Published on in Vol 4, No 4 (2021): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28165, first published .
Personalized Visual Mapping Assistive Technology to Improve Functional Ability in Persons With Dementia: Feasibility Cohort Study

Personalized Visual Mapping Assistive Technology to Improve Functional Ability in Persons With Dementia: Feasibility Cohort Study

Personalized Visual Mapping Assistive Technology to Improve Functional Ability in Persons With Dementia: Feasibility Cohort Study

Original Paper

1Birmingham/Atlanta VA Geriatric Research Education and Clinical Center, Atlanta, GA, United States

2MapHabit, Inc, Atlanta, GA, United States

3Atlanta VA Health Care System, Decatur, GA, United States

4Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United States

5Division of Hospital Medicine, Department of Medicine, Emory University, Atlanta, GA, United States

6Division of Geriatrics & Gerontology, Department of Medicine, Emory University, Atlanta, GA, United States

*all authors contributed equally

Corresponding Author:

Jessica Kelleher, MSc

Birmingham/Atlanta VA Geriatric Research Education and Clinical Center

3101 Clairmont RD

Atlanta, GA, 30329

United States

Phone: 1 404 315 4100 ext 373125

Email: jessica.kelleher@va.gov


Background: Mobile health (mHealth) apps using novel visual mapping assistive technology can allow users to develop personalized maps that aid people living with cognitive impairment in the recall of steps needed to independently complete activities of daily living (ADLs), such as bathing, toileting, and dressing.

Objective: This study aims to determine the feasibility and preliminary impact of an mHealth assistive technology app providing guidance to aid individuals living with cognitive impairment in the recall of steps to independently complete ADLs.

Methods: A total of 14 Veterans (mean age 65 SD 9.5 years; 14/14, 100% male; 10/14, 71.4% Black) and 8 non-Veterans (mean age 78, SD 10.3 years; 5/8, 62.5% male; 8/8, 100% Black) were recruited and enrolled from the Department of Veterans Affairs (VA) and non-VA cognitive care clinics. A visual mapping software program, MapHabit, was used to generate a series of personalized visual map templates focused on ADLs created within the MapHabit app. The visual maps were accessed through a tablet device. A 19-item exit questionnaire was administered to the participants to assess perceived improvement in their functional ability after using the MapHabit system for 3 months.

Results: A total of 13 (93%) VA clinic participants and 8 (100%) non-VA clinic participants completed the 3-month study. Baseline cognitive testing indicated impaired to significantly impaired cognitive function. After 3 months of using the MapHabit system, VA clinic participants reported perceived improvement in social engagement (P=.01) and performance of ADLs (P=.05) compared to the baseline, whereas non-VA clinic participants reported improvements in the performance of ADLs (P=.02), mood (P=.04), social engagement (P=.02), and memory (P=.02). All study participants reported they would recommend the MapHabit system to a colleague, and 85% (11/14) of VA and 100% (8/8) of non-VA clinic participants reported a willingness to participate in a future study.

Conclusions: Older VA and non-VA clinic participants with cognitive impairment were willing to use an mHealth app to assist with the completion of ADLs, and they reported positive preliminary effects. A larger study is warranted to assess the efficacy in the setting of a randomized controlled trial.

JMIR Aging 2021;4(4):e28165

doi:10.2196/28165

Keywords



More than 16 million family members provide unpaid care to a person with Alzheimer disease or other dementias [1]. A recent report estimated that 18.6 billion hours of unpaid care are provided annually, totaling to a value of US $244 billion [1]. In the future, an increase for in-home or institutional care and unpaid assistance by family and friends will be needed as the numbers of those with Alzheimer disease and other forms of cognitive impairment continue to grow. Maintenance of functional ability has been linked to improved quality of life among persons with dementia, and strategies that promote functional ability and independence are of high priority in dementia care research [2,3].

Two recent developments have converged in an attempt to effectively address this challenge. First, developments in the field of assistive technology, including the use of smart devices (eg, tablets, phones, and wearables) have provided ways to enhance the ability of caregivers—both family and professional—to assist individuals with dementia and memory impairment to successfully perform activities of daily living (ADLs), such as bathing, toileting, and dressing [4]. Importantly, there is cumulating evidence that technology adoption is being progressively embraced both among dementia care recipients and their caregivers, findings that bode well for the potential effectiveness of assistive technology interventions [5-7]. Second, developments in the field of neuroscience have shown that there are at least two systems important for memory: the declarative memory system, which is important for conscious recollection of facts and events in our lives, and a more recently recognized procedural, or habit system, that can underlie the development and maintenance of nonconscious habits, motor skills, and other forms of nonconscious procedural learning, often called implicit memory [8]. The present report takes advantage of these two developments in assistive technology and habit memory development and explores the possibility of their use in enhancing the quality of life and functional ability of individuals living with dementia.

