Assist technology to support everyday living: MCI & dementia



Norwegian health policy encourages older citizens to remain at home for as long as possible and to stay active and fit.1–4 Government strategies recommend participation in activities and socialization to preserve health and well-being. Older citizens should be enabled to master independent living at home during their lifetime.2 Due to expected demographic changes, the numbers of older adults with mild cognitive impairment (MCI) and dementia (D) are expected to grow, both in Norway ( and worldwide.5,6 The prevalence of dementia in Norway in 2020 was 101,800 and is expected to more than double to 238,499 by 2050.7 Dementia is a general term for chronic or progressive neurodegenerative diseases that affect the brain and influence cognitive function, psychological health, behavior, motor skills, and the ability to cope with everyday life.8

Dementia increases with age, and the most frequent type is Alzheimer’s disease (60–70%). Vascular dementia, Lewy body dementia and frontotemporal dementia are other major types. MCI is a neurocognitive disorder, often attributable to an underlying disease of the nervous system, an infection, or to trauma to the brain.9 MCI may progress to dementia, remain stable or gradually recover/disappear. However, mortality rate is high.10 Frequently reported problems for people with MCI/D include remembering appointments, planning and doing shopping, preparing food, paying bills, doing the laundry, and keeping track of day and night.8 In the early phases of dementia, digital assistive technology is expected to support both the person with MCI/D and their family carer.

Digital assistive technology is expected not only to improve coping and safety for the person with MCI/D but also to alleviate the carer burden. Prior research has found that family carers of relatives with dementia are more often at risk of ill health and depression than family carers of relatives with other diseases.11–13 However, the carer burden can be experienced differently. Family caregivers who considered themselves to have control of the situation were more likely to cope with their caring obligations.11 A more recent study found that adult children carers considered themselves to play an important role supporting elderly parents in need of care.14 Since 2011, community health care services have been encouraged to integrate digital assistive technology in the home care services to increase quality and efficiency in the health services and to reduce costs.15 This is in line with international policy and research.16–18

More than 300 municipalities have joined the Norwegian national project to implement digital assistive technologies such as global positioning system (GPS), electronic medicine dispensers, and electronic door locks (to secure access for health care workers). Results from these trials demonstrate the potential economic benefits that can be realized within the home care services.19 Expectations of the potential of technology to support older adults at home and the home care services are therefore high, however, it though contingent on usability and acceptability.

Usability is defined by International Organization for Standardization as

the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use.20

Weichbrot (2020) conducted a systematic literature review and identified many criteria for usability, among which learnability (easy to use), memorability (easy to remember how to use), cognitive load and errors were in the top seven, along with effectiveness, efficiency, and satisfaction.21 Acceptability is defined as “the degree of primary users’ predisposition to carry out daily activities using the intended device”.22–24

In 2020 we reproduced the literature search to explore whether there had been any developments regarding trials of new digital assistive technologies to assist older adults with MCI/D at home. The research questions for the current literature review are:

  • What types of technologies were explored in trials with home-dwelling older adults with MCI/D during 2017–2020?
  • What were the main outcomes regarding usability and acceptability of the technology interventions?
  • What was the impact on occupational performance, quality of life (QoL), and human dignity for independent living?

Materials and Methods

This systematic literature search identified literature published between January 2017 and September 2020.

Information Sources

We reused the same inclusion and exclusion criteria and the same search strategy as in the 2017 review. We searched in the five databases MEDLINE, PsycINFO, Embase, Amed and Cinahl using each base’s medical subject heading terms (MeSH) to ensure validity in the respective thesauri (Table 1). Three specialist librarians at Oslo Metropolitan University assisted with the search in September 2020.

Table 1 Search Strategy PsycINFO With Mesh Terms

Inclusion Criteria

  • Primary studies on technology trials with older people with mild cognitive impairment and dementia (MCI/D)
  • Titles or keywords including technology or type of technology
  • Titles or keywords including a population with mild cognitive impairment, dementia, early-stage dementia or Alzheimer’s disease
  • Home-dwelling older adults

Exclusion Criteria

  • Not target population (MCI/D)
  • Not primary study/technology trial
  • Laboratory studies (including smart labs)
  • Not technology for supporting everyday living eg wheel chairs, shower rails and seats, mobility aids, etc.
  • Long-term care/nursing home/assisted living
  • Conference papers, editorials, research protocols
  • Review articles or meta-analyses
  • Books, book chapters

The Study Selection

A total of 1452 references from the period 2017–2020 was identified. We used an adapted version of the Prisma statement for selecting papers.25 After removing duplicates (47), 1405 references remained for screening to identify primary studies with the following selection criteria: MCI/D, technology, and home-dwelling. All titles were screened for relevance by all three authors using the Rayyan web-based tool, and those meeting the inclusion criteria were selected.26 This resulted in 1365 papers being declined and 40 papers being deemed eligible for full-text reading. Twenty-six references were excluded after reading the full-text versions, due to wrong context (nursing home, assistive living or lab studies) (12), wrong population (not MCI/D) (3), wrong design (not primary study/trial) (10), or to being a conference paper (1). The number of remaining papers eligible for review was 14 (Figure 1).

