Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Prioritizing and Overcoming Barriers to e-Health Use among Elderly People: Implementation of the Analytical Hierarchical Process (AHP)

Prioritizing and Overcoming Barriers to e-Health Use among Elderly People: Implementation of the... Hindawi Journal of Healthcare Engineering Volume 2022, Article ID 7852806, 11 pages https://doi.org/10.1155/2022/7852806 Research Article Prioritizing and Overcoming Barriers to e-Health Use among Elderly People: Implementation of the Analytical Hierarchical Process (AHP) 1,2 Ayesha Mumtaz School of Public Administration, Hangzhou Normal University, Hangzhou, China College of Public Administration, Zhejiang University, Hangzhou, China Correspondence should be addressed to Ayesha Mumtaz; ayeshamumtaz04@gmail.com Received 13 November 2021; Accepted 11 March 2022; Published 11 April 2022 Academic Editor: Ilker Ozsahin Copyright © 2022 Ayesha Mumtaz. (is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Rise in the aging population brings new challenges to modern societies. Old age is associated with several morbidities and usual issues related to health. (erefore, the provision of healthy and timely care has become the dire need to maintain their quality of life and wellbeing. (e evolution of the e-health care system put pressure on societies to implement it successfully to ensure a safe and prompt provision of care services to the most vulnerable population successfully. (erefore, the provision and imple- mentation of the e-health care system is a challenge for the health industry in terms of multi-objective decision-making. Multicriteria decision-making is a generalizable approach to making decisions with dependence and feedback and is known as an effective tool in decision-making processes, particularly in the healthcare sector. (e present study aims to present an e-healthcare framework by identifying and prioritizing potential barriers towards the use of e-health by the elderly population. (e analytical hierarchy process approach is adopted to calculate weights of identified potential barriers, respectively, and then rank them based on their degree of significance. (e findings show that health and the ability-related barrier is ranked highest, followed by socio- environmental and attitudinal barriers. (is research contributes to healthcare decision-making regarding e-health usage by implementing MCDA techniques. Our study will assist the public health practitioners and policymakers in drawing decisions on the best strategy to minimize the risks in using the e-healthcare system by the aging population, which significantly contributes to the smart healthcare system. [1]. Under these circumstances, the issues of elderly care 1.Introduction attract wide attention from scholars and policymakers, (e world enters a new stage of development under the resulting in a large amount of research done in this field. pressure of an aging population. Globally, the elderly (e use of e-health care systems by elderly people has population aged 65 exceeded 703 million [1]. (e number of already become a common trend worldwide [2]. To ensure older persons is projected to double to 1.5 billion in 2050. the promotion of a healthy society, the need for modern care Nevertheless, the awareness about the aging challenge is services has become a dire need of age, which is evidenced by sharp. While this sudden trend in the aging population the extensive e-healthcare requirements adopted during the towards old age is already prominent in high-income recent Covid-19 pandemic [3]. To improve the healthcare countries, for instance, in Japan, where 30% of the total system for elderly people, most of the developing countries population is already over 60years old. (us, the trends in are also growing their smart care industries and modern- the aging population in developing and, middle- or low- izing their health care settings [4]. (e elderly health care income countries are also in transition. It is being estimated industry is shifting from traditional family care to the smart that two-thirds of the population in the world aged 60 or care system to facilitate the elderly and their caregivers. over will live in low- and middle-income countries in 2050 Efficient use of technology is especially imperative in 2 Journal of Healthcare Engineering To help readers understand the context, the following creating a more independent and supportive living envi- ronment for older people [5], stimulate their physical and section identifies the various barriers identified by previous research studies as well as models for using e-healthcare psychosocial wellbeing, and enables them to feel more in- dependent at their daily chores [6], interact with their technology. (e previous researches have highlighted some families and friends [7], and to contribute to the elderly basic factors which provided a foundation to identify the healthcare sector. (e usage and adoption of e-health critical factors pertinent to e-health use. However, there is a technology have become an established research area tar- lack of research in concepts relevant to this study which are geting at investigating the influencing factors affecting the all aligned to provide a methodological base to this study. usage of e-health [8–10]. Research in this area mainly fo- (e primary research question addressed in this study is “what are the potential barriers affecting the use of the cused on developed countries [8, 11], while the experiences of developing countries are rarely discussed, particularly e-healthcare system by elderly people, and how can these barriers be prioritized pertinent to the old age group”? Based addressing the e-health care industry. Based on this, including the importance of e-healthcare on the review of the previous studies, 13 age-specific barriers were identified and categorized into main three categories. in the present era, the adhesion of elderly people to e-health acceptance, and the recognition that elderly people in (e literature review method is used in this study to identify Pakistan are less optimistic about using technology, we were the barriers of e-healthcare use. Next, Analytical hierarchal motivated to investigate this research gap. By keeping in process (AHP) decision-making analysis is used to allocate viewthe vulnerable situation of the e-health careindustry for weights to the main and sub-barriers by using the pairwise the elderly, and the lack of research in this area, the re- matrix technique [13]. (e study includes the MCDM searchers aimed to provide a foundation by conducting a methodology, findings, discussion, and conclusion in sub- sequent sections. pioneer research study. (e use of e-health among the el- derly is not a very common trend in Pakistan, and there is a lack of research in gerontechnology. However, the majority 2. Literature Review of the cities in Pakistan have telecommunication links and 531,787 broadband connections are provided to more than Previous research studies mainly based on the intention or 1800 cities and 400 cities have the facility of fiber optics in motivation to use technology [5, 14, 15],whereas, the research Pakistan, which gives them access to universal healthcare is scarce addressed the question of why older adults fail to use information to elderly and their families. (ere are orga- technology and what are the potential barriers? In this study, nizational barriers, lack of the interest of stakeholders, less e-health system is defined as the digital or electronic motivation from friends and family,anxiety to use and adopt healthcare products and services which increase the social technology and also healthcare professionals do not play independenceandparticipationofelderlypeoplerelativelyfor their role to promote the use of technology in Pakistan [12]. health purposes [16]. (e few researches that already have Given the scarcity of research on the technology usage sought to investigate the reasons for using or not using behavior of elderly people in Pakistan, we were motivated to technology have yielded somewhat contradictory results [17]. identify the barriers that influence the e-health usage be- Although researchers revealed that older people have a havior of elderly people. positive attitude towards technology [5, 18], hence they are Initially, a review of previous literature on the use of less likely to use those technologies due to some barriers as technology among the elderly has been conducted for this compared to young adults [19–21]. (ere are several reasons purpose. Further, a set of specific factors in different revealed by different studies for the use or nonuse of tech- domains were identified based on the previous research nology by elderly people. A study revealed that elderly people findings. By answering the research question and ob- have negative attitudes towards using technology due to the jective, the subsequent contributions are proposed. (e health risks, addiction to technological products, the gener- main contribution of this research to academia is the ation gap, safety issues, and social isolation [22]. Moreover, identification of the barriers to e-health care usage and social interaction is mentioned as one of the main reasons or detailed review of existing technology acceptance liter- motivation for using technology for elderly people as they ature. Research on gerontechnology is scarce and our think that interacting with other people is crucial for their study intends to provide a detailed examination of the wellbeing [23]. It has been discovered that social interactions barriers to the usage of e-healthcare. Furthermore, for the extend the social circles and help the elderly to meet new business sector, our research identifies factors to consider friends and make them easy to interact with the younger when promoting e-healthcare products and services. (e generation. Researchers mentioned that older people use elderly smart care industry is developing very fast in the technology to reduce their effort, to enhance their work, to whole world. (us, such research is critical for the elderly cope with their needs and problems, and to compensate for smart care industry, which is considering developing their physical weakness [5]. Mahmood et al. [23] conducted a smart technology products for its elderly consumer pilot study to explore the attitudes, preferences, and opinions market segment. Moreover, the methodological contri- of elderly people regarding the use of technology to extend bution of this study also provides new insights regarding and support their ability to “aging in place.” (e results show e-healthcare, with the application of AHP as a premise to that Safety and independence are also important factors for identify the less and more potential criteria for re- the elderly to use or nonuse of technology and they believe searchers and decision-makers. that the use of technology would significantly lead them to be Journal of Healthcare Engineering 3 acceptance and use of technology (UTAUT), which iden- safe and independent daily life [23]. Moreover, a qualitative study conducted to assess the usage of the patient portal by tified three direct predictors of usage intention, i.e., per- formance expectancy, effort expectancy, and social older patients with multiple chronic conditions shows that older people have the impression that usage of online portal influence, and two direct predictors of usage behavior saves time and money and give proper health information. (behavior intention and facilitating conditions), and also (e results also showed that older adults were more intent to added four moderators as gender, age, experience, and use online portals because of the convenience of the health voluntariness of use [30]. management system and perceived usefulness [21]. Literature (e purpose of the current research is to identify the list also found that elderly people have a positive attitude towards ofthe influencingindicatorsbyusing the Delphimethodand to apply the multiple criteria decision analysis to prioritize mobile technology but they are also concerned about some complex functions, such as, age, attention, and capability of the more or less potential barriers for the optimal solution to promote e-healthcare system usage among elderly people. processing speed are critical factors that affected their usage [2]. Gaita´n and colleagues reported that the technology usage We calculated priority weights of criteria and subcriteria by using AHP. the list of the main barriers and sub-barriers is behavior of elderly people is affected by habit, performance expectancy, price value, and effort expectancy [24]. Similarly, compiled by the review of the previous literature shown in they highlighted some reasons for the non-use of technology Table 1. Next, the research framework and results and byelderly people,such as;dispositional barriers,technological findings are discussed in subsequent sections. barriers, and situational barriers. For instance, forgetfulness is one of the dispositional barriers to the nonuse of technology 3. Research Framework and Methods by elderly people as they are easy to forget passwords of ATM etc.Healthandabilityconditions,likepoorvisionandhearing (e framework in this study provides an insight for the are also reported as the reasons for nonuse of technology [2]. healthcare providers and policymakers to closely observe Chen and Chan added the age related health and ability and tackle the barriers to e-health usage. (e research factors including; self-reported health conditions, functional framework of our study is shown in Figure 1, where the and cognitive abilities and attitude to ageing and life satis- DMAIC (define, measure, analyze, improve, and control) six faction as the predictors of technology usage of elderly people sigma tool is used to design the checklist consisting of the [19]. Moreover, negative self-evaluated beliefs (too old to use potential barriers regarding the e-healthcare system usage. technology), mental effort needed to operate advanced (DMAIC) is a data-driven strategy used to improve complex technologies, lack of interest, lack of time and assistance, processes. (is methodology is widely used in healthcare limited access to and exposure to technology, expense, research [31–34]. complexity, and safety are the reasons for nonuse of tech- (erewerefive stepsin DMAIC,the firststep isto define. nology by elderly people mentioned by several studies It is all about content validity which is done by reviewing the [5, 19, 20, 25–28]. (is suggests that use of e-health among previous literature. (e next step according to the DMAIC is elderly people is affected by several factors and generalizing the Measure “which means data collection here.” For our them may not be the solution or compensation mechanism study, we used the Delphi method to collect the required for all older people. data for this study. Delphi method is a widely used data (ere are several technology acceptances models and collection technique in multiple criteria decision-making theories that provided various factors predicting the usage, research [31, 35, 36]. (is method provides a systematic way acceptance, and adoption of the technology by older people. of getting the opinions from experts by using focused group In 1989, for the first time, Davis presented the technology discussions and questionnaires. (e whole data collection acceptance model to predict who is more likely to accept the was done in several steps. (e data was collected by dis- new technology, which was the adaptation of the two of the seminating the checklist to 10 experts in March 2021 and well-known theory of reasoned action presented by Fishbean getting the complete responses in April 2021. (ere was a and Ajzens in 1975, and the theory of planned behavior by total of 13 potential barriers in the checklist which were Ajzan in 1991. (e technology acceptance model issomehow compiled in 3 major categories presented in Table 2. After the adaptation of the theory of reasoned action which states identifying the potential barriers from the literature, the that beliefs determine the behavior intention of the user items were modified according to the Pakistani context. which determines the actual behavior. Hence, technology (en, the list was modified and verified by the group of acceptance behavior is different from the theory of planned experts again, to confirm whether the selected indicators are behavior as it states that the acceptance of technology is not favorable in the Pakistani context or not. solely dependent on the beliefs of the users. Venkatesh and (e next step in the DMAIC was “Analyze and improve” Davis in 2000, extended the technology acceptance model the model. Multi-criteria decision analysis is a generalizable known as TAM2, states that decision of the technology method for making decisions with dependencies and feedback adoption depends on the outcome of the evaluation of the [37]. Analytical hierarchy process (AHP) is a widely used perceived ease of use (difficulty in using technology), their technique in multiple criteria decision-making analysis, used beliefs on perceived usefulness (using technology will in- by our study to analyze the e-healthcare barriers. (is method crease their job performance), and subjective norms that has been used by researchers from diversified fields to simplify state the influence of the people who are important to them decision-making problems [38–42]. (e detailed description of [29]. In 2003, Venkatesh presented a new united theory of multiplecriteriadecisionanalysisandstepsoftheAHPmethod 4 Journal of Healthcare Engineering Table 1: Potential barriers to e-health usage system for the aging population. Main barriers Sub-barriers References Attitudinal (AD-1) Negative attitude towards using technology (AD-11) Lack of perceived usefulness (AD-12) [19–21, 24, 28] Lack of perceived Ease of use (AD-13) Negative attitude towards life and life satisfaction (AD-14) Socio-Environmental (SE-2) Insufficient facilitating conditions (SE-21) Negative subjective norm (SE-22) [23, 24, 30] Lack of social support (SE-23) Insufficient funds/Cost Tolerance (SE-24) Health and Ability (HA-3) Physical health (HA-31) Lack of psychological fitness (HA-32) Lack of cognitive ability (HE-33) [2, 22] [5, 19, 20] Lack of self-efficacy (HA-34) Suffering from anxiety (HA-35) DEFINE Literature review Identification of barriers MEASURE Delphi method Expert’s opinion Finalization of barriers Categorization of main barriers ANALYZE Categorization of sub-barriers MCDM (AHP) Approval of final I model IMPROVE Hierarchical structure of the Results and decision problem CONTROL discussion Pair-wise comparison Consistency index Consistency ratio Figure 1: Research framework operationalized in the study. Table 2: Estimated AHP weights for main and sub-barriers. Main barriers Main barriers weights Sub-barriers code Consistency ratio (CR) Priority weight Final weight Attitudinal (AD-1) 0.1061 AD-11 0.03 0.0688 0.007 AD-12 0.1725 0.018 AD-13 0.2314 0.025 AD-14 0.5357 0.057 Socio-Environmental (SE-2) 0.2604 SE-21 0.03 0.0986 0.026 SE-22 0.0922 0.024 SE-23 0.2477 0.065 SE-24 0.5666 0.148 Health and Ability (HA-3) 0.6334 HA-31 0.01 0.0535 0.034 HA-32 0.1077 0.068 HA-33 0.1046 0.066 HA-34 0.2509 0.159 HA-35 0.4833 0.306 Journal of Healthcare Engineering 5 (1) Step-I: Constructing Hierarchy. First of all, the problem are explained in the next section. Finally, the last step in the DMAIC framework contains “control” which is all about has to be structured into hierarchies with different layers defined as a goal, criteria, and alternatives. (e goal is the concluding results, keeping them verified, committing to improvement, and passing along best recommendations to main purpose of constructing the model. (e second level of future researchers. the hierarchy must be composed of some criteria based on whichthe researcherisgoing toevaluatethe alternatives.(e third important part or layer of hierarchy is the alternatives 3.1. Data Collection. Past studies used a different number of or the main areas of evaluation. (e respondents have to be experts to obtain reliable results for multiple criteria decision selecting the alternatives based on the given criteria. (e analysis; for example, Ikram et al. [43] used 10 experts to hierarchy can consist of many sub-criteria and alternatives. prioritize the barriers for integrated management assessment According to Saaty, the criteria for each dimension should using the MCDM method. Whereas, another study used 4 be mutually independent [13]. experts for MCDM analysis to develop a model to choose an appropriate Computerized Maintenance Management Sys- (2) Step-II: Deriving Weights or Priorities for the Criteria. tem (CMMS) for a dairy company [44]. For the current (e next step is to perform a pairwise comparison of the research, 10 experienced experts were selected to rank the respondents’ or experts’ judgments to determine the barriers and sub barriers. (e participants were from aca- comparative weights. (is step yields the ranked priorities demics from an aging research background, the healthcare for the alternatives under each criterion. Based on a sector, and policymakers. (ey were asked to prioritize the standard evaluation scheme, Saaty developed a scale for barriers based on their experts’ opinions and experiences. All pairwise comparisons. In this step, the components of a of the selected experts were having more than 10 years of certain level are compared with respect to a specific experience, and have some research background in the aging component in the direct upper level. (e consequential care and e-healthcare management system. weights of the components may be referred to as local weights. 3.2. Multiple Criteria Decision-Making (MCDM). MCDM is (3) Step-III: Calculating Priorities. (e judgment matrices a method of operational research that is commonly used to are then used to calculate the priorities. (e Eigenvalue solve decision problems [45]. MCDM enables assessment method is the method most commonly used by researchers and multiple expert judgments, and it is used to overcome for this step [49–51]. the presence of imprecision and ambiguity during the evaluation process [46]. Several MCDM techniques have (4) Step-IV: Model synthesis or Final Ranking. In this step, been discussed in the previous literature [37, 47]. However, the calculated priorities are combined or aggregated as a each technique has unique characteristics and applications. weighted sum to establish or obtain the overall ranking of (e analytic hierarchy process (AHP) method of MCDM is the best alternative. used in this study to identify potential barriers to e-health use among the aging population. (5) Step-V: Consistency. After getting the results, it is re- quired to check the consistency to verify the model. (e Saaty introduced the threshold of 10% or 0.01 as the ac- 3.2.1. Analytical Hierarchical Process (AHP). (e AHP is a ceptable inconsistencies in the data. AHP computes the theory of measurement proposed by Saaty [13]. AHP is consistency ratio (CR), by comparing the consistency index introduced to simplify the decision-making problems. (CI) ofthe matrixin question(with our evaluations) with the AHP aims to compute relative priorities for a specified set consistency index of a random matrix (RI). (e formula for of alternatives on a ratio scale which are centered on the the consistency check is given by Saaty as decisions of experts, firmly following the consistency CI standard of pairwise comparison in the process of decision- (1) CR � , RI making [48]. (e strong point of this method is that it provides a structured yet relatively simple solution and where organizes tangible and intangible factors in a logical way to λ − n max (2) the decision-making problems (Shen & Li, 2005). In this CI � . n − 1 study, the Analytical hierarchy process (AHP) is used to identify e-healthcare barriers. (is method is used because Here CI represents consistency index, and CR as con- of its unique utilization of a hierarchy structure to rep- sistency ratio, λ represents the biggest eigenvalue of the max resent a problem in the form of a goal, criteria, and al- pair-wise comparison matrix, n is the matrix order, and RI is ternatives [13]. AHP’s main components are pairwise a random index. If the value of CR is less than 10% then the comparisons, developing and comparing matrices, and matrix is considered as having an acceptable consistency. In ensuring their consistency. (is technique assists all de- some cases, 20% can also be acceptable but not more [13]. If cision-makers in selecting and ranking complex problems the CR does not lie within the given threshold or acceptable rationally. (e following steps are involved in the com- range then decision-makers have to be revised their putations of this method: judgments. 6 Journal of Healthcare Engineering Barriers and sub-barriers Negative attitude Insufficient facilitating Physical health towards technology use conditions (SE-21) (HA-31) (AD-11) Lack of perceived Negative subjective norm Lack of psychological usefulness (AD-12) (SE-22) fitness (HA-32) Lack of perceived Lack of social support Lack of cognitive ease of use (AD-13) (SE-23) ability (HA-33) Lack of self-efficacy Negative attitude towards life Insufficient funds/Cost and life satisfaction (HA-34) tolerance (SE-24) (AD-14) Suffering from anxiety (HA-35) Figure 2: Hierarchical structure of e-health management system barriers. weights by using a geometric mean. We used the group- 0.1061, 11% based decision-making approach to calculate the weights for the e-healthcare barriers and sub-barriers. For the MCDM analysis, we categorized sub-barriers into three main bar- riers, i.e., Attitudinal barriers, socio-environmental barriers, and health and ability barriers. (e weights were calculated for the 3 main barriers first and then for the sub-barriers. 0.2604, 26% Figure 2, shows the hierarchal structure of e-healthcare barriers and sub-barriers. Table 2 shows the results of the 0.6334, 63% AHP method. 