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      Determinants of the intention to use e-Health by community dwelling older people

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          Abstract

          Background

          In the future, an increasing number of elderly people will be asked to accept care delivered through the Internet. For example, health-care professionals can provide treatment or support via telecare. But do elderly people intend to use such so-called e-Health applications? The objective of this study is to gain insight into the intention of older people, i.e. the elderly of the future, to use e-Health applications. Using elements of the Unified Theory of Acceptance and Use of Technology (UTAUT), we hypothesized that their intention is related to the belief that e-Health will help (performance expectancy), the perceived ease of use (effort expectancy), the beliefs of important others (social influence), and the self-efficacy concerning Internet usage.

          Methods

          A pre-structured questionnaire was completed by 1014 people aged between 57 and 77 (response 67%). The hypothesized relationships were tested using nested linear regression analyses.

          Results

          If offered an e-Health application in the future, 63.1% of the respondents would definitely or probably use it. In general, people with a lower level of education had less intention of using e-Health. The majority of respondents perceived e-Health as easy to use (60.8%) and easy to learn (68.4%), items that constitute the scale for effort expectancy. Items in the performance expectancy scale generally scored lower: 45.8% perceived e-Health as useful and 38.2% perceived it as a pleasant way to interact. The tested model showed that expected performance and effort were highly related to intention to use e-Health. In addition, self-efficacy was related to intention to use while social influence was not.

          Conclusions

          Acceptance of e-Health can be increased by informing people about the potential benefits of e-Health and letting them practice with the application. Special attention should be paid to people with less education and people who have not used the Internet before.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12913-015-0765-8) contains supplementary material, which is available to authorized users.

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          Most cited references28

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          Factors influencing acceptance of technology for aging in place: a systematic review.

          To provide an overview of factors influencing the acceptance of electronic technologies that support aging in place by community-dwelling older adults. Since technology acceptance factors fluctuate over time, a distinction was made between factors in the pre-implementation stage and factors in the post-implementation stage.
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            Understanding Determinants of Consumer Mobile Health Usage Intentions, Assimilation, and Channel Preferences

            Background Consumer use of mobile devices as health service delivery aids (mHealth) is growing, especially as smartphones become ubiquitous. However, questions remain as to how consumer traits, health perceptions, situational characteristics, and demographics may affect consumer mHealth usage intentions, assimilation, and channel preferences. Objective We examine how consumers’ personal innovativeness toward mobile services (PIMS), perceived health conditions, health care availability, health care utilization, demographics, and socioeconomic status affect their (1) mHealth usage intentions and extent of mHealth assimilation, and (2) preference for mHealth as a complement or substitute for in-person doctor visits. Methods Leveraging constructs from research in technology acceptance, technology assimilation, consumer behavior, and health informatics, we developed a cross-sectional online survey to study determinants of consumers’ mHealth usage intentions, assimilation, and channel preferences. Data were collected from 1132 nationally representative US consumers and analyzed by using moderated multivariate regressions and ANOVA. Results The results indicate that (1) 430 of 1132 consumers in our sample (37.99%) have started using mHealth, (2) a larger quantity of consumers are favorable to using mHealth as a complement to in-person doctor visits (758/1132, 66.96%) than as a substitute (532/1132, 47.00%), and (3) consumers’ PIMS and perceived health conditions have significant positive direct influences on mHealth usage intentions, assimilation, and channel preferences, and significant positive interactive influences on assimilation and channel preferences. The independent variables within the moderated regressions collectively explained 59.70% variance in mHealth usage intentions, 60.41% in mHealth assimilation, 34.29% in preference for complementary use of mHealth, and 45.30% in preference for substitutive use of mHealth. In a follow-up ANOVA examination, we found that those who were more favorable toward using mHealth as a substitute for in-person doctor visits than as a complement indicated stronger intentions to use mHealth (F 1,702=20.14, P<.001) and stronger assimilation of mHealth (F 1,702=41.866, P<.001). Conclusions Multiple predictors are shown to have significant associations with mHealth usage intentions, assimilation, and channel preferences. We suggest that future initiatives to promote mHealth should shift targeting of consumers from coarse demographics to nuanced considerations of individual dispositions toward mobile service innovations, complementary or substitutive channel use preferences, perceived health conditions, health services availability and utilization, demographics, and socioeconomic characteristics.
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              If We Offer it, Will They Accept? Factors Affecting Patient Use Intentions of Personal Health Records and Secure Messaging

              Background Personal health records (PHRs) are an important tool for empowering patients and stimulating health action. To date, the volitional adoption of publicly available PHRs by consumers has been low. This may be partly due to patient concerns about issues such as data security, accuracy of the clinical information stored in the PHR, and challenges with keeping the information updated. One potential solution to mitigate concerns about security, accuracy, and updating of information that may accelerate technology adoption is the provision of PHRs by employers where the PHR is pre-populated with patients’ health data. Increasingly, employers and payers are offering this technology to employees as a mechanism for greater patient engagement in health and well-being. Objective Little is known about the antecedents of PHR acceptance in the context of an employer sponsored PHR system. Using social cognitive theory as a lens, we theorized and empirically tested how individual factors (patient activation and provider satisfaction) and two environment factors (technology and organization) influence patient intentions to use a PHR among early adopters of the technology. In technology factors, we studied tool empowerment potential and value of tool functionality. In organization factors, we focused on communication tactics deployed by the organization during PHR rollout. Methods We conducted cross-sectional analysis of field data collected during the first 3 months post go-live of the deployment of a PHR with secure messaging implemented by the Air Force Medical Service at Elmendorf Air Force Base in Alaska in December 2010. A questionnaire with validated measures was designed and completed by 283 participants. The research model was estimated using moderated multiple regression. Results Provider satisfaction, interactions between environmental factors (communication tactics and value of the tool functionality), and interactions between patient activation and tool empowerment potential were significantly (P<.05) associated with behavioral intentions to use the PHR tool. The independent variables collectively explained 42% of the variance in behavioral intentions. Conclusions The study demonstrated that individual and environmental factors influence intentions to use the PHR. Patients who were more satisfied with their provider had higher use intentions. For patients who perceived the health care process management support features of the tool to be of significant value, communication tactics served to increase their use intentions. Finally, patients who believed the tool to be empowering demonstrated higher intentions to use, which were further enhanced for highly activated patients. The findings highlight the importance of communication tactics and technology characteristics and have implications for the management of PHR implementations.
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                Author and article information

                Contributors
                a.deveer@nivel.nl
                j.peeters@nivel.nl
                a.brabers@nivel.nl
                f.schellevis@nivel.nl
                j.rademakers@nivel.nl
                a.francke@nivel.nl
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                15 March 2015
                15 March 2015
                2015
                : 15
                : 103
                Affiliations
                [ ]NIVEL, Netherlands Institute for Health Services Research, PO box 1568, 3500 BN Utrecht, The Netherlands
                [ ]Department of General Practice and Elderly Care Medicine/EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
                [ ]Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands
                [ ]Expertise Center for Palliative Care Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
                Article
                765
                10.1186/s12913-015-0765-8
                4364096
                25889884
                37c5a41e-7839-42d3-bf4b-32634025641e
                © de Veer et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 September 2014
                : 27 February 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Health & Social care
                technology acceptance,e-health,utaut,community,older people
                Health & Social care
                technology acceptance, e-health, utaut, community, older people

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