Figure 1 PRISMA flowchart for selection of papers. Adapted from Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009) Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009;6(7): e1000097.25

The Review Processes

The three authors read all the 14 papers eligible for review. The quality of the papers was appraised according to the Mixed Method Appraisal Tool (MMAT), version 2018.27 MMAT allows empirical studies, ie experimental, simulation or observational studies, and different research designs (qualitative, quantitative, and mixed method). Each author reviewed two-thirds of the papers, to meet the criteria of two authors being involved in the appraisal process and reaching agreement on each criterion.27


The 14 studies included in this review took place in UK (7), France (1), Germany (2), Finland (1), Greece (1), Denmark (1), and USA (1). By comparison, the top three countries conducting trials on technology with older adults with MCI/D in the 2017 review were: UK (five studies), the Netherlands (five studies) and Sweden (four studies). Moreover, the research design had changed; while the 2017 review largely consisted of research papers with a qualitative design and few participants, the 2020 review consisted of more research papers with quantitative design and more participants. The study design of the reviewed papers was distributed as follows:27

Design 1.Qualitative: 1 study

Design 2.Quantitative randomized controlled trials: 2 studies

Design 3.Quantitative non-randomized: 6 studies

Design 4.Quantitative descriptive: 2 studies

Design 5.Mixed method: 3 studies

Table 2 shows an overview of the quality of the papers included, according to MMAT. Numbers of Y (yes) indicate higher quality, ie seven Ys indicate the highest quality. Numbers of N (no) or CT (cannot tell) indicate lower methodological quality.

Table 2 Quality Assessment According To MMAT20

Table 3 provides an overview of abstracted data structured in the following categories: name of author, title of paper, year of publishment, doi, and country; type of technology used in the trial; aim and purpose of the study; design according to MMAT and quality assessment; number of participants with MCI/D, family carers/staff and age; method; duration of intervention; reports on usability and acceptability; Reports on impact on QoL, occupational performance, human dignity; and results/conclusion.

Types of Technologies Identified and Categorized

To answer the first research question, the types of assistive technologies explored in trials with home-dwelling older adults with MCI/D during 2017–2020 can be categorized into five groups:

1.Wearables. Five papers on wearable technologies; wristband biosensors, smartwatches with GPS, wrist-worn activity monitors, and binaural hearing aids.28,31,34,37 The purpose of these devices is to support safe and healthy living.

2.Environmental sensors and Internet-of-Things (IoT). Two papers on sensors communicating to promote reminders and safety at home and monitoring the home environment.30,32

3.Apps. Three papers exploring mobile phone apps to support activities of daily living (ADL), reminiscence, and a web-based mobile app and smartwatch.35,36,42

4.Tablet computers with touchscreen. Three papers on screens for prompting multi-step ADL tasks for viewing art.29,33,41

5.Various other supportive devices. Two papers. One on comparing the performance of using a blood pressure monitor, mobile phone and e-book reader in people with MCI/D and cognitively healthy, and one on four different devices to support people with dementia at home: a GPS bracelet, a web chat tablet computer, an audio alarm and a motion sensor with reminder.38,43

Usability and Acceptability of the Technologies in the Reviewed Papers

The answers to the second research question about the outcomes of using the technologies with regard to usability and acceptability will be presented in the five sections below.


The purpose of the studies in Group 1 was to monitor people with dementia and their body functions, report on activity, and report physical and physiological markers of significance.

One pilot study from Greece, as part of the EU project INLIFE, explored a wearable wristband connected to a tablet and a telemonitoring platform. The wristband transmitted bio-parameters such as blood pressure, heart rate, daily steps, and hours of sleep. The application provided alerts, warnings and motivational messages to the user and family caregiver. The 230 participants with MCI/D, 160 family carers and 30 health care staff accepted the technology, and health care staff were enthusiastic about being able to remotely monitor patients. Usability of the wristband was not reported.34

A second study tested usability and acceptability of two equivalent GPS clocks on 17 dyads among individuals with MCI/D and their family caregivers. They tested one of two commercially available smartwatches for four weeks. Thereafter, the dyads tried the second smartwatch for four new weeks. The results showed that even though the products were similar, the dyads preferred one smartwatch over the other, resulting in new knowledge on design features. The device should contain few buttons, show a clear font with parsimonious text, and have a battery capacity of at least 24 hours. The usability score decreased after four weeks of use, which may indicate that the users’ expectations could not be fully met or that technical difficulties may have contributed to fewer ratings of usability.37

One study by Farina et al measured physical activity in 26 community-dwelling people with dementia using wrist-worn activity monitors and evaluated acceptability and feasibility of the monitors.31 The study found that most of the participants were underactive. The wristband was accepted and was feasible for use by people with dementia. Furthermore, the participants saw project participation as vital to learning about their own activity profile as well as to contributing to dementia research. The participants’ suggestion for avoiding non-use of the activity monitors was to incorporate the device as part of a daily routine. However, technology malfunctions were reported in eight of the 17 activity monitors, which failed to report all activity during the four weeks. The eight devices stopped recording prior to the 30-day record capacity, probably due to battery insufficiency. The reason why the devices could not record during the whole period of only 23 days may have been due to an error in the device or because the researcher provided a device that was not fully charged.31

