Background: Information and communication technology (ICT) offers considerable potential for supporting older adults in managing their health, including chronic diseases. However, there are mixed opinions about the benefits and effectiveness of ICT interventions for older adults with chronic diseases.
Objective: We aim to map the use of ICT interventions in health care and identified barriers to and enablers of its use among older adults with chronic disease.
Methods: A scoping review was conducted using 5 databases (Ovid MEDLINE, Embase, Scopus, PsycINFO, and ProQuest) to identify eligible articles from January 2000 to July 2020. Publications incorporating the use of ICT interventions, otherwise known as eHealth, such as mobile health, telehealth and telemedicine, decision support systems, electronic health records, and remote monitoring in people aged ≥55 years with chronic diseases were included. We conducted a strengths, weaknesses, opportunities, and threats framework analysis to explore the implied enablers of and barriers to the use of ICT interventions.
Results: Of the 1149 identified articles, 31 (2.7%; n=4185 participants) met the inclusion criteria. Of the 31 articles, 5 (16%) mentioned the use of various eHealth interventions. A range of technologies was reported, including mobile health (8/31, 26%), telehealth (7/31, 23%), electronic health record (2/31, 6%), and mixed ICT interventions (14/31, 45%). Various chronic diseases affecting older adults were identified, including congestive heart failure (9/31, 29%), diabetes (7/31, 23%), chronic respiratory disease (6/31, 19%), and mental health disorders (8/31, 26%). ICT interventions were all designed to help people self-manage chronic diseases and demonstrated positive effects. However, patient-related and health care provider–related challenges, in integrating ICT interventions in routine practice, were identified. Barriers to using ICT interventions in older adults included knowledge gaps, a lack of willingness to adopt new skills, and reluctance to use technologies. Implementation challenges related to ICT interventions such as slow internet connectivity and lack of an appropriate reimbursement policy were reported. Advantages of using ICT interventions include their nonpharmacological nature, provision of health education, encouragement for continued physical activity, and maintenance of a healthy diet. Participants reported that the use of ICT was a fun and effective way of increasing their motivation and supporting self-management tasks. It gave them reassurance and peace of mind by promoting a sense of security and reducing anxiety.
Conclusions: ICT interventions have the potential to support the care of older adults with chronic diseases. However, they have not been effectively integrated with routine health care. There is a need to improve awareness and education about ICT interventions among those who could benefit from them, including older adults, caregivers, and health care providers. More sustainable funding is required to promote the adoption of ICT interventions. We recommend involving clinicians and caregivers at the time of designing ICT interventions.
Chronic diseases represent a significant public health challenge worldwide and are the predominant cause of death among older adults . Older adults are also vulnerable to occupational injuries arising from the effects of chemical, physical, and biological exposure in the workplace. In 2016, approximately 70% of deaths and 40% of disability-adjusted life years because of occupational injuries occurred in persons aged ≥55 years [ ]. The burden of chronic diseases such as cardiovascular diseases (CVDs), diabetes, neurological disorders, and musculoskeletal disorders falls heavily on older adults [ ]. The population aged ≥60 years is expected to increase to 2 billion by 2050 worldwide [ ]. Consequently, the global burden of chronic diseases among older adults is anticipated to rise [ , ]. Given the increasing prevalence of aging and chronic diseases, it is essential to focus on health care innovation to improve personal health services such as self-management. Self-management is based on the concept that people can learn to manage their health using their skills and resources and thus become less dependent on external agents [ ].
Information and communication technology (ICT) has been used in several settings to help individuals diagnose, treat, and manage chronic diseases better . ICT interventions in health care, which we define herein as eHealth, have been shown to be cost-effective for monitoring and controlling congestive heart failure, stroke, chronic obstructive pulmonary disorder (COPD), diabetes, hypertension, asthma, dementia, and depression [ - ]. ICT interventions have also been used to support caregivers [ ]. For example, mobile health (mHealth) has the potential to reduce the caregiver’s work burden by supporting the monitoring of medication use and providing significant interaction with older adults, thus minimizing the need for hospitalization [ ]. Hence, ICT interventions may provide a solution to some of the challenges of aging and chronic diseases. However, there is conflicting evidence regarding the effectiveness of using ICT interventions among older adults with chronic diseases. Some positive outcomes have been identified for simple telephone interventions [ ], which in some cases generated similar outcomes to more complex technologies [ - ]. As per suggestions made by other authors, there are opportunities to explore and compare perceptions among direct service providers, older adults living with chronic diseases, and caregivers about the challenges of various types of ICT interventions in both high- and low-income countries [ - ]. Therefore, there is a strong impetus for exploring the efficacy of ICT interventions and how this effectiveness differs in various settings.