4.1. Main Barriers. (e weights of each main barrier were calculated by using the AHP technique. (e results in Figure 3, show that ‘Health and ability’ are resulted to be the most potential barrier weighting (0.6334), followed by socio- Attitudinal (AD-1) environmental (0.2604), and attitudinal barrier (0.1061), Scio-environmental (SE-2) respectively. (ese barriers seem to be a challenge for Health and Ability (HA-3) implementing the e-healthcare system for the aging pop- Figure 3: Ranking of main barriers based on AHP. ulation. Sound health and ability constructs are the foremost barriers highlighted to be addressed to ensure the effective use of e-health among older adults. Manufacturers, poli- 4.Results and Discussion cymakers, and healthcare providers should focus on age- (is study aims to identify barriers to the use of the related health problems while framing and implementing e-healthcare system by elderly people, to better facilitate the e-healthcare technology. Socio-environmental and at- the future development of a digital healthcare system for the titudinal barriers are placed at second and third priorities by aging population. (e AHP method was used to calculate the the experts. To facilitate e-health use among the aging Attitudinal (AD-1) Scio-environmental (SE-2) Health and ability (HA-3) Journal of Healthcare Engineering 7 population, the manufacturers and policymakers should Negative Attitude towards Life and 0.5357 life satisfaction (AD-14) carefully prioritize the barriers as per their potential Lack of Perceived Ease of strengths and weaknesses. E-healthcare manufacturers 0.2314 Use (AD-13) should design the products in a manner that can overcome Lack of Perceived the barriers and construct an elderly user-friendly e-health 0.1725 usefulness (AD-12) technology system for more optimal outcomes while con- Negative Attitude towards 0.0688 sidering these potential barriers. Gerontechnologies should Using technology (AD-11) manufacture to facilitate the users without facing any 0 0.2 0.4 0.6 challenges. (ere is a need to accept the age-specific re- Figure 4: (e ranking order of attitudinal sub-barriers. quirements to better implement the use and to facilitate the e-health care system for elderly people. Finally, attitudinal characteristics are turned out as the least important barrier, positive attitude towards technology motivates the elderly to revealing that the use of e-health can be impacted by atti- accept and use e-health technology. Results are displayed in tudinal beliefs but with less intensity. Additionally, the 14 Figure 4. sub-barriers were assessed by using a pairwise comparisons matrix. 4.2.2. Socio-Environmental Sub-Barriers. (e ranking of the sub-barriers under the category of socio-environmental barrier is as follows: 4.2. Sub-barriers. (e detailed results of the sub-barriers are given as follows. SE − 24>SE − 23>SE − 21>SE − 22. (4) Insufficient funds (0.5666) have resulted as the greatest 4.2.1. Attitudinal Sub-Barriers. (e Attitudinal sub-barriers challenge for elderly people to use e-healthcare technology. are ranked as follows: (e findings show that the cost of e-health for the aging population shouldbeeconomical forbetter healthoutcomes. AD − 14>AD − 13>AD − 12>AD − 11. (3) (erefore, sufficient funds or cost tolerance would increase Negative attitude towards life and life satisfaction the use of e-health among elderly and the facilitate the smart appeared as the most potential sub-barrier (AD-14) of at- health care agenda of policymakers. Several studies have titudinal barrier with a weight of (0.53). (is ranking rep- considered the importance of the financial status, occupa- resents the reality that lack of life satisfaction leads older tion, and income, that may influence the technology usage adults towards isolation and increase depression and feeling behavior of elderly people [20, 55, 56]. Pakistan is a de- of social withdrawn. Such feelings may lead older towards veloping country and per capita income is relatively low as the lack of interest in technology and e-health system. (e compared with other developed countries [57], especially older people who have a low socio-economic background positive life satisfaction in older age depends on multiple factors, such as poverty, lack of income, poor health, and and are concerned with the costs of technological products and services. Hence, we may assume that Cost tolerance is a depression, as mentioned in a previous study [45, 52]. (e second sub-barrier is the lack of perceived ease of use among significant predictor of e-health usage behavior of elderly older adults (AD-13) with 0.2314 priority weight. Perceived people. ease of use is defined as “the degree to which a person Lack of social support is prioritized as the second po- believes that using a technology will be free from effort” tential sub-barrier (SE-23, 0.2477) under this category. El- (p.320). Previous studies maintained that perceived ease is derly people who suffer from social exclusion and lack of strongly associated with the use of technology among older social support from friends and family may have the least adults [21, 53]. User-friendly and effort-free e-healthcare interest in using e-health which affects their healthcare products encourage the use of e-health among older adults. access. A previous study also mentioned social interaction as the motivation for using technology for elderly people as Moreover, perceived usefulness is resulted to be the third influential sub-barrier (AD-12) under the category of atti- they think that interacting with other people is crucial for their wellbeing [23]. tudinal barrier with a weight of (0.1725). Perceived use- fulness is defined as “the extent to which a person believes Insufficient facilitating conditions are prioritized as the that using a particular technology will enhance his/her job third potential (SE-21, 0.0986) sub-barrier under the cate- performance” [54]. factors affecting technology usage gory of the socio-environmental barrier. Facilitating con- among older adults within the literature focus on the im- ditions are the environmental factors that support the usage portance of attitudinal factors, whereas some studies of technology by elderly people. Venketesh in 2003, pre- revealed that there is no significant effect of Perceived sented a united theory of technology acceptance (UTAUT) usefulness on the technology usage behavior of older adults and found the facilitating conditions as a direct predictor of [19, 20]. Further, a negative attitude towards using tech- technology usage behavior [30]. A study in India about the ICT usage behavior of elderly people revealed that facili- nology has appeared as the least important sub-barrier (AD- 11, 0.0688) of the Attitudinal barrier. Attitude towards using tating conditions are positively associated with technology technology is mainly used as a dependent variable in the usage [58]. Hence, a lack of facilitating conditions may affect previous studies, influence by several other factors [21]. A the successful promotion of e-health use. 8 Journal of Healthcare Engineering Insufficient funds /Cost Tolerance (SE-24) 0.5666 Lack of Social support (SE-23) 0.2477 Insufficient Facilitating conditions (SE-21) 0.0986 Negative Subjective Norm (SE-22) 0.0922 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Figure 5: (e ranking of socio-environmental sub-barriers. Suffering from Anxiety (HA-35) 0.4833 Lack of Self-Efficacy (HA-34) 0.2509 Lack of Psychological Fitness (HA-32) 0.1077 Lack of Cognitive Ability (HA-33) 0.1046 Physical Health (HA-31) 0.0535 0 0.1 0.2 0.3 0.4 0.5 0.6 Figure 6: (e ranking of health and ability sub-barriers. (e last sub-barrier under the socio-environmental older adults [20].Lack of cognitive ability is prioritized asthe barrier isthe negative subjective norm (SE-22) with(0.0922). third sub-barrier (HA-33) in this category with the weight of Subjective norm is defined here as the influence of the people (0.1046). A previous study stated the importance of cognitive abilities for older adults in using technology [14]. (e dif- who are important to the elderly [29]. Negative influence from peers and family may hinder access to e-health usage ference between (HA-33) and (HA-32) weights is 0.0031, and result in poor health care [59]. See Figure 5. which shows their almost equal importance for e-healthcare use among elderly people. psychological health factors are positively affecting the technology usage behavior of older 4.2.3. Health and Ability Barriers. Figure 6 shows the results people [19]. (e last sub-barrier under this category is of sub-barriers under the category of health and ability physical health with (0.0535) weight, showing its least im- barriers with the results as follows: portance in the use of e-health system. HA − 35>HA − 34>HA − 32>HA − 33>HA − 31. (5) 4.3. 5e Overall Ranking of Sub-Barriers. Figure 7, shows the Based on the expert’s opinion, anxiety is prioritized as overall ranking of all the sub-barriers by calculating the final the most potential sub-barrier (HA-35) with weight weights of all sub-barriers. (e calculations are done by (0.4833). Anxiety is defined as the individual hesitation using the weight of each sub-barrier and multiplying it by when he or she intends to use the system [60]. Chen and the weight of its respective main barrier. (e results of the Chan used anxiety in their senior technology acceptance ranking of overall sub-barriers are as follows: model and the results show that anxiety has a negative influence on the technology usage behavior of elderly people HA − 35>HE34>SE − 24>HA32>HE − 33>SE [20]. Hence, the proper guidelines and understanding of the − 23>AD − 14>HA − 31>SE − 21>AD − 13>SE healthcare system may help elderly people to reduce anxiety and increase their motivation towards the effective use of the − 22>AD − 12>AD − 11. e-health system. Furthermore, self-efficacy has resulted as a (6) second potential sub-barrier (HA-34, 0.2509) under the health and ability barriers. Self-efficacy is generally defined Anxiety is resulted to be the ranked first potential sub- as the person’s judgment of his or her ability to use the barrier with the weight (0.306) among all other, followed by system [45]. It has been declared as a potential factor in self-efficacy (0.159), insufficient funds (0.148), and lack of previous studies which affects the use of technology among psychological fitness (0.068). (e least three sub-barriers Journal of Healthcare Engineering 9 Suffering from Anxiety (HA-35) 0.306 Lack of Self-Efficacy (HA-34) 0.159 Insufficient funds /Cost Tolerance (SE-24) 0.148 Lack of Psychological Fitness (HA-32) 0.068 Lack of Cognitive Ability (HE-33) 0.066 Lack of Social support (SE-23) 0.065 Negative Attitude towards Life and life satisfaction (AD-14) 0.057 Physical Health (HA-31) 0.034 Insufficient Facilitating conditions (SE-21) 0.026 Lack of Perceived Ease of Use (AD-13) 0.025 Negative Subjective Norm (SE-22) 0.024 Lack of Perceived usefulness (AD-12) 0.018 Negative Attitude towards Using technology (AD-11) 0.007 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 Figure 7: (e overall ranking of sub-barriers. have resulted as a negative subjective norm (0.024), lack of the e-health system that plays a significant role in facilitating the smart health care industry for the aging population. perceived usefulness (0.018), and negative attitude towards technology (0.007) respectively. More importantly, this investigation facilitates researchers with an MCDA roadmap to help them enhance the quality of their studies and their understanding of how to use MCDA 5.Conclusion techniques to evaluate and prioritize the influencing factors affecting e-health use in healthcare research. (e need for tools that aid in decision-making occurs in a variety of healthcare settings and these tools are employed to Data Availability varying degrees in different settings [61]. In this study, we focus on the possibilities of using a specific multiple criteria (e data used to support the findings of this study are decision-making technique in ranking potential barriers for available from the corresponding author upon request. e-health use among elderly people. (e findings show that health and ability constructs are crucial to address while Conflicts of Interest encouraging the use of e-health system for elderly people. (e authors declare that they have no conflicts of interest. Our findings are vital to decision makers in the field of geriatrics and healthcare technology to focus on the age References related health and ability characteristics while introducing any innovation in an e-health system. [1] WHO, Ageing and Health, 2021, Retrieved from https://www. Since the identification of the potential barriers and sub- who.int/news-room/fact-sheets/detail/ageing-and-health. barriers is an innately complex system that cannot be [2] J. Li, Q. Ma, A. H. Chan, and S. S. Man, “Health monitoring represented using a single metric only, multidimensional through wearable technologies for older adults: smart wear- (MCDA) approaches are highly suggested to identify po- ables acceptance model,” Applied Ergonomics, vol. 75, tential risks. Hence, our study aimed to investigate the pp. 162–169, 2019. feasibility of employing the AHP approach to identify [3] T. R. Wind, M. Rijkeboer, G. Andersson, and H. Riper, “(e COVID-19 pandemic: (e ‘black swan’ for mental health care possible barriers to e-health use among older adults. (e and a turningpoint fore-health,”Internet interventions,p. 20, technique presented in this paper is quite simple. Any spreadsheet may be used to execute mathematical opera- [4] C. Ramprasad, L. Tamariz, J. Garcia-Barcena, Z. Nemeth, and tions, which is very important for small sample sizes. (e A. Palacio, “(e use of tablet technology by older adults in AHP technique may be successfully utilized in the healthcare health care settings—is it effective and satisfying? a systematic domain to analyze, compare, and identify the potential review and meta analysis,” Clinical Gerontologist, vol. 42, barriers, and to prioritize them according to their worst no. 1, pp. 17–26, 2019. scenarios, as shown in the studies and analyses presented [5] K. Chen and A. Chan, “Use or non-use of gerontechnology-A here. Utilizing the MCDA techniques in the present study qualitative study,” International Journal of Environmental will assist the public health practitioners and policymakers Research and Public Health, vol. 10, no. 10, pp. 4645–4666, in drawing decisions on the best way to minimize the risks in 2013. 