A more common wearable is hearing aids. It was hypothesized that older adults with MCI/D and age-related hearing loss (ARHL) would demonstrate fewer behavioral symptoms if provided with binaural hearing aids. Binaural aids are devices that are fitted to both ears and connected to give an overall sound. This ensures that the wearer can understand their surroundings without being overloaded with too many different sounds. The study found that access to hearing aids neither reduced neuropsychiatric symptoms nor increased quality of life. The paper did not report on usability or acceptability.28

Environmental Sensors and the Internet of Things

Group 2 concerns technologies that have emerged from smart homes and home-based technology aimed at promoting safety and well-being using the Internet of Things (IoT). One study (Technology Integrated Health Management (THIM)) discussed a technology-assisted monitoring system that uses IoT.30 It combined machine learning algorithms to analyze the correlation between environmental data (from PIR sensors, movement sensors, door sensors and pressure sensors) and psychological data (from measuring blood pressure, heart rate, body temperature and weight, and hydration twice daily) to detect changes in health status and well-being in people with MCI/D. The algorithms were trained to recognize agitation and unusual patterns with up to 80% accuracy, which is useful for diagnostic work and decision-making in caring for and supporting people with MCI/D and their family caregivers. The paper did not report on usability or acceptability of the technologies.30

A second study explored how family caregivers could monitor a non-cohabiting person with dementia by monitoring sensors (3rings digital plug) connected to a bedside lamp, TV or electric kettle via a mobile application. After a four-month trial, all the individuals with dementia were happy to be connected to the family caregiver through the device, and 18 of the 30 family caregivers reported a decrease in burden of care. If no alerts occurred in the morning, they could relax. This study provided an understanding of the use of monitoring technology, and the device was found acceptable and useful by the participants.32

Mobile Applications

The objective of the assistive technology presented in Group 3 was to support memory in people with MCI/D to better cope with daily activities and to better structure their everyday life. Applications made for smartphones can contain different functionalities. One study described a holistic cloud-based solution with a calendar that interacted with other features such as contacts, diary notes, memos and checklists, and that explored the applicability and usability of such an app for people with MCI/D and for their caregivers.42 The participants, 112 people with MCI/D and 98 family caregivers, had to download and activate the app themselves. Sixty-five people with MCI/D used the app for 90 days. They were divided into four groups according to frequency of use: 1) short use, 1–10 days, 2) early abandonment, 11–31 days, 3) late abandonment, 32–90 days, and 4) adopters, 90 days or longer. Different methods were used to investigate usability and applicability of the app and how often it was used. Timely introduction may explain successful adoption. However, 47 of the participants with MCI/D and 78 of the family caregivers never activated the app. The reasons for this varied; some felt it was too early to introduce the application or found it too difficult to use, while others preferred to buy alternative off-the-shelf solutions or to continue with a paper diary. The small number of participants made it difficult to draw any conclusions.42

Another study examined the use of a reminiscence app with 30 dyads of MCI/D and family caregivers for 12 weeks.36 A technology-based reminiscence app can facilitate opportunities for people with MCI/D to retain an empowered role and enjoy conversations around memories. However, access to relevant materials relies on the caregivers’ willingness to participate and on source memorabilia. The study aimed to investigate how the dyads engaged in the app and how machine learning could identify behavioral clusters that typified different levels of user engagement. The participants were divided into four clusters: 1) independent and consistent use of the app, 2) reliant on family caregiver for support in using the app and unpredictable usage patterns, 3) highly reliant on family caregiver for engagement with the app and inconsistent usage patterns, and 4) infrequent usage. The family caregivers’ views on and attitudes toward the technology impacted the relationship with and significance of the app. Those who did not accept the app could not support its use.36

A third study explored the feasibility and utility of a web-based mobile app and smartwatch called Social Support Aid (SSA) employing facial recognition software. It aimed to promote social engagement by assisting older adults with memory impairment to recall people they interacted with. The app was tested by 20 participants in the intervention group and 28 participants in the control group, with data collection after three and six months.35 The facial recognition failed because the camera only worked from certain angles. It took time to take photos and did not work in all types of lighting. Moreover, some found the device too heavy and bulky to carry around the neck, and the text too small to read. After six months, most of the participants concluded that the app was not useful for reasons of complexity and functionality, impracticality and stigma, and the enrollment process. However, some participants felt the device had potential to be useful and recommended improvements.35

Tablet Computers

One study explored how a tablet computer could prompt multi-step tasks at home for people with MCI/D by providing instructions in the form of text, photos/pictures, video clips or verbal messages. The study found that instructions with photo/picture prompts and video prompts required too much interpretation and therefore distracted the users if used alone. The combination of recorded voice audio prompts reinforced with text prompts was more effective, powerful, and best understood.29

Another study explored whether a “DIY-kit prompter package” consisting of a touchscreen with a user-friendly interface, a multi-step prompting software, and a manual could be used independently by people with MCI/D and their family caregivers at home, with little or no training.33 The prompter package aimed to support people with MCI/D to cope independently with daily tasks such as food preparation and household chores. Fourteen dyads were recruited, of which three withdrew and 11 participated by trying the prompter package for four weeks. All 11 family caregivers reported to have succeeded in loading at least one activity and its steps onto the tablet. Eight of the 11 people with MCI/D had been able to read and follow the steps and complete at least one activity successfully. There were no significant differences between the participants regarding cognitive functioning, though the successful dyads used the prompter more often than the unsuccessful dyads. Another finding was that family caregivers initiated use of the prompter more often than did the person with MCI/D.33

