Designing for the Co-Use of Consumer Health Technology in Self-Management of Adolescent Overweight and Obesity: Mixed Methods Qualitative Study

Analysis of the mediating effect between ehealth literacy and health self-management of undergraduate nursing students' mental health literacy

BACKGROUND

Good health self-management positively affects the health of healthcare providers and their ability to manage their patients' health. This study explored the relationship between ehealth literacy, health self-management skills, and mental health literacy among undergraduate nursing students. Some studies have confirmed the correlation between e-health literacy and health self-management skills, while mental health literacy may be correlated with both, and this study aims to explore the relationship between the three.

METHODS

A descriptive cross-sectional survey was conducted at a medical university in northwestern China among 385 Chinese undergraduate nursing students. Participants completed the General Information Questionnaire, the Adult Health Self-Management Skills Rating Scale, the Mental Health Literacy Rating Scale, and the eHealth Literacy Scale, and provided valid responses. The IBM SPSS 27.0 statistical software was used for data entry and descriptive analysis, t-test, ANOVA, and Pearson correlation analysis. The IBM Amos 26.0 was used to construct the mediation effect model, and the Bootstrap method was employed to test mediating effects.

RESULTS

Mental health literacy, ehealth literacy, and health self-management skills of undergraduate nursing students were at a moderate to high level. Mental health literacy, ehealth literacy, and health self-management were positively correlated. Mental health literacy, particularly, played a partial mediating role of 31.1% ( 95% CI [0.307-1.418] ) between ehealth literacy and health self-management.

CONCLUSIONS

Undergraduate nursing students' mental health literacy partially mediates the link between eHealth literacy and health self-management skills. Schools should emphasize the development of nursing students' e-health literacy and mental health literacy in order to improve their health self-management skills, which will not only bring about a better health outcome for the students, but will also benefit the health of the social population.

Portuguese Validation of the Unified Theory of Acceptance and Use of Technology Scale (UTAUT) to a COVID-19 Mobile Application: A Pilot Study

The use of technology has proven to be a powerful tool in the fight against COVID-19 and its variants of concern (Gamma, Beta, Alpha, Delta, and Omicron). The urgency of responding to this worldwide pandemic has accelerated the development of monitoring systems and contact tracing applications. Without technology's contribution, the adverse effects on humanity economically, socially, and psychologically would be even more devastating. This study aimed to translate, adapt, and validate the Unified Theory of Acceptance and Use of Technology (UTAUT) model in a Portuguese university population, to evaluate adherence to a mobile application for tracking COVID-19. An observational cross-sectional study was developed using a sample with 1081 participants (71% female, 59.2% with ages between 16 and 24, and 78.2% of the respondent's university students). The Portuguese version model showed a good reliability (Cronbach's α = 0.82) and an acceptable overall adjustment to the sample under study (χ²/df = 3.732, CFI = 0.955, TLI = 0.944, RMSEA = 0.05, SRMR = 0.06); however, this model could be improved, as we proved. Since this is a pilot study, more studies are needed. The results indicated that the P-UTAUT can be improved for evaluating adherence to a COVID-19 mobile application.

Impact of Actual Use Behavior of Healthcare Wearable Devices on the Quality of Life: A Cross-Sectional Survey of People with Dementia and Their Caregivers in Ghana

The increasing prevalence of dementia has necessitated the introduction and use of healthcare wearable devices to augment the healthcare services delivered to people with dementia (PWDs). Unfortunately, evidence on user feedback and the real impact of the actual use of these devices on the quality of life of PWDs has not been fully explored, especially in the context of developing countries. This study, therefore, seeks to evaluate the impact of actual use behavior (AUB) of healthcare wearable devices on the quality of life (QoL) of PWDs in Ghana by using constructs from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model and the SF-36 quality of life instrument. Data were collected from people with dementia and, in some cases, caregivers (acting as proxies) in three administrative regions of Ghana using structured questionnaires. Of the 420 questionnaires distributed, 356 were returned, giving a response rate of (356/420, 84.8%). Three hundred and twenty (320) responses were used for further analysis, employing the Partial Least Squares based on Structural Equation Modeling. The results showed a significant positive relationship between AUB and QoL (p < 0.001). Other predictors such as behavioral intention, facilitating conditions, effort expectancy and social influence were also found to significantly impact the actual use behavior of healthcare wearable devices among PWDs. The study also revealed that 4% (14) of patients rated their reported health transition associated with the use of healthcare wearable devices as excellent, 42.5% (136) as very good, and 39.4% (126) as good, respectively at the time of the study compared to a year ago. This study provided empirical evidence of the positive impact of the actual use of healthcare wearable devices on the quality of life of PWDs and further highlighted the factors that drive actual use behavior among PWDs in Ghana. Based on the findings of this study, stakeholders need to create the necessary conditions that will facilitate the adoption and use of healthcare wearable devices, as this will help improve the quality of life, reduce the burden of the disease on caregivers, and enable independent living of PWDs.

