Exploring the Experiences of Wearable Health Monitoring Devices among the Aging Population: A Qualitative Systematic Review ()
1. Introduction
Integrating the Internet of Things (IoT) in healthcare aims to lower costs, improve quality of life, and enhance user experience through various applications, including remote health monitoring, exercise regimens, elderly care, and chronic illness management [1]. Among IoT technologies, wearable health devices are anticipated to transform healthcare and lifestyles significantly, particularly in the fitness and healthcare sectors [2] [3]. These devices, defined as smart equipment, gather data about users and their environments to enhance self-awareness and benefit the user [4] [5]. They also remotely provide real-time, accurate health data [6] [7]. Wearable Health Monitoring Devices (WHMD) can be categorised into head-mounted devices, wrist-worn gadgets, e-textiles, e-patches, and smart ornaments, with primary functions including fall prevention, body movement monitoring, vital sign tracking, and position tracking [8]-[10].
The global aging population, a result of increased life expectancy, presents significant challenges to healthcare systems [11] [12]. Individuals aged 60 and older are projected to rise from 1 billion in 2019 to 2.1 billion by 2050, indicating substantial financial impacts on the public and private sectors [13]. Supporting elderly individuals to monitor and manage their health at home is a major challenge, prompting governments to seek technological solutions [14]. Wearable technology, integral to the concept of “active aging” [15], is particularly beneficial in aiding older adults in managing their health and supporting remote health monitoring [16] [17].
Studies highlight that older adults (O.A) are motivated to use wearable technology for its helpful features and efficiency [18]-[20]. However, despite the perceived benefits, elderly individuals express concerns about potential risks and usability issues [20]. Although they are well-suited to benefit from technological advancements, older adults are often stereotyped as resistant to technology [21] and use wearables less frequently than other age groups [22]. Nonetheless, the benefits of wearable technology for older adults are substantial, as it enables caregivers and healthcare professionals to monitor their independence and anticipate health changes.
Despite the varying user experiences and dispositions of older adults to wearables, there remains a significant gap in research examining this behaviour among this demographic [23]. Among the few researches that have been made, its conclusions are limited by the exploratory nature of the study design, the number of participants [24] or by insufficient data collection practices, such as collecting only quantitative ratings of users experience [25] [26]. These are insufficient to understand the underlying reasons affecting the adoption of wearable devices among the elderly population. The adoption and acceptance of wearables, according to Hart and Sutcliffe [27], is a dynamic process in which users’ attitudes, perceptions, and usage behaviours can be changed by many factors at different stages. Hence, there is a clear need for further studies to comprehend these variations during the adoption process [28] [29]. Gaining more insight into these events can help guide future investigations and provide design inspiration for devices that optimise user experience for this demographic.
2. Materials and Methods
The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed for this qualitative systematic review. The SPIDER tool (Sample, Phenomenon of Interest, Design, Evaluation, Research type) was utilised to organise keywords and phrases for the systematic search. A technical roadmap is provided in Figure 1 to visually demonstrate the research development process, which included the following steps:
1) Systematic Search: Conducted across six electronic databases: Embase, PubMed, ScienceDirect, Scopus, Springer, and Cochrane. Additional papers were identified by screening the reference lists of included studies, as well as searching Google Scholar and open grey literature.
2) Inclusion Criteria: Studies that recruited older adults (≥60 years), utilised qualitative research methods, were published between 2013 and 2023, and focused on wearable health monitoring devices were eligible for inclusion.
3) Study Selection: Covidence tool was employed to ensure accuracy and efficiency in the selection process, resulting in 18 studies being included.
4) Data Extraction and Analysis: Data were extracted and analysed, with the methodological quality of the studies assessed using the Critical Appraisal Skills Programme (CASP).
Technical Roadmap:
Step 1: Define research questions and objectives.
Step 2: Develop search strategy using SPIDER tool to identify keywords and phrases.
Step 3: Conduct systematic search across specified databases.
Step 4: Screen and select studies using inclusion criteria.
Step 5: Extract data and assess methodological quality.
Step 6: Analyze data and synthesize findings.
This comprehensive approach ensured a thorough examination of the experiences of older adults using wearable health monitoring devices.
3. Results
The results from the various tools used are presented in Tables 1-3 and Figure 1, Figure 2.
Table 1. Spider tool for keywords and phrases.
| SPIDER TOOL |
SEARCH TERMS |
| S |
“elder” OR “senior” OR “aging” OR “older adults” OR “geriatrics” |
| P and I |
“wearable device” OR “wearables” OR “wearable sensor” OR
“wearable monitoring systems” |
| D |
“interview” OR “focus group” OR “observe” OR “case study” |
| E |
“experience” OR “attitude” OR “perception” |
| R |
“qualitative” OR “mixed methods” |
Table 2. Themes, definitions and supporting comments.
| THEME |
DEFINITION |
SUB-THEME |
SUPPORTING COMMENTS |
| Health Behaviour Impact |
The effect of WHMD on health-related
behaviours |
Physical Activity |
- “I’ve changed my behaviour somehow. I am now more likely to walk to shops. Previously, I took the car” Scholman et al. (2016)- “You could see how far you have walked; I have not registered that previously. It was fun” Ehn et al. (2018)- “I think it’s helpful for us older people because we’ve never been able to have something like this to help get us motivated and move” Chung et al. (2022) |
Enhanced
well-being |
- “I found it was novel, and good in the sense that one can have it on all day to mark pain intensity and the time it happened.” Rodriguez et al. (2017) |
| User experience and satisfaction |
How OA perceive and interact with WHMD |
Usability |
- “I liked the colors from these two little things, it’s like calling on the phone” Abouzahraa et al. (2019)- “It protrudes too much, it should be smaller, more adaptable to the body.” Abouzahraa et al. (2019) |
| Perception |
- “Based on the results that the app has shown me, my daily activity level is consistently above average, according to the WHO. This is interesting and important for my confidence and encouragement to continue to be active.” Hvalič-Touzery et al. (2022) |
| Comfort |
- “The neck position was comfortable and loose for the participants “because let’s see, it did not bother me at all, really at all. It’s like wearing a necklace: more comfortable, friendlier” Rodriguez et al. (2017) |
| Motivation |
Factors influencing the adoption and continuous use of WHMD |
Support systems |
- “I am no longer afraid of moving around my bed because I know help is readily available in cases of an emergency, thanks to my
monitor” Fotoyi et al. (2022)- “At my age, I cannot be bothered with learning how to use a mobile device. That is why I have a permanent caregiver who helps me with such things” Fotoyi et al. (2022) |
Long-term
engagements |
- “It’s something that clicks in your mind. You have to make that commitment, and once you do, the technology is very motivating. But, until you take the step of getting it and tuning into it, it isn’t going to work” Kononova et al. (2019) |
Social and
emotional support |
- “Many of my friends use Fitbit or similar wearables. They said
Fitbit was very good in tracking their steps and calories.”
Abouzahraa et al. (2019) |
| Socio-psychological barriers |
Internal hurdles and external factors
limiting adoption |
Personal barriers |
“I used to check the heart rate, but I did not understand its meaning. Therefore, I did not use it this week.”1 Well mum’s not really using it It’s kind of on-off, on-off, on-off Yeah. And even now it’s never on now I think actually it was too tight. I think mum’s wrist might have got a bit bigger It swelled with the infection So once it was off But she kept on it for a fair bit too” O’Sullivan et al. (2022)—“During my time at school there were no computers, only type-writers”. Fotoyi et al. (2022) |
| Stigma |
“And the stigma too, probably of having something, ‘oh you’re wearing one of those’ I don’t think I’d be affected by stigma.” Chaudhuri et al. (2015). t should be used under your clothes because nobody would notice, nobody would criticise me, nobody would be pointing out that I use it or not” Cajamarca et al. (2018) |
Economic
Constraints |
Financial limitations experienced with the use of WHMD |
Affordability |
“As an elderly woman living alone, it is important that I surround myself with all these gadgets even though they may sometimes be expensive. However, the cost is outweighed by the peace of mind in knowing I am taken care of even in my sleep” Fotoyi et al. (2022) |
| “It is so disheartening not being able to find information because my pension money does not stretch far into the month and data is too expensive” Fotoyi et al. (2022) |
| Data Reliability and accuracy |
The precision,
dependability and trustworthiness of Health data collected by WHMD |
Data Accuracy |
“No. Because one night, it said I woke up 19 times, and there is no way I could even go the next day if I had woken up 19 times. So, I don’t think it is very accurate.” Fausset et al. (2022) |
| - “At many times, Fitbit would not wake up, and I couldn’t see my data. At other times, it did not show any heart rate. This made me so frustrated.” Abouzahraa et al. (2019) |
Privacy and
security |
Perceptions about the safety of health data collected by WHMDs |
Data security
concerns |
How can providers make sure our personal health profiles will not be accessed by unauthorised people? Will they track any additional data using the device without informing us or analyse our data in any unintended ways? Will they even sell our data to any third
parties to gain commercial benefits?” (Streitz & Konomi, 2018) |
| Technological Barriers |
Obstacles that
hinder the use and implementation of technology |
Connectivity issues |
“I can hardly hear and plus you have instructions to what? Hold for 7 seconds, if you’re destroyed, you’re scared, you are panicking, your arm… I don’t like it, sorry.” Chaudhuri et al. (2015)“At many times, Fitbit would not wake up, and I couldn’t see my data. At other times, it did not show any heart rate. This made me so frustrated.” Abouzahraa et al. (2019) |
| Interoperability |
- “The scenario will become even more complicated when
considering the very strict regulations and rules of hospitals, which may not allow doctors to accept and use data supplied by different wearable devices used by elderly people” Xing et al. (2021) |
Limited
functionality |
- “It would be nice to have a range of devices that fit your situation. Then it would [be] what I need, and not put on a lot of extra stuff that’s gonna cost me more, because you know I think it’s essential to keep it within reasonable price range where you can afford it if you need. But if you don’t need it you don’t have to take it” Fausset et al. (2013) |
Table 3. Study characteristics.
Lead
author/
Year |
Country |
Aim of Study |
Study design |
Data
collection |
Population
description |
Total
number of participants |
Device |
Trial
duration |
| Yolan de Fotoyi (2022) |
South Africa |
To investigate the factors that will improve the adoption of MMC systems for healthcare monitoring by the elderly living at home in South Africa. |
Qualitative |
Interview |
Elderly people residing in Eastern Cape with an
average age of 72.7 years |
15 |
Mobile
monitoring and care devices |
N/A |
| Anna Schlomann |
Germany |
To evaluate the experiences,
opportunities, and obstacles of self-monitoring when applied by older adults. To investigate the usability of a wear |
Qualitative |
Focus groups |
Elderly
female retirees
(67 - 78 years) |
6 |
Fitness tracker (steps per day, distance walked, burned calories, movement
during sleep) |
4 weeks |
| Friederike J. S. Thilo (2018) |
Switzerland |
able, waterproof, automatically alerting, fall detection prototype, through the involvement of community-dwelling older people in a qualitative study using a real field-testing approach. |
Qualitative |
Focus groups |
Community - dwelling older people (75 - 92 years) |
15 |
Wearable fall detector |
9 Days |
| Theresa A. Floegel (2018) |
USA |
To examine feasibility and
acceptability of continuous
objective activity monitor use
in an aging clinical population during and after hospitalization |
Qualitative |
Interview; Observation |
Older adults with Heart failure |
27 |
Inclinometric accelerometers (record posture) Ankle
accelerometer (record
ambulatory activity) |
5 months |
| Cara Bailey Fauss e (2013) |
USA |
To investigate how older adults integrated activity monitoring products into their lives over two weeks in their own homes |
Qualitative |
Interview |
Elderly individuals without prior experience
with Activity
monitoring devices (61 - 69 years) |
8 |
Activity
monitoring technologies (Striiv, Fitbit®, Nike +
FuelBand, and
MyFitnessPal) |
2 weeks |
| Maria Ehn (2018) |
Sweden |
To investigate how seniors
experience using activity monitors (AMs) as support for PA in daily life. |
Qualitative |
Interview |
community-dwelling older adults (>75 years) |
8 |
Activity monitor (Withings,
Jawbone) |
9 days |
| Gabriela Cajarnarca (2018) |
Chile |
This study proposes the use of wearable devices to identify the bodily postures of older persons, while also looking into the
perceptions of the users |
Qualitative |
Interview |
Older adults living in a residential home (60 - 83 years) |
30 |
StraightenUp + (posture
monitor) |
50 - 65 minutes/participants |
| Shomir Chaudhuri (2015) |
USA |
To evaluate older adults’
perceptions of FDDs and
specifically examine what factors affect their willingness to use these devices and suggestions for improvement. |
Qualitative |
Focus groups |
Older adults from independent and assisted living communities around the Puget Sound region. |
27 |
Fall detection device |
4 months |
| Fei Xing (2018) |
China |
To address this knowledge gap by reporting on an exploratory study that investigated older people’s user requirements towards
wearable medical devices and explored potential challenges
and difficulties for large-scale deployment of such devices. |
Qualitative |
Focus groups |
Family containing 1 - 2 older adults (>60 years) plus 2-4 younger family members. |
7 older adults, 12 family members |
N/A |
N/A |
| Fei Xing (2021) |
China |
To obtain an in-depth
understanding and holistic
exploration of potential barriers and issues influencing large-scale deployment of AI-enabled
WMDs in the Chinese context. |
Qualitative |
Focus groups |
Chinese elderly users and their families, 2 WMD providers, and 2 public health
organizations. |
8 elderly individuals, 12 family members |
N/A |
N/A |
| Anastasia Kononova (2019) |
USA |
To investigate older adults’
perceptions and uses of activity trackers at different points of use: from nonuse and short-term use to long-term use and abandoned use to determine the factors to maintain tracker use and prevent users from discontinuing tracker usage. |
Qualitative |
Focus groups |
Adults aged 65 years and older
(66 - 94 years) |
48 |
Wearable
activity trackers (Garmin
Vivofit 2) |
6 weeks |
| Mohamed Abouzahraa (2019) |
Canada |
To examine the factors that
influence seniors’ use of wearable devices and the effect of these devices on seniors’ behavior. |
Qualitative |
Interviews |
Elders who have never used
wearables before (65 - 75 years) |
26 |
Activity tracker (Fitbit) |
2 months |
| Iyubanit Rodríguez (2017) |
Chile |
To study whether mobile or wearable devices are appropriate to self-report pain levels and to find which body position is more appropriate for elderly people to wear a device to self-report pain |
Mixed methods |
Interviews |
Older adults
(60 - 93 years) |
18 |
RepWear
(A Wearable Io) |
24 minutes |
| Wei Peng (2021) |
USA |
To uncover the mechanism
underlying the long-term
continued use of wearable devices among older adults through the theoretic lens of habit formation |
Qualitative interview |
|
Older adults
(aged 65+ years) who had used wearable activity trackers for more than 6 months. 55% Female |
20 |
Garmin Miband |
6 months |
| Zhaoyi Ma (2022) |
China |
To investigate the changes in the usage behaviours, perceptions, and attitudes of older people towards wearables over four weeks |
Mixed method |
|
Retired employees from Inter Higher Institution (62 - 74 years) Female-5 Male-15 |
20 |
Smart bracelets and smart watches (Xiaomi Band 4 & 5, Honor Band 6, Amazfit GTS 2, Huawei Honor Watch Magic 3) |
4 weeks |
| Grace O’ Sullivan (2022) |
Ireland |
To explore the acceptability and feasibility of using a FitBit Charge 3 among people with dementia, living in the community, who took part in the physical exercise component of the Comprehensive Resilience-building psychosocial intervention pilot study |
Mixed method |
|
Older people with dementia (>60 years) and their caregivers |
9 older adults, 9 caregivers |
Wrist-worn tracker (Fitbit) |
9weeks |
| Jane Chung (2022) |
USA |
To examine older adults’
perceptions of GPS-enabled smart watches and to identify potential barriers and facilitators of smartwatch and sensor data use |
Mixed method |
|
Elderly individuals (>60 years) |
30 |
Wearable
activity tracker (Fitbit Surge 3) and smart watch |
30 days |
Simon
Hvalica Touzery (2022) |
Slovenia |
To explore the benefits of
combining wearable activity
monitors and telecare for older adults |
Mixed method: Quasi-experimental |
|
Dyads of older primary users
(>60 years) |
13 |
Wearable
activity tracker (GoLiveClip device) |
4 months |
![]()
Figure 1. The critical appraisal skills programme (CASP) checklist.
Figure 2. Prisma flow chat.
4. Discussion
This systematic review highlights the experiences of 335 older adults and 33 family members and caregivers across 10 countries, revealing varying degrees of the older adults’ interactions with WHMD. Within this study, eight themes emerged, providing insights into the varied dimensions of the benefits, motivations, and challenges encountered by older adults while using these WHMDs. The study illustrated the positive impact of WHMDs on the health status of older adults. From enhancing physical activity and detecting falls to improving posture and sleep, these devices enabled the promotion of a healthier lifestyle among older adults. This is in tandem with the study by Majumder et al. [30], which states the potential for WDs to achieve such results among elders. In addition, part of the gratification revealed by older adults in this study was the sense of safety they felt through connectivity with their family, healthcare providers and caregivers by sharing health data with them on these devices, which was also discovered to be the most significant feature of WD’s for older adults in a study by Wu et al. (2019) [31]. Contrary to the concerns of elders revealed by [32] about frequent hospital visits and the financial burden it imposed on elders, the findings of this study, however, discovered unexpected benefits such as cost reduction in transportation and reduced hospital visits, emphasizing the multifaceted advantages associated with WHMD use. Overall, these benefits improved the self-awareness and independence of older adults, mirroring the studies by [33].