The current high use of ICT among young people shows that ICT could be a future intervention model in health care, enhancing the number of people in need who are reached . However, the approach of older adults to internet and health technology differs from that of younger people. Older adults may have lower rates of computer use and health-related internet use than younger adults [ ]. Indeed, Heart et al [ ] found that older adults require some skills to adopt the use of ICT interventions. Older adults with chronic diseases have also been reported to face numerous challenges such as altered cognition, visual and hearing difficulties, lack of trust, and privacy concerns as they encounter technology [ , ]. Without adopting these skills and addressing barriers, older adults might not receive the optimal benefits of ICT interventions in routine care. Hence, there is a critical need to better understand and map the barriers associated with the use of ICT interventions among older adults with chronic diseases to maximize the future uptake of ICT interventions and support personalized health care [ ]. It is also essential to identify enablers of the use of ICT interventions so as to facilitate the design of mitigating strategies to overcome the barriers to use. Most ICT interventions described in the literature have targeted children, adolescents, or younger adults. We are not aware of any previous systematic or scoping review of the enablers of and barriers to the adoption of ICT interventions for supporting older adults with chronic diseases.
In this review, we aim to identify (1) the available ICT interventions that have been used for managing older adults with chronic diseases and (2) the barriers to and enablers of using ICT interventions among older adults with chronic diseases.
This scoping review was conducted using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews) guidelines  and adopting the Arksey and O’Malley [ ] framework. This framework outlines five stages for completing a scoping review: (1) identifying the research question; (2) identifying relevant published reports; (3) publication selection; (4) charting the data; and (5) collating, summarizing, and reporting the results [ ], all of which have been followed in the conduct of this review.
Database Selection and Search Strategy
A literature search was performed using 4 databases: Ovid MEDLINE, Embase, Scopus, and PsycINFO. We also used the ProQuest database to include eligible papers and proceedings published in association with computer science and technology conferences. We included articles and conference papers published from January 2000 to July 2020, which had full text in English and were peer reviewed. We selected the time frame of the past 2 decades to identify recent work undertaken on ICT interventions among older adults with chronic diseases. The population of older adults with chronic diseases could benefit from targeted health education interventions. We defined older adults as those ≥aged 55 years , so only studies with this definition were included. The search strategies were drafted through team discussions and checked and revised by an experienced librarian. We used the following search terms: information and communication technology or mHealth or mobile health or telehealth or eHealth or remote monitoring or clinical decision support system or mobile phone technology or electronic health record and arthritis or asthma or back pain or carcinoma or cardiovascular disease or chronic obstructive pulmonary disease or diabetes or mental health or non-communicable diseases or chronic diseases and ageing or elderly or older adults or 55+ age group and barriers or enablers or challenges or opportunities or benefits or threats. We included eight major groups of chronic diseases in the review: arthritis, asthma, back pain, cancer, CVDs, COPD, diabetes, and mental health conditions. contains the search strategies and Boolean expressions for each database.
A total of 2 reviewers (SBZ and RKK) screened the titles and abstracts of the selected articles and identified duplicates. In cases of conflicting opinions regarding the eligibility of specific articles, the reviewers discussed their views with a third reviewer (SMSI) to reach a consensus. If inclusion was unclear from the title, the abstract was screened. Similarly, if inclusion was unclear from the abstract, the reviewer read the full text. We included original articles, all types of reviews, and conference papers () for this scoping review. Once we identified suitable articles, we also looked for qualitative data included in the analysis. Here, we particularly looked for specific information related to barriers, enablers, and uses of ICT for supporting the care of older adults with chronic disease.
ICT Types and End Users
Our definition of ICT interventions in health care, otherwise known as eHealth, includes the following: mHealth, electronic health records (EHRs), clinical decision support systems (CDSSs), telehealth and telemedicine, virtual reality in health care, and information technology systems used in health care settings. mHealth includes the use of mobile phones, mobile apps, PDAs, and PDA phones (eg, smartphones and handheld and ultraportable computers such as tablet devices) . Telemedicine and telehealth are considered subdomains of eHealth and comprise communication networks to deliver health care interventions from one geographical location to another [ ]. A remote monitoring system is defined as a subset of mHealth and telemedicine, which uses sensors to generate patient data.
We use the following ICT terminology in this paper:
- ICT device: refers to hardware only
- ICT intervention: refers to a specific program of research or implementation of ICT (eg, computer, mobile phone or tablet apps, and telehealth)
We considered older adults living with chronic diseases, their caregivers or family members, and health care providers as end users of ICT interventions.