MapHabit is a novel mobile health (mHealth) assistive technology app that allows users and/or caregivers to develop personalized maps that aid people living with cognitive impairment in the recall of steps needed to complete the above-described ADLs [4,9]. With repeated use of these maps, people with impaired memory can develop a habit of consulting their visual maps routinely and independently of their caregivers. In this paper, we describe the results from feasibility studies conducted in two clinical samples to determine whether people with cognitive impairment were willing to use the MapHabit system and whether there is evidence of potential benefit to inform a larger, more definitive study.


Study Setting and Ethical Approval

Participants for the feasibility study were recruited from two outpatient clinical programs: a Department of Veterans Affairs (VA) clinic and a non-VA academic health system clinic, focused on serving the needs of older adults with cognitive impairment. The protocol for each clinical cohort was approved by the Emory University Institutional Review Board, and all participants provided written informed consent. The protocols differed primarily based upon the requirement to recruit a care recipient–caregiver dyad in the non-VA clinic population. This provided the opportunity to assess the impact of assistive technology on two separate groups with similar levels of impairment belonging to two different US health systems. Data were analyzed separately for each cohort in order to comply with data information security protocols established by the VA. Here, we present data based on the outcomes assessed among participants living with cognitive impairment in each study group.

Intervention

A visual mapping software program was used to generate a series of visual map templates created by an assistive technology company, MapHabit, Inc. Participants accessed the software and visual maps through a mobile tablet device. Visual maps consisted of pictures and keywords in a step-by-step sequence to guide and assist participants with memory impairment in organizing and successfully accomplishing ADLs [4]. Participants were encouraged to self-select visual maps based on personal preferences and needs, and they could add images from their own environment to personalize the selected templates. Snapshots of the MapHabit system are presented in Figure 1. Visual maps involving ADL performance were commonly selected, with those pertaining to medication, bathing, and dressing being the most popular. After a staff member conducted initial training and development of selected ADL maps, participants were given an iPad to access and use the MapHabit system.

Figure 1. Screenshots of the MapHabit system app on mobile and tablet devices.
View this figure

Measures

Demographic characteristics included age, sex, self-reported race and ethnicity, and the presence of a caregiver. Baseline cognition was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), a brief, individually administered test measuring attention, language, visuospatial or constructional abilities, and immediate and delayed memory. The RBANS consists of 12 subtests, which yield 5 index scores of the measures described above, and a total scale score [10]. A 19-item overall exit questionnaire was administered to assess whether any change (positive or negative) occurred as a result of using the MapHabit system for 3 months. The questionnaire is provided in Multimedia Appendix 1. Questions were grouped to assess the various domains of ADL independence (questions #2, #3, #4, and #5 in the exit questionnaire), mood (questions #1, #7, #8, #9, #10, and #11), social engagement (questions #6, #13, #16, and #17), quality of life (questions #14 and #15), and self-reported memory impairment (question #12). The remaining questions of the measurement tool assessed the participants’ overall satisfaction with the MapHabit system. The questionnaire was administered orally to the participants, using a Likert scale with a self-rating format (5=much better, 4=better, 3=not much change, 2=worse, or 1=much worse). A 2-item yes/no questionnaire assessed participants’ overall user experience with the system.

Statistical Analysis

Baseline characteristics for each clinical sample were analyzed using descriptive statistics. Exit interview responses were compared using the Wilcoxon signed rank test to assess any differences from an expected result of “not much change”—that is, a score of 3 on the Likert scale for the exit questionnaire. Analyses were conducted using the RStudio statistical package (version 1.1.463).


In all, 14 VA clinic (mean age 65 SD 9.5 years; 14/14, 100% male; 10/14, 71% Black) and 8 non-VA clinic (mean age 78, SD 10.3 years; 5/8, 62.5% male; 8/8, 100% Black) participants were enrolled in the study (Table 1). Following the 3-month intervention, 13 of the 14 (93%) VA clinic participants and all 8 (100%) non-VA clinic participants completed the study. Baseline cognition measured by the RBANS indicated impaired to significantly impaired cognitive function, on average, across all 5 indices of neuropsychological function [6]. Immediate memory scores indicated impaired ability to remember information immediately after it was presented. Visuospatial or construction scores indicated impaired ability to perceive spatial relations and to construct a spatially accurate copy of a drawing. Language scores indicated impaired ability to respond verbally to either naming or retrieving learned material. Attention scores indicated impaired capacity to remember and manipulate both visually and orally presented information in short-term memory. Delayed memory scores indicated impaired anterograde memory. Total scale scores were calculated by summing the abovementioned 5 index scores.

