Background: Technology use among older adults is increasingly common. Even though there is potential in leveraging technology to help them manage their health, only a small fraction of them use it for health-related purposes.
Objective: This study seeks to understand the perspectives of and experiences with digital health (DH) among older adults in Singapore.
Methods: A total of 16 participants (age range 60-80 years; n=11, 69% female) were interviewed for approximately an hour (range 27-64 minutes) about their health, DH use, and DH experiences. The interviews were recorded, transcribed verbatim, and thematically analyzed.
Results: Five main themes emerged from the interview: support in developing DH literacy, credibility, cost and benefit considerations, intrinsic drive to be healthy, and telehealth. Older adults need support in familiarizing themselves with DH. When considering DH options, older adults often relied on credible sources and preferred DH to be free. Monetary incentives were brought up as motivators. The intrinsic drive to live longer and healthily was expressed to be a huge encouragement to use DH to help obtain health-related knowledge and achieve healthy living goals. The idea of telehealth was also appealing among older adults but was seen to be more suited for individuals who have issues accessing a physical clinic.
Conclusions: Our findings offer insights into the various aspects that matter to older adults in the adoption of DH, which in turn can help reshape their health-seeking behavior and lifestyle. As such, policy makers and DH implementors are encouraged to take these into consideration and align their strategies accordingly.
Background: Artificial intelligence (AI)-based chatbots have emerged as potential tools to assist individuals in reducing anxiety and supporting well-being.
Objective: This study aimed to identify the factors that impact individuals' intention to engage and their engagement behavior with AI-based well-being chatbots by using a novel research model to enhance service levels, thereby improving user experience and mental health intervention effectiveness.
Methods: We conducted a web-based questionnaire survey of adult users of well-being chatbots in China via social media. Our survey collected demographic data, as well as a range of measures to assess relevant theoretical factors. Finally, 256 valid responses were obtained. The newly applied model was validated through the partial least squares structural equation modeling approach.
Results: The model explained 62.8% (R2) of the variance in intention to engage and 74% (R2) of the variance in engagement behavior. Affect (β=.201; P=.002), social factors (β=.184; P=.007), and compatibility (β=.149; P=.03) were statistically significant for the intention to engage. Habit (β=.154; P=.01), trust (β=.253; P<.001), and intention to engage (β=.464; P<.001) were statistically significant for engagement behavior.
Conclusions: The new extended model provides a theoretical basis for studying users' AI-based chatbot engagement behavior. This study highlights practical points for developers of AI-based well-being chatbots. It also highlights the importance of AI-based well-being chatbots to create an emotional connection with the users.
Background: Chronic low back pain (CLBP) is a major economic and social problem worldwide. Despite the variety of recommended treatments, long-term self-management of this condition is complex and requires the development of innovative interventions. Mobile health (mHealth) technologies hold great promise for the management of chronic pain, particularly to support physical activity. However, their implementation is challenged by a lack of user compliance and limited engagement, which may be due to insufficient consideration of the needs of potential users during development.
Objective: This study aims to explore the needs of people with CLBP and health care professionals regarding mHealth technologies to support self-managed physical activity, and to delineate design recommendations based on identified needs.
Methods: A participatory study was conducted using a 3-phase, user-centered design approach: needs investigation with a group of experts in a workshop (phase 1), needs exploration with end users in focus groups (phase 2), and validation of needs using Delphi questionnaires followed by the development of a set of recommendations (phase 3).
Results: A total of 121 people with CLBP, expert patients, health care professionals, rehabilitation researchers, and biomechanical engineers participated in this study. The results indicated how technology could help people with CLBP overcome their difficulties with managing physical activity. Specific needs were formulated concerning device objectives, expected strategies, functionalities, technical features, conditions of use, and potential facilitators and barriers to use. These needs were validated by consensus from the potential end users and translated into design recommendations.
Conclusions: This study provides design recommendations for the development of an mHealth device specifically adapted for people with CLBP.
Background: Deep pressure therapy (DPT) is widely used to reduce anxiety in children with autism spectrum disorder (ASD), but evidence of its efficacy is limited.
Objective: This study aims to design a usable, nonstigmatizing compressive armchair that can be easily controlled, electronically, by the user.
Methods: A user-centered approach was used to assess the usability of the device. Testing was carried out in a day hospital for children with ASD in France, with a convenience sample of children with severe forms of ASD and intellectual deficiency (N=39). The Witteman design guideline was used. The System Usability Scale and time of use were reported.
Results: The final product is a compressive armchair designed to be user centered, with 4 different cells that can be inflated to induce tailored pressure on the body. The pressure level is recorded electronically. Usability was between good and excellent. The device was used by 39 children, once or twice weekly, over a period of 31 months. Each session lasted between 3 and 20 minutes. The armchair takes up less space than a hug machine. Performing sessions with the chair is feasible.
Conclusions: First clinical impressions show a decrease in anxiety, improved emotional regulation, and improved attention. DPT is widely used in occupational therapy and frequently requested by parents, but efficacy studies are too scarce to make evidence-based recommendations for its use. The results presented here support further controlled efficacy studies of DPT in the treatment of anxiety in children with ASD.
