International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923 – Vol. 13, No. 10, 2019 Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older Adults: From the Perspective of Expanded Technology Acceptance Model https://doi.org/10.3991/ijim.v13i10.11285 Murtaja Ali Saare (), Azham Hussain Universiti Utara Malaysia, Kedah, Malaysia alisaare16@aol.com Wong Seng Yue Universiti Malaya, Kuala Lumpur, Malaysia Abstract—The aim of this article is to discuss how different factors affect the decision of intention to use and adopt mobile health applications using the extended technology acceptance model (TAM) among older adults in Iraq. “Perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), and facilitating conditions (FC)” were four key predictors. Gender and age were included as factors for moderating the impact of two key TAM com- ponents in the proposed model (PU and PEU) on intention to use and adoption behaviors. The results of the past studies indicated that PU, PEU and SN were important predictors of adoption of mobile health applications among older adults in Iraq, While PU, SN, and FC were important predictors of the intention to use mobile health applications. Previous studies highlighted a strong impact of PEU on the intention to use mobile health applications on older adults than for younger adults. Implications are discussed for future research and practices. Keywords—Mobile health applications adoption, Mobile health applications use intention, Older adults, TAM, Perceived usefulness, perceived ease of use, Subjective norm, Facilitating conditions. 1 Introduction Technological development such as a smartphone has been witnessed in healthcare (Bujnowska-Fedak & Pirogowicz, 2014). According to World Health Organization, mobile health (mHealth) technology is the use of mobile device into a medical profes- sion. In terms of smartphone ownership, many studies indicate an increase in mobile health adoption as a result of increase in ownership, specifically, among younger adults rather than older adults. Literature found that 18% of older adults has adopted to smartphone (Anderson & Perrin, 2017; Smith, 2014). For example, Smartphone penetration rate is 17% in Iraq (Ameen & Willis, 2018). However, the age group adopting technology was younger adults. Pew research Project (Rainie & Fox, 2012) found that not all age groups accept and use Smartphone, for example, only 18 percent of older adults have adopted 28 http://www.i-jim.org https://doi.org/10.3991/ijim.v13i10.11285 Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… Smartphone (Anderson & Perrin, 2017; Saare, Hussain, & Yue, 2019; Smith, 2014) The possible reason that literature reveals is a significant gap in terms of user inter- face design requirements (Poushter, 2016). For example, complex structures of the menu cause older adults to experience stress because older adults need to think about what to select for a longer time to select. As cognitive refers to thinking patterns which has declined in older adults due to their age, motor skills are dexterity of their fingers and vision are lost. Moreover, the design of healthcare applications (Saare, Murtaja Ali; Jasim, Osamah Mohammed; Mahdi, Alia Ahmed; Hussain, 2018) in par- ticular is skewed towards younger adults (Grindrod et al., 2018; Kuerbis, Mulliken, Muench, Moore, & Gardner, 2017a; Petrovčič, Taipale, Rogelj, & Dolničar, 2018; Tsai, Shillair, & Cotten, 2017), however, the requirements of older adults are different from those of younger adults (Joshi & Bråthen, 2016) because they experience age related decline in cognition (Chin et al., 2017). Nevertheless, the specific require- ments of older adults did not meet their needs as they are poorly captured (Young, Koppel, & Charlton, 2016). Digital divide has become an important issue of concern in various developing countries as the health issues could be overcome through technology (Hussain, Saare, Jasim, & Mahdi, 2018) as technology has proved to be beneficial by providing eco- nomical technological solutions that reduce the economic burden of a patient's disease (Bastawrous & Armstrong, 2013). Smart phones are one of the most important mobile devices in modern life that have played an increasingly important role in health care. Many studies have shown that m-health has developed to support diseases and are convenient (Ameen & Willis, 2018). Moreover, there is a gap found in term of m- health applications adoption as older adult reached over 50 years old is found to be considerably less adopters than their younger counterparts (Boulos, Wheeler, Tavares, & Jones, 2011). The aim of this study is to identify different factors influencing the intention to use and adopt mobile health among Iraqi older adults. As the population of older adults is continuously increasing therefore, it is important to capture the needs of this growing population. The present study considers expanding technology acceptance model which is an improvement of the original technology acceptance model (TAM). The TAM has become most popular model that many researchers