Data Extraction and Synthesis
SBZ, RK, and SMSI developed a data extraction form based on the aims of this review. SBZ and RK extracted data on the article title, names of first authors, publication year, study types or methods, setting, sample size, findings or recommendations, and expected or experienced barriers for all selected articles. Outcomes related to the use of ICT interventions were presented as positive, no difference or negative based on the conclusion reported in the included articles. No negative or neutral (no difference) outcomes were identified. In the case of qualitative data, factors related to barriers and enablers were coded in the data extraction form according to themes that emerged from the studies.
Second, we described and identified various ICT interventions—mHealth, EHR and CDSS, telemedicine, and remote monitoring—that were used for older adults with chronic diseases. Third, we reviewed articles to identify challenges in using ICT interventions among older adults with chronic diseases. For example, factors such as lack of motivation, comorbidities, poor adherence to treatment following ICT interventions, and absence of prior experience in the operation of ICT devices for older adults were considered as challenges. Issues related to costs of implementation, infrastructure, data security, and delays in making a decision were considered in the implementation category. Finally, we conducted a strengths, weaknesses, opportunities, and threats (SWOT)  analysis to explore the enablers of and barriers to the use of ICT interventions among older adults with chronic diseases. We used a codebook for the domains of strength, weakness, opportunity, and threat to report a descriptive analysis. Before this qualitative analysis, strategies for data coding were identified. SBZ and RK independently read and coded the articles. Each of the domains of SWOT was grouped into two categories: patient-related factors (operational) or health care provider–related factors. The patient-related category included factors associated with ICT interventions, which we define as operational here. We then applied this conceptual framework to identify emerging themes in each of these categories from the selected articles. Codes were then grouped into categories and eventually aggregated into 4 domains. After the initial round of coding, the 2 coders met with a senior researcher (SMSI) to cross-check the coding; thus, a final set of codes was agreed upon. The reviewers used Microsoft Excel 2014 to sort the articles.
A total of 1149 articles, including conference papers (863/1149, 75.12%), were identified. Of the 1149 articles, 44 (3.83%) were duplicates (). We excluded 86.51% (994/1149) of articles that were either not related to ICT interventions for older adults with chronic diseases or studies already reported in the systematic reviews that we included. Of the 1149 articles, after screening the titles and abstracts, 46 (4%) additional articles were excluded, leaving 63 (5.48%) articles for full-text screening. Of the 63 articles, there were 4 (6%) conference papers that were mostly based on formative research (design and development). As these papers lacked both quantitative and qualitative data (patient recruitment and barriers to and enablers of using ICT), we did not include them in the final selection. Finally, of the 63 articles, 26 (41%) were excluded following a full-text review, with 31 (49%) articles remaining ( ).
Characteristics of Articles Included in the Review
The characteristics of the included articles are presented in. Of the 31 included papers (total number of participants, n=4185), 2 (6%) were randomized controlled trials (RCTs) [ , ], 10 (32%) described non-RCT design intervention studies [ - ], and 13 (42%) were review articles [ - ]. These 13 review articles comprised 4 (31%) systematic reviews [ , , , ] and 2 (15%) scoping reviews [ , ]. In addition, 19% (6/31) were conference papers that described cross-sectional studies [ - ] ( ).
|Study||Country||Study design or type of article||ICTa|
|Instrument||Sample or articles||Target condition||Findings or|
|Limitations or challenges of ICT interventions|
|Miguel et al, 2013 ||Australia||RCTb (6-month study period)||Telehealth intervention||Face-to-face interviews||80||COPDc|
|Barbera et al, 2018 ||Finland, France, and the Netherlands||RCT||Internet-based approaches||N/Ad||2725||Dementia, CHFe, DMf, and dyslipidemia|
|Barron et al, 2014 ||United States||Qualitative||Patient portal (EHRg)||Cognitive walkthrough||14||COPD and CHF|
|Bhattarai et al, 2020 ||Australia||Qualitative||App for self-management of pain||Semistructured interviews||6||Arthritic pain|
|Chang et al, 2017 ||Taiwan||Qualitative||Telehealth||Semistructured (technology acceptance model)||18||DM|
|Coley et al, 2019 ||Finland, France, and the Netherlands||Mixed||eHealth intervention or internet counseling||Web-based questionnaire and semistructured interviews||343||CVDsh and diabetes|