Background: Poor sleep is a common problem in adolescents aged 14 to 18 years. Difficulties with sleep have been found to have a bidirectional link to mental health problems.
Objective: This new research sought to involve young people in the co-creation of a new app, particularly those from underserved communities. The Sleep Solved app uses science-based advice to improve sleep-related behaviors and well-being. The app was developed using the person-based approach, underpinned by the social cognitive theory and the social-ecological model of sleep health.
Methods: Young people (aged 14-18 y) were recruited from across the United Kingdom to contribute to patient and public involvement (PPI) activities. In partnership with our peer researcher (MHJ), we used a multitude of methods to engage with PPI contributors, including web-based workshops, surveys, think-aloud interviews, focus groups, and app beta testing.
Results: A total of 85 young people provided PPI feedback: 54 (64%) young women, 27 (32%) young men, 2 (2%) genderfluid people, 1 (1%) nonbinary person, and 1 (1%) who reported "prefer not to say." Their levels of deprivation ranged from among the 40% most deprived to the 20% least deprived areas. Most had self-identified sleep problems, ranging from 2 to 3 times per week to >4 times per week. Attitudes toward the app were positive, with praise for its usability and use of science-based yet accessible information. Think-aloud interviews and a focus group identified a range of elements that may influence the use of the app, including the need to pay attention to language choices and readability. User experiences in the form of narrated audio clips were used to normalize sleep problems and provide examples of how the app had helped these users.
Conclusions: Young people were interested in using an app to better support their sleep and mental health. The app was co-created with strong links to theory- and evidence-based sleep hygiene behaviors. Future work to establish the effectiveness of the intervention, perhaps in a randomized controlled trial, would provide support for potential UK-wide rollout.
Background: Caregiver wellness programs need to be easily accessible to address caregivers' constraints to participation.
Objective: We aimed to assess the feasibility of 5Minutes4Myself app's mindfulness module (usability, usage, and impact on caregivers' levels of mindfulness and perceived stress).
Methods: Before and after participation in the 5Minutes4Myself program, 15 participants were asked to complete the Perceived Stress Scale (PSS) and Five Facet Mindfulness Questionnaire (FFMQ). Data on the usage of app-delivered meditations were collected electronically via the app, and app usability was rated on the Modified System Usability Scale. Analyses assessed participants' frequency of use of app-delivered meditations, app usability, and changes in participants' stress and mindfulness post intervention.
Results: Overall, participants completed 10.9 minutes of mindfulness meditations per week and rated the app 76.7, indicating above-average usability. Related samples t tests (2-tailed) found that group PSS (t10=1.20, P=.26) and FFMQ (t10=-1.57, P=.15) pre- or postintervention mean scores were not significantly different. However, a visualization of pre- and post-PSS and mindfulness scores suggested there was a group of responders who had decreased stress with increased mindfulness. This was confirmed via an individual change analysis. The effect size of the FFMQ scores (d=0.47) suggests there may be treatment effects with a larger sample. A hierarchical multiple regression analysis examined the degree mindfulness impacted perceived stress; 20% of the variance in participants' perceived stress could be attributed to increases in self-rated mindfulness (P=.04) when controlling for preintervention stress levels.
Conclusions: Caregivers found the app highly usable and on average used low-dose levels of mindfulness meditations (10 min/wk). For responders, increased mindfulness was related to stress reduction to population-based levels.
Background: The emergence and integration of mobile health care technology have fundamentally transformed the health care industry, providing unprecedented opportunities to improve health care services and professional practice. Despite its immense potential, the adoption of mobile health care technology among health care professionals remains uneven, particularly in resource-limited regions.
Objective: This study aims to explore the use and influencing factors of mobile health care among health care professionals in the Sichuan-Chongqing region of China and make recommendations.
Methods: Convenience sampling was used in a cross-sectional study conducted from November 8 to November 14, 2023, to survey frontline clinical health care professionals at 5 district-level secondary public hospitals in the Sichuan-Chongqing region. A web-based questionnaire was used to investigate the use of mobile health care and its influencing factors among the participants. Descriptive analysis and logistic regression analysis were used in the study.
Results: A total of 550 valid questionnaires were completed. Among the surveyed health care professionals, only 18.7% (103/550) used mobile health care, with a satisfaction rate of only 50.5% (52/103). Around 81.3% (447/550) did not use any form of mobile health care. The age group of 30-39 years was found to be a significant factor influencing the use of mobile health care by health care professionals (P=.03). The main reasons for not using mobile health care among health care professionals were lack of appropriate technical training and support (266/447, 59.5%), lack of suitable management-specific apps (204/447, 45.6%), and concerns about increased workload (180/447, 40.3%). There were significant differences in the single-factor analysis of the reasons for the nonuse of mobile health care among health care professionals from different specialties (P=.04). Logistic regression analysis indicated that age was the only significant factor influencing the use of mobile health care by health care professionals (P=.04).
Conclusions: The utilization rate of mobile health care among health care professionals in the Sichuan-Chongqing region is low. Age is a significant factor that influences whether health care professionals use mobile health care. Providing appropriate technical training and support may help improve the enthusiasm of health care professionals in using mobile health care.
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