used to examine tech- nology adoption and it was originated from the reasoned action theory (Ajzen & Fishbein, 1975). Moreover, the factors that determine the adoption and intention of m- health by elderly people should be clearly examine and understood rather than looking at the techniques of adoption. The physical design aspects of the technology as well as the societal status need to be considered in making technology adoption decisions (see figure 1). For instance, social status of individuals and experiences could determine whether to support the technology or not. The four key predictors of TAM are: “Per- ceived usefulness”, “perceived ease of use”, “subjective norm”, and “facilitating con- ditions”. In our proposed framework, moderating factors such as gender and age have been included for perceived usefulness and perceived ease of use on use intention and adoption behaviour (see Figure 1). This study has an empirical and theoretically significant contribution to aging and technology studies. First of all, the TAM model was used to investigate the adoption iJIM ‒ Vol. 13, No. 10, 2019 29 Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… of m-health among the elderly in Iraq, which was not widely studied in the literature. Secondly, it added two factors, “subjective norm” and “facilitating conditions”, to the TAM model, so that we can understand better of how m-health adoption among older adults in Iraq is affected by subjective norm, and by certain environmental. For exam- ple, lack of access to mobile health, training of staffs and users as well as technical support from third party. Thirdly, notable variation in mobile heath adoption with the elderly as a diverse group have been noticed (Phongtankuel et al., 2018; Vesel, Hipgrave, Dowden, & Kariuki, 2015). The study contributed to this knowledge by examining whether TAM factors effect of on the adoption and intention to use m- health application can be moderated by the older adults ' age and gender. The results of the study will have an impact for those who want to promote m-health application among Iraqian older adults. Fig. 1. The influence of perceived usefulness, perceived ease of use, subjective norm, and fa- cilitating conditions on intention and adoption of m-health application and the moderat- ing role of gender and age 2 Literature Review 2.1 Technology acceptance model Some basic and Important human behaviour theories derived from Social psychol- ogy has suggested the adoption and use of new technologies by individuals, including the theory of diffusion (Rogers, 1995) as well as reasoned action (Ajzen & Fishbein, 1975) and social cognitive (Bandura, 1986) with planned behaviour (Ajzen, 1991). This study used the most widely use model among researchers Davis, (1989) suggests that technology can be used to determine behavioural intention, which is impacted by two key beliefs, “perceived usefulness and perceived ease of use”. Perceived useful- ness is defined as “the extent to which a person believes that using a particular tech- nology will enhance her/his job performance” (p. 320). It has been defined perceived 30 http://www.i-jim.org Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… ease of use as “the degree to which a person believes that using a technology will be free from effort” (p. 320). Many research has shown that PU and PEOU can signifi- cantly predict the intention and behavior of the user with new technology such as a Smartphone (Saare, Sa, Lashari, & Sari, 2018), Internet (Kuerbis, Mulliken, Muench, Moore, & Gardner, 2017b), instant messaging (Lu, Zhou, & Wang, 2009), telemedi- cine (Dwivedi, Rana, Jeyaraj, Clement, & Williams, 2017), e-mail (Gastaldi, Segato, Radaelli, Lettieri, & Corso, 2017), PDA (Arning & Ziefle, 2007), mobile banking (Abbas et al., 2018), and m-health (Kalimullah & Sushmitha, 2017). Some factors may be included. To test the assumption, the work suggested these hypotheses: • H1a. The perceived usefulness will have a positive impact on the intention of using m-health. • H1b. The perceived usefulness will have a positive impact on the adoption of m- health. • H2a. The perceived ease of use has a positive impact on the intention to use m- health. • H2b. The Perceived ease of use will have a positive effect on the adoption of m- health. 2.2 The expanded TAM model TAM parsimony is the most powerful model for predicting the acceptance of tech- nology in different situations. However, the limitation of original TAM 's parsimony cannot be exaggerating due to it difficulty in providing enough information to under- stand the behaviour of adoption. To examine the theoretical models of technology acceptance, Venkatesh, Morris, Davis, & Davis, (2003) investigated 8 theoretical models that are widely used in the acceptance of technology. The significance of the addition two additional direct determinants to the TAM “social influence and facilitat- ing conditions”. These two important constructs are potentially crucial to understand the acceptance of the user, as almost all play a crucial role in determining how new technologies are adopted by users. 