|Kim et al, 2019 ||United States||Mixed||Telehealth||Web-based surveys and in-depth interviews||20||Depression care|
|Zettel-Watson et al, 2016 ||United States||Cross-sectional- exploratory study||Web-based health management tools||Web-based survey||169||Chronic diseases|
|Lee et al, 2016 ||United States||Pilot study||Android tablet with an installed app||A mobile-based health technology intervention||18||CVDs and CHF|
|Mirza et al, 2008 ||New Zealand||Pilot study (qualitative nature)||mHealth initiative (through SMS text messaging)||Semistructured interviews||18||Diabetes and heart disease|
|Radhakrishnan et al, 2016 ||United States||Qualitative||Telehealth||Semistructured interviews||23||Cardiac disease, pulmonary disease, and DM|
|Nymberg et al, 2019 ||Sweden||Qualitative||eHealth (EMRj, telehealth, and mHealth)||Focus group interviews||15||Hypertension, diabetes, and COPD|
|Rocha et al, 2019 ||N/A||Systematic review||mHealth||A systematic review of reviews and meta-analyses||66 reviews||DM, mental illness, cancer, COPD, and CVDs|
|Searcy et al, 2019 ||N/A||Narrative review||mHealth technologies||—l||—||CVDs|
|Peek ST et al, 2014 ||N/A||Systematic review||Electronic technologies||—||16 articles||Chronic diseases|
|Vollenbroek-Hutten et al, 2017 ||N/A||Narrative review||Various ICT platforms||—||673||Chronic pain, COPD|
|Wildenbos et al, 2018 ||N/A||Scoping review||mHealth||Framework analysis||—||Chronic diseases|
|Blass et al, 2006 ||United States||Narrative||Telehealth||Ethics and public policy (ethical challenges)||—||Physical or psychiatric illness|
|Bostrom et al, 2020 ||N/A||Narrative review||Various mHealth technology||mHealth cardiac rehabilitation||—||CVD, hypertension, arrhythmia, and CHF|
|Christensen et al, 2020 ||N/A||Systematic review||Video consultations||Different survey instruments||21 studies||Mental health practice (unipolar depression)|
|Gilbert et al, 2015 ||United States||Narrative||Gerontechnology: mHealth||Applications of gerontechnology by stakeholders||—||Chronic diseases|
|Henriquez-Camacho et al, 2014 ||N/A||Narrative review||eHealth technologies||Problems related to age and technology||—||Chronic diseases|
|Harerimana et al, 2019 ||N/A||Systematic review||Telehealth interventions||Users’ perceptions of a telehealth intervention||13 articles||Chronic diseases|
|Jimison et al, 2008 ||N/A||Narrative review||Health IT||Barriers and drivers to the use of health IT||129 articles||Chronic diseases|
|Matthew-Maich et al, 2016 ||N/A||Scoping review||mHealth||Designing, implementing, and evaluating mHealth technologies||42 articles||Chronic diseases|
|D’Haeseleer et al, 2019 ||Italy||Conference paper||Various ICT platforms for self-monitoring services||Focus group interview||12||Chronic diseases|
|Hosseinpour et al, 2019 ||Iran||Conference paper||Telecare||Medical records||38||Acute coronary syndrome|
|Lorenz et al, 2007 ||Germany||Conference paper||mHealth||Semistructured interviews||8||Chronic diseases|
|Pikna et al, 2018 ||Slovakia||Conference paper||ICT||Semistructured interviews||5||Chronic diseases|
|Termeh et al, 2015 ||Iran||Conference paper||Smart-watches and sensors||Implementation of a U-Healthm system||—||Heart failure and arterial fibrillation|
|Wang et al, 2018 ||United States||Conference paper||ICT||Semistructured interviews||12||Chronic diseases|
aICT: information and communication technology.
bRCT: randomized controlled trial.
cCOPD: chronic obstructive pulmonary disorder.
dN/A: not applicable.
eCHF: chronic heart failure.
fDM: diabetes mellitus.
gEHR: electronic health record.
hCVD: cardiovascular disease.
imHealth: mobile health.
jEMR: electronic medical record.
kIT: information technology.
mU-Health: ubiquitous health.
In total, the systematic reviews used in the current synthesis included 122 independent studies. We did not include studies already reported in the systematic reviews as individual studies to avoid duplication. Clinical trial intervention studies (RCTs and non-RCTs) were conducted in Finland, France, the Netherlands [, ], Taiwan [ ], the United States [ , - , , ], Australia [ , ], New Zealand [ ], Germany [ ], Slovakia [ ], Italy [ ], and Sweden [ ]. Except for Iran [ , ], no studies were conducted in low- to middle-income countries (LMICs). Most of the studies, except 1 [ ], were pilot studies or short-term interventions. Original articles were either qualitative [ - ] or used mixed methods [ , ]. Various methods were used to measure the outcome of interest, including cognitive walk-throughs [ ], semistructured interviews [ , , - , , , ], in-depth interviews [ ], focus groups [ , ], and web-based surveys [ - ]. The Technology Acceptance Model [ ] and the Unified Theory of Acceptance and Use of Technology Model [ ] were also used to assess the feasibility of ICT interventions in 2 studies.