10 Journal of Healthcare Engineering [6] E. M. Agree, “(e potential for technology to enhance in- [22] S. T.M. Peek, K. G. Luijkx,M. D. Rijnaardet al., “Older adults’ dependence for those aging with a disability,” Disability and reasons for using technology while aging in place,” Geron- health journal, vol. 7, no. 1, pp. S33–S39, 2014. tology, vol. 62, no. 2, pp. 226–237, 2016. [7] Q. Ma, K. Chen, A. H. S. Chan, and P.-L. Teh, “Acceptance of [23] A. Mahmood, T. Yamamoto, M. Lee, and C. Steggell, “Per- ICTs by older adults: A review of recent studies,” in Inter- ceptions and use of gerotechnology: Implications for aging in national Conference on Human Aspects of IT for the Aged place,” Journal of Housing for the Elderly, vol. 22, no. 1-2, pp. 104–126, 2008. Population, Springer, Cham, Switzerland, 2015. [8] S. J. Czaja, J. Sharit, C. C. Lee et al., “Factors influencing use of [24] J. A. Gaita´n, B. Peral Peral, and M. Ramo´n Jero´nimo, “El- derly and internet banking: An application of UTAUT2,” an e-health website in a community sample of older adults,” Journal of the American Medical Informatics Association, Journal of Internet Banking and Commerce, vol. 20, no. 1, vol. 20, no. 2, pp. 277–284, 2013. pp. 1–23, 2015. [9] R. Kampmeijer, M. Pavlova, M. Tambor, S. Golinowska, and [25] N.-H. Chen and S. C.-T. Huang, “Domestic technology W. Groot, “(e use of e-health and m-health tools in health adoption: comparison of innovation adoption models and promotion and primary prevention among older adults: a moderators,” Human Factors and Ergonomics in systematic literature review,” BMC Health Services Research, Manufacturing & Service Industries, vol. 26, no. 2, pp. 177– 190, 2016. vol. 16, no. 5, pp. 467–479, 2016. [10] J. Wilson, M. Heinsch, D. Betts, D. Booth, and F. Kay- [26] M. Hoque and G. Sorwar, “Factors influencing mHealth acceptance among elderly people in Bangladesh,” arXiv Lambkin, “Barriers and facilitators to the use of e-health by older adults: a scoping review,” BMC Public Health, vol. 21, preprint arXiv:1606.00874, 2016. [27] B. Klimova, I. Simonova, P. Poulova, Z. Truhlarova, and no. 1, pp. 1–12, 2021. [11] H. J. (ompson, G. Demiris, T. Rue et al., “A Holistic ap- K. Kuca, “Older people and their attitude to the use of in- proach to assess older adults’ wellness using e-health tech- formation and communication technologies–a review study nologies,” Telemedicine and e-Health, vol. 17, no. 10, with special focus on the Czech Republic (Older people and pp. 794–800, 2011. their attitude to ICT),” Educational Gerontology, vol. 42, no. 5, [12] Q. A. Qureshi, B. Shah, A. Nawaz, I. Khan, M. Waseem, and pp. 361–369, 2016. F. Muhammad, “E-health in Pakistan: issues and prospects,” [28] Q. Li and Y. Luximon, “Understanding older adults’ post- adoption usage behavior and perceptions of mobile tech- Journal of Biology, Agriculture and Healthcare, vol. 4, no. 17, pp. 106–115, 2014. nology,” International Journal of Design, vol. 12, no. 3, [13] T. L. Saaty, “Decision making with the analytic hierarchy pp. 93–110, 2018. process,” International Journal of Services Sciences, vol. 1, [29] V. Venkatesh and F. D. Davis, “A theoretical extension of the no. 1, pp. 83–98, 2008. technology acceptance model: four longitudinal field studies,” [14] S. J. Czaja, N. Charness, A. D. Fisk et al., “Factors predicting Management Science, vol. 46, no. 2, pp. 186–204, 2000. the use of technology: findings from the center for research [30] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, and education on aging and technology enhancement “User acceptance of information technology: toward a unified (CREATE),” Psychology and Aging, vol. 21, no. 2, pp. 333–352, view,” MIS Quarterly, vol. 27, no. 3, pp. 425–478, 2003. [31] N. Aydin and S. Seker, “Determining the location of isolation [15] L. Dogruel, S. Joeckel, and N. D. Bowman, “(e use and hospitals for COVID-19 via Delphi-based MCDM method,” acceptance of new media entertainment technology by elderly International Journal of Intelligent Systems, vol. 36, no. 6, users: development of an expanded technology acceptance pp. 3011–3034, 2021. model,” Behaviour & Information Technology, vol. 34, no. 11, [32] G. Cesarelli, R. Petrelli, C. Ricciardi et al., “Reducing the pp. 1052–1063, 2015. healthcare-associated infections in a rehabilitation hospital [16] D. Hallberg and N. Salimi, “Qualitative and quantitative under the guidance of lean six sigma and DMAIC,” analysis of definitions of e-health and m-health,” Healthcare Healthcare (Basel), vol. 9, no. 12, p. 1667, 2021. informatics research, vol. 26, no. 2, pp. 119–128, 2020. [33] A. M. Ponsiglione, C. Ricciardi, A. Scala et al., “Application of [17] M. D. C. Miranda-Duro, L. Nieto-Riveiro, P. Concheiro- DMAIC cycle and modeling as tools for health technology Moscoso et al., “Occupational therapy and the use of tech- assessment in a university hospital,” Journal of healthcare nology on older adult fall prevention: A scoping review,” engineering, vol. 2021, 2021. International Journal of Environmental Research and Public [34] C. Ricciardi, A. Gubitosi, D. Vecchione et al., “Comparing two Health, vol. 18, no. 2, p. 702, 2021. approaches for thyroidectomy: a health technology assess- [18] Q. Ma, A. H. S. Chan, and K. Chen, “Personal and other factors ment through DMAIC cycle,” Healthcare (Basel), vol. 10, affecting acceptance of smartphone technology by older Chi- no. 1, p. 124, 2022. nese adults,” Applied Ergonomics, vol. 54, pp. 62–71, 2016. [35] S. Bid and G. Siddique, “Human risk assessment of Panchet [19] K. Chen and A. H. S. Chan, “Predictors of gerontechnology dam in India using TOPSIS and WASPAS multi-criteria acceptance by older Hong Kong Chinese,” Technovation, decision-making (MCDM) methods,” Heliyon, vol. 5, no. 6, vol. 34, no. 2, pp. 126–135, 2014. Article ID e01956, 2019. [36] Y. R. Lim, A. S. Ariffin, M. Ali, and K.-L. Chang, “A hybrid [20] K. Chen and A. H. S. Chan, “Gerontechnology acceptance by elderly Hong Kong Chinese: A senior technology acceptance MCDM model for live-streamer selection via the fuzzy delphi model(STAM),” Ergonomics,vol. 57,no. 5, pp.635–652, 2014. method, AHP, and TOPSIS,” Applied Sciences, vol. 11, no. 19, [21] J. D. Portz, E. A. Bayliss, S. Bull et al., “Using the technology p. 9322, 2021. acceptance model to explore user experience, intent to use, [37] S. Rehman, E. Rehman, I. Hussain, and Z. Jianglin, “Socio- and use behavior of a patient portal among older adults with economic influence on cardiac mortality in the south asian multiple chronic conditions: descriptive qualitative study,” region: new perspectives from grey modeling and G-TOPSIS,” Journal of Medical Internet Research, vol. 21, no. 4, Article ID Journal of healthcare engineering, vol. 2021, Article ID e11604, 2019. 6866246, 2021. Journal of Healthcare Engineering 11 [38] Y. Liu, C. M. Eckert, and C. Earl, “A review of fuzzy AHP [53] M. J. S. Diño and A. B. de Guzman, “Using partial least methods for decision-making with subjective judgements,” squares (PLS) in predicting behavioral intention for telehealth use among Filipino elderly,” Educational Gerontology, vol. 41, Expert Systems with Applications, vol. 161, Article ID 113738, no. 1, pp. 53–68, 2015. [54] F. D. Davis, “Perceived usefulness, perceived ease of use, and [39] H.-M. Lyu, W.-H. Zhou, S.-L. Shen, and A.-N. Zhou, “In- user acceptance of information technology,” MIS Quarterly, undation risk assessment of metro system using AHP and vol. 13, no. 3, pp. 319–340, 1989. TFN-AHP in Shenzhen,” Sustainable Cities and Society, [55] A. Alam, M. Ibrar, and P. Khan, “Socio-economic and psy- vol. 56, Article ID 102103, 2020. chological problems of the senior citizens of Pakistan,” [40] M. Mathew, R. K. Chakrabortty, and M. J. Ryan, “A novel Peshawar Journal of Psychology and Behavioral Sciences approach integrating AHP and TOPSIS under spherical fuzzy (PJPBS), vol. 2, no. 2, pp. 249–261, 2016. sets for advanced manufacturing system selection,” Engi- [56] F. Manzoor, L. Wei, A. Hussain, M. Asif, and S. I. A. Shah, neering Applications of Artificial Intelligence, vol. 96, Article “Patient satisfaction with health care services; an application ID 103988, 2020. of physician’s behavior as a moderator,” International Journal [41] U. F. Sahibzada, K. F. Latif, Y. Xu, and R. Khalid, “Catalyzing of Environmental Research and Public Health, vol. 16, no. 18, knowledgemanagementprocessestowardsknowledgeworker p. 3318, 2019 Retrieved from https://www.mdpi.com/1660- satisfaction: fuzzy-set qualitative comparative analysis,” 4601/16/18/3318. Journal of Knowledge Management, vol. 24, no. 10, 2020. [57] F. Manzoor, L. Wei, and M. Siraj, “Small and medium-sized [42] U. F. Sahibzada, Y. Xu, G. Afshan, and R. Khalid, “Knowl- enterprises and economic growth in Pakistan: an ARDL edge-oriented leadership towards organizational perfor- bounds cointegration approach,” Heliyon, vol. 7, no. 2, Article mance: symmetrical and asymmetrical approach,” Business ID e06340, 2021. Process Management Journal, vol. 27, no. 6, 2021. [58] A. Pargaonkar, W. Mishra, and S. Kadam, “A study on elderly [43] M. Ikram, Q. Zhang, and R. Sroufe, “Developing integrated individuals’ attitude towards,” in Research into Design for a management systemsusing an AHP-Fuzzy VIKORapproach,” Connected World, pp. 723–734, Springer, 2019. Business Strategy and the Environment, vol. 29, pp. 2265– [59] H.-Y. Yan and M.-J. Wang, “What factors affect physicians’ 2283, 2020. decisions to use an e-health care system?” 2012. [44] A. Zare, M. Feylizadeh, A. Mahmoudi, and S. Liu, “Suitable [60] X. Xu, F. Manzoor, S. Jiang, and A. Mumtaz, “Unpacking the computerized maintenance management system selection mental health of nurses during COVID-19: evidence from using grey group TOPSIS and fuzzy group VIKOR: a case Pakistan,” Journal of Clinical Medicine, vol.10, no.16, p. 3546, study,” Decision Science Letters, vol. 7, no. 4, pp. 341–358, 2021, Retrieved from https://www.mdpi.com/2077-0383/10/ 16/3546. [45] A. Mumtaz, F. Manzoor, S. Jiang, and M. Anisur Rahaman, [61] S. Rehman, N. Rehman, M. Naz, A. Mumtaz, and Z. Jianglin, “COVID-19 and mental health: A study of stress, resilience, “Application of grey-based SWARA and COPRAS techniques and depression among the older population in Pakistan,” in disease mortality risk assessment,” Journal of healthcare Healthcare, vol. 9, no. 4, p. 424, 2021 Retrieved from https:// engineering, vol. 2021, Article ID 7302157, 2021. www.mdpi.com/2227-9032/9/4/424. [46] S. Rehman, E. Rehman, A. Mumtaz, and Z. Jianglin, “A multicriteria decision-making approach in exploring the nexus between wind and solar energy generation, economic development, fossil fuel consumption, and CO2 emissions,” Frontiers in Environmental Science, vol. 659, 2022. [47] A. Mumtaz, E. Rehman, S. Rehman, and I. Hussain, “Impact of environmental degradation on human health: an assess- ment using multicriteria decision making,” Frontiers in Public Health, vol. 9, Article ID 812743, 2022. [48] I. Syamsuddin and J. Hwang, “A new fuzzy MCDM frame- work to evaluate e-government security strategy,” in Pro- ceedings of the 2010 4th International Conference on Application of Information and Communication Technologies, pp. 1–5, IEEE, Tashkent, Uzbekistan, October 2010. [49] M. I. Al Khalil, “Selecting the appropriate project delivery method using AHP,” International Journal of Project Man- agement, vol. 20, no. 6, pp. 469–474, 2002. [50] D. H. Byun, “(e AHP approach for selecting an automobile purchase model,” Information & Management, vol. 38, no. 5, pp. 289–297, 2001. [51] A. E. Ezzat and H. S. Hamoud, “Analytic hierarchy process as module for productivity evaluation and decision-making of the operation theater,” Avicenna Journal of Medicine, vol. 6, no. 1, pp. 3–7, 2016. [52] S. S. Celik, Y. Celik, N. Hikmet, and M. M. Khan, “Factors affecting life satisfaction of older adults in Turkey,” 5e In- ternational Journal of Aging and Human Development, vol. 87, no. 4, pp. 392–414, 2018. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Healthcare Engineering Hindawi Publishing Corporation

Prioritizing and Overcoming Barriers to e-Health Use among Elderly People: Implementation of the Analytical Hierarchical Process (AHP)

Journal of Healthcare Engineering , Volume 2022 – Apr 11, 2022

Loading next page...