2.3 Subjective norm Many definitions were provided for subjective norms but the most acceptable one included theory in term of reasoned actions (Ajzen & Fishbein, 1975) and behaviour (Ajzen, 1991). This study considered subjective norms rather to build the research model, as subjective norms are commonly referred to in the research papers. In addi- tion to that, some definitions were given to subjective norm in term of perceptions and the user behaviour (Ajzen & Fishbein, 1975, p. 302). This concept highlights the so- cial influence capacity in determining the behavior of people. Many researchers have found subjective norm have as direct and positive influence on intention and adoption behaviours. (Hsu & Lu, 2004; Karahanna, Straub, & Chervany, 1999; Tarhini, Hone, Liu, & Tarhini, 2017). Therefore, the research suggested the following hypotheses: iJIM ‒ Vol. 13, No. 10, 2019 31 Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… • H3a. Subjective norm will have a positive impact on the intention to use m-health. • H3b. Subjective norm will have a positive impact on the adoption of m-health. 2.4 Facilitating conditions Facilitating conditions refers to how a person believes that its use of the infor- mation system would support an existing technical infrastructure (Tams, Grover, & Thatcher, 2014). Thompson, Higgins, & Howell, (1991) present some factors affect- ing acceptance and use of technology. They revealed in their study the effect of facili- tating the use of computers 1994. However, lack of attempts to investigate the effect of potential factors that act as a barrier among older adults in adoption of m-health (Cook et al., 2017; Hoque, Bao, & Sorwar, 2017; Stellefson et al., 2017; Zhao, Ni, & Zhou, 2017). It was found that many older adults recently complained that they choose to adopt Smartphone if they offered relevant classes more conveniently (Choudrie, Pheeraphuttharangkoon, & Ojiako, 2017). Another prohibitive factor has been found to be financial costs (Macedo, 2017). In addition, Very few technological applications have been developed on the market for older users. (Fischer, David, Crot- ty, Dierks, & Safran, 2014). In general, the perception of older adults about advance state of technical assistance, specifically access, costs, and the availability significant- ly influences m- health usage intention and later adoption. However,the effect of these advance states in research into the use of m- health was generally overlooked. This led to the formulation of the following hypotheses: • H4a. Facilitating conditions will have a positive influence on the intention to use m-health. • H4b. Facilitating conditions will have a positive influence on adoption of m-he. 2.5 The moderating effect of gender and age Venkatesh et al., (2003) studied the effect of PEOU and PU for technology use and adoption also discussed gender and age as moderating factors. This studied lead to the development of United Theory of Acceptance and Use of Technology model (UTAUT). 2.6 Gender Gender form a major factor contributing the adoption and intention to use technol- ogy. Previous studies have found that males are more positive and less concerned about technological innovations (Suki, 2011). Cai, Fan, & Du, (2017) found that men perceived e-learning system useful and easy to use. Furthermore, studies have shown that instrumental factors such as usefulness motivate men whereas, process factors such as the PEOU for technology adoption (Liu, 2017; Teo & Milutinovic, 2015) can easily influence women. In the context of Arab countries, previous evidence has highlighted the difference in gender in the adoption of smartphones (Rhema, 2013) due to cultural differences 32 http://www.i-jim.org Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… (Yasin, Alavi, Czuchry, & Shafieyoun, 2014). Gender difference are crucial to discuss as Arab women face cultural restrictions in the adoption of mobile phones (Ameen & Willis, 2016). Moreover, found gender to be a significant moderating factor that has strong effect on the smartphone technology adoption (Venkatesh, Thong, & Xu, 2012). Therefore, we have suggested the hypotheses below: • H5a. The affect of PU on the intention to use m-health application will be stronger for male seniors than for female seniors. • H5b. The effect of perceived usefulness on adoption m-health will be stronger for male seniors than female seniors. • H6a. The effect of perceived ease of use on intention to use m-health will be stronger for female seniors than male seniors. • H6b. The effect of perceived ease of use on adoption m-health will be stronger for female seniors than male seniors. 