ICT Interventions Used in Health Care
All articles provided evidence that ICT interventions are beneficial for health care among older adults with chronic diseases (). We identified various ICT platforms used for supporting health care providers as they manage chronic diseases in older adults. A total of 3 studies and 2 reviews mentioned the use of ≥1 mixed eHealth intervention such as electronic technologies, internet counseling, video consultation, EHR, and telehealth [ , , , , ]. A total of 3 studies and 5 reviews, including 2 scoping reviews, focused particularly on mHealth [ , , , , , , ], including mobile apps [ , ]. A total of 4 studies and 2 reviews focused on telehealth [ , , , , , ]. One study specifically focused on the use of a patient portal or EHR [ ]. One study was on a web-based health management tool [ ] for chronic care. Finally, 7 further reviews incorporated the use of a combination of ICT interventions [ , , ], including EHR, mHealth, and video consultation, in providing care for older adults with chronic diseases. shows the distribution of ICT interventions that have been primarily used or described in the included original articles or reviews.
All the included articles reported a positive outcome for supporting the management of chronic diseases such as CVDs (eg, chronic heart failure, atrial fibrillation, and hypertension) [, , - , , ], diabetes [ , , , - ], COPD [ , , - , ], dyslipidemia [ ], arthritic pain [ , ], mental illness including depression and dementia [ , , , , ], and cancer [ ]. Thus, there were no reports of neutral or negative effects that might underdetermine the use of ICT interventions.
Challenges to and Enablers of Implementing ICT Interventions in Health Care
[ - , - ] describes the primary SWOT assessment outcomes.
In many cases, identified in 48% (15/31) of articles, participants reported that the use of an ICT intervention was a fun or effective way for improving health [, , , - , - , , , , ] by increasing their motivation and supporting self-management tasks [ , - , , - , - , , - ]. Approximately 48% (15/31) of articles identified that patients were frequently satisfied with using 1 or a combination of ICT interventions [ , - , - , , - , - ]. They encountered fewer face-to-face interactions with clinical staff and with other patients [ , , , , - , , - , - , ], thus mitigating their functional dependency [ , , , , , , - , , , , , - , - ] on clinical or hospital services. The use of ICT interventions gave them reassurance and peace of mind [ , , - , , , - , - , - ] by improving a sense of security and reducing anxiety [ , , , , , , , , , - ]. Older adults with chronic diseases who participated in studies reported getting direct access to treatment and benefited from additional medical monitoring when they felt unwell. The use of ICT interventions also encouraged them to continue physical activity, maintain a healthy diet, and stop smoking [ , - , , , , , - , ].
Health Care Provider–Related Factors
One of the biggest advantages of ICT interventions that was identified was their nonpharmacological nature [, , - , , , , - , - ]. This point was made in 58% (18/31) of articles, with a particular focus on the value, for managing older adults with chronic disease, of providing health education and regular follow up. Health care providers reported the use of interactive push-notification features [ , , - , - , , , ], larger screens [ , , , , , ] and written instructions [ , , ] for ICT devices as helpful. Health care providers also expressed a desire to get more available functions, such as voice demonstration and video chatting, for integrating ICT interventions into routine systems (mentioned in 9/31, 29% articles) [ , - , , , , , ].
The most common limiting factor, identified in 35% (11/31) of articles, was the lack of confidence in computer skills [, , , , , - , , , ]. In addition, inconvenience arising from the need to have a continuous internet connection was identified in 48% (15/31) of articles [ , , - , , , - , - ]. Approximately 39% (9/23) of articles identified that participants felt embarrassed when they failed to correctly operate ICT devices [ , - , , , , - , , , , ]. As a result, they were sometimes dependent on other family members to operate the devices. This dependency made some people feel uncomfortable and concerned about bothering their family members for assistance with ICT devices [ , , , - , , , ]. Approximately 32% (10/31) of articles identified instances when participants did not voluntarily learn to use the ICT devices if their family members could operate it for them [ , , , , , , - , ]. Participants also required support (supervision) for adhering to disease management behaviors [ , , , , , , , , - ] and maintaining their ICT devices. Some people were concerned regarding the potential loss of data or lack of protection of their privacy [ , , , , , , , , ] when using ICT interventions. Approximately 39% (12/31) of articles identified that older adults lacked confidence in the use of an internet-based intervention, even if they had the necessary computer skills [ , , - , - , , , ]. Some participants reported inconveniences associated with the ICT device itself, such as small screens or cramped keyboards [ , - , - , ] or inadequate battery life lasting 4 to 5 hours [ , - , , - ]. Approximately 39% (12/31) of articles reported that participants found the ICT devices hard to use because of a lack of familiarity with the medical terms used in the instructions of these devices [ , , , - , , , , , ].