 
/lp/hindawi-publishing-corporation/prioritizing-and-overcoming-barriers-to-e-health-use-among-elderly-voO1GIUT0y

References (60)

Publisher
Hindawi Publishing Corporation
Copyright
Copyright © 2022 Ayesha Mumtaz. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ISSN
2040-2295
eISSN
2040-2309
DOI
10.1155/2022/7852806
Publisher site
See Article on Publisher Site

Abstract

Hindawi Journal of Healthcare Engineering Volume 2022, Article ID 7852806, 11 pages https://doi.org/10.1155/2022/7852806 Research Article Prioritizing and Overcoming Barriers to e-Health Use among Elderly People: Implementation of the Analytical Hierarchical Process (AHP) 1,2 Ayesha Mumtaz School of Public Administration, Hangzhou Normal University, Hangzhou, China College of Public Administration, Zhejiang University, Hangzhou, China Correspondence should be addressed to Ayesha Mumtaz; ayeshamumtaz04@gmail.com Received 13 November 2021; Accepted 11 March 2022; Published 11 April 2022 Academic Editor: Ilker Ozsahin Copyright © 2022 Ayesha Mumtaz. (is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Rise in the aging population brings new challenges to modern societies. Old age is associated with several morbidities and usual issues related to health. (erefore, the provision of healthy and timely care has become the dire need to maintain their quality of life and wellbeing. (e evolution of the e-health care system put pressure on societies to implement it successfully to ensure a safe and prompt provision of care services to the most vulnerable population successfully. (erefore, the provision and imple- mentation of the e-health care system is a challenge for the health industry in terms of multi-objective decision-making. Multicriteria decision-making is a generalizable approach to making decisions with dependence and feedback and is known as an effective tool in decision-making processes, particularly in the healthcare sector. (e present study aims to present an e-healthcare framework by identifying and prioritizing potential barriers towards the use of e-health by the elderly population. (e analytical hierarchy process approach is adopted to calculate weights of identified potential barriers, respectively, and then rank them based on their degree of significance. (e findings show that health and the ability-related barrier is ranked highest, followed by socio- environmental and attitudinal barriers. (is research contributes to healthcare decision-making regarding e-health usage by implementing MCDA techniques. Our study will assist the public health practitioners and policymakers in drawing decisions on the best strategy to minimize the risks in using the e-healthcare system by the aging population, which significantly contributes to the smart healthcare system. [1]. Under these circumstances, the issues of elderly care 1.Introduction attract wide attention from scholars and policymakers, (e world enters a new stage of development under the resulting in a large amount of research done in this field. pressure of an aging population. Globally, the elderly (e use of e-health care systems by elderly people has population aged 65 exceeded 703 million [1]. (e number of already become a common trend worldwide [2]. To ensure older persons is projected to double to 1.5 billion in 2050. the promotion of a healthy society, the need for modern care Nevertheless, the awareness about the aging challenge is services has become a dire need of age, which is evidenced by sharp. While this sudden trend in the aging population the extensive e-healthcare requirements adopted during the towards old age is already prominent in high-income recent Covid-19 pandemic [3]. To improve the healthcare countries, for instance, in Japan, where 30% of the total system for elderly people, most of the developing countries population is already over 60years old. (us, the trends in are also growing their smart care industries and modern- the aging population in developing and, middle- or low- izing their health care settings [4]. (e elderly health care income countries are also in transition. It is being estimated industry is shifting from traditional family care to the smart that two-thirds of the population in the world aged 60 or care system to facilitate the elderly and their caregivers. over will live in low- and middle-income countries in 2050 Efficient use of technology is especially imperative in 2 Journal of Healthcare Engineering To help readers understand the context, the following creating a more independent and supportive living envi- ronment for older people [5], stimulate their physical and section identifies the various barriers identified by previous research studies as well as models for using e-healthcare psychosocial wellbeing, and enables them to feel more in- dependent at their daily chores [6], interact with their technology. (e previous researches have highlighted some families and friends [7], and to contribute to the elderly basic factors which provided a foundation to identify the healthcare sector. (e usage and adoption of e-health critical factors pertinent to e-health use. However, there is a technology have become an established research area tar- lack of research in concepts relevant to this study which are geting at investigating the influencing factors affecting the all aligned to provide a methodological base to this study. usage of e-health [8–10]. Research in this area mainly fo- (e primary research question addressed in this study is “what are the potential barriers affecting the use of the cused on developed countries [8, 11], while the experiences of developing countries are rarely discussed, particularly e-healthcare system by elderly people, and how can these barriers be prioritized pertinent to the old age group”? Based addressing the e-health care industry. Based on this, including the importance of e-healthcare on the review of the previous studies, 13 age-specific barriers were identified and categorized into main three categories. in the present era, the adhesion of elderly people to e-health acceptance, and the recognition that elderly people in (e literature review method is used in this study to identify Pakistan are less optimistic about using technology, we were the barriers of e-healthcare use. Next, Analytical hierarchal motivated to investigate this research gap. By keeping in process (AHP) decision-making analysis is used to allocate viewthe vulnerable situation of the e-health careindustry for weights to the main and sub-barriers by using the pairwise the elderly, and the lack of research in this area, the re- matrix technique [13]. (e study includes the MCDM searchers aimed to provide a foundation by conducting a methodology, findings, discussion, and conclusion in sub- sequent sections. pioneer research study. (e use of e-health among the el- derly is not a very common trend in Pakistan, and there is a lack of research in gerontechnology. However, the majority 2. Literature Review of the cities in Pakistan have telecommunication links and 531,787 broadband connections are provided to more than Previous research studies mainly based on the intention or 1800 cities and 400 cities have the facility of fiber optics in motivation to use technology [5, 14, 15],whereas, the research Pakistan, which gives them access to universal healthcare is scarce addressed the question of why older adults fail to use information to elderly and their families. (ere are orga- technology and what are the potential barriers? In this study, nizational barriers, lack of the interest of stakeholders, less e-health system is defined as the digital or electronic motivation from friends and family,anxiety to use and adopt healthcare products and services which increase the social technology and also healthcare professionals do not play independenceandparticipationofelderlypeoplerelativelyfor their role to promote the use of technology in Pakistan [12]. health purposes [16]. (e few researches that already have Given the scarcity of research on the technology usage sought to investigate the reasons for using or not using behavior of elderly people in Pakistan, we were motivated to technology have yielded somewhat contradictory results [17]. identify the barriers that influence the e-health usage be- Although researchers revealed that older people have a havior of elderly people. positive attitude towards technology [5, 18], hence they are Initially, a review of previous literature on the use of less likely to use those technologies due to some barriers as technology among the elderly has been conducted for this compared to young adults [19–21]. (ere are several reasons purpose. Further, a set of specific factors in different revealed by different studies for the use or nonuse of tech- domains were identified based on the previous research nology by elderly people. A study revealed that elderly people findings. By answering the research question and ob- have negative attitudes towards using technology due to the jective, the subsequent contributions are proposed. (e health risks, addiction to technological products, the gener- main contribution of this research to academia is the ation gap, safety issues, and social isolation [22]. Moreover, identification of the barriers to e-health care usage and social interaction is mentioned as one of the main reasons or detailed review of existing technology acceptance liter- motivation for using technology for elderly people as they ature. Research on gerontechnology is scarce and our think that interacting with other people is crucial for their study intends to provide a detailed examination of the wellbeing [23]. It has been discovered that social interactions barriers to the usage of e-healthcare. Furthermore, for the extend the social circles and help the elderly to meet new business sector, our research identifies factors to consider friends and make them easy to interact with the younger when promoting e-healthcare products and services. (e generation. Researchers mentioned that older people use elderly smart care industry is developing very fast in the technology to reduce their effort, to enhance their work, to whole world. (us, such research is critical for the elderly cope with their needs and problems, and to compensate for smart care industry, which is considering developing their physical weakness [5]. Mahmood et al. [23] conducted a smart technology products for its elderly consumer pilot study to explore the attitudes, preferences, and opinions market segment. Moreover, the methodological contri- of elderly people regarding the use of technology to extend bution of this study also provides new insights regarding and support their ability to “aging in place.” (e results show e-healthcare, with the application of AHP as a premise to that Safety and independence are also important factors for identify the less and more potential criteria for re- the elderly to use or nonuse of technology and they believe searchers and decision-makers. that the use of technology would significantly lead them to be Journal of Healthcare Engineering 3 acceptance and use of technology (UTAUT), which iden- safe and independent daily life [23]. Moreover, a qualitative study conducted to assess the usage of the patient portal by tified three direct predictors of usage intention, i.e., per- formance expectancy, effort expectancy, and social older patients with multiple chronic conditions shows that older people have the impression that usage of online portal influence, and two direct predictors of usage behavior saves time and money and give proper health information. (behavior intention and facilitating conditions), and also (e results also showed that older adults were more intent to added four moderators as gender, age, experience, and use online portals because of the convenience of the health voluntariness of use [30]. management system and perceived usefulness [21]. Literature (e purpose of the current research is to identify the list also found that elderly people have a positive attitude towards ofthe influencingindicatorsbyusing the Delphimethodand to apply the multiple criteria decision analysis to prioritize mobile technology but they are also concerned about some complex functions, such as, age, attention, and capability of the more or less potential barriers for the optimal solution to promote e-healthcare system usage among elderly people. processing speed are critical factors that affected their usage [2]. Gaita´n and colleagues reported that the technology usage We calculated priority weights of criteria and subcriteria by using AHP. the list of the main barriers and sub-barriers is behavior of elderly people is affected by habit, performance expectancy, price value, and effort expectancy [24]. Similarly, compiled by the review of the previous literature shown in they highlighted some reasons for the non-use of technology Table 1. Next, the research framework and results and byelderly people,such as;dispositional barriers,technological findings are discussed in subsequent sections. barriers, and situational barriers. For instance, forgetfulness is one of the dispositional barriers to the nonuse of technology 3. Research Framework and Methods by