After 3 months of using the MapHabit system, analysis of the overall exit questionnaire responses showed that both VA and non-VA clinic participants reported perceived improvement in social engagement (P=.01 and P=.02, respectively) and performance of ADLs (P=.05 and P=.02, respectively) compared to the baseline (Figure 2). Non-VA clinic participants also reported perceived improvement in mood (P=.04) and memory (P=.02; Figure 2). There was no significant perceived change in quality of life for either group (P=.09). Many participants reported using a particular map daily, such as to guide teeth-brushing, toileting, or showering. All VA and non-VA clinic participants reported they would recommend the MapHabit system to a colleague, and 85% (11/14) of VA and 100% (8/8) non-VA clinic participants reported a willingness to participate in a future study.

Table 1. Baseline characteristics of the Veterans Affairs (VA) and non-VA clinic participants.
CharacteristicVA cognitive clinic
(n=14)
Non-VA cognitive clinic
(n=8)
Age (years), mean (SD)65 (9.5)78 (10.3)
Gender, n (%)

Female0 (0)3 (37.5)

Male14 (100)5 (62.5)
Race, n (%)

White4 (28.6)0 (0)

Black or African American10 (71.4)8 (100)

Other0 (0)0 (0)
Are you of Hispanic or Latino origin, n (%)

Yes1 (7.1)0 (0)

No13 (92.9)8 (100)
Marital status, n (%)

Single3 (21.4)0 (0.0)

Married9 (64.4)5 (62.5)

Divorced1 (7.1)0 (0)

Widowed0 (0)3 (37.5)

Unknown1 (7.1)0 (0)
Baseline RBANSa, mean (SD)

Immediate memory score70.50 (18.7)56.75 (20.6)

Visuospatial score67.36 (10.6)70.12 (19.4)

Language score85.57 (14.2)71.00 (21.9)

Attention score74.64 (11.9)69.62 (10.3)

Delayed memory score62.00 (18.6)52.12 (20.4)

Total scale score63.07 (13.3)58.00 (15.6)

aRBANS: Repeatable Battery for the Assessment of Neuropsychological Status.

Figure 2. Exit interview responses from study participants 3 months after using personalized visual maps. Non-VA: non–Veterans Affairs clinic participants; VA: Veterans Affairs clinic participants.
View this figure

Principal Findings

The findings from the present studies indicate that the use of visual mapping, specifically the MapHabit system as an assistive technology, is feasible for individuals with memory impairment. Participants reported a positive experience in using the MapHabit system as an assistive technology, adding they would recommend it, and they would again engage with the MapHabit system if the opportunity arose in the future. Furthermore, our study findings suggest that use of the MapHabit system for 3 months may result in perceived improvement in social engagement and performance of ADLs.

Although it has been previously speculated that the use of technology is not widely accepted by older adults, the present results suggest otherwise. Similarly, a study investigating the feasibility of personalized technology use in individuals with mild cognitive impairment found that technology adoption was excellent among both care recipients and their caregivers [5]. Both the present MapHabit system and technology used in the previous study in a senior living community population [5] are personalized, which may suggest that personalization, wherein users are engaged in the selection of activities, serves as a facilitator in technology use among diverse populations of older adults.

Regarding the potential benefit of technology to users’ independence, a recent systematic review of the literature assessing assistive technology use among older adults found that both users and caregivers reported these technologies assisted caregivers by reducing the time, level of assistance, and energy expended on caregiving, as well as anxiety and fear, task difficulty, and safety risk. Previous research has suggested that these improvements were associated with increased independence of the user and reduced need for physical assistance with ADLs [11]. In our studies, both VA and non-VA clinic participants reported perceived improvement in performance of ADLs, echoing the finding that the use of assistive technologies may decrease caregiver burden by promoting increased independence in ADLs by the user.

Limitations

These studies are not without limitations. As feasibility studies, they were not designed to determine efficacy or definitive evaluation across all outcomes of interest. The outcomes were self-reported; however, patient-reported outcomes are likely the most relevant for determining the initial feasibility of an assistive technology in this population. Although these were not long-term studies, assistive technology appears to be a feasible delivery method for visual maps, and participants were willing to use the technology for at least 3 months. A larger, randomized controlled trial evaluating the visual MapHabit system in individuals living with memory impairment is warranted with a longer follow-up, to determine sustainability.

Conclusions

Novel findings from this study suggest that the assistive technology MapHabit system is a feasible delivery method for personalized visual maps that can aid people living with cognitive impairment in the recall of steps needed to complete ADLs with greater independence. Strong endorsement from two diverse clinical samples of older adults with cognitive impairment (eg, Black vs White, VA vs non-VA, and male vs female) suggests a potential broad appeal of personalized visual mapping as an assistive technology. Based on research priorities aimed at new strategies to promote ADL independence in individuals with cognitive impairment, the next step entails a definitive study to assess efficacy of personalized visual mapping.

