This study was performed to investigate possible gender differences in the relationship of technology acceptance factors and the intention to use medical applications among older adults. To do so, technology acceptance factors were explored that have potential for policy makers and care givers to act on in the pursuit of a greater uptake of mHealth among older adults. 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 the intention to use medical applications rather than women (59.4% vs. 43.4% respectively). In addition, men had more prior experience with internet (92.3% vs. 79.9% respectively men vs. women), which could possibly be related to a higher intention to use. This first finding is supported by previous research , and could be explained by the social role of men, being more adventurous and more open to try new things when it comes to technology .
We used a wide variety of sources to collect our data (a hospital, general practitioners offices, elderly leisure activity clubs) in various regions across the Netherlands, using both online and paper questionnaires. These efforts were all aimed at creating a representative sample contributing to generalizability of the findings. In addition, our population had comparable quality of life and ADL scores as the general population in the Netherlands [55, 56]. However, the intention to use medical applications might be different in an elderly population where (multiple) chronic diseases are more prevalent [57, 58]. Therefore, future study needs to distinguish this particular group also because on average they are likely to be older and may need other policies to increase mHealth uptake.
Our results showed there was a significant difference between male and female groups regarding two factors: Perceived usefulness and Attitude toward use. Perceived usefulness was more strongly linked to intention to use for men than for women. A possible explanation for this is that men are primarily focused on practical purposes and the accomplishment of goals, and therefore more concerned with the usefulness of new technologies [29, 36, 59]. Having positive attitudes toward the use of technology was also a more strong predictor for the intention to use medical applications for elderly men compared to women. This finding is supported by earlier research which showed that females in general have a lower Attitude toward technology than males [30, 60]. Cai et al. (2017) state that the scarce participation of women in technology, based on the general view that technology is a male dominated area, could be one of the explaining factors for their lower attitude because these social prejudgments could form a barrier for women to gather interest about technology. There are studies showing that women are more concerned with their health, more active in seeking health-related information and seek help of healthcare professionals more early compared to men [61,62,63]. As our results showed that females are less likely to adopt technology for the good of their own health, this points to contradictory results regarding mHealth as compared to these other health behaviors suggesting other policies are needed for mHealth implementation among women to increase the uptake and strengthen long-lasting adoption. In addition, we found that the factors Attitude toward use, Sense of control, Personal innovativeness, Self-perceived effectiveness, Service availability and Facilitating circumstances were relevant for both the female and male groups. These findings are relevant when placing them in the context of facilitating the uptake of medical applications among older adults. Medical applications can contribute in the delivery of long-term care for chronic diseases [64, 65]. This is relevant for older adults, because of the high prevalence of these diseases in that population .
An argument could be made that older adults who live alone (e.g. without a partner) could benefit even more from this technology, as their need for self-management is even greater. Elderly women live alone more often than their male counterparts , hence the need for mHealth solutions might be greater for women. Additionally, our findings suggest that females are lagging behind in the use of medical applications when compared to males. This suggests that to increase the uptake of mHealth among older adults, females might be the group to consider first as the greatest potential for an increase in uptake lies within this group. In accordance, our findings suggest that the uptake of mHealth applications could be stimulated by putting an emphasis on the needs of women while creating policy and interventions.
Comparison with prior work
To the best of our knowledge, this is the first study investigating the differences in gender regarding influencing acceptance factors among older adults and therefore comparison which earlier studies might be difficult. However, in the study done by Faqih et al. in 2015, the influence of gender on the relationship between TAM factors and behavioral intention regarding mobile health was investigated not specifically among older adults . In this research they studied several hypotheses of which two are of interest: 1) ‘Perceived usefulness’ influences behavioral intention to adopt mHealth more strongly for men than women; and 2) ‘Perceived ease of use’ influences behavioral intention to adopt mHealth more strongly for women than men. Their results showed that hypothesis one was not supported, however hypothesis two was supported.
Their results are not in line with our results for older men and women. Our analyses showed that the ‘Perceived usefulness’ influenced the intention to use medical applications more strongly for older men compared to older women. In addition, we found that Perceived ease of use did not have a stronger effect on the intention to use for older women compared to older men. Still, other studies in non-healthcare domains have reported findings in harmony with our study results [36, 67, 68].