Health Care Provider–Related Factors
Only a few weaknesses were reported for health care provider–related factors. Health care providers reported that some older adults with chronic diseases were dependent on family members or friends for using their ICT devices [, , , , ]. Hence, these participants, who were dependent on others, were sometimes not interested in learning how to operate the technology independently. In such cases, health care providers sometimes found it difficult to directly interact with patients using ICT interventions. An additional list of barriers to and challenges for the use of ICT interventions synthesized from current evidence is provided in .
The authors of 58% (18/31) of articles reported that ICT interventions supported older adults in maintaining regular medical checkups [, , , - , , , - , - ] and attaining benefits from lifestyle changes [ , , , - , , , , , - , - ]. The authors (19/31, 61% articles) also reported that most participants received encouragement from physicians and nurses to use ICT interventions [ , , , - , , , , , - , - ] and develop their self-care disease management skills [ , - , - , - , - ]. Most participants were partially willing to pay for taking up the ICT interventions [ , , - , , ] if they were affordable. Most of the participants, identified in 35% (11/31) of articles, were also keen to recommend the ICT interventions to others [ , , , , , , , , , , ].
A range of operational factors was identified in relation to the use of hardware and software related to ICT interventions. Most of the investigators reported that the local context should be considered during the development of an ICT intervention [, , , , - , , - ]. For example, a mobile app should have personalization features to suit the user’s preferences in their language [ , , - , , , - , ]. Furthermore, participants wanted the ICT devices to be portable, rechargeable [ , , - , , , - ], simple, and easy to use [ , - , - , - ].
Health Care Provider–Related Factors
In 48% (15/31) of articles, providers reported that they were satisfied that the ICT interventions allowed them to give special care to older adults with cognitive or sensory dysfunction [, , - , , - , , , , , ]. There was consensus that clinicians’ active involvement is crucial for the integration of an ICT intervention into a self-management strategy [ , , - , - , - , - ].
The authors of 32% (10/31) of articles reported that some older adults had hearing and sight impairment and that these disabilities restricted communication with health care providers [, , , , , , , ]. Cost was another factor, which was identified in 39% (12/31) of articles, that influenced the uptake of ICT interventions. Despite significant improvement in the self-care ability of patients, participants were unwilling to continue ICT interventions that attracted a fee [ , , , , , - , , ]. For example, a home telehealth program could not be sustained because of financial challenges, technical complexities, and communication-related issues, even after operating for 12 years [ ]. When the participants perceived a new ICT intervention as expensive and complex [ , , , , - , , , ], they lost interest in using that intervention [ , , , , , ]. Some participants reported that a breach of confidentiality [ , , , ] occurred while using an ICT intervention.
Health Care Provider–Related Factors
The authors of 23% (7/31) of the articles reported that providers were influential in motivating their patients to use or stop the use of ICT interventions [, , , , , - , , ]. For example, patients were found to stop using an ICT intervention if their physicians did not encourage them to use the respective intervention [ , , - , - , , , ]. Most health care providers believed that ICT interventions should only be deemed as an adjunct to the medical management of chronic diseases. However, some providers expressed concerns regarding the widespread use of ICT interventions replacing traditional health care delivery models (mentioned in 10/31, 32% articles), which could result in job loss [ , , , , , , , , , ].
Overall, findings from this scoping review highlight the potential benefit of ICT interventions or eHealth (eg, mHealth and mobile apps, EHR, remote monitoring, CDSS, and telemedicine) for supporting older adults in self-managing chronic diseases. The review highlighted a range of operational and technical barriers to using these ICT interventions for older adults. Our review highlighted age-related barriers to using ICT interventions, including cognition, motivation, physical limitations (eyesight and fine motor skills), and perception, which limited the use of ICT interventions among older adults with chronic diseases. In this case, personalized learning may meet the unique needs, interests, and capacities of individual users to mitigate these limitations . Some of these limitations could be resolved via design optimization of ICT interventions, such as increasing the screen contrast to mitigate the loss of visual acuity or simplifying task movements to facilitate ICT use in patients with arthritis or physical disability [ ]. A number of challenges and enablers in integrating ICT interventions into routine practice were also identified. Most of the included studies were pilot or short-term interventions conducted in a controlled environment. Hence, longitudinal studies aimed at assessing the long-term effectiveness of ICT interventions should be a priority.
Our results indicate that some older adults with chronic diseases might have reservations when it comes to engaging with ICT interventions. We found operational and technical challenges, including a lack of willingness to adopt new skills, poor confidence, and the lack of necessary skills to operate ICT devices. These findings are consistent with the results of other studies where older people expressed no interest in using novel technology and struggled to think of the need for such an application in their own lives [, ]. Acceptance of these electronic or digital technologies may be more difficult for the current generation of older adults who did not grow up with these technologies [ , ]. Mitigating strategies to increase ICT literacy using short e-learning courses (eg, 2 weeks with 10-minute sessions each day) have been shown to be suitable for older adults [ , ].
