Assessment of the Intention to Use Mobile Health Applications Using a Technology Acceptance Model in an Israeli Adult Population

Shemesh, Tomer; Barnoy, Sivia

doi:10.1089/tmj.2019.0144

Cited by 38 publications

(24 citation statements)

References 28 publications

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“…Previous studies conducted in Israel showed that patients and physicians are willing to use digital technology instead of faceto-face appointments when their preferences are considered (29). Another study found that the high use of HMOs' mobile health apps across the socio-demographic spectrum indicates telemedicine's high perceived usefulness (30). The lockdown prompted many clinicians and patients to realize these tools' potential and compelled them-some for the first time-to utilize them when face-to-face appointments were precluded (31).…”

Section: Discussionmentioning

confidence: 99%

Using Telemedicine During the COVID-19 Pandemic: Attitudes of Adult Health Care Consumers in Israel

Reicher

Sela²,

Toren

2021

Front. Public Health

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Introduction: The COVID-19 pandemic has affected health care services worldwide due to lockdowns, prevention measures, and social distancing. During this period, patients, including older adults and those with chronic conditions, need ways to obtain medical attention other than going physically to the clinic, such as telemedicine services. The purpose of the present study was to evaluate attitudes toward telemedicine during the COVID-19 lockdown in Israel, assess willingness to use such services in the future, and evaluate the extent to which consumers have changed their minds regarding these services.Method: A cross-sectional, descriptive, correlational study was conducted among adults (age 20–90) using social media networks (N = 693). Data were collected using an online questionnaire explicitly designed to measure attitudes toward telemedicine.Results: Most of the participants had to use telemedicine during the lockdown and were satisfied therewith. The majority also stated that they would continue using telemedicine in the future. However, only a third stated that they had changed their minds regarding telemedicine. The main predictors of willingness to use telemedicine in the future were the necessity of using such services during lockdown, preference for going to a clinic, and satisfaction with telemedicine, alongside gender and having a chronic illness. Importantly, we found that a preference for visiting the clinic was negatively correlated with willingness to use telemedicine in the future. Education and being single were predictors of the change of mind regarding telemedicine. Participants with chronic conditions are more likely to use these services, and specific attention should be directed to their needs. A small portion of the study sample prefers live appointments with a physician.Conclusions: Telemedicine use is rapidly changing. It is vital for health care providers to identify non-telemedicine users and their common characteristics. Monitoring patients' attitudes regarding telemedicine is essential in the future after the pandemic ends. Targeted outreach plans should be formulated. These plans should be directed at identifying barriers to using telemedicine, and they should generate specific, focused plans.

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Section: Discussionmentioning

confidence: 99%

Using Telemedicine During the COVID-19 Pandemic: Attitudes of Adult Health Care Consumers in Israel

Reicher

Sela²,

Toren

2021

Front. Public Health

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“…For example, tech rejectors and unsure acceptors did not perceive the use of symptom checkers to be easy which was evident by their lower odds of using symptom checkers in the future. While age was not explored in our study due to the young age of our sample, another study found that younger populations displayed more confidence with the use of mHealth apps and were less concerned about compromising the confidentiality of their health records [ 26 ]. Answers to TAM-related questions among mHealth apps users were significantly more positive compared with non-users [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

“…While age was not explored in our study due to the young age of our sample, another study found that younger populations displayed more confidence with the use of mHealth apps and were less concerned about compromising the confidentiality of their health records [ 26 ]. Answers to TAM-related questions among mHealth apps users were significantly more positive compared with non-users [ 26 ]. Interestingly, as found in our study, the endorsement of health apps by health organizations can play an influential role in technology acceptance and utilization as well as support efforts in shaping regulation [ 26 , 27 ].…”

