Knowledge Gaps in Mobile Health Research for Promoting Physical Activity in Adults With Autism Spectrum Disorder

Abstract

A growing body of research highlights that adults with autism spectrum disorder (ASD) have poor health outcomes, yet effective health interventions are lacking for this population. While mobile health applications demonstrate potential for promoting physical activity (PA) in adults with ASD, scientific evidence for supporting this tool’s long-term effectiveness on PA behavior change remains inconclusive. This study aimed to provide the latest information on PA research and the prospective role of mobile health applications for promoting PA in adults with ASD. A literature review demonstrated that a few available studies show contradictory results regarding PA levels in adults with ASD, and behavior change techniques and gamification-guided mobile health applications can be promising tactics to leverage autism’s strengths and increase PA in these individuals. Optimizing design decisions based on needs analysis and user feedback is crucial to identifying and developing a sustainable mobile health intervention for PA promotion in adults with ASD.

Understanding the determinants of ePharmacy services: the moderating effect of technology discomfort

“…Only a few previous studies have focused on specific antecedents of ePharmacy, such as PE, effort expectancy, SI, hedonic motivation, etc., as these determinants; however, it is very clear that these few factors are inadequate for properly determining BI (Srivastava and Raina, 2021), and thus ePharmacy is still an unexplored area in academia (Meng et al, 2020). We also focused on young consumers' BI to use ePharmacy services, which are very limited (Lee, 2021). Again, previous studies have examined TD in relation to various technology usage theories, including Davis' (1989) technology acceptance model (TAM) and theory of planned behavior (TPB) (Tsourela and Roumeliotis, 2015), but to date, no study has evaluated TD using the UTAUT-2 model.…”

“…Tu et al (2021) found that older people expressed great concern about using new health technologies because of the technological barriers they encountered. While health applications are potentially convenient for older people, scientific evidence of their popularity among younger generations is scarce (Lee, 2021; Schuuring et al , 2016). Although younger people are more inclined to use new technologies, they are indifferent to using health technologies (Wu et al , 2022).…”

“…Hampshire et al (2015) mentioned that the death rate of young people is increasing for many reasons, including apathy toward using digital health technology, making it a major concern. Among the younger generations, members of Generation Z are characterized as being smart consumers of technology (Yunos and Din, 2019), although they have demonstrated some hesitation and anxiety regarding the use of technologies (Lee, 2021; Warden et al , 2020). Pandey et al (2021) found that the younger generation had a negative attitude toward using online technologies because of discomfort and fear.…”

Adoption of mobile health services using the unified theory of acceptance and use of technology model: Self-efficacy and privacy concerns

“…Mobile health (mHealth) services refer to the provision of medical services to users through mobile devices, such as smartphones, tablet computers, and satellite communications ( Jovanov and Zhang, 2004 ; Bai et al, 2020 ; Bally and Cesuroglu, 2020 ; Lee, 2021 ; Sujarwoto et al, 2022 ). mHealth services have changed the traditional healthcare and played an increasing important role in the medical service delivery through their unique features, such as ease of use, usefulness and convenience ( Liu et al, 2019 ; Crowell et al, 2022 ; Zhao et al, 2022 ).…”