Although the population size of Faqih and Riad Mousa Jaradat (2015) is almost identical to ours, there are some significant differences to be found, possibly explaining the difference in results. First, their population does not consist of older adults. Only 4.6% of their respondents was over 50 years of age. Since age had a moderating effect on the relationships between TAM-factors and intention to use, it is not possible to draw fully accurate comparisons between our study and the study of Faqih and Riad Mousa Jaradat, (2015). Second, a large part of the population of Faqih and Riad Mousa Jaradat (2015) consists of participants with a fairly high educational level (65% of the participants have either a bachelor’s degree or a bachelor’s and a master’s degree). It can be argued that due to the relatively young and highly educated population the overall tech-savviness is expected to be higher. This in turn can greatly influence both the behavioral intention, in our case intention to use, as well as what is perceived as useful.
For example, their second hypothesis can be explained through social role division. Women tend to be more concerned with ease of use, rather than the accomplishment of tasks when using a new technology [36, 69]. Other empirical results support that women are highly motivated by Perceived ease of use, although none of these studies looked specifically at the elderly population [67, 68]. A possible explanation for this difference is that this social role division is less prominent in the older generations. Among the elderly, both genders are evenly unexperienced with regard to new technology because they were not raised with such technology. Therefore, both genders face the same difficulties in ease of use of a new technology.
Our study also has some limitations. In the current study we only used “male” and “female” as answering options. Even though we did not have missing values, future research should include a category for “others” given that the gender discussion is much broader than male versus female.
Another limitation was, that the questionnaire used to collect the data was rather elaborate. Although steps were taken to minimize the impact of the length of the questionnaire, such as printing out the questionnaire so participants could take breaks or sitting with the respondents while they filled out the questionnaire, some participants still showed signs of response-fatigue. Respondent fatigue is a well-documented phenomenon that occurs when survey participants become tired of the survey task and the quality of the data they provide begins to deteriorate. It occurs when survey participants' attention and motivation drop toward later sections of a questionnaire .
We noticed that some of the participants, especially the group with an age above 75, struggled with grasping what medical applications fundamentally are, how they work, how they could be used, etc. Although, this might result in situations where participants’ answers might not fully reflect their actual opinion, we tried to provide additional explanation about medical applications both within the questionnaire, verbally or by means of demonstration when this was necessary in addition to the written explanation and pictures in the questionnaire.
Our study had a cross-sectional design. Therefore, no claims of causality can be made  and the results might suffer from self-report bias . Longitudinal studies are needed to investigate the causal relationship between gender and acceptance factors. Further investigation could study the mechanisms underlying the acceptance factors influencing the intention to use. In addition, some differences between this study and the current available literature were found. Although the differences could be attributed to the differences between the population under study, future research should validate the proposed study results in other elderly populations.
Lastly, this study is based on TAM and several adapted versions of this model. A critical point can be made that the frequent adaption has weakened the model and distanced it from the theory it was originally based on . Although TAM in its original form can have a high explained variance in technology adoption, researchers call for more context specificity, especially in the healthcare context . TAM must also be adapted to study relatively new technology like mobile applications . Therefore, extensive literature research and careful selection of additional factors was done to facilitate an as-complete-as-possible analysis of a set of related factors of technology adoption among the elderly. As described in an earlier paper (Askari et al., 2020), high odds ratios and explained variance indicate that the most important factors associated with the intention to use medical apps have been identified supporting content validity of the measurement instrument.
Implication and recommendations
This study provided specific areas of focus for policy makers and care/software providers to take into account when facing problems on the uptake of medical applications. This study can recommend that policy based on technology acceptance factors should acknowledge the gender difference. Since elderly females are the group that is suggested to be the most difficult to reach, and at the same time the group that could benefit from mHealth interventions the most, the adoption factors that best define the difference in intention to use should be taken into account when creating interventions. Perceived ease of use, Sense of control, Personal innovativeness, Self-perceived effectiveness, Service availability and Facilitating circumstances are a good means to stimulate mHealth uptake among the general elderly population. Interventions based on Perceived usefulness and Attitude towards use are more appropriate when targeting elderly males. Therefore, if the aim of policy is to stimulate mHealth use among females, other factors should be considered first.
The gender gap in technology use is already closing due to educational and social developments . Policymakers could make use of this existing movement. This requires traditional ways of thinking about social role division with regard to technology use to be disregarded. An example of this could be interventions that pose to increase awareness of the benefits and the added value of medical applications. In addition, interventions that improve trust in mHealth could help to increase the appreciation of the usefulness of medical applications among women . These interventions might entail promoting the usefulness and necessity of medical applications as well as training the elderly females on functionalities of the application. Education has been proven to be an effective way to stimulate positive attitudes toward technology use among women . Training and providing information could be specifically targeted at women by including it as a standard part of a treatment for chronic conditions that affect relatively more women than men.