One study described how an art app on a tablet computer could be used for art-based interventions to provide well-being in 12 people with MCI/D and their family caregivers.41 The aim was to explore the impact of viewing art on a tablet computer; how it impacted subjective well-being in people with MCI/D, how they experienced the activity, and the family caregivers’ impressions of the impact of the activity on their relative. The tablet contained pictures from different art genres, and the dyads were asked to use it at least five times over two weeks. The art viewing sessions lasted 20 minutes and included 30 pictures on average. The qualitative findings indicated that reminiscence and cognitive stimulation occurred spontaneously, that the dyads had enjoyable conversations, and that they found a new shared activity that led to engagement in new activities such as visiting an art gallery or collecting new images from library books. The results suggest touchscreen-based art activities to be usable, acceptable and to yield well-being for this target group, ie older adults with MCI/D.41

Supportive Devices and Safety Systems

Some assistive technology may be presented as having a supportive purpose for home-dwelling people with MCI/D and their family caregivers. One German study assessed the occupational performance of 80 older adults, 39 with MCI and 41 healthy controls, using a blood pressure monitor, a mobile phone and a paper diary.43 By video-recording their performance and analyzing the video clips, they compared the two groups’ performance and handling of assistive technology. People with MCI made more mistakes and needed more support in using the devices than the healthy controls. Frequent errors included incorrect arm position or placement of the blood pressure cuff. The attitudes toward technology did not differ between the groups, even though all of them were relatively inexperienced users of technology. The study did not report on usability or acceptability of the technologies.43

Another study in this group explored the ability of four different assistive technologies to support family caregivers’ work and to support independence in people with MCI/D: a GPS safety bracelet, a web chat tablet, a short-range audio alarm and a reminder with motion sensor.38 The four technologies were tested for 25 and 38 days by four people with MCI/D at home and five people in an assisted living facility, respectively. The solution with the motion sensor and the mat pressure sensors connected at the short-range alarm to monitor door exits was perceived as useful and easy to use, despite seven of nine participants finding the sound quality poor. However, the study revealed problems regarding disturbances affecting the video phones and the battery in mobile applications quickly running out of power. The technology based on wireless networks and browser-based service management systems was particularly susceptible to failure. Far from all these issues could be resolved during the project period. The conclusion was that assistive technologies have the potential to support people with MCI/D and their family caregivers if the devices are found usable and easy to install, maintain and tailor individually to the user.38 In sum, findings on user-friendliness and acceptability of technology among the user groups continue to diverge.

Impact on Occupational Performance, QoL, and Human Dignity for Independent Living

Our third research question dealt with the impact of the technologies on occupational performance, QoL, and human dignity for independent living. Column nine in Table 3 presents the findings related to QoL, occupational performance, and human dignity in the reviewed studies (Table 3). None of the papers reported any explicit impact of technology to improve QoL in the participants. Some terms other than “quality of life” were used, ie reduced burden of care and positive impact on relationship, which can be linked to QoL.32,36,41 The term “occupational performance” was reported in only one of the 14 papers, ie on occupational performance from using three different devices.43 Human dignity was neither studied nor reported in any of the 14 papers.

Purposes of Digital Assistive Technology in the Review

Table 4 presents an overview of technologies evaluated and grouped according to the Norwegian Directorate of Health’s categorization, also used in our 2017 review:15 However, multi-purpose technologies were challenging to categorize since they could fit into more than one category.

Table 4 Overview of Types and Purposes of Technologies

● technology for safe walking indoors and outdoors,

● technology for safety at home,

● technology for independent living, and

● technology for entertainment and social communication.


This review aimed to compare the technologies explored in trials with older adults with MCI/D from the decade 2007–2017 and from the past three years (2017–2020), and to discuss usability and acceptability of new digital solutions regarding occupational performance, QoL, and human dignity for independent living. To summarize, we found that assistive technology solutions seem to have become more multifunctional over the past three years, with wearables, apps and sensor technology often combined with computers, functionality for two-way communication, with or without a camera. The studies placed more emphasis on supporting coping strategies and independence in the person with MCI/D by use of apps, and computer technology for entertainment, cognitive stimulation and for prompting successful performance of tasks to improve independence and well-being.29,33,36,38,41,42,44 Furthermore, sensor technology for monitoring physical health markers such as blood pressure, oxygen uptake, heart rate, etc. and for monitoring environmental conditions such as indoor temperature, controlling lighting, detecting presence or falls, predicting actions and alerting if something is wrong.30,32,34,43 This may indicate that the smaller studies elaborated knowledge that could be built on in quantitatively designed studies. It may also be that digital assistive technologies have become cheaper and more available for research projects. Monitoring technologies make it easier to evaluate use and benefit through logged events.