2.7 Age It has been deduced that young people attach more importance to the extrinsic ad- vantages of technology, such as its usefulness. Ameen & Willis (2016) found that the perceived usefulness had an impact on intention to use technology among youthful generation was stronger than for elderly generation in Iraq. Consequently, the elderly can be more process-oriented, possible to examine the effort needed to adopt a new emerging technology and more carefully to exploit the risks of these intentions and their benefits. In terms of empirical evidence, studies shown that the physical interre- lation among different older people in terms of technology usage were important in achieving maximum usefulness (Arning & Ziefle, 2007; Venkatesh et al., 2003). Fur- thermore, below hypotheses were formulated: • H7a. The effect of perceived usefulness on the intention to use m- health will be stronger for younger adults than older adults. • H7b. The effect of perceived usefulness on adoption m-health will be stronger for younger adults than older adults. • H8a. The effect of perceived ease of use on the intention to use m- health will be stronger for older adults than younger adults. • H8b. The effect of perceived ease of use on adoption m-health will be stronger for older adults than younger adults. iJIM ‒ Vol. 13, No. 10, 2019 33 Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… Fig. 2. Four aspects addressed by mobile health intention and adoption factors 3 Methods Various research articles have been reviewed for this study. Some of the indexing searches engines consider for the searches were google scholar, Scopus, and web of science among others using search keywords. Similar studies and related search re- sults included in the references have also been examined. The study investigated other related journals and conferences including book chapters to obtain information. Dur- ing the early stage of the search review, the research exclude all research papers that not directly focusing on user interaction design related problems. The research also excluded all core technical design papers but included the multi disciplinary aspect of such similar papers, especially on single project. We focused on the recently published papers and found at least 69 with factor iden- tification within their references published between 2013 and above. The references guided research to obtain relevant results though some researchers criticize on differ- ent views but up to now no clearly scientific justification to that claims. Research pa- pers from different field were consulted and review. Such papers came from Geronto- logical journals, Journal of the American Geriatrics Society, Ageing International, Psychology and Aging, Ageing and Society, and Journal of Applied Gerontology among others. MIS Quarterly, the Emerging Technologies and Society International Journal were such journals considered from information technology field. Business related journals mainly on marketing and operation management were also included. For instance, the research reviewed papers from Journals from marketing research. Furthermore, the research reviewed papers from reputable journals as well as confer- ences were consulted, and information was retrieved. These papers help to obtain in- formation on human factors as well as design studies. Moreover, medical related jour- nals were not left behind as medical information and the Internet in medicine are sig- nificant in mobile health field. The research reviewed theoretical and empirical evi- dence into the adoption of technology by older adults. Based on the references con- sulted for medical journals, several studies were outlined to guide our new research. 34 http://www.i-jim.org Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… Table 1. Past studies on factors affecting technology adoption and intention to use Theme Factor References Benefits expected of technology Increased safety (Chung, Demiris, & Thompson, 2016; Peek et al., 2014) Perceived usefulness (Appelboom et al., 2014; Arnhold, Quade, & Kirch, 2014) Increased independence (van Hoof, Kort, Rutten, & Duijnstee, 2011) Reduced burden on family care- givers (Appelboom et al., 2014; Fischer et al., 2014) Social influence Influence of family and friends (Peek, Aarts, & Wouters, 2017) Influence of professional care- givers (van Hoof et al., 2011) Use by peers (Alamri et al., 2013; Wilson, Hargreaves, & Hauxwell-Baldwin, 2015) Characteristics of older adults Desire to age in place (Steggell, Hooker, Bowman, Choun, & Kim, 2010; van Hoof et al., 2011) Cultural background (Lai, Chung, Leung, Wong, & Mak, 2010; Steggell et al., 2010) Familiarity with electronic tech- nology (Courtney, Demeris, Rantz, & Skubic, 2008; Steele, Lo, Secombe, & Wong, 2009) Housing type (Courtney et al., 2008; Steele et al., 2009) 4 Discussion and Conclusion Technology is considered as an efficient way to keep older people interactive (Kuerbis et al., 2017a). However, due to absence in the assessment of the lifestyles, needs, and expectations of older adults, m-health applications are not widely used by older adults. In designing, developing, and adopting m-health applications requires careful understanding to avoid any kind of bias (Lee, 2013). Previous studies concen- trated mainly on providing the design guidelines that would help application designs to adopt changes whenever needed. However, other features that are mainly important were not considered. This study reviewed