The intention to use mHealth applications among Dutch older adults prior and during the COVID pandemic.

Background: Mobile health (mHealth) applications are widely valued for their potential to increase self-management among older adults and reduce their healthcare demands. However, the intention to use mHealth of Dutch older adults before the COVID-19 pandemic was modest. Healthcare access was considerably reduced during the pandemic and mHealth services substituted for in person health services. As older adults utilize health services more frequently and have been particularly vulnerable to the pandemic, they can be viewed to have especially benefitted from the transition toward mHealth services. Furthermore, one might expect their intention to use these services and reap the potential benefits has increased, especially during the pandemic. Objective: The aim of this study was to examine whether the intention of Dutch older adults to use medical applications increased during the COVID pandemic and how the explanatory power of the extended Technology Acceptance Model (TAM) developed for this purpose was affected by the onset of the pandemic. Methods: We conducted a cross-sectional survey using two samples collected before (n = 315) and after (n = 501) the onset of the pandemic. Data was collected using questionnaires which were distributed digitally and on paper, by convenience sampling and snowballing. Participants were 65 years or older, lived independently or in a senior living facility, without cognitive impairment. A controlled analysis was performed to test for significant differences in the intention to use mHealth. The before and after differences in extended TAM variables and their relationship with intention to use (ITU) were analyzed using controlled (multivariate) logistic and linear regression models. These models were also used to explore whether the onset of the pandemic had an effect on ITU not captured by the extended TAM model. Results: While the two samples differed in ITU (p = 0.017; uncontrolled) there was no statistically significant difference in ITU in the controlled logistic regression analysis (p = 0.107). The scores of the extended TAM variables explaining intention to use were all significantly higher, except for Subjective norm and Feelings of Anxiety. The relationships of these variables with intention to use before and after the onset of the pandemic were similar, except for Social relationships which lost its significance. We found no indications of effects of the pandemic on intention to use not captured by our instrument. Conclusion: The intention to use mHealth applications of Dutch older adults has not changed since the onset of the pandemic. The extended TAM model has robustly explained intention to use, with only minor differences after the first months of the pandemic. Interventions targeting facilitation and support are likely to promote the uptake of mHealth. Follow-up studies are needed to investigate whether the pandemic has had long term effects on the ITU of the older adult.

Gender differences regarding intention to use mHealth applications in the Dutch elderly population: a cross-sectional study.

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.