Interestingly, the search results in September 2020 for the previous three years (2017–2020) identified far more studies on trials than did the 2017 search for the period 2007–2017, with 1452 titles compared with 359 in 2017. Many studies on digital assistive technology among various user groups are currently taking place worldwide, and although MCI/D and home-dwelling people were inclusion criteria, several papers that also appeared in the search results reported on acquired brain impairment (ABI), cognitive impairments in children and adolescents, studies in nursing homes, and lab studies.

Moreover, the number of participants had also increased in terms of people with MCI/D, family carers, and health care workers (Table 2). A quick calculation reveals a tendency toward including almost twice as many participants in the studies in the 2017–2020 review, as in the 2007–2017 review.

The technologies explored in trials with people with MCI/D and their family carers seem to have shifted since the 2017 review from stand-alone devices at home toward technologies that can be worn on the body to monitor body functions and report states or imbalances. Moreover, research interest is more focused on mobile phones with apps and in wearables providing reminders and timely support, and monitoring health status.

Types of Technology

As stated above, digital assistive technologies seem to have developed between the two reviews, and have become smaller, more integrated systems, often with multiple purposes.30,34 Three strategies for support seem evident: prompting and reminding people with dementia, and monitoring people with dementia at home using environmental sensors and biosensors, and providing safety outdoors using GPS.30,32,37,38,43 Several of the papers aimed to evaluate feasibility and usability of the devices, reveal the preferred kind of prompting format, and to offer compensatory strategies using different apps.29,33,35,36,42 A few studies aimed to explore how tablet computers can offer entertainment and meaningful leisure.41,44 In the screening process we came across several papers describing trials with robot technology and augmented reality (AR).45–50 However, these were lab studies, or scoping studies and thus did not meet the inclusion criteria in the current review. Moreover, earlier trials have stressed usability issues such as user interface applicability for people with dementia. Grundy stated that technology should aim to make challenges associated with ageing less limiting.51 We would like to add challenges associated with cognitive impairment. Thus, new technology, which to a great extent is wearable or is provided as apps, must be explored with regard to user interface applicability for people with MCI/D. Moreover, wearable technologies should be comfortable, self-explanatory, usable, and acceptable by older adults with MCI/D.

Regarding Usability and Acceptability of the Technologies in the Review

Usability and acceptability are important to ensure older adults’ adoption of technologies. Column 8 in Table 3 presents details on usability and acceptability of the technologies explored in the trials. None of the papers explicitly addressed the concepts of usability and acceptability. Five of 14 papers did not use these terms at all. However, some used the terms useful, successful use, sense of gain, acceptable or utility in the sense that the technology may be user-friendly and of use. Two of the papers reported less usability of the technology due to technical problems, functionality, and complex user interfaces.35,38

User-friendly technology is perceived as a requirement for acceptability and adoption. The need for adapting technologies to older adults’ individual skills and preferences determines whether the technology will be used and found acceptable Person-centered tailoring of digital assistive technology is thus important. Research has found that appropriate services based on a whole systems approach to care is of importance to facilitate technology-enriched accommodation for people with dementia.52 Such knowledge indicates that a more extensive collaboration between health care and technology development companies is required to ensure that technology enriches older adult’s accommodations in a trustworthy way rather than create barriers and unreliable services. Moreover, user participation workshops for piloting technology regarding interfaces, user-friendliness, etc. will still be required to optimize usability and acceptability.

A more recent term, “intuitive design”, defines intuitive use as a characteristic of the interactive process between a specific user and the design.53 It means that the product’s design is based on principles from other domains that are well known to us, so that we can use our past experience to reason how it should be used. The designer must thus acquire knowledge of the target audience in order to succeed. None of the reviewed papers discussed intuitive design. This actualizes the call for user involvement in research and technology development.

Impact on Occupational Performance, QoL, and Human Dignity for Independent Living

The main interest in the 14 reviewed papers concerned feasibility and effectiveness of the technology. One study only explored occupational performance (Schmidt and Wahl). No questions were asked about QoL or human dignity. We may interpret this to indicate that developers are more interested in the technological features and possibilities than in how the technology influences everyday living. We argue that timely access to technology may support people with MCI/D to better cope with everyday situations by facilitating and simplifying occupational performance. This may lead to an improved sense of quality of life and human dignity.54 Most of us have an innate need to master daily activities that are important to us and to be respected as human beings. If technology were to address these issue, maybe more older adults would be willing to adopt digital assistive technology.

User Involvement in Technology Development Research

None of the papers reported on user/caregiver/stakeholder involvement in the design process of the technology evaluated. However, one study invited participants to keep notes in a diary about using the device, and at the end of the trial they were interviewed about their opinions on and satisfaction with wearing and using the device.31

The current review demonstrates the necessity to evaluate new digital technology with the target groups. Recruiting people with MCI/D and their family carers to research projects will create knowledge about cognitive impairment and how consequences manifest in everyday living as well as how technology could be incorporated. Such knowledge contributes to improved awareness of user needs for people with MCI/D and their carers.

