Background The increasing health service demand driven by the aging of the global population calls for the development of modes of health service delivery that are less human resource–intensive. Electronic health (eHealth) and medical apps are expected to play an important role in this development. Although evidence shows mobile medical apps might be effective in improving the care, self-management, self-efficacy, health-related behavior, and medication adherence of older adults, little is known about older adults’ intention to use these technologies when needed, or the factors influencing this intention. Objective The objective of this study was to investigate the relationship of technology acceptance factors and intention to use mobile medical apps among community-dwelling older adults. Methods Data was collected using questionnaires. The factors selected from the literature have been validated using Cronbach α and tested for significance using logistic regressions. Results Almost half (49.7%) of the included older adults reported no intention to use medical apps. Adjusted logistic regression analysis per factor showed that the factors Attitude toward use (odds ratio [OR] 8.50), Perceived usefulness (OR 5.25), Perceived ease of use (OR 4.22), Service availability (OR 3.46), Sense of control (OR 3.40), Self-perceived effectiveness (OR 2.69), Facilities (OR 2.45), Personal innovativeness (OR 2.08), Social relationships (OR 1.79), Subjective norm (OR 1.48), and Feelings of anxiety (OR 0.62) significantly influenced the intention to use mobile medical apps among older adults, whereas the factor Finance (OR 0.98) did not. When considered together, a controlled multivariate logistic regression yielded high explained variances of 0.542 (Cox-Snell R2) and 0.728 (Nagelkerke R2). Conclusions The high odds ratios and explained variance indicate that the factors associated with the intention to use medical apps are largely understood and the most important factors have been identified. To advance the evidence base, experimental controlled research should investigate the causality between the factors, intention to use, and actual use. For this purpose, our evidence suggests that policies designed to improve Attitude toward use appear most effective, followed by policies addressing Perceived usefulness, Perceived ease of use, Service availability, and Sense of control.

Background Considering the increasing demand for health services by older people and the ongoing COVID-19 pandemic, digital health is commonly viewed to offer a pathway to provide safe and affordable health services for older adults, thus enabling self-management of their health while health care systems are struggling. However, several factors cause older people to be particularly reluctant to adopt digital health technologies such as mobile health (mHealth) tools. In addition to previously studied technology acceptance factors, those related to perceived risks of mHealth use (eg, leakage of sensitive information or receiving incorrect health recommendations) may further diminish mHealth adoption by older adults. Objective The aim of this study was to explore the relationship between perceived risks of using mHealth applications and the intention to use these applications among older adults. Methods We designed a cross-sectional study wherein a questionnaire was used to collect data from participants aged 65 years and older in the Netherlands. Perceived risk was divided into four constructs: privacy risk, performance risk, legal concern, and trust. Linear regression analyses were performed to determine the associations between these perceived risk constructs and the intention to use mHealth applications. Results Linear regression per perceived risk factor showed that each of the four constructs is significantly associated with the intention to use mobile medical applications among older adults (adjusted for age, sex, education, and health status). Performance risk (β=–.266; P=<.001), legal concern (β=–.125; P=.007), and privacy risk (β=–.100; P=.03) were found to be negatively correlated to intention to use mHealth applications, whereas trust (β=.352; P=<.001) was found to be positively correlated to the intention to use mHealth applications. Conclusions Performance risk, legal concern, and privacy risk as perceived by older adults may substantially and significantly decrease their intention to use mHealth applications. Trust may significantly and positively affect this intention. Health care professionals, designers of mHealth applications, and policy makers can use these findings to diminish performance risks, and tailor campaigns and applications to address legal and privacy concerns and promote mHealth uptake and health care access for older adults, especially during the COVID-19 pandemic.

Background In light of the increasing demands in health care, a call has been made for the development of new strategies. One of these strategies is placing a higher emphasis on individuals, who are expected to better manage their own health and illness. mHealth applications could increase this self-management behaviour among older adults. However, it is crucial to know the intention to use mHealth of older adults before implementing these services. Even less is known regarding differences between genders on factors influencing this intention to use mHealth applications. Objective The aim of this study was to study the gender differences regarding the relationship between technology acceptance factors and the intention to use mHealth applications in the Dutch elderly population. Methods We conducted a quantitative cross-sectional study using questionnaires. The participants were 65 years or older, lived independently or in a senior living facility, without cognitive impairment. Logistic regression with interaction terms was done to determine gender differences in the relationship between the intention to use mHealth applications and technology acceptance factors. Results While we found that half of the studied population had intention to use medical applications (50.3%) a notable difference was observed within gender groups which showed more men had intention to use medical applications rather than women (59.4% vs. 43.4% respectively). Adjusted logistic regression analysis per factor on the male and female part of the study population respectively showed that the factors Perceived usefulness (OR 21,69 and 2,39, resp.), Perceived ease of use (OR 7,21 and 2,74), Attitude toward use (OR 24,61 and 4,94), Sense of control (OR 4,12 and 2,67), Personal innovativeness (OR 2,54 and 1,58), Self-perceived effectiveness (OR 3,21 and 2,34), Service availability (OR 4,38 and 2,51) and Facilitating circumstances (OR 3,04 and 2,18) had a statistically significant influence on intention to use in both models. Logistic regression with interaction terms showed that two of the technology acceptance factors differed statistically significant in their relationship with intention to use when comparing females to males, namely Perceived usefulness (OR 0,11) and Attitude toward use (OR 0.24). Both factors were more strongly associated with intention to use for men compared to women. Conclusion Policymakers and interventions aiming to stimulate the uptake of mHealth applications should acknowledge gender differences. Interventions based on improving the Perceived usefulness and Attitude toward use among female users could be a means to stimulate the full potential of medical applications and improve the uptake.