elderly people as they are easy to forget passwords of ATM etc.Healthandabilityconditions,likepoorvisionandhearing (e framework in this study provides an insight for the are also reported as the reasons for nonuse of technology [2]. healthcare providers and policymakers to closely observe Chen and Chan added the age related health and ability and tackle the barriers to e-health usage. (e research factors including; self-reported health conditions, functional framework of our study is shown in Figure 1, where the and cognitive abilities and attitude to ageing and life satis- DMAIC (define, measure, analyze, improve, and control) six faction as the predictors of technology usage of elderly people sigma tool is used to design the checklist consisting of the [19]. Moreover, negative self-evaluated beliefs (too old to use potential barriers regarding the e-healthcare system usage. technology), mental effort needed to operate advanced (DMAIC) is a data-driven strategy used to improve complex technologies, lack of interest, lack of time and assistance, processes. (is methodology is widely used in healthcare limited access to and exposure to technology, expense, research [31–34]. complexity, and safety are the reasons for nonuse of tech- (erewerefive stepsin DMAIC,the firststep isto define. nology by elderly people mentioned by several studies It is all about content validity which is done by reviewing the [5, 19, 20, 25–28]. (is suggests that use of e-health among previous literature. (e next step according to the DMAIC is elderly people is affected by several factors and generalizing the Measure “which means data collection here.” For our them may not be the solution or compensation mechanism study, we used the Delphi method to collect the required for all older people. data for this study. Delphi method is a widely used data (ere are several technology acceptances models and collection technique in multiple criteria decision-making theories that provided various factors predicting the usage, research [31, 35, 36]. (is method provides a systematic way acceptance, and adoption of the technology by older people. of getting the opinions from experts by using focused group In 1989, for the first time, Davis presented the technology discussions and questionnaires. (e whole data collection acceptance model to predict who is more likely to accept the was done in several steps. (e data was collected by dis- new technology, which was the adaptation of the two of the seminating the checklist to 10 experts in March 2021 and well-known theory of reasoned action presented by Fishbean getting the complete responses in April 2021. (ere was a and Ajzens in 1975, and the theory of planned behavior by total of 13 potential barriers in the checklist which were Ajzan in 1991. (e technology acceptance model issomehow compiled in 3 major categories presented in Table 2. After the adaptation of the theory of reasoned action which states identifying the potential barriers from the literature, the that beliefs determine the behavior intention of the user items were modified according to the Pakistani context. which determines the actual behavior. Hence, technology (en, the list was modified and verified by the group of acceptance behavior is different from the theory of planned experts again, to confirm whether the selected indicators are behavior as it states that the acceptance of technology is not favorable in the Pakistani context or not. solely dependent on the beliefs of the users. Venkatesh and (e next step in the DMAIC was “Analyze and improve” Davis in 2000, extended the technology acceptance model the model. Multi-criteria decision analysis is a generalizable known as TAM2, states that decision of the technology method for making decisions with dependencies and feedback adoption depends on the outcome of the evaluation of the [37]. Analytical hierarchy process (AHP) is a widely used perceived ease of use (difficulty in using technology), their technique in multiple criteria decision-making analysis, used beliefs on perceived usefulness (using technology will in- by our study to analyze the e-healthcare barriers. (is method crease their job performance), and subjective norms that has been used by researchers from diversified fields to simplify state the influence of the people who are important to them decision-making problems [38–42]. (e detailed description of [29]. In 2003, Venkatesh presented a new united theory of multiplecriteriadecisionanalysisandstepsoftheAHPmethod 4 Journal of Healthcare Engineering Table 1: Potential barriers to e-health usage system for the aging population. Main barriers Sub-barriers References Attitudinal (AD-1) Negative attitude towards using technology (AD-11) Lack of perceived usefulness (AD-12) [19–21, 24, 28] Lack of perceived Ease of use (AD-13) Negative attitude towards life and life satisfaction (AD-14) Socio-Environmental (SE-2) Insufficient facilitating conditions (SE-21) Negative subjective norm (SE-22) [23, 24, 30] Lack of social support (SE-23) Insufficient funds/Cost Tolerance (SE-24) Health and Ability (HA-3) Physical health (HA-31) Lack of psychological fitness (HA-32) Lack of cognitive ability (HE-33) [2, 22] [5, 19, 20] Lack of self-efficacy (HA-34) Suffering from anxiety (HA-35) DEFINE Literature review Identification of barriers MEASURE Delphi method Expert’s opinion Finalization of barriers Categorization of main barriers ANALYZE Categorization of sub-barriers MCDM (AHP) Approval of final I model IMPROVE Hierarchical structure of the Results and decision problem CONTROL discussion Pair-wise comparison Consistency index Consistency ratio Figure 1: Research framework operationalized in the study. Table 2: Estimated AHP weights for main and sub-barriers. Main barriers Main barriers weights Sub-barriers code Consistency ratio (CR) Priority weight Final weight Attitudinal (AD-1) 0.1061 AD-11 0.03 0.0688 0.007 AD-12 0.1725 0.018 AD-13 0.2314 0.025 AD-14 0.5357 0.057 Socio-Environmental (SE-2) 0.2604 SE-21 0.03 0.0986 0.026 SE-22 0.0922 0.024 SE-23 0.2477 0.065 SE-24 0.5666 0.148 Health and Ability (HA-3) 0.6334 HA-31 0.01 0.0535 0.034 HA-32 0.1077 0.068 HA-33 0.1046 0.066 HA-34 0.2509 0.159 HA-35 0.4833 0.306 Journal of Healthcare Engineering 5 (1) Step-I: Constructing Hierarchy. First of all, the problem are explained in the next section. Finally, the last step in the DMAIC framework contains “control” which is all about has to be structured into hierarchies with different layers defined as a goal, criteria, and alternatives. (e goal is the concluding results, keeping them verified, committing to improvement, and passing along best recommendations to main purpose of constructing the model. (e second level of future researchers. the hierarchy must be composed of some criteria based on whichthe researcherisgoing toevaluatethe alternatives.(e third important part or layer of hierarchy is the alternatives 3.1. Data Collection. Past studies used a different number of or the main areas of evaluation. (e respondents have to be experts to obtain reliable results for multiple criteria decision selecting the alternatives based on the given criteria. (e analysis; for example, Ikram et al. [43] used 10 experts to hierarchy can consist of many sub-criteria and alternatives. prioritize the barriers for integrated management assessment According to Saaty, the criteria for each dimension should using the MCDM method. Whereas, another study used 4 be mutually independent [13]. experts for MCDM analysis to develop a model to choose an appropriate Computerized Maintenance Management Sys- (2) Step-II: Deriving Weights or Priorities for the Criteria. tem (CMMS) for a dairy company [44]. For the current (e next step is to perform a pairwise comparison of the research, 10 experienced experts were selected to rank the respondents’ or experts’ judgments to determine the barriers and sub barriers. (e participants were from aca- comparative weights. (is step yields the ranked priorities demics from an aging research background, the healthcare for the alternatives under each criterion. Based on a sector, and policymakers. (ey were asked to prioritize the standard evaluation scheme, Saaty developed a scale for barriers based on their experts’ opinions and experiences. All pairwise comparisons. In this step, the components of a of the selected experts were having more than 10 years of certain level are compared with respect to a specific experience, and have some research background in the aging component in the direct upper level. (e consequential care and e-healthcare management system. weights of the components may be referred to as local weights. 3.2. Multiple Criteria Decision-Making (MCDM). MCDM is (3) Step-III: Calculating Priorities. (e judgment matrices a method of operational research that is commonly used to are then used to calculate the priorities. (e Eigenvalue solve decision problems [45]. MCDM enables assessment method is the method most commonly used by researchers and multiple expert judgments, and it is used to overcome for this step [49–51]. the presence of imprecision and ambiguity during the evaluation process [46]. Several MCDM techniques have (4) Step-IV: Model synthesis or Final Ranking. In this step, been discussed in the previous literature [37, 47]. However, the calculated priorities are combined or aggregated as a each technique has unique characteristics and applications. weighted sum to establish or obtain the overall ranking of (e analytic hierarchy process (AHP) method of MCDM is the best alternative. used in this study to identify potential barriers to e-health use among the aging population. (5) Step-V: Consistency. After getting the results, it is re- quired to check the consistency to verify the model. (e Saaty introduced the threshold of 10% or 0.01 as the ac- 3.2.1. Analytical Hierarchical Process (AHP). (e AHP is a ceptable inconsistencies in the data. AHP computes the theory of measurement proposed by Saaty [13]. AHP is consistency ratio (CR), by comparing the consistency index introduced to simplify the decision-making problems. (CI) ofthe matrixin question(with our evaluations) with the AHP aims to compute relative priorities for a specified set consistency index of a random matrix (RI). (e formula for of alternatives on a ratio scale which are centered on the the consistency check is given by Saaty as decisions of experts, firmly following the consistency CI standard of pairwise comparison in the process of decision- (1) CR � , RI making [48]. (e strong point of this method is that it provides a structured yet relatively simple solution and where organizes tangible and intangible factors in a logical way to λ − n max (2) the decision-making problems (Shen & Li, 2005). In this CI � . n − 1 study, the Analytical hierarchy process (AHP) is used to identify e-healthcare barriers. (is method is used because Here CI represents consistency index, and CR as con- of its unique utilization of a hierarchy structure to rep- sistency ratio, λ represents the biggest eigenvalue of the max resent a problem in the form of a goal, criteria, and al- pair-wise comparison matrix, n is the matrix order, and RI is ternatives [13]. AHP’s main components are pairwise a random index. If the value of CR is less than 10% then the comparisons, developing and comparing matrices, and matrix is considered as having an acceptable consistency. In ensuring their consistency. (is technique assists all de- some cases, 20% can also be acceptable but not more [13]. If cision-makers in selecting and ranking complex problems the CR does not lie within the given threshold or acceptable rationally. (e following steps are involved in the com- range then decision-makers have to be revised their putations of this method: judgments. 6 Journal of Healthcare Engineering Barriers and sub-barriers Negative attitude Insufficient facilitating Physical health towards technology use conditions (SE-21) (HA-31) (AD-11) Lack of perceived Negative subjective norm Lack of psychological usefulness (AD-12) (SE-22) fitness (HA-32) Lack of perceived Lack of social support Lack of cognitive ease of use (AD-13) (SE-23) ability (HA-33) Lack of self-efficacy Negative attitude towards life Insufficient funds/Cost and life satisfaction (HA-34) tolerance (SE-24) (AD-14) Suffering from anxiety (HA-35) Figure 2: Hierarchical structure of e-health management system barriers. weights by using a geometric mean. We used the group- 0.1061, 11% based decision-making approach to calculate the weights for the e-healthcare barriers and sub-barriers. For the MCDM analysis, we categorized sub-barriers into three main bar- riers, i.e., Attitudinal barriers, socio-environmental barriers, and health and ability barriers. (e weights were calculated for the 3 main barriers first and then for the sub-barriers. 0.2604, 26% Figure 2, shows the hierarchal structure of e-healthcare barriers and sub-barriers. Table 2 shows the results of the 0.6334, 63% AHP method. 