Careful assessment of and dialog with the target groups are needed to obtain this knowledge. It requires meeting places for mapping and discussing user needs and the time to exchange views. One study by Lund et al reports on dialog cafés as a method of co-creation of knowledge.55 The time aspect proved to be particularly important, since the participants needed time to acquaint themselves with the form of involvement, and to feel comfortable in the groups and with the technology topics that were introduced. The study gave an example of how dialog cafés facilitated user involvement and enabled older adults to express their needs and provide their perspectives on assistive technologies, which in fact directed research and development in the main project.55

Adoption of technology is known to be slow in older adults. One study on older adults’ perspectives on assistive technology found that 60 of 82 respondents perceived themselves to be too old to get involved with technology. Furthermore, 55 of 82 agreed that technology was useful for others but not for them, yet 49 of 82 reported being accustomed to using computers, mobile phones and other technical equipment.56 This may indicate that there are huge differences in older adults’ knowledge of and practice in using technology. One may conclude that adoption of technology is dependent upon technology literacy. However, it could also be due to lack of information and training, of Wi-Fi or of the economic resources to buy equipment and subscriptions to data services and programs. One recent study found that older adults could learn to use a tablet with a touchscreen successfully through five coping strategies: 1. having a supportive environment encouraging the person to use it and offer help to do so; 2. interest and motivation were created when they realized they could continue doing meaningful activities on the tablet, such as reading newspapers; 3. operating the tablet seemed easy for many, which led to positive experiences and confidence in using it; 4. being able to maintain contact with family, friends and society was the most important aspect of using the tablet; and 5. having personal strategies to ease use of the tablet, such as using the little finger or a tablet pen to be sure to click on the right button contributed to a positive experience.57

Possible Biases

Several biases may threaten the credibility of our study. First, due to terminological variations in the databases and the large number of keywords in our search strategy, we had to convert the keywords to relevant MeSH terms for each database. For example, the original keyword “assistive technology” was converted to “assistive or self-help or everyday or daily living or dementia friendly or welfare, technology or device* or aid” (Table 1). However, using the same search strategy as in the 2017 review was found to be fruitful and appropriate for exploring the field three years later.

Moreover, the quality assessment process using the MMAT criteria was carried out separately by each author, before the three authors met to agree on the ratings. If any discrepancies arose, the author who had not rated the paper in question was asked to assess it.


Research interest in technology to support older citizens with MCI/D at home is increasing. This is important because there is a need for more knowledge on how technology works in practical settings and how it influences everyday living for people with MCI/D. This systematic review demonstrates that research studies conducted over the past three years have increasingly reported on wearable and environmental digital assistive technologies, often with multiple purposes. Three strategies for support seem evident: prompting and reminding people with dementia, monitoring people with dementia at home using environmental sensors and biosensors and providing safety outdoors. Nonetheless, dementia-friendly technologies have yet to be developed. Thus, there is still a need for further research on the impact of these technologies on occupational performance, QoL, and human dignity for independent living.


We want to thank librarians Linn Kristine Kristensen, Malene Wøhlk Gundersen and Hege Kristin Ringnes at Oslo Metropolitan University for their supervision and support in performing systematic searches in all the relevant databases.


The authors report no conflicts of interest in this work.


1. Morgendagens omsorg. Meld.St 29 (2012-2013). [The Care of Tomorrow]; 2013.

2. Meld. St. 15 (2017-2018). Leve hele livet – en kvalitetsreform for eldre. Helse- og omsorgsdepartementet. [A full life – all your life — a Quality Reform for Older Persons. Ministry of Health and Care Services]; 2018.

3. World Health Organization. Global action plan on the public health response to dementia. World Health Organization. Available from:;jsessionid=4DA480FA93471AC53988E52B35F416D8?sequence=1. Accessed April 1, 2022.

4. World Health Organization. Decade of healthy ageing: baseline report. World Health Organization. Available from: Accessed April 1, 2022.

5. Alzheimer Europe. Dementia in Europe yearbook 2019: estimating the prevalence of dementia in Europe. Available from: Accessed April 1, 2022.

6. Alzheimer’s Association. Fact and figures. Available from: Accessed April 1, 2022

7. Gjøra L, Kjelvik G, Strand BH, Kvello-Alme M, Selbæk G. Forekomst av demens i Norge. [Prevalence of dementia in Norway]. Forlaget Aldring og helse; 2020.

8. Engedal K, Haugen PK, eds. Demens – Sykdommer, Diagnostikk Og Behandling. 1. Utgave. [Dementia – Diseases, Diagnostics and Treatment]. Forlaget Aldring og helse – akademisk; 2018.

9. World Health Organization. Dementia. Available from: Accessed July 20, 2020.

10. Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment – beyond controversies, towards a consensus: report of the International working group on mild cognitive impairment. J Intern Med. 2004;256(3):240–246. doi:10.1111/j.1365-2796.2004.01380.x

11. Bruvik FK, Ulstein ID, Ranhoff AH, Engedal K. The effect of coping on the burden in family carers of persons with dementia. Aging Ment Health. 2013;17(8):973–978. doi:10.1080/13607863.2013.790928

12. Bjorge H, Kvaal K, Smastuen MC, Ulstein I. Relationship quality and distress in caregivers of persons with Dementia: a cross-sectional study. Am J Alzheimers Dis Other Demen. 2017;32(3):157–165. doi:10.1177/1533317517691121

13. Ulstein I, Bruun Wyller T, Engedal K. The relative stress scale, a useful instrument to identify various aspects of carer burden in dementia? Int J Geriatr Psychiatry. 2007;22(1):61–67. doi:10.1002/gps.1654

14. Jakobsen FA, Ytterhus B, Vik K. Adult children’s experiences of family occupations following ageing parents’ functional decline. J Occup Sci. 2020;28(4):525–536. doi:10.1080/14427591.2020.1818611

15. NOU 11. Innovasjon i omsorg. [Innovation in care services]; 2011.

16. EU. Assistive technologies for disabled people. Part IV: legal and socio-ethical perspectives. IN-DEPTH ANALYSIS Science and Technology Options Assessment EPRS. Available from: Accessed October 21, 2021.