Shifting From Tokenism to Meaningful Adolescent Participation in Research for Obesity Prevention: A Systematic Scoping Review

Background: Traditionally, adolescent participation in research has been tokenistic. Adolescents are rarely afforded the opportunity to influence decision-making in research designed to prevent obesity. Engaging adolescents in meaningful decision-making may enhance research translation. This review aimed to analyze the current modes and nature of adolescent participation in obesity prevention research decision-making. Methods: A systematic scoping review was conducted using Arksey and O'Malley's six-stage framework. Six major databases were searched for peer-reviewed primary research studies with adolescent participation related to obesity, physical activity, and diet. Modes of adolescent participation were categorized based on the Lansdown-UNICEF conceptual framework for measuring outcomes of adolescent participation. The framework outlines three modes of meaningful participation: (i) consultative, which involves taking opinions and needs into consideration; (ii) collaborative, where adolescents are partners in the decision-making process; and (iii) adolescent-led participation where adolescents have the capacity to influence the process and outcomes. The degree of involvement in research cycles was classified based on the National Health and Medical Research Council consumer engagement framework. Five stages of the research cycle were determined: identify, design and develop, conduct, analyze and disseminate. Results: In total, 126 papers describing 71 unique studies were identified. Of these, 69% (49/71) took place in the USA, and 85% (52/61) were conducted in minority or underserved communities, while males were more likely to be under-represented. In 49% (35/71) of studies, participation was consultative and 9% (6/71) of studies involved an adolescent-led approach. Furthermore, 87% (62/71) of studies incorporated adolescent participation in one or more of the research cycle's formative phases, which involve eliciting views, opinions and idea generation. Only 11% of studies engaged adolescents in all five stages of the research cycle where adolescents could have more influence over the research process. Conclusion: Meaningful adolescent participation in the obesity prevention research cycle is limited. Empowering and mobilizing equal partnership with adolescents should be at the forefront of all adolescent-related obesity prevention research.

How Clinicians Perceive Artificial Intelligence-Assisted Technologies in Diagnostic Decision Making: Mixed Methods Approach

Background

With the rapid development of artificial intelligence (AI) and related technologies, AI algorithms are being embedded into various health information technologies that assist clinicians in clinical decision making.

Objective

This study aimed to explore how clinicians perceive AI assistance in diagnostic decision making and suggest the paths forward for AI-human teaming for clinical decision making in health care.

Methods

This study used a mixed methods approach, utilizing hierarchical linear modeling and sentiment analysis through natural language understanding techniques.

Results

A total of 114 clinicians participated in online simulation surveys in 2020 and 2021. These clinicians studied family medicine and used AI algorithms to aid in patient diagnosis. Their overall sentiment toward AI-assisted diagnosis was positive and comparable with diagnoses made without the assistance of AI. However, AI-guided decision making was not congruent with the way clinicians typically made decisions in diagnosing illnesses. In a quantitative survey, clinicians reported perceiving current AI assistance as not likely to enhance diagnostic capability and negatively influenced their overall performance (β=–0.421, P=.02). Instead, clinicians’ diagnostic capabilities tended to be associated with well-known parameters, such as education, age, and daily habit of technology use on social media platforms.

Conclusions

This study elucidated clinicians’ current perceptions and sentiments toward AI-enabled diagnosis. Although the sentiment was positive, the current form of AI assistance may not be linked with efficient decision making, as AI algorithms are not well aligned with subjective human reasoning in clinical diagnosis. Developers and policy makers in health could gather behavioral data from clinicians in various disciplines to help align AI algorithms with the unique subjective patterns of reasoning that humans employ in clinical diagnosis.