4.1. Main Barriers. (e weights of each main barrier were calculated by using the AHP technique. (e results in Figure 3, show that ‘Health and ability’ are resulted to be the most potential barrier weighting (0.6334), followed by socio- Attitudinal (AD-1) environmental (0.2604), and attitudinal barrier (0.1061), Scio-environmental (SE-2) respectively. (ese barriers seem to be a challenge for Health and Ability (HA-3) implementing the e-healthcare system for the aging pop- Figure 3: Ranking of main barriers based on AHP. ulation. Sound health and ability constructs are the foremost barriers highlighted to be addressed to ensure the effective use of e-health among older adults. Manufacturers, poli- 4.Results and Discussion cymakers, and healthcare providers should focus on age- (is study aims to identify barriers to the use of the related health problems while framing and implementing e-healthcare system by elderly people, to better facilitate the e-healthcare technology. Socio-environmental and at- the future development of a digital healthcare system for the titudinal barriers are placed at second and third priorities by aging population. (e AHP method was used to calculate the the experts. To facilitate e-health use among the aging Attitudinal (AD-1) Scio-environmental (SE-2) Health and ability (HA-3) Journal of Healthcare Engineering 7 population, the manufacturers and policymakers should Negative Attitude towards Life and 0.5357 life satisfaction (AD-14) carefully prioritize the barriers as per their potential Lack of Perceived Ease of strengths and weaknesses. E-healthcare manufacturers 0.2314 Use (AD-13) should design the products in a manner that can overcome Lack of Perceived the barriers and construct an elderly user-friendly e-health 0.1725 usefulness (AD-12) technology system for more optimal outcomes while con- Negative Attitude towards 0.0688 sidering these potential barriers. Gerontechnologies should Using technology (AD-11) manufacture to facilitate the users without facing any 0 0.2 0.4 0.6 challenges. (ere is a need to accept the age-specific re- Figure 4: (e ranking order of attitudinal sub-barriers. quirements to better implement the use and to facilitate the e-health care system for elderly people. Finally, attitudinal characteristics are turned out as the least important barrier, positive attitude towards technology motivates the elderly to revealing that the use of e-health can be impacted by atti- accept and use e-health technology. Results are displayed in tudinal beliefs but with less intensity. Additionally, the 14 Figure 4. sub-barriers were assessed by using a pairwise comparisons matrix. 4.2.2. Socio-Environmental Sub-Barriers. (e ranking of the sub-barriers under the category of socio-environmental barrier is as follows: 4.2. Sub-barriers. (e detailed results of the sub-barriers are given as follows. SE − 24>SE − 23>SE − 21>SE − 22. (4) Insufficient funds (0.5666) have resulted as the greatest 4.2.1. Attitudinal Sub-Barriers. (e Attitudinal sub-barriers challenge for elderly people to use e-healthcare technology. are ranked as follows: (e findings show that the cost of e-health for the aging population shouldbeeconomical forbetter healthoutcomes. AD − 14>AD − 13>AD − 12>AD − 11. (3) (erefore, sufficient funds or cost tolerance would increase Negative attitude towards life and life satisfaction the use of e-health among elderly and the facilitate the smart appeared as the most potential sub-barrier (AD-14) of at- health care agenda of policymakers. Several studies have titudinal barrier with a weight of (0.53). (is ranking rep- considered the importance of the financial status, occupa- resents the reality that lack of life satisfaction leads older tion, and income, that may influence the technology usage adults towards isolation and increase depression and feeling behavior of elderly people [20, 55, 56]. Pakistan is a de- of social withdrawn. Such feelings may lead older towards veloping country and per capita income is relatively low as the lack of interest in technology and e-health system. (e compared with other developed countries [57], especially older people who have a low socio-economic background positive life satisfaction in older age depends on multiple factors, such as poverty, lack of income, poor health, and and are concerned with the costs of technological products and services. Hence, we may assume that Cost tolerance is a depression, as mentioned in a previous study [45, 52]. (e second sub-barrier is the lack of perceived ease of use among significant predictor of e-health usage behavior of elderly older adults (AD-13) with 0.2314 priority weight. Perceived people. ease of use is defined as “the degree to which a person Lack of social support is prioritized as the second po- believes that using a technology will be free from effort” tential sub-barrier (SE-23, 0.2477) under this category. El- (p.320). Previous studies maintained that perceived ease is derly people who suffer from social exclusion and lack of strongly associated with the use of technology among older social support from friends and family may have the least adults [21, 53]. User-friendly and effort-free e-healthcare interest in using e-health which affects their healthcare products encourage the use of e-health among older adults. access. A previous study also mentioned social interaction as the motivation for using technology for elderly people as Moreover, perceived usefulness is resulted to be the third influential sub-barrier (AD-12) under the category of atti- they think that interacting with other people is crucial for their wellbeing [23]. tudinal barrier with a weight of (0.1725). Perceived use- fulness is defined as “the extent to which a person believes Insufficient facilitating conditions are prioritized as the that using a particular technology will enhance his/her job third potential (SE-21, 0.0986) sub-barrier under the cate- performance” [54]. factors affecting technology usage gory of the socio-environmental barrier. Facilitating con- among older adults within the literature focus on the im- ditions are the environmental factors that support the usage portance of attitudinal factors, whereas some studies of technology by elderly people. Venketesh in 2003, pre- revealed that there is no significant effect of Perceived sented a united theory of technology acceptance (UTAUT) usefulness on the technology usage behavior of older adults and found the facilitating conditions as a direct predictor of [19, 20]. Further, a negative attitude towards using tech- technology usage behavior [30]. A study in India about the ICT usage behavior of elderly people revealed that facili- nology has appeared as the least important sub-barrier (AD- 11, 0.0688) of the Attitudinal barrier. Attitude towards using tating conditions are positively associated with technology technology is mainly used as a dependent variable in the usage [58]. Hence, a lack of facilitating conditions may affect previous studies, influence by several other factors [21]. A the successful promotion of e-health use. 8 Journal of Healthcare Engineering Insufficient funds /Cost Tolerance (SE-24) 0.5666 Lack of Social support (SE-23) 0.2477 Insufficient Facilitating conditions (SE-21) 0.0986 Negative Subjective Norm (SE-22) 0.0922 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Figure 5: (e ranking of socio-environmental sub-barriers. Suffering from Anxiety (HA-35) 0.4833 Lack of Self-Efficacy (HA-34) 0.2509 Lack of Psychological Fitness (HA-32) 0.1077 Lack of Cognitive Ability (HA-33) 0.1046 Physical Health (HA-31) 0.0535 0 0.1 0.2 0.3 0.4 0.5 0.6 Figure 6: (e ranking of health and ability sub-barriers. (e last sub-barrier under the socio-environmental older adults [20].Lack of cognitive ability is prioritized asthe barrier isthe negative subjective norm (SE-22) with(0.0922). third sub-barrier (HA-33) in this category with the weight of Subjective norm is defined here as the influence of the people (0.1046). A previous study stated the importance of cognitive abilities for older adults in using technology [14]. (e dif- who are important to the elderly [29]. Negative influence from peers and family may hinder access to e-health usage ference between (HA-33) and (HA-32) weights is 0.0031, and result in poor health care [59]. See Figure 5. which shows their almost equal importance for e-healthcare use among elderly people. psychological health factors are positively affecting the technology usage behavior of older 4.2.3. Health and Ability Barriers. Figure 6 shows the results people [19]. (e last sub-barrier under this category is of sub-barriers under the category of health and ability physical health with (0.0535) weight, showing its least im- barriers with the results as follows: portance in the use of e-health system. HA − 35>HA − 34>HA − 32>HA − 33>HA − 31. (5) 4.3. 5e Overall Ranking of Sub-Barriers. Figure 7, shows the Based on the expert’s opinion, anxiety is prioritized as overall ranking of all the sub-barriers by calculating the final the most potential sub-barrier (HA-35) with weight weights of all sub-barriers. (e calculations are done by (0.4833). Anxiety is defined as the individual hesitation using the weight of each sub-barrier and multiplying it by when he or she intends to use the system [60]. Chen and the weight of its respective main barrier. (e results of the Chan used anxiety in their senior technology acceptance ranking of overall sub-barriers are as follows: model and the results show that anxiety has a negative influence on the technology usage behavior of elderly people HA − 35>HE34>SE − 24>HA32>HE − 33>SE [20]. Hence, the proper guidelines and understanding of the − 23>AD − 14>HA − 31>SE − 21>AD − 13>SE healthcare system may help elderly people to reduce anxiety and increase their motivation towards the effective use of the − 22>AD − 12>AD − 11. e-health system. Furthermore, self-efficacy has resulted as a (6) second potential sub-barrier (HA-34, 0.2509) under the health and ability barriers. Self-efficacy is generally defined Anxiety is resulted to be the ranked first potential sub- as the person’s judgment of his or her ability to use the barrier with the weight (0.306) among all other, followed by system [45]. It has been declared as a potential factor in self-efficacy (0.159), insufficient funds (0.148), and lack of previous studies which affects the use of technology among psychological fitness (0.068). (e least three sub-barriers Journal of Healthcare Engineering 9 Suffering from Anxiety (HA-35) 0.306 Lack of Self-Efficacy (HA-34) 0.159 Insufficient funds /Cost Tolerance (SE-24) 0.148 Lack of Psychological Fitness (HA-32) 0.068 Lack of Cognitive Ability (HE-33) 0.066 Lack of Social support (SE-23) 0.065 Negative Attitude towards Life and life satisfaction (AD-14) 0.057 Physical Health (HA-31) 0.034 Insufficient Facilitating conditions (SE-21) 0.026 Lack of Perceived Ease of Use (AD-13) 0.025 Negative Subjective Norm (SE-22) 0.024 Lack of Perceived usefulness (AD-12) 0.018 Negative Attitude towards Using technology (AD-11) 0.007 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 Figure 7: (e overall ranking of sub-barriers. have resulted as a negative subjective norm (0.024), lack of the e-health system that plays a significant role in facilitating the smart health care industry for the aging population. perceived usefulness (0.018), and negative attitude towards technology (0.007) respectively. More importantly, this investigation facilitates researchers with an MCDA roadmap to help them enhance the quality of their studies and their understanding of how to use MCDA 5.Conclusion techniques to evaluate and prioritize the influencing factors affecting e-health use in healthcare research. (e need for tools that aid in decision-making occurs in a variety of healthcare settings and these tools are employed to Data Availability varying degrees in different settings [61]. In this study, we focus on the possibilities of using a specific multiple criteria (e data used to support the findings of this study are decision-making technique in ranking potential barriers for available from the corresponding author upon request. e-health use among elderly people. (e findings show that health and ability constructs are crucial to address while Conflicts of Interest encouraging the use of e-health system for elderly people. (e authors declare that they have no conflicts of interest. Our findings are vital to decision makers in the field of geriatrics and healthcare technology to focus on the age References related health and ability characteristics while introducing any innovation in an e-health system. [1] WHO, Ageing and Health, 2021, Retrieved from https://www. Since the identification of the potential barriers and sub- who.int/news-room/fact-sheets/detail/ageing-and-health. barriers is an innately complex system that cannot be [2] J. Li, Q. Ma, A. H. Chan, and S. S. Man, “Health monitoring represented using a single metric only, multidimensional through wearable technologies for older adults: smart wear- (MCDA) approaches are highly suggested to identify po- ables acceptance model,” Applied Ergonomics, vol. 75, tential risks. Hence, our study aimed to investigate the pp. 162–169, 2019. feasibility of employing the AHP approach to identify [3] T. R. Wind, M. Rijkeboer, G. Andersson, and H. Riper, “(e COVID-19 pandemic: (e ‘black swan’ for mental health care possible barriers to e-health use among older adults. (e and a turningpoint fore-health,”Internet interventions,p. 20, technique presented in this paper is quite simple. Any spreadsheet may be used to execute mathematical opera- [4] C. Ramprasad, L. Tamariz, J. Garcia-Barcena, Z. Nemeth, and tions, which is very important for small sample sizes. (e A. Palacio, “(e use of tablet technology by older adults in AHP technique may be successfully utilized in the healthcare health care settings—is it effective and satisfying? a systematic domain to analyze, compare, and identify the potential review and meta analysis,” Clinical Gerontologist, vol. 42, barriers, and to prioritize them according to their worst no. 1, pp. 17–26, 2019. scenarios, as shown in the studies and analyses presented [5] K. Chen and A. Chan, “Use or non-use of gerontechnology-A here. Utilizing the MCDA techniques in the present study qualitative study,” International Journal of Environmental will assist the public health practitioners and policymakers Research and Public Health, vol. 10, no. 10, pp. 4645–4666, in drawing decisions on the best way to minimize the risks in 2013. 