17. Thordardottir B, Malmgren Fange A, Lethin C, Rodriguez Gatta D, Chiatti C. Acceptance and use of innovative assistive technologies among people with cognitive impairment and their caregivers: a systematic review. Biomed Res Int. 2019;2019:9196729. doi:10.1155/2019/9196729

18. World Health Organization. Assistive technology Available from: Accessed October 21., 2021.

19. Norwegian Directorate of Health. Gevinstrealiseringsrapport. En kunnskapsoppsummering fra Nasjonalt Velferdsteknologiprogram. [Report on benefits realization. A knowledge summary from the national program on welfare technology]. Helsedirektoratet, Direktoratet for e-helse, KS. Gevinstrealiseringsrapport – en kunnskapsoppsummering fra Nasjonalt Velferdsteknologiprogram; 2021.

20. Standardization IOf. ISO 9241-110:2020 Ergonomics of human-system interaction — part 110: interaction principles ISO. Available from: Accessed April 1, 2022.

21. Weichbroth P. Usability of mobile applications: a systematic literature study. IEEE Access. 2020;8:55563–55577. doi:10.1109/access.2020.2981892

22. Holthe T, Halvorsrud L, Karterud D, Hoel KA, Lund A. Usability and acceptability of technology for community-dwelling older adults with mild cognitive impairment and dementia: a systematic literature review. Clin Interv Aging. 2018;13:863–886. doi:10.2147/CIA.S154717

23. Thordardottir B, Malmgren Fänge A, Lethin C, Rodriguez Gatta D, Chiatti C. Acceptance and use of innovative assistive technologies among people with cognitive impairment and their caregivers: a systematic review. Biomed Res Int. 2019;2019:1–18. Article ID 9196729. doi:10.1155/2019/9196729

24. Cavallo F, Aquilano M, Arvati M. An ambient assisted living approach in designing domiciliary services combined with innovative technologies for patients with Alzheimer’s disease: a case study. Am J Alzheimers Dis Other Demen. 2015;30(1):69–77. doi:10.1177/1533317514539724

25. Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009) Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009;6(7): e1000097.

26. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210. doi:10.1186/s13643-016-0384-4

27. Hong QN, Pluye P, Fabregues S, et al. Mixed Methods Appraisal Tool (MMAT) version 2018. User guide. Canada; 2018.

28. Adrait A, Perrot X, Nguyen MF, et al. Do hearing aids influence behavioral and psychological symptoms of dementia and quality of life in hearing impaired Alzheimer’s disease patients and their caregivers? J Alzheimers Dis. 2017;58(1):109–121. doi:10.3233/JAD-160792

29. Boyd HC, Evans NM, Orpwood RD, Harris ND. Using simple technology to prompt multistep tasks in the home for people with dementia: an exploratory study comparing prompting formats. Dementia. 2017;16(4):424–442. doi:10.1177/1471301215602417

30. Enshaeifar S, Zoha A, Markides A, et al. Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques. PLoS One. 2018;13(5):e0195605. doi:10.1371/journal.pone.0195605

31. Farina N, Sherlock G, Thomas S, Lowry RG, Banerjee S. Acceptability and feasibility of wearing activity monitors in community-dwelling older adults with dementia. Int J Geriatr Psychiatry. 2019;34(4):617–624. (). doi:10.1002/gps.5064

32. Fowler-Davis S, Barnett D, Kelley J, Curtis D. Potential for digital monitoring to enhance wellbeing at home for people with mild dementia and their family carers. J Alzheimers Dis. 2020;73(3):867–872. doi:10.3233/JAD-190844

33. Harris N, Boyd H, Evans N, et al. A preliminary evaluation of a client-centred prompting tool for supporting everyday activities in individuals with mild to moderate levels of cognitive impairment due to dementia. Dementia. 2021;20(3):867–883. doi:10.1177/1471301220911322

34. Kaimakamis E, Karavidopoulou V, Kilintzis V, Stefanopoulos L, Papageorgiou V. Development/Testing of a monitoring system assisting MCI patients: the European project INLIFE. Stud Health Technol Inform. 2017;242:583–586.

35. McCarron HR, Zmora R, Gaugler JE. A web-based mobile app with a smartwatch to support social engagement in persons with memory loss: pilot randomized controlled trial. JMIR Aging. 2019;2(1):e13378. doi:10.2196/13378

36. McCauley CO, Bond RB, Ryan A, et al. Evaluating user engagement with a reminiscence app using cross-comparative analysis of user event logs and qualitative data. Cyberpsychol Behav Soc Netw. 2019;22(8):543–551. doi:10.1089/cyber.2019.0076

37. Megges H, Freiesleben SD, Ludtke V, Rosch C, Peters O. A longitudinal user study testing two locating systems in home dementia care. Alzheimers Dementia. 2017;13(7):P165–P166. doi:10.1016/j.jalz.2017.06.2614

38. Nauha L, Keranen NS, Kangas M, Jamsa T, Reponen J. Assistive technologies at home for people with a memory disorder. Dementia. 2018;17(7):909–923. doi:10.1177/1471301216674816

39. Oksnebjerg L, Janbek J, Woods B, Waldemar G. Assistive technology designed to support self-management of people with dementia: user involvement, dissemination, and adoption. A scoping review. Int Psychogeriatr. 2020;32(8):937–953. doi:10.1017/S1041610219001704

40. Schmidt LI, Wahl H-W. Predictors of performance in everyday technology tasks in older adults with and without mild cognitive impairment. Gerontologist. 2019;59(1):90–100. doi:10.1093/geront/gny062

41. Tyack C, Camic PM. Touchscreen interventions and the well-being of people with dementia and caregivers: a systematic review. Int Psychogeriatr. 2017;29(8):1261–1280. doi:10.1017/S1041610217000667

42. Oksnebjerg L, Woods B, Vilsen CR, et al. Self-management and cognitive rehabilitation in early stage dementia – merging methods to promote coping and adoption of assistive technology. A pilot study. Aging Ment Health. 2020;24(11):1894–1903. doi:10.1080/13607863.2019.1625302

43. Schmidt LI, Wahl HW. Predictors of performance in everyday technology tasks in older adults with and without mild cognitive impairment. Gerontologist. 2019;59(1):90–100. doi:10.1093/geront/gny062

44. Silva AR, Pinho MS, Macedo L, Moulin C, Caldeira S, Firmino H. It is not only memory: effects of sensecam on improving well-being in patients with mild Alzheimer disease. Int Psychogeriatr. 2017;29(5):741–754. doi:10.1017/S104161021600243X

45. D’Onofrio G, Sancarlo D, Raciti M, et al. MARIO project: validation and evidence of service robots for older people with Dementia. J Alzheimers Dis. 2019;68(4):1587–1601. doi:10.3233/JAD-181165

46. Darragh M, Ahn HS, MacDonald B, et al. Homecare robots to improve health and well-being in mild cognitive impairment and early stage dementia: results from a scoping study. J Am Med Dir Assoc. 2017;18(12):1099.e1–1099.e4. doi:10.1016/j.jamda.2017.08.019

47. Law M, Sutherland C, Ahn HS, et al. Developing assistive robots for people with mild cognitive impairment and mild dementia: a qualitative study with older adults and experts in aged care. BMJ Open. 2019;9(9):e031937. doi:10.1136/bmjopen-2019-031937

48. Wang RH, Sudhama A, Begum M, Huq R, Mihailidis A. Robots to assist daily activities: views of older adults with Alzheimer’s disease and their caregivers. Int Psychogeriatr. 2017;29(1):67–79. doi:10.1017/S1041610216001435

49. Chandrasekera T, Kang M, Hebert P, Choo P. Augmenting space: enhancing health, safety, and well-being of older adults through hybrid spaces. Technol Disabil. 2017;29(3):141–151. doi:10.3233/tad-170159

50. Rohrbach N, Gulde P, Armstrong AR, et al. An augmented reality approach for ADL support in Alzheimer’s disease: a crossover trial. J Neuroeng Rehabil. 2019;16(1). doi:10.1186/s12984-019-0530-z

51. Grundy J, Mouzakis K, Vasa R, et al. Supporting Diverse Challenges of Ageing with Digital Enhanced Living Solutions. In: Telehealth for Our Ageing Society. IOS Press; 2018:75–90. doi:10.3233/978-1-61499-845-7-75

52. Rondon-Sulbaran J, Daly Lynn J, McCormack B, Ryan A, Martin S. The transition to technology-enriched supported accommodation (TESA) for people living with dementia: the experience of formal carers. Ageing Soc. 2020;40(10):2287–2308. doi:10.1017/S0144686X19000588

53. Interaction Design Foundation. Intuitive Design; 2021. Available from: Accessed August 26, 2021.

54. Tranvag O, Petersen KA, Naden D. Relational interactions preserving dignity experience: perceptions of persons living with dementia. Nurs Ethics. 2015;22(5):577–593. doi:10.1177/0969733014549882

55. Lund A, Holthe T, Halvorsrud L, et al. Involving older adults in technology research and development discussions through dialogue cafes. Res Involv Engagem. 2021;7(1):26. doi:10.1186/s40900-021-00274-1

56. Halvorsrud L, Holthe T, Karterud D, Thorstensen E, Lund A. Perspectives on assistive technology among older Norwegian adults receiving community health services. Disabil Rehabil Assist Technol. 2021:1–8. doi:10.1080/17483107.2021.1906962

57. Sølvsberg AM, Lund A. Det var jo en voldsom åpenbaring. En studie av nettbrettbruk i hverdagslivet til Omsorg+-beboere. [What a revelation. A study on using tablets as part of everyday living for residents in a care home]. Ergoterapeuten. 2021;2:38–47.

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