BACKGROUND Considering the increasing demand for health services by older people and the ongoing COVID-19 pandemic, digital health is commonly viewed to offer a pathway to provide safe and affordable health services for older adults, thus enabling self-management of their health while health care systems are struggling. However, several factors cause older people to be particularly reluctant to adopt digital health technologies such as mobile health (mHealth) tools. In addition to previously studied technology acceptance factors, those related to perceived risks of mHealth use (eg, leakage of sensitive information or receiving incorrect health recommendations) may further diminish mHealth adoption by older adults. OBJECTIVE The aim of this study was to explore the relationship between perceived risks of using mHealth applications and the intention to use these applications among older adults. METHODS We designed a cross-sectional study wherein a questionnaire was used to collect data from participants aged 65 years and older in the Netherlands. Perceived risk was divided into four constructs: privacy risk, performance risk, legal concern, and trust. Linear regression analyses were performed to determine the associations between these perceived risk constructs and the intention to use mHealth applications. RESULTS Linear regression per perceived risk factor showed that each of the four constructs is significantly associated with the intention to use mobile medical applications among older adults (adjusted for age, sex, education, and health status). Performance risk (<i>β</i>=–.266; <i>P</i>=&lt;.001), legal concern (<i>β</i>=–.125; <i>P</i>=.007), and privacy risk (<i>β</i>=–.100; <i>P</i>=.03) were found to be negatively correlated to intention to use mHealth applications, whereas trust (<i>β</i>=.352; <i>P</i>=&lt;.001) was found to be positively correlated to the intention to use mHealth applications. CONCLUSIONS Performance risk, legal concern, and privacy risk as perceived by older adults may substantially and significantly decrease their intention to use mHealth applications. Trust may significantly and positively affect this intention. Health care professionals, designers of mHealth applications, and policy makers can use these findings to diminish performance risks, and tailor campaigns and applications to address legal and privacy concerns and promote mHealth uptake and health care access for older adults, especially during the COVID-19 pandemic.

BACKGROUND The increasing health service demand driven by the aging of the global population calls for the development of modes of health service delivery that are less human resource–intensive. Electronic health (eHealth) and medical apps are expected to play an important role in this development. Although evidence shows mobile medical apps might be effective in improving the care, self-management, self-efficacy, health-related behavior, and medication adherence of older adults, little is known about older adults’ intention to use these technologies when needed, or the factors influencing this intention. OBJECTIVE The objective of this study was to investigate the relationship of technology acceptance factors and intention to use mobile medical apps among community-dwelling older adults. METHODS Data was collected using questionnaires. The factors selected from the literature have been validated using Cronbach α and tested for significance using logistic regressions. RESULTS Almost half (49.7%) of the included older adults reported no intention to use medical apps. Adjusted logistic regression analysis per factor showed that the factors Attitude toward use (odds ratio [OR] 8.50), Perceived usefulness (OR 5.25), Perceived ease of use (OR 4.22), Service availability (OR 3.46), Sense of control (OR 3.40), Self-perceived effectiveness (OR 2.69), Facilities (OR 2.45), Personal innovativeness (OR 2.08), Social relationships (OR 1.79), Subjective norm (OR 1.48), and Feelings of anxiety (OR 0.62) significantly influenced the intention to use mobile medical apps among older adults, whereas the factor Finance (OR 0.98) did not. When considered together, a controlled multivariate logistic regression yielded high explained variances of 0.542 (Cox-Snell R²) and 0.728 (Nagelkerke R²). CONCLUSIONS The high odds ratios and explained variance indicate that the factors associated with the intention to use medical apps are largely understood and the most important factors have been identified. To advance the evidence base, experimental controlled research should investigate the causality between the factors, intention to use, and actual use. For this purpose, our evidence suggests that policies designed to improve Attitude toward use appear most effective, followed by policies addressing Perceived usefulness, Perceived ease of use, Service availability, and Sense of control.