previous literature to understand the intention and adoption of mobile health application among older adults in Iraq. The results indicate that the pro- posed model can effectively and efficiently help in intention to use and adopt technol- ogy based on empirical evidences. It can also address any issues of user interaction with the technology. Furthermore, the research investigated the practical implications of the proposed model utilizing different literatures. These literatures identified 6 fac- tors which gender and age serve as their moderating effect. Each factor plays an im- portant role in mobile health adoption and therefore, the research found them worth- while to discuss. Moreover, the research adopted TAM model to examine how user intent to use the mobile health and adopt. The results showed how the perceived ease of use within mobile application (Saare, Ta’a, Lashari, & Sari, 2018) has significant effect as compared to perceive usefulness which is merely important for use of mobile health users such as elderly (Arning & Ziefle, 2007; Venkatesh et al., 2003). iJIM ‒ Vol. 13, No. 10, 2019 35 Paper—Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older… Social characteristics among individuals also contributed to the adoption of mobile health and several factors can be included to improve the decision to adopt and use any emerging technology (Saare & Hussain, 2018). The system design has been also recognised as an important factor for any ergonomics system (Barnes Hofmeister & Stibe, 2017). Although there is not sufficient discussion on how elderly adults can use mobile health, this provides the needs for further research in the area. In future, inte- grating our literature findings with other similar but related factors can basically ad- dresses adoption issues. Moreover, the proposed model can be empirically tested in different contexts that will serve as another direction which needs to be look into and addressed. In addition to that, the relationship between several factors and each factor can connect to im- prove user interaction with mobile heath application which can also be serving as in- teresting area to looked into further. Adult, especially elderly ones were complaining about their satisfaction with the technology (Young et al., 2016). Design should not only focus on design for younger adults, but also on the decrease in cognition associ- ated with the age of the older adult. Another possible topic for future studies would therefore be to look more closely at the service side of m-health applications. Most of the previous works concentrated mainly how to improve the design and incorporate some factors that would add values for younger adults. Such factors could be able to achieve the objectives of any interaction design principle. Moreover, such factors must also be useful to older adults on different types of technology been it simple or complex. This is because different categories of technology have interactivity and such the unify design which will improve not only for older adults but all users of m- health applications. 5 References [1] Abbas, S. K., Hassan, H. A., Asif, J., Ahmed, B., Hassan, F., & Haider, S. S. (2018). Inte- gration of TTF, UTAUT, and ITM for mobile Banking Adoption. 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Toward best practice in human ma- chine interface design for older drivers: a review of current design guidelines. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2016.06.010 [71] Zhao, Y., Ni, Q., & Zhou, R. (2017). What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age. International Journal of Infor- mation Management https://doi.org/10.1016/j.ijinfomgt.2017.08.006 6 Authors Murtaja Ali Saare is a Ph.D. student at School of Computing, Sintok, Universiti Utara Malaysia, Kedah, Malaysia. He holds a master’s degree in computer science. His research interests include aging and cognition, e-health, and human-computer interaction. He has published his work in reputable Scopus indexed journals. Azham Hussain is the Associate Professor of Software Engineering at School of Computing, Universiti Utara Malaysia, Kedah, Malaysia. He is the founder of Hu- man-Centered Computing Research Group, which is affiliated with the Software Technology Research Platform Center at School of Computing, Universiti Utara Ma- laysia. Azham Hussain is a member of the US-based Institute of Electrical and Elec- tronic Engineers (IEEE), and actively involved in both IEEE Communications and IEEE Computer societies. Dr Wong Seng Yue is a senior lecturer at the Centre for the Initiation of Talent & Industrial Training, Universiti Malaya, Kuala Lumpur, Malaysia. He received PhD degree in information science. He current researches include mobile augmented reali- ty in STEM, gamification and e-health with industry 4.0. Article submitted 2019-06-12. Resubmitted 2019-07-17. Final acceptance 2019-07-22. Final version published as submitted by the authors. iJIM ‒ Vol. 13, No. 10, 2019 41 https://doi.org/10.1016/j.aap.2016.06.010 https://doi.org/10.1016/j.ijinfomgt.2017.08.006