10 Journal of Healthcare Engineering [6] E. M. Agree, “(e potential for technology to enhance in- [22] S. T.M. Peek, K. G. Luijkx,M. D. Rijnaardet al., “Older adults’ dependence for those aging with a disability,” Disability and reasons for using technology while aging in place,” Geron- health journal, vol. 7, no. 1, pp. S33–S39, 2014. tology, vol. 62, no. 2, pp. 226–237, 2016. [7] Q. Ma, K. Chen, A. H. S. Chan, and P.-L. Teh, “Acceptance of [23] A. Mahmood, T. Yamamoto, M. Lee, and C. Steggell, “Per- ICTs by older adults: A review of recent studies,” in Inter- ceptions and use of gerotechnology: Implications for aging in national Conference on Human Aspects of IT for the Aged place,” Journal of Housing for the Elderly, vol. 22, no. 1-2, pp. 104–126, 2008. Population, Springer, Cham, Switzerland, 2015. [8] S. J. Czaja, J. Sharit, C. C. Lee et al., “Factors influencing use of [24] J. A. Gaita´n, B. Peral Peral, and M. Ramo´n Jero´nimo, “El- derly and internet banking: An application of UTAUT2,” an e-health website in a community sample of older adults,” Journal of the American Medical Informatics Association, Journal of Internet Banking and Commerce, vol. 20, no. 1, vol. 20, no. 2, pp. 277–284, 2013. pp. 1–23, 2015. [9] R. Kampmeijer, M. Pavlova, M. Tambor, S. Golinowska, and [25] N.-H. Chen and S. C.-T. Huang, “Domestic technology W. Groot, “(e use of e-health and m-health tools in health adoption: comparison of innovation adoption models and promotion and primary prevention among older adults: a moderators,” Human Factors and Ergonomics in systematic literature review,” BMC Health Services Research, Manufacturing & Service Industries, vol. 26, no. 2, pp. 177– 190, 2016. vol. 16, no. 5, pp. 467–479, 2016. [10] J. Wilson, M. Heinsch, D. Betts, D. Booth, and F. Kay- [26] M. Hoque and G. Sorwar, “Factors influencing mHealth acceptance among elderly people in Bangladesh,” arXiv Lambkin, “Barriers and facilitators to the use of e-health by older adults: a scoping review,” BMC Public Health, vol. 21, preprint arXiv:1606.00874, 2016. [27] B. Klimova, I. Simonova, P. Poulova, Z. Truhlarova, and no. 1, pp. 1–12, 2021. [11] H. J. (ompson, G. Demiris, T. Rue et al., “A Holistic ap- K. Kuca, “Older people and their attitude to the use of in- proach to assess older adults’ wellness using e-health tech- formation and communication technologies–a review study nologies,” Telemedicine and e-Health, vol. 17, no. 10, with special focus on the Czech Republic (Older people and pp. 794–800, 2011. their attitude to ICT),” Educational Gerontology, vol. 42, no. 5, [12] Q. A. Qureshi, B. Shah, A. Nawaz, I. Khan, M. Waseem, and pp. 361–369, 2016. F. Muhammad, “E-health in Pakistan: issues and prospects,” [28] Q. Li and Y. Luximon, “Understanding older adults’ post- adoption usage behavior and perceptions of mobile tech- Journal of Biology, Agriculture and Healthcare, vol. 4, no. 17, pp. 106–115, 2014. nology,” International Journal of Design, vol. 12, no. 3, [13] T. L. Saaty, “Decision making with the analytic hierarchy pp. 93–110, 2018. process,” International Journal of Services Sciences, vol. 1, [29] V. Venkatesh and F. D. Davis, “A theoretical extension of the no. 1, pp. 83–98, 2008. technology acceptance model: four longitudinal field studies,” [14] S. J. Czaja, N. Charness, A. D. Fisk et al., “Factors predicting Management Science, vol. 46, no. 2, pp. 186–204, 2000. the use of technology: findings from the center for research [30] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, and education on aging and technology enhancement “User acceptance of information technology: toward a unified (CREATE),” Psychology and Aging, vol. 21, no. 2, pp. 333–352, view,” MIS Quarterly, vol. 27, no. 3, pp. 425–478, 2003. [31] N. Aydin and S. Seker, “Determining the location of isolation [15] L. Dogruel, S. Joeckel, and N. D. Bowman, “(e use and hospitals for COVID-19 via Delphi-based MCDM method,” acceptance of new media entertainment technology by elderly International Journal of Intelligent Systems, vol. 36, no. 6, users: development of an expanded technology acceptance pp. 3011–3034, 2021. model,” Behaviour & Information Technology, vol. 34, no. 11, [32] G. Cesarelli, R. Petrelli, C. Ricciardi et al., “Reducing the pp. 1052–1063, 2015. healthcare-associated infections in a rehabilitation hospital [16] D. Hallberg and N. Salimi, “Qualitative and quantitative under the guidance of lean six sigma and DMAIC,” analysis of definitions of e-health and m-health,” Healthcare Healthcare (Basel), vol. 9, no. 12, p. 1667, 2021. informatics research, vol. 26, no. 2, pp. 119–128, 2020. [33] A. M. Ponsiglione, C. Ricciardi, A. Scala et al., “Application of [17] M. D. C. Miranda-Duro, L. Nieto-Riveiro, P. Concheiro- DMAIC cycle and modeling as tools for health technology Moscoso et al., “Occupational therapy and the use of tech- assessment in a university hospital,” Journal of healthcare nology on older adult fall prevention: A scoping review,” engineering, vol. 2021, 2021. International Journal of Environmental Research and Public [34] C. Ricciardi, A. Gubitosi, D. Vecchione et al., “Comparing two Health, vol. 18, no. 2, p. 702, 2021. approaches for thyroidectomy: a health technology assess- [18] Q. Ma, A. H. S. Chan, and K. Chen, “Personal and other factors ment through DMAIC cycle,” Healthcare (Basel), vol. 10, affecting acceptance of smartphone technology by older Chi- no. 1, p. 124, 2022. nese adults,” Applied Ergonomics, vol. 54, pp. 62–71, 2016. [35] S. Bid and G. Siddique, “Human risk assessment of Panchet [19] K. Chen and A. H. S. Chan, “Predictors of gerontechnology dam in India using TOPSIS and WASPAS multi-criteria acceptance by older Hong Kong Chinese,” Technovation, decision-making (MCDM) methods,” Heliyon, vol. 5, no. 6, vol. 34, no. 2, pp. 126–135, 2014. Article ID e01956, 2019. [36] Y. R. Lim, A. S. Ariffin, M. Ali, and K.-L. Chang, “A hybrid [20] K. Chen and A. H. S. Chan, “Gerontechnology acceptance by elderly Hong Kong Chinese: A senior technology acceptance MCDM model for live-streamer selection via the fuzzy delphi model(STAM),” Ergonomics,vol. 57,no. 5, pp.635–652, 2014. method, AHP, and TOPSIS,” Applied Sciences, vol. 11, no. 19, [21] J. D. Portz, E. A. Bayliss, S. Bull et al., “Using the technology p. 9322, 2021. acceptance model to explore user experience, intent to use, [37] S. Rehman, E. Rehman, I. Hussain, and Z. Jianglin, “Socio- and use behavior of a patient portal among older adults with economic influence on cardiac mortality in the south asian multiple chronic conditions: descriptive qualitative study,” region: new perspectives from grey modeling and G-TOPSIS,” Journal of Medical Internet Research, vol. 21, no. 4, Article ID Journal of healthcare engineering, vol. 2021, Article ID e11604, 2019. 6866246, 2021. Journal of Healthcare Engineering 11 [38] Y. Liu, C. M. Eckert, and C. Earl, “A review of fuzzy AHP [53] M. J. S. Diño and A. B. de Guzman, “Using partial least methods for decision-making with subjective judgements,” squares (PLS) in predicting behavioral intention for telehealth use among Filipino elderly,” Educational Gerontology, vol. 41, Expert Systems with Applications, vol. 161, Article ID 113738, no. 1, pp. 53–68, 2015. [54] F. D. Davis, “Perceived usefulness, perceived ease of use, and [39] H.-M. Lyu, W.-H. Zhou, S.-L. Shen, and A.-N. Zhou, “In- user acceptance of information technology,” MIS Quarterly, undation risk assessment of metro system using AHP and vol. 13, no. 3, pp. 319–340, 1989. TFN-AHP in Shenzhen,” Sustainable Cities and Society, [55] A. Alam, M. Ibrar, and P. Khan, “Socio-economic and psy- vol. 56, Article ID 102103, 2020. chological problems of the senior citizens of Pakistan,” [40] M. Mathew, R. K. Chakrabortty, and M. J. Ryan, “A novel Peshawar Journal of Psychology and Behavioral Sciences approach integrating AHP and TOPSIS under spherical fuzzy (PJPBS), vol. 2, no. 2, pp. 249–261, 2016. sets for advanced manufacturing system selection,” Engi- [56] F. Manzoor, L. Wei, A. Hussain, M. Asif, and S. I. A. Shah, neering Applications of Artificial Intelligence, vol. 96, Article “Patient satisfaction with health care services; an application ID 103988, 2020. of physician’s behavior as a moderator,” International Journal [41] U. F. Sahibzada, K. F. Latif, Y. Xu, and R. Khalid, “Catalyzing of Environmental Research and Public Health, vol. 16, no. 18, knowledgemanagementprocessestowardsknowledgeworker p. 3318, 2019 Retrieved from https://www.mdpi.com/1660- satisfaction: fuzzy-set qualitative comparative analysis,” 4601/16/18/3318. Journal of Knowledge Management, vol. 24, no. 10, 2020. [57] F. Manzoor, L. Wei, and M. Siraj, “Small and medium-sized [42] U. F. Sahibzada, Y. Xu, G. Afshan, and R. Khalid, “Knowl- enterprises and economic growth in Pakistan: an ARDL edge-oriented leadership towards organizational perfor- bounds cointegration approach,” Heliyon, vol. 7, no. 2, Article mance: symmetrical and asymmetrical approach,” Business ID e06340, 2021. Process Management Journal, vol. 27, no. 6, 2021. [58] A. Pargaonkar, W. Mishra, and S. Kadam, “A study on elderly [43] M. Ikram, Q. Zhang, and R. Sroufe, “Developing integrated individuals’ attitude towards,” in Research into Design for a management systemsusing an AHP-Fuzzy VIKORapproach,” Connected World, pp. 723–734, Springer, 2019. Business Strategy and the Environment, vol. 29, pp. 2265– [59] H.-Y. Yan and M.-J. Wang, “What factors affect physicians’ 2283, 2020. decisions to use an e-health care system?” 2012. [44] A. Zare, M. Feylizadeh, A. Mahmoudi, and S. Liu, “Suitable [60] X. Xu, F. Manzoor, S. Jiang, and A. Mumtaz, “Unpacking the computerized maintenance management system selection mental health of nurses during COVID-19: evidence from using grey group TOPSIS and fuzzy group VIKOR: a case Pakistan,” Journal of Clinical Medicine, vol.10, no.16, p. 3546, study,” Decision Science Letters, vol. 7, no. 4, pp. 341–358, 2021, Retrieved from https://www.mdpi.com/2077-0383/10/ 16/3546. [45] A. Mumtaz, F. Manzoor, S. Jiang, and M. Anisur Rahaman, [61] S. Rehman, N. Rehman, M. Naz, A. Mumtaz, and Z. Jianglin, “COVID-19 and mental health: A study of stress, resilience, “Application of grey-based SWARA and COPRAS techniques and depression among the older population in Pakistan,” in disease mortality risk assessment,” Journal of healthcare Healthcare, vol. 9, no. 4, p. 424, 2021 Retrieved from https:// engineering, vol. 2021, Article ID 7302157, 2021. www.mdpi.com/2227-9032/9/4/424. [46] S. Rehman, E. Rehman, A. Mumtaz, and Z. Jianglin, “A multicriteria decision-making approach in exploring the nexus between wind and solar energy generation, economic development, fossil fuel consumption, and CO2 emissions,” Frontiers in Environmental Science, vol. 659, 2022. [47] A. Mumtaz, E. Rehman, S. Rehman, and I. Hussain, “Impact of environmental degradation on human health: an assess- ment using multicriteria decision making,” Frontiers in Public Health, vol. 9, Article ID 812743, 2022. [48] I. Syamsuddin and J. Hwang, “A new fuzzy MCDM frame- work to evaluate e-government security strategy,” in Pro- ceedings of the 2010 4th International Conference on Application of Information and Communication Technologies, pp. 1–5, IEEE, Tashkent, Uzbekistan, October 2010. [49] M. I. Al Khalil, “Selecting the appropriate project delivery method using AHP,” International Journal of Project Man- agement, vol. 20, no. 6, pp. 469–474, 2002. [50] D. H. Byun, “(e AHP approach for selecting an automobile purchase model,” Information & Management, vol. 38, no. 5, pp. 289–297, 2001. [51] A. E. Ezzat and H. S. Hamoud, “Analytic hierarchy process as module for productivity evaluation and decision-making of the operation theater,” Avicenna Journal of Medicine, vol. 6, no. 1, pp. 3–7, 2016. [52] S. S. Celik, Y. Celik, N. Hikmet, and M. M. Khan, “Factors affecting life satisfaction of older adults in Turkey,” 5e In- ternational Journal of Aging and Human Development, vol. 87, no. 4, pp. 392–414, 2018.

Journal

Journal of Healthcare EngineeringHindawi Publishing Corporation

Published: Apr 11, 2022

There are no references for this article.