Review ArticleMobile-Health Applications for the Efficient Delivery ofHealth Care Facility to People with Dementia (PwD) andSupport to Their Carers: A Survey

Kanwal Yousaf ,1 Zahid Mehmood ,2 Tanzila Saba ,3 Amjad Rehman,4

Asmaa Mahdi Munshi,5 Riad Alharbey ,5 andMuhammad Rashid6

1Department of Software Engineering, University of Engineering and Technology, Taxila 47050, Pakistan2Department of Computer Engineering, University of Engineering and Technology, Taxila 47050, Pakistan3College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia4College of Business Administration, Al-Yamamah University, Riyadh 11512, Saudi Arabia5College of Computer Science and Engineering, University of Jeddah, Jeddah 21577, Saudi Arabia6Department of Computer Engineering, Umm Al-Qura University, Makkah 21421, Saudi Arabia

Correspondence should be addressed to Kanwal Yousaf; kanwal.yousaf@uettaxila.edu.pkand Zahid Mehmood; zahid.mehmood@uettaxila.edu.pk

Received 5 December 2018; Accepted 5 March 2019; Published 27 March 2019

Academic Editor: Stavros Baloyannis

Copyright © 2019 Kanwal Yousaf et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Dementia directly influences the quality of life of a person suffering from this chronic illness. The caregivers or carers of dementiapeople provide critical support to thembut are subject to negative health outcomes because of burden and stress.The interventionofmobile health (mHealth) has become a fast-growing assistive technology (AT) in therapeutic treatment of individuals with chronicillness. The purpose of this comprehensive study is to identify, appraise, and synthesize the existing evidence on the use of mHealthapplications (apps) as a healthcare resource for people with dementia and their caregivers. A review of both peer-reviewed andfull-text literature was undertaken across five (05) electronic databases for checking the articles published during the last five years(between 2014 and 2018). Out of 6195 searches yielded articles, 17 were quantified according to inclusion and exclusion criteria.The included studies distinguish between five categories, viz., (1) cognitive training and daily living, (2) screening, (3) health andsafety monitoring, (4) leisure and socialization, and (5) navigation. Furthermore, two most popular commercial app stores, i.e.,Google Play Store and Apple App Store, were searched for finding mHealth based dementia apps for PwