Swiss Medical
Informatics
Current use and openness to use assistive technologies among home-dwelling elders in Switzerland: a cross-sectional study
Digitalization General Internal Medicine Prevention and Public Health
Peer-review

Current use and openness to use assistive technologies among home-dwelling elders in Switzerland: a cross-sectional study

Original article
Digitalization General Internal Medicine Prevention and Public Health
Flaka Siqecaa
Additional authors
Suzanne Dhainia, Sabina De Geesta,b, Andreas Zellerc, Mieke Deschodtd,e, Thekla Brunkerta,f
DOI:
https://doi.org/10.4414/smi.2024.1533586071
Swiss Med Informatics. 2024:1533586071
Affiliations
a Department Public Health, Nursing Science, University of Basel, Switzerland
b Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, Belgium
c Department Clinical Research, Center for Primary Health Care, University of Basel, Switzerland
d Department of Public Health and Primary Care, Gerontology and Geriatrics, KU Leuven, Belgium
e Competence Center of Nursing, University Hospitals Leuven, Belgium
f University Geriatric Medicine FELIX PLATTER, Basel, Switzerland

Published on 17.06.2024

Corresponding author: Sabina De Geest PhD, RN Sabina.degeest@unibas.ch

Abstract

Research question: This study aimed to examine the current use and the openness to future use of assistive technologies (ATs) as well as factors that drive the latter among home-dwelling elders. Our research question is twofold: (1) what is the current and anticipated use of ATs (telemedicine, phone/SMS, wearables and assistive robots)? and (2) which factors are associated with this population’s openness to use ATs?
Methods: This is a secondary data analysis of a survey among home-dwelling elders aged 75+ in Basel-Landschaft, Switzerland (n=8876). We descriptively assessed their current use and openness to future use of the four abovementioned types of ATs. Moreover, multiple logistic regression was used to determine factors associated with openness to future use of ATs.
Results: Only few participants (17.9%) reported to currently use ATs. Openness to use ATs was associated with current use of telemedicine (OR: 5.7, 95% CI: 4.9–6.5), phone/SMS (OR: 2.7, 95% CI: 2.5–2.9), wearables (OR: 4.8, 95% CI: 4.3–5.3) and assistive robots (OR: 8.6, 95% CI: 7.2–10.1), as well as receiving support from a spouse/partner (OR: 1.1; 95% CI: 1.0–1.2). Older age (OR: 0.9; 95% CI: 0.9–0.9) and being female (OR: 0.7; 95% CI: 0.6–0.8) were associated with lower odds of being open to use ATs.
Conclusions: Understanding which factors drive openness to future use of ATs among home-dwelling elders is key to improving independence and supporting older adults in achieving their desired goal of aging in place.

Background

As individuals age, the risk of frailty and chronic conditions rises leading to increased health and social care needs [1]. Most elders prefer aging at home to living in a nursing home or an assisted-living facility [2]. Fostering this community-based living is also encouraged by policymakers as a cost-effective alternative to long-term care placements [3] and is known as aging in place [4].
Aging in place can be facilitated by assistive technologies (ATs). ATs include any device, equipment, or software primarily aimed at maintaining an individual’s functional status and independence while delaying impairments or secondary complications [5]. Furthermore, ATs promise to support elders in maintaining their desired autonomy and social inclusion [6, 7]. They serve purposes like health monitoring, detecting a deteriorating functional status or onset of frailty, facilitating (instrumental) activities of daily living or assisting communication between the elders and their care providers [6-17].
Despite technological advancements, a systematic approach in developing and implementing ATs in the care of elders is lacking. To ensure that the innovations are relevant and of lasting effect, understanding the populations’ needs and concerns is paramount [18]. However, the involvement of elders in this process remains limited [19] and there is a mismatch in priorities and relevance of ATs for them [20, 21]. In parallel, a plethora of concerns related to using ATs have been identified and need to be addressed to improve their acceptability and usage. Previous research shows that age-associated cognitive impairment, reduced fine motor movements, difficulties in hearing or seeing, and emotional anxiety can pose challenges to using ATs [22, 23]. Barriers like the lack of familiarity and access, functionality/added value, costs, stigma, issues of trust, and concerns about privacy have also been reported to reduce the confidence in using ATs [15, 24].
Therefore, there is an emphasis on gaining an understanding of what influences the attitude of home-dwelling elders towards ATs [24, 25]. A literature review found older age, being female, lower health status and lack of social support were associated with lower openness to using ATs [26]. In another longitudinal study, being older and female, having a lower income, and the presence of frailty were also found to be associating factors [27]. With older age, diminished health may impede the ability to perform tasks or to understand processes involved in using ATs, whereas the availability of social support and the level of income may influence the ability to acquire such devices [28-30]. In Switzerland, two cross-sectional studies looked into current use and barriers towards usage of ATs among people aged 65 years and above [31, 32]. One survey (n=1149) focused on barriers and attitudes towards usability of ATs and found complicated use, security concerns, and too much effort to learn and use ATs to be hindering factors [32]. The other survey (n=537) focused on the frequency of using a wider array of ATs, and found males and those younger than 80 to be more frequent users [31].
Accordingly, using a population-based survey of home-dwelling elders in Basel-Landschaft (BL), Switzerland, we aimed to: (1) describe the current and anticipated use of ATs (telemedicine, phone/SMS, wearables and assistive robots) and (2) assess the factors associated with openness to using ATs.

Methods

Design, setting and participants

This is a secondary data analysis of the INSPIRE Population Survey, conducted in 2019 in BL [33]. The survey was sent to all home-dwelling elders aged 75 years and older living in this region and 8,786 participants returned the questionnaire (Response Rate = 30.7%) [33]. The entire sample was used for the current study. Details on the development of the survey and participants characteristics are reported in the original survey [33].

Variables and measurements

Outcome variable

Openness to use ATs was assessed by asking if participants would be open to a) use telemedicine to communicate with their healthcare providers, b) use a mobile phone or SMS for information or reminders about medication intake, c) utilize wearables like heart rate and blood sugar monitors or d) use assistive robots for chores and other tasks. The answers were dichotomized to “Yes” (“Yes” and “Maybe”) and “No” (“No” and “I do not understand what it is used for”).
We also generated a combined outcome, where 0 was assigned to those open to none and 1 to those open to at least one type of AT.

Predictor variables

Current use of ATs was captured by asking which of the four types of ATs (telemedicine, phone/SMS, wearables, assistive robots) participants were currently using (Yes/No).
Living situation was assessed by asking who they currently live with. Answers were grouped in “Living alone” vs “Living with others” (“With a spouse/partner”, “With another adult”, “With siblings”, “With adult children”, “With a professional/paid caretaker”).
Daily informal support was measured by asking whom participants receive daily support from. This was a multiple response question with the answers “From a spouse/partner”, “From a younger family member”, “From friends or neighbors” and “Currently do not need support”.
The Groningen Frailty Indicator (GFI) was used to assess the prevalence of frailty, defined as “the state of physiological vulnerability with a diminished capacity to manage external stressors” [34]. It includes fifteen questions measuring loss of function in the four domains physical, cognitive, social and psychological [35]. Answers are dichotomous “Yes (1)/No (0)”, 1 indicating a problem. The GFI ranges between 0 and 15, with ≥4 representing frailty [35]. The tool has been validated (r -0.62) and adapted to German [36].
Age was recorded as a continuous variable, using the year of birth at the time of the survey.
Gender information was collected as “Male” or “Female”.
The original answers on level of education were regrouped using the International Standard Classification of Education [37]: “Tertiary” (“University”, “University of Applied Sciences”), “Secondary/Professional apprenticeship” (“Gymnasium”, “Apprenticeship”), “Primary or None” (“Elementary School” and “No degree”) and “Other”.
Monthly household income in Swiss francs was dichotomized for analysis into “Below national average” and “Above national average” based on the national average income data between 2008 and 2018 [38].

Statistical analysis

Categorical variables are reported as frequencies and percentages, whereas age is reported in mean and standard deviation (SD). The multiple response question is reported as a percentage of cases. We checked for multicollinearity using the χ2 test. Five variables had more than 5% missing data: openness to use phone/SMS (6.2%), wearables (8.4%), assistive robots (8.4%), individual income (5.3%), and GFI (14.2%). As recommended by Jakobsen et al. [39], we imputed data using multiple imputation by chained equations (mice) [40].
We used multiple logistic regression to test the association of predictor variables and outcomes (combined outcome and all four types of ATs separately). We used a backward elimination approach and the Akaike information criterion (AIC) to determine model fit, a lower AIC denoting a stronger model. The p-value was set at 0.05.
Analysis was performed using R and R Studio, version 1.3.1093 for Mac OS [41, 42].

Results

Description of the sample

All participants (N=8786) were included. The mean age was 81.8 years (SD = 4.8), 51.8% were women, and 26.8% had a GFI score of ≥4. About 25% had a tertiary education, and 45.8% reported their income to be below national average [38]. Over half of the participants (63.0%) stated to be living with others, and support from a spouse/partner (36.4%) was the most common. See table 1 for a summary of participants’ characteristics.

Descriptive results of current use and openness to use ATs

Only a small number reported to currently use ATs (17.9%), with phones/SMS (12.9%) being used most frequently. Openness to use ATs was highest for wearables (62.2%) and telemedicine (56.9%) (table 1).

Factors associated with openness to use ATs

Openness to use ATs was associated with current use of telemedicine (OR: 5.7, 95% CI: 4.9–6.5), phone/SMS (OR: 2.7, 95% CI: 2.5–2.9), wearables (OR: 4.8, 95% CI: 4.3–5.3) and assistive robots (OR: 8.6, 95% CI: 7.2–10.1), as well as with receiving support from a spouse/partner (OR: 1.1; 95% CI: 1.0–1.2). On the contrary, older age (OR: 0.9; 95% CI: 0.9–0.9) and female gender (OR: 0.7; 95% CI: 0.6–0.8) were associated with lower odds of being open to use ATs (table 2).

Discussion

Using a population-based survey, we aimed to describe current and anticipated use of ATs and assess factors associated with the use of ATs among home-dwelling elders in BL, Switzerland. Overall, our results indicated a rather low current usage of ATs among participants (17.9%). Specifically, only 12.9% of participants indicated to use phone/SMS for health services, less than half compared to findings from previous surveys in Switzerland [32].
We found current use of ATs was associated with openness to use ATs in the future. Similar to Seifert et al. [32], advanced age and female gender were associated with lower odds of being open to use ATs. In contrast to their findings, we found no significant association between openness to use ATs and level of education. This might be related to the higher age of our participants. With increased age, support from caregivers might come more into play than level of education [43]. Accordingly, we could show that receiving support from a spouse/partner was associated with higher odds of being open to use ATs. This highlights the importance of informal caregiver availability, as older adults might require additional help to operate some of the devices [44].
To harness the potential of technology to enable aging in place, understanding what facilitates or obstructs the use of ATs is of utmost importance [47]. Despite their wide availability, few products are used routinely in the care for home-dwelling adults. Researchers frequently find that only some are used beyond piloting, indicating their adoption to enhance independence is lagging behind [20]. Development and implementation of innovative ATs should not only focus on process evaluation, but also on important outcomes for independence, quality of life and social autonomy [20]. Furthermore, their evaluation should not be restricted to quantitative assessments, but lived experiences, expectations and personal values of elders as end users should be qualitatively explored [20]. Co-creation, especially by involving vulnerable individuals, e.g., those with multimorbidity or a cognitive decline [48], is particularly important to improve acceptance and openness to use ATs.
Our study corroborates findings from international and national literature [26, 31, 32] and provides insights into drivers of openness to ATs among home-dwelling elders. We consider the response rate to be a strength, which is high compared to other mail-based population surveys [49], especially considering that this population is challenging to reach and might need support to respond [50]. However, the study comes with some limitations. The outcome was assessed by a limited number of questions and we could not assess other factors influencing openness to use ATs, such as perceived usefulness or expected benefits [26]. We substantially reduced the number questions, as stakeholders were concerned about the length burdening the participants. Future surveys should be designed specifically for the purpose of exploring technology openness guided by conceptual frameworks to account for behaviors and attitudes towards ATs [51, 52].

Conclusion

Our study made a first attempt to gain insight into the current usage and openness to future use of ATs in home-dwelling elders. We found current use of ATs, sociodemographic factors, frailty and receiving informal support from a caregiver to play important roles in openness to use ATs. Understanding what drives the openness of home-dwelling elders to use ATs is important as it can enhance their autonomy and supports them to age in place.

1 Rechel B, Grundy E, Robine JM, Cylus J, Mackenbach JP, Knai C, et al. Ageing in the European Union. Lancet. 2013;381(9874):1312-22.
2 Wiles JL, Leibing A, Guberman N, Reeve J, Allen RE. The meaning of "aging in place" to older people. Gerontologist. 2012;52(3):357-66.
3 Graybill EM, McMeekin P, Wildman J. Can aging in place be cost effective? A systematic review. PLoS One. 2014;9(7):e102705.
4 Ilinca S, Rodrigues R, Leichsenring K. From care in homes to care at home: European experiences with (de)institutionalisation in long-term care. Policy Brief 12/2015. Vienna: European Centre.
5 Global report on assistive technology. Geneva: World Health Organization and the United Nations Children’s Fund (UNICEF), 2022. Licence: CC BY-NC-SA 3.0 IGO.
6 Kim KI, Gollamudi SS, Steinhubl S. Digital technology to enable aging in place. Exp Gerontol. 2017;88:25-31.
7 Tun SY, Madanian S, Mirza F. Internet of things (IoT) applications for elderly care: a reflective review. Aging Clin Exp Res. 2021;33(4):855-67.
8 Chen YR, Schulz PJ. The Effect of Information Communication Technology Interventions on Reducing Social Isolation in the Elderly: A Systematic Review. J Med Internet Res. 2016;18(1):e18.
9 Şahin E, Yavuz Veizi BG, Naharci MI. Telemedicine interventions for older adults: A systematic review. J Telemed Telecare. 2024;30(2):305-319.
10 Khosravi P, Ghapanchi AH. Investigating the effectiveness of technologies applied to assist seniors: A systematic literature review. Int J Med Inform. 2016;85(1):17-26.
11 Liu L, Stroulia E, Nikolaidis I, Miguel-Cruz A, Rios Rincon A. Smart homes and home health monitoring technologies for older adults: A systematic review. Int J Med Inform. 2016;91:44-59.
12 Pal D, Triyason T, Funikul S. Smart Homes and Quality of Life for the Elderly: A Systematic Review. 2017 IEEE International Symposium on Multimedia (ISM), Taichung, Taiwan. 2017;413-419.
13 Peek ST, Luijkx KG, Vrijhoef HJ, Nieboer ME, Aarts S, van der Voort CS, et al. Understanding changes and stability in the long-term use of technologies by seniors who are aging in place: a dynamical framework. BMC Geriatr. 2019;19(1):236.
14 Sokullu R, Akkaş M, Demir E. IoT supported smart home for the elderly. Internet Things (Amst). 2020;11:100239.
15 Yusif S, Soar J, Hafeez-Baig A. Older people, assistive technologies, and the barriers to adoption: A systematic review. Int J Med Inform. 2016;94:112-6.
16 Camp N, Lewis M, Hunter K, Johnston J, Zecca M, Di Nuovo A, et al. Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults. Int J Environ Res Public Health. 2020;18(1):163.
17 Liu L, Daum C, Cruz AM, Neubauer N, Rincón AR. Technology to Facilitate Independence in Self Care—ADL and IADL. In: Liu L, Daum C, Cruz AM, Neubauer N, Rincón AR. Autonomy and Independence: Aging in an Era of Technology. Synthesis Lectures on Technology and Health. Cham: Springer International Publishing; 2022. p. 83-95.
18 Kaisler RE, Missbach B. Co-creating a patient and public involvement and engagement ‘how to’guide for researchers. Res Involv Engagem. 2020 Jun;6:32.
19 Mannheim I, Schwartz E, Xi W, Buttigieg SC, McDonnell-Naughton M, Wouters EJ, et al. Inclusion of Older Adults in the Research and Design of Digital Technology. Int J Environ Res Public Health. 2019;16(19):3718.
20 Van Grootven B, van Achterberg T. The European Union’s Ambient and Assisted Living Joint Programme: An evaluation of its impact on population health and well-being. Health Informatics J. 2019;25(1):27-40.
21 Lund A, Holthe T, Halvorsrud L, Karterud D, Johannessen AF, Lovett HM, et al. Involving older adults in technology research and development discussions through dialogue cafés. Res Involv Engagem. 2021;7(1):26.
22 Wang S, Bolling K, Mao W, Reichstadt J, Jeste D, Kim HC, et al. Technology to Support Aging in Place: Older Adults’ Perspectives. Healthcare (Basel). 2019;7(2):60.
23 Di Giacomo D, Ranieri J, D'Amico M, Guerra F, Passafiume D. Psychological Barriers to Digital Living in Older Adults: Computer Anxiety as Predictive Mechanism for Technophobia. Behav Sci (Basel). 2019;9(9):96.
24 Abolhassani N, Santos-Eggimann B, Chiolero A, Santschi V, Henchoz Y. Readiness to accept health information and communication technologies: A population-based survey of community-dwelling older adults. Int J Med Inform. 2019;130:103950.
25 Korkmaz Yaylagul N, Kirisik H, Bernardo J, Dantas C, van Staalduinen W, Illario M, et al. Trends in Telecare Use among Community-Dwelling Older Adults: A Scoping Review. Int J Environ Res Public Health. 2022;19(24):16672.
26 Peek ST, Wouters EJ, van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJ. Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform. 2014;83(4):235-48.
27 He W, Cao L, Liu R, Wu Y, Zhang W. Factors associated with internet use and health information technology use among older people with multi-morbidity in the United States: findings from the National Health Interview Survey 2018. BMC Geriatr. 2022;22(1):733.
28 Quittschalle J, Stein J, Luppa M, Pabst A, Löbner M, Koenig HH, et al. Internet Use in Old Age: Results of a German Population-Representative Survey. J Med Internet Res. 2020;22(11):e15543.
29 Hunsaker A, Hargittai E. A review of Internet use among older adults. New Media Soc. 2018;20(10):3937-54.
30 Crouch E, Gordon NP. Prevalence and Factors Influencing Use of Internet and Electronic Health Resources by Middle-Aged and Older Adults in a US Health Plan Population: Cross-Sectional Survey Study. JMIR Aging. 2019;2(1):e11451.
31 Schumacher Dimech A, Misoch S. Nutzung von digitalen Dienstleistungen bei Menschen 65+. Oct 2017. St. Gallen: FHS St. Gallen und think tank thurgau.
32 Seifert A, Schelling H. Digitale Senioren. Nutzung von Informations- und Kommunikationstechnologien (IKT) durch Menschen ab 65 Jahren in der Schweiz im Jahr 2015. Zurich: Pro Senectute Schweiz; 2015.
33 Siqeca F, Obas K, Yip O, Stenz S, Vounatsou P, Briel M, et al. The INSPIRE Population Survey: development, dissemination and respondent characteristics. BMC Med Res Methodol. 2021;21(1):131.
34 Vetrano DL, Palmer K, Marengoni A, Marzetti E, Lattanzio F, Roller-Wirnsberger R, et al.; Joint Action ADVANTAGE WP4 Group. Frailty and Multimorbidity: A Systematic Review and Meta-analysis. J Gerontol A Biol Sci Med Sci. 2019;74(5):659-66.
35 Steverink N, Slaets J, Schuurmans H, Lis M. Measuring frailty: Developing and testing the GFI (Groningen Frailty Indicator). Gerontologist. 2001;41(Special Issue 1):236-7.
36 Braun T, Grüneberg C, Thiel C. German translation, cross-cultural adaptation and diagnostic test accuracy of three frailty screening tools: PRISMA-7, FRAIL scale and Groningen Frailty Indicator. Z Gerontol Geriatr. 2018;51(3):282-92.
37 UNESCO Institute for Statistics. Montreal Quebec: International Standard Classification of Education (ISCED); 2017 Available from: http://uis.unesco.org/en/topic/international-standard-classification-education-isced.
38 Federal Statistical Office. Neuchâtel: Wages, income from employment and labour costs; 2020. Available from: https://www.bfs.admin.ch/bfs/en/home/statistics/work-income/wages-income-employment-labour-costs.html.
39 Jakobsen JC, Gluud C, Wetterslev J, Winkel P. When and how should multiple imputation be used for handling missing data in randomised clinical trials - a practical guide with flowcharts. BMC Med Res Methodol. 2017;17(1):162.
40 van Buuren S, Groothuis-Oudshoorn K. mice: Multivariate Imputation by Chained Equations in R. J Stat Soft. 2011;45(3):1-67.
41 R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria; 2020.
42 RStudio Team. RStudio: Integrated Development Environment for R [Internet]. Boston, MA: PBC; 2019.
43 Madara Marasinghe K. Assistive technologies in reducing caregiver burden among informal caregivers of older adults: a systematic review. Disabil Rehabil Assist Technol. 2016;11(5):353-60. Erratum in: Disabil Rehabil Assist Technol. 2019;14(6):643.
44 Lindeman DA, Kim KK, Gladstone C, Apesoa-Varano EC. Technology and Caregiving: Emerging Interventions and Directions for Research. Gerontologist. 2020;60 Suppl 1:S41-S9.
45 Gitlow L. Technology Use by Older Adults and Barriers to Using Technology. Phys Occup Ther Geriatr. 2014;32(3):271-280.
46 Fischer SH, David D, Crotty BH, Dierks M, Safran C. Acceptance and use of health information technology by community-dwelling elders. Int J Med Inform. 2014;83(9):624-35.
47 Peek ST, Luijkx KG, Rijnaard MD, Nieboer ME, van der Voort CS, Aarts S, et al. Older Adults' Reasons for Using Technology while Aging in Place. Gerontology. 2016;62(2):226-37.
48 Swallow D, Petrie H, Power C, Lewis A, Edwards AD. Involving Older Adults in the Technology Design Process: A Case Study on Mobility and Wellbeing in the Built Environment. Stud Health Technol Inform. 2016;229:615-23.
49 Sinclair M, O'Toole J, Malawaraarachchi M, Leder K. Comparison of response rates and cost-effectiveness for a community-based survey: postal, internet and telephone modes with generic or personalised recruitment approaches. BMC Med Res Methodol. 2012;12(1):132.
50 delman LS, Yang R, Guymon M, Olson LM. Survey methods and response rates among rural community dwelling older adults. Nurs Res. 2013;62(4):286-91.
51 Venkatesh V, Bala H. Technology Acceptance Model 3 and a Research Agenda on Interventions. Decis Sci. 2008;39(2):273-315.
52 Davis FD. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. Manage Inf Syst Q. 1989;13(3):319-40.

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