Acknowledgments

We would like to acknowledge all study participants, as well as the study staff at Emory University and the Atlanta Veterans Affairs (VA) Health Care System for their contributions to the successful implementation of these trials. Both projects were funded by awards from the Georgia Research Alliance to Emory University. CPV receives support from the Birmingham/Atlanta VA Geriatric Research Education and Clinical Center. MWP receives support from the Goizueta Alzheimer’s Disease Research Center at Emory University (NIA 3P50AG025688). The study sponsors had no role in the design or conduct of the study; in the collection, management, analysis, or interpretation of the data; or in the approval of the manuscript for publication. All coauthors revised the article critically for important intellectual content and gave final approval of the version to be published.

Conflicts of Interest

An in-kind donation of the MapHabit system was made by MapHabit, Inc. SZ and MG are current employees of MapHabit, Inc. SL served on the Advisory Board of MapHabit, Inc. The researchers do not hold a direct financial interest in the sponsors, or the product being studied.

Multimedia Appendix 1

Exit interview questionnaire for caregivers or study participants.

DOCX File , 17 KB

  1. 2020 Alzheimer's disease facts and figures. Alzheimers Dement 2020 Mar 10;16(3):391-460. [CrossRef] [Medline]
  2. Martyr A, Nelis SM, Quinn C, Rusted JM, Morris RG, Clare L, IDEAL programme team. The relationship between perceived functional difficulties and the ability to live well with mild-to-moderate dementia: Findings from the IDEAL programme. Int J Geriatr Psychiatry 2019 Aug 20;34(8):1251-1261 [FREE Full text] [CrossRef] [Medline]
  3. Pickett J, Bird C, Ballard C, Banerjee S, Brayne C, Cowan K, et al. A roadmap to advance dementia research in prevention, diagnosis, intervention, and care by 2025. Int J Geriatr Psychiatry 2018 Jul 22;33(7):900-906 [FREE Full text] [CrossRef] [Medline]
  4. Boatman F, Golden M, Jin J, Kim Y, Law S, Lu A, et al. Assistive technology: visual mapping combined with mobile software can enhance quality of life and ability to carry out activities of daily living in individuals with impaired memory. THC 2020 Mar 20;28(2):121-128. [CrossRef]
  5. Kerssens C, Kumar R, Adams AE, Knott CC, Matalenas L, Sanford JA, et al. Personalized Technology to Support Older Adults With and Without Cognitive Impairment Living at Home. Am J Alzheimers Dis Other Demen 2015 Jan 22;30(1):85-97. [CrossRef]
  6. Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, et al. Current concepts in mild cognitive impairment. Arch Neurol 2001 Dec 01;58(12):1985-1992. [CrossRef] [Medline]
  7. Chaurasia P, McClean SI, Nugent CD, Cleland I, Zhang S, Donnelly MP, et al. Modelling assistive technology adoption for people with dementia. J Biomed Inform 2016 Oct;63:235-248 [FREE Full text] [CrossRef] [Medline]
  8. Squire LR, Zola SM. Structure and function of declarative and nondeclarative memory systems. Proc Natl Acad Sci U S A 1996 Nov 26;93(24):13515-13522 [FREE Full text] [CrossRef] [Medline]
  9. iCare-AD/ADRD Eureka Challenge Winners. National Institute on Aging. 2019 Oct.   URL: https://www.nia.nih.gov/icare-ad-adrd-eureka-challenge-winners [accessed 2021-06-01]
  10. Randolph C, Tierney MC, Mohr E, Chase TN. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): preliminary clinical validity. J Clin Exp Neuropsychol 1998 Jun 09;20(3):310-319. [CrossRef] [Medline]
  11. Madara Marasinghe K. Assistive technologies in reducing caregiver burden among informal caregivers of older adults: a systematic review. Disabil Rehabil Assist Technol 2016 Sep 15;11(5):353-360. [CrossRef] [Medline]


ADLs: activities of daily living
mHealth: mobile health
RBANS: Repeatable Battery for the Assessment of Neuropsychological Status.
VA: Department of Veterans Affairs


Edited by J Wang; submitted 23.02.21; peer-reviewed by H Strauven, S Ge; comments to author 01.06.21; revised version received 07.07.21; accepted 15.07.21; published 19.10.21

Copyright

©Jessica Kelleher, Stuart Zola, Xiangqin Cui, Shiyu Chen, Caroline Gerber, Monica Willis Parker, Crystal Davis, Sidney Law, Matthew Golden, Camille P Vaughan. Originally published in JMIR Aging (https://aging.jmir.org), 19.10.2021.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Aging, is properly cited. The complete bibliographic information, a link to the original publication on https://aging.jmir.org, as well as this copyright and license information must be included.