Section: Discussionmentioning

confidence: 99%

“…Answers to TAM-related questions among mHealth apps users were significantly more positive compared with non-users [ 26 ]. Interestingly, as found in our study, the endorsement of health apps by health organizations can play an influential role in technology acceptance and utilization as well as support efforts in shaping regulation [ 26 , 27 ].…”

Section: Discussionmentioning

confidence: 99%

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Latent classes associated with the intention to use a symptom checker for self-triage

et al. 2021

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It is currently unknown which attitude-based profiles are associated with symptom checker use for self-triage. We sought to identify, among university students, attitude-based latent classes (population profiles) and the association between latent classes with the future use of symptom checkers for self-triage. Informed by the Technology Acceptance Model and a larger mixed methods study, a cross-sectional survey was developed and administered to students (aged between 18 and 34 years of age) at a University in Ontario. Latent class analysis (LCA) was used to identify attitude-based profiles that exist among the sample while general linear modeling was applied to identify the association between latent classes and future symptom checker use for self-triage. Of the 1,547 students who opened the survey link, 1,365 did not use a symptom checker in the past year and were thus identified as “non-users”. After removing missing data (remaining sample = n = 1,305), LCA revealed five attitude-based profiles: tech acceptors, tech rejectors, skeptics, tech seekers, and unsure acceptors. Tech acceptors and tech rejectors were the most and least prevalent classes, respectively. As compared to tech rejectors, tech seekers and unsure acceptors were the latent classes with the highest and lowest odds of future symptom checker use, respectively. After controlling for confounders, the effect of latent classes on symptom checker use remains significant (p-value < .0001) with the odds of future use in tech acceptors being 5.6 times higher than the odds of future symptom checker use in tech rejectors [CI: (3.458, 9.078); p-value < .0001]. Attitudes towards AI and symptom checker functionality result in different population profiles that have different odds of using symptom checkers for self-triage. Identifying a person’s or group’s membership to a population profile could help in developing and delivering tailored interventions aimed at maximizing use of validated symptom checkers.

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“…Analyses of eHealth technology acceptance models have been conducted in the context of various medical technologies, such as telemedicine in ambulatory care settings (Dünnebeil et al, 2012), personal health data management systems (Koivumäki et al, 2017), patient portals (Lazard et al, 2016), and mobile health applications (Shemesh & Barnoy, 2020). In general, acceptance and use models such as the TAM have proven successful at explaining many of the technology-use related factors influencing the adoption of eHealth technologies (Mohamed et al, 2011;Uribe-Toril et al, 2021).…”

Section: Technology Acceptance and Use Modelsmentioning

confidence: 99%

Combined Model of Technology Use and Medical Adherence in eHealth Technology Implementation

Devkota

Montalvo

McConnell

et al. 2021

Proceedings of the Human Factors and Ergonomics Society Annual

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eHealth applications are expected to improve the effectiveness and efficiency of healthcare systems by providing improved medical information flow between medical providers and patients. Although the technology is expected to empower patients, lower treatment costs, and provide real-time collection of health data, individuals may be apprehensive about the use and efficacy of eHealth technologies. Medical professionals are often unaware of human factors technology acceptance or usability models which impact the use of medically focused technology, such as eHealth applications. Similarly, human factors professionals are often unaware of treatment adherence models which map the relationship of illness factors and individual differences to treatment protocols. The present paper presents a theoretical approach through which technology acceptance and usability models should be combined with medical treatment adherence models to ensure that eHealth applications are used properly and effectively.

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Assessment of the Intention to Use Mobile Health Applications Using a Technology Acceptance Model in an Israeli Adult Population

Cited by 38 publications

References 28 publications

Using Telemedicine During the COVID-19 Pandemic: Attitudes of Adult Health Care Consumers in Israel

Using Telemedicine During the COVID-19 Pandemic: Attitudes of Adult Health Care Consumers in Israel

Latent classes associated with the intention to use a symptom checker for self-triage

Combined Model of Technology Use and Medical Adherence in eHealth Technology Implementation

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