Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study

Abstract

Background Prevention of the risk factors for metabolic syndrome (MetS) in middle-aged individuals is an important public health issue. Technology-mediated interventions, such as wearable health devices, can aid in lifestyle modification, but they require habitual use to sustain healthy behavior. However, the underlying mechanisms and predictors of habitual use of wearable health devices among middle-aged individuals remain unclear. Objective We investigated the predictors of habitual use of wearable health devices among middle-aged individuals with risk factors for MetS. Methods We proposed a combined theoretical model based on the health belief model, the Unified Technology of Acceptance and Use of Technology 2, and perceived risk. We conducted a web-based survey of 300 middle-aged individuals with MetS between September 3 and 7, 2021. We validated the model using structural equation modeling. Results The model explained 86.6% of the variance in the habitual use of wearable health devices. The goodness-of-fit indices revealed that the proposed model has a desirable fit with the data. Performance expectancy was the core variable explaining the habitual use of wearable devices. The direct effect of the performance expectancy on habitual use of wearable devices was greater (β=.537, P<.001) than that of intention to continue use (β=.439, P<.001), and the total effect estimate of the performance expectancy was 0.909 (P<.001), including the indirect effect (β=.372, P=.03) on habitual use of wearable devices via intention to continue use. Furthermore, performance expectancy was influenced by health motivation (β=.497, P<.001), effort expectancy (β=.558, P<.001), and risk perception (β=.137, P=.02). Perceived vulnerability (β=.562, P<.001) and perceived severity (β=.243, P=.008) contributed to health motivation. Conclusions The results suggest the importance of the users’ performance expectations for wearable health devices for the intention of continued use for self-health management and habituation. Based on our results, developers and health care practitioners should find better ways to meet the performance expectations of middle-aged individuals with MetS risk factors. They also should generate device use easier and find a way to encourage users’ health motivation, thereby reducing users’ effort expectancy and resulting in a reasonable performance expectancy of the wearable health device, to induce users’ habitual use behaviors.

Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM

“…Consistent with previous research (19,(49)(50)(51)(52), this study demonstrated that the public's performance expectancy, social influence, hedonic motivation, and habit perception directly and positively influence women's continued intention to use women's health WeChat public accounts. This suggests that the UTAUT2 model exhibits consistency in explaining the influencing factors of user's continued intention to use health WeChat public accounts targeting different audiences and content.…”

“…If the content of the public account is exciting and enjoyable, allowing users to experience fun, they may have a higher acceptance of the health WeChat public account and be more willing to read its content in the long term ( 53 ). The hedonic motivation for acceptance and intention to use a product has also been explained in other mobile health technologies ( 50 – 52 ). This study also indicated that habit can promote the continued intention to use women’s health WeChat public accounts.…”

“…This suggests that the UTAUT2 model exhibits consistency in explaining the influencing factors of user’s continued intention to use health WeChat public accounts targeting different audiences and content. Among these, performance expectancy remains the most important predictive factor for mobile health usage behavior ( 7 ), indicating that users are more willing to continue using women’s health WeChat public accounts when they perceive them as beneficial to their health ( 50 ). Recommendations and usage by family and friends can also enhance user loyalty to health WeChat public accounts ( 19 ).…”

“…Previous research indicated that individuals with higher perceived threats are more likely to consider preventive electronic healthcare services useful compared to those in good health ( 72 ). A high level of perceived health threats leads to strong health motivation, increasing performance expectations for wearable devices ( 50 ). Additionally, higher perceived health threats are associated with stronger intentions for online platform usage ( 73 ) and a more positive attitude toward using health applications ( 74 ).…”

Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study

“…Factors, such as PE, EE, and FCs, were found to be positively influencing the adoption of similar mHealth technologies for diabetes management in previous research [33,34]. However, recent studies focusing on the influencing factors of wearable devices for diabetes and other conditions management have observed that although PE, EE, and BI were high; FCs, PPR, SI, and PI were found to be of low or negative impact on the intentions to adopt wearable devices [35][36][37][38]. Issues, such as privacy and security concerns, have significantly influenced the user's trust in wearable devices, which had an indirect impact on the adoption of wearable devices.…”