Motivation for adopting WHMDs varied and was driven by positive user experiences, aesthetic appeal, comfort, usefulness, and social influence. The intertwining of these factors played a significant role in motivating elders to embrace and utilize wearable devices. The study by [31] highlighted similar motivators for elders to use wearable sensors. Despite the affirmation by elders of these motivators, some older adults expressed dissatisfaction with the location of the device, stating the abdomen and neck were the preferred locations. However, the non-dominant wrist and the waist were chosen in previous studies [34]. Furthermore, support from family and society played a pivotal role in the widespread acceptance of WD’s by elders in this study, thus echoing the research of some renowned writers [35] [36] whose discovery revealed that support from family aids the adoption of WHMD’s among elders. Wu et al. (2019) believed that social integration is a strong motivation for elders to adopt WD’s, which was evident in this research.
Amidst the positive encounters and motivations, elders still encountered challenges with the devices, which hindered their adoption and use of wearables. The papers in this study showed that elders were discouraged by the short battery life, high volume, difficult buttons, false alarms and complexity of the device, which aligns with the factors outlined by other scholars [37] [38]. A researcher [39] reckons that the WD industry still faces many challenges that can limit its use, especially in the healthcare sector. One of which is the interoperability and connectivity issues discovered in this study, which limits the process of health data sharing between elders and their healthcare providers.
While a researcher believes that using wearable devices will provide a cost-effective solution, findings from this study revealed a contrary situation as elders found the WD’s to be expensive, similar to the findings of another [40].
Additionally, stress monitoring was discovered to be an essential feature for older adults [41], whereas, this study disclosed that older adults did not consider it necessary due to their lack of understanding of its benefits. Thus, this highlights the impact of poor health literacy and poor knowledge of device usefulness among elders, as presented in similar work [42]. Hence, scientists [43] beckons for user education and support in promoting adoption among elders. Similar to this study, a researcher disclosed that the reliability and trustworthiness of health data collected by WHMDs raised a lot of concerns. Thus, to build the trust of users, accuracy concerns need to be addressed, otherwise it will continue to pose a huge challenge to adoption. Data security remains a major concern with the use of wearables; this was displayed in that study. Therefore, there is a need to address these challenges comprehensively in the design and implementation of WHMDs that cater to the unique needs of older individuals in diverse contexts.
In summary, 18 studies were included in this study, spanning 10 different countries, including three developing countries. The common barriers to adoption were technological barriers, socio-psychological barriers, limited functionality of the device, privacy, and security concerns. The benefits derived by older adults were mainly associated with improvements in their physical activities, sleep, posture, and overall well-being, thereby promoting independence and self-awareness. Additionally, older adults were motivated mainly by social influence and support from friends and family. This study highlighted the need for user-centred approaches in the development of wearable health monitoring devices.
5. Conclusion
This study highlights the experiences of older adults using wearable health monitoring devices. The findings reveal that while these devices offer significant benefits in managing health and promoting independence, they also present challenges related to usability, data privacy, and the need for ongoing support. The benefits of wearable health monitoring devices include enhanced self-monitoring, early detection of health issues, and improved communication with healthcare providers. However, the study also identifies significant challenges, such as difficulty using the devices, concerns about data privacy, and the necessity for technical support.
6. Suggestions for Future Research
Future research should focus on designing more user-friendly interfaces tailored to the cognitive and physical abilities. Additionally, investigating and developing robust measures to address data privacy concerns is crucial. Exploring the creation of comprehensive support systems, including technical assistance and user training programs, will also be beneficial. Conducting long-term studies to assess the sustained impact of wearable health monitoring devices on the well-being and health outcomes of older adults is essential. By addressing these areas, future research can contribute to the development of more effective and acceptable wearable health technologies for older adults, ultimately enhancing their quality of life and health management.
Conflicts of Interest
The authors declare no conflicts of interest.