We found strong motivation and desire to use ICT interventions among older adults with chronic diseases because of the nonpharmacological nature of the intervention. Self-management of chronic diseases includes the maintenance of a healthy lifestyle and adherence to medication. However, older adults seem to require specific motivation to make practical changes, such as eating a healthy diet and being physically active, even if they are already aware of their value . Nilsen et al [ ] reported that the traditional approach of episodic care provided in the clinic or through hospital support systems might not be sufficient to prevent chronic diseases without incorporating ICT interventions in health care. Therefore, health care providers are motivated to use ICT interventions to communicate with their patients to know whether they follow their advice.
It is imperative to understand the duration that people require to achieve a cost-effective outcome from ICT interventions. Findings from this scoping review suggest that older adults living with chronic diseases and caregivers were unwilling to pay for the use of ICT interventions, although they were happy with the service. Most participants only offered to pay partially. An explanation for this result is that all participants in the studies we reviewed were from high-income countries and frequently reported the lack of an appropriate insurance scheme and reimbursement for procuring devices required for ICT interventions. Without addressing the payment model, it will be challenging to ensure the proper use of ICT interventions in health care, even if older adults desire to use them. Chen and Chan  also reported that implementation costs were not adequately highlighted in designing specific ICT interventions in many countries. Therefore, the high cost seems to be a critical factor in determining the ability of an older adult to accept these interventions. Similarly, we also reported a home telehealth program’s failure after more than a decade of use because of financial challenges [ ]. Hence, more sustainable funding and reimbursement are essential for promoting the adoption of ICT interventions.
In addition to the financial factors discussed above, this review highlights workload as an additional determinant of the adoption of ICT interventions. Managing life-threatening events, such as arrhythmia or heart attack, requires an immediate response from health care providers, and such a rapid response can be challenging to execute in many places, particularly in hard-to-reach areas. Failure to react to patients immediately may exacerbate the health risks of older adults with chronic diseases and render health care providers susceptible to accusations of negligence . There is also the risk of generating false-positive alarms from these ICT interventions, which may require physical verification. Thus, such alarms could increase the workload of clinicians if they are required to personally evaluate every call. This may partly explain why not all clinicians were receptive to their patients using ICT interventions. Training can be a significant factor that influences health professionals’ eagerness to use or refer their patients for using ICT interventions at home [ - ].
Future app developers should consider involving end users in the design and development process for ICT interventions. We reported that clinicians’ involvement in the recruitment process appeared to influence the decision of participants to take part in the trials or studies. Hence, their involvement will be crucial for motivating patients to use ICT interventions. The authors also point out the necessity of ensuring that health care providers are encouraged and committed to recommending ICT interventions for their patients [, ]. Otherwise, the willingness to use ICT interventions will never develop among patients, despite their ability to operate these devices. The general assumption that education is a relevant factor in adopting the use of ICT may not always be accurate, with the authors of an article reporting that level of education was not positively associated with the uptake of ICT interventions in the sample of patients they studied [ ]. Health care providers can be an additional barrier to the adoption of ICT interventions by older patients. For example, Smelcer et al [ ] reported that 30% of EHR system implementations worldwide failed because of their underutilization or inappropriate use by the clinician. They identify the concept of medical authority, where clinicians or health care providers affect medical practices such as diagnosis and management of chronic diseases for their patients, as critical for the implementation of EHR [ ]. It seems likely that medical authority is also an essential factor in the implementation of other forms of ICT interventions.
Management of chronic diseases may require the engagement of multiple health care service providers . This arrangement could be too complex for older adults with chronic diseases who are disabled or living in rural areas, particularly in hard-to-reach areas. Here, ICT interventions can play a significant role by offering interconnectedness among multiple providers. For example, some ICT interventions (CDSS and EHR) provide valuable features such as sharing data with other providers (interoperability) and providing patient-specific information such as drug adherence [ ]. In doing so, we also report that some participants raised ethical and legal concerns related to sharing data (eg, privacy and security) with several providers. These barriers can be overcome if clinicians, health care workers, and service providers are obliged to maintain confidentiality and report all harmful events associated with the use of ICT interventions [ , , , ].
