user acceptance of the iStoppFalls system. Usability was measured with the System Usability Scale (SUS). For user experience the Physical Activity Enjoyment Scale (PACES) was applied. User acceptance was assessed with the Dynamic Acceptance Model for the Re-evaluation of Technologies (DART). To collect more detailed data on usability, user experience and user acceptance, additional qualitative interviews and observations were conducted with participants. Results: Participants evaluated the usability of the system with an overall score of 62 (Standard Deviation, SD 15.58) out of 100, which suggests good usability. Most users enjoyed the iStoppFalls games and assessments, as shown by the overall PACES score of 31 (SD 8.03). With a score of 0.87 (SD 0.26), user acceptance results showed that participants accepted the iStoppFalls system for use in their own home. Interview data suggested that certain factors such as motivation, complexity or graphical design were different for gender and age. Conclusions: The results suggest that the iStoppFalls system has good usability, user experience and user acceptance. It will be important to take these along with factors such as motivation, gender and age into consideration when designing and further developing ICT-based fall prevention systems

Substance abuse and intimate partner violence: treatment considerations

Given the increased use of marital- and family-based treatments as part of treatment for alcoholism and other drug disorders, providers are increasingly faced with the challenge of addressing intimate partner violence among their patients and their intimate partners. Yet, effective options for clinicians who confront this issue are extremely limited. While the typical response of providers is to refer these cases to some form of batterers' treatment, three fundamental concerns make this strategy problematic: (1) most of the agencies that provide batterers' treatment only accept individuals who are legally mandated to complete their programs; (2) among programs that do accept nonmandated patients, most substance-abusing patients do not accept such referrals or drop out early in the treatment process; and (3) available evidence suggests these programs may not be effective in reducing intimate partner violence. Given these very significant concerns with the current referral approach, coupled with the high incidence of IPV among individuals entering substance abuse treatment, providers need to develop strategies for addressing IPV that can be incorporated and integrated into their base intervention packages

Empowering Qualitative Research Methods in Education with Artificial Intelligence

Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology to mention a few. However, one of the disciplines in which artificial intelligence has not been fully explored and exploited yet is education. In this discipline, many research methods are employed by scholars, lecturers and practitioners to investigate the impact of different instructional approaches on learning and to understand the ways skills and knowledge are acquired by learners. One of these is qualitative research, a scientific method grounded in observations that manipulates and analyses non-numerical data. It focuses on seeking answers to why and how a particular observed phenomenon occurs rather than on its occurrences. This study aims to explore and discuss the impact of artificial intelligence on qualitative research methods. In particular, it focuses on how artificial intelligence have empowered qualitative research methods so far, and how it can be used in education for enhancing teaching and learning

Deconstructing Dad

Fatherhood is seen as a natural right—a transition that is the ultimate sign that a man is virile, and bestows concomitant status, rights and privileges. The demographic, social, and economic changes across the last few decades have led to increased scrutiny of parenthood. Much of the focus is on fertility trends and the impact of childlessness for women. However, although there are more childless men than childless women, there is very little research literature on the impact of male involuntary childlessness