There are opportunities for implementing ICT interventions in LMICs to support the care of older adults with chronic diseases. Approximately 6.5 billion people reside in LMICs, and the proportion of older adults within this population will increase in the near future in these countries . Most intervention studies that we included were from high-income countries. However, very few were from LMICs. Most developing countries lack the necessary financial strength to fund and implement ICT interventions properly. The good news is that the governments of many LMICs are also interested in investing in deploying eHealth to enhance health services, particularly in remote areas [ ]. Finally, ICT interventions should help patients self-manage chronic diseases with minimal support from health care providers or clinics. Hence, clinicians and health care providers are required to convince patients to use ICT interventions in addition to routine clinic visits. None of the included reviews on ICT interventions reported harm. However, there are challenges to the implementation of these ICT interventions, particularly for older adults with chronic diseases. The provision of ICT literacy by health care providers and user-centered design by app developers may help older adults widen their engagement with ICT interventions [ ]. Hence, longitudinal studies aimed at assessing the long-term effectiveness of ICT interventions should be a priority. Another priority should be to determine whether ICT interventions are clinically effective and cost-effective when used by rural health care providers. Hence, we recommend conducting a systematic review of existing studies on ICT interventions to evaluate their efficacy.
To the best of our knowledge, this is the first review of its type to use the SWOT framework to identify strengths, weaknesses, opportunities, and threats for the use of ICT interventions to support the care of older adults with chronic diseases. A potential limitation of our approach is that we did not consult external experts during the review process. Nevertheless, by conducting a scoping review on this topic, we have defined the nature, extent, and range of research activities on ICT interventions for older adults with chronic diseases. Although we searched the literature exhaustively using 4 academic databases, in addition to ProQuest, there is a possibility that we missed some important studies. In this scoping review, we focused on providing an overview of the available research evidence on the use of ICT interventions in older adults with chronic diseases. Therefore, we included a good range of original studies, systematic reviews, and conference papers to help answer our research question. Importantly, none of the studies included in these reviews overlapped. We did not perform a critical appraisal of the literature, which was beyond the scope of our objectives (PRISMA-ScR checklist is given in[ ]).
ICT interventions might help support the care of older adults with chronic diseases by increasing adherence to treatment and healthy lifestyles. However, the incorporation of ICT interventions into medical practice is still challenging. The involvement of clinicians is crucial for motivating people with chronic diseases to adopt ICT interventions to support self-management. There is a need to improve awareness and training in the available and effective ICT interventions among older adults and health care providers. Widespread implementation of ICT interventions will also require more sustainable approaches to funding and reimbursement. We recommend involving clinicians and caregivers when designing ICT interventions and integrating them into routine medical care.
The authors are grateful to Zubair Ahmed Ratan, Mulugeta Birhanu, Lana Coleman, and Rajshree Thapa for their help in preparing the manuscript. SBZ received a scholarship from the Australian Government Research Training Program to support his academic career. SMSI is funded by the National Heart Foundation of Australia (102112) and the National Health and Medical Research Council Emerging Leadership Fellowship (GNT1195406).
SBZ, RGE, and SMSI conceived and designed the review. SBZ, RKK, and SMSI performed the literature searches and analyzed the data. SBZ, AGT, RGE, RKK, RM, and SMSI wrote the paper.
Conflicts of Interest
RGE reports grants from the National Health and Medical Research Council (Australia) and the National Heart Foundation of Australia outside the submitted work. RGE has also received consulting fees from Medtronic Australasia in relation to work other than that described in this manuscript. AGT reports grants from Monash University during the conduct of the study and grants from the National Health and Medical Research Council (Australia) outside the submitted work.
Search strategies for Ovid MEDLINE, Embase, Scopus, and PsycInfo databases.DOCX File , 31 KB
Framework analysis of strengths, weaknesses, opportunities, and threats on the use of information and communication technology in health care among older adults.DOCX File , 46 KB
List of barriers to and challenges for the use of information and communication technology.DOCX File , 23 KB
PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist.PDF File (Adobe PDF File), 204 KB
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|CDSS: clinical decision support system|
|COPD: chronic obstructive pulmonary disorder|
|CVD: cardiovascular disease|
|EHR: electronic health record|
|ICT: information and communication technology|
|LMIC: low- to middle-income country|
|mHealth: mobile health|
|PRISMA-ScR: Preferred Reporting Items for Systematic Reviews and Meta-Analysis|
|RCT: randomized controlled trial|
|SWOT: strengths, weaknesses, opportunities, and threats|
Edited by J Wang; submitted 17.12.20; peer-reviewed by J Marquard, C Kruse; comments to author 15.03.21; revised version received 10.05.21; accepted 26.09.21; published 07.01.22Copyright
©Sojib Bin Zaman, Raihan Kabir Khan, Roger G Evans, Amanda G Thrift, Ralph Maddison, Sheikh Mohammed Shariful Islam. Originally published in JMIR Aging (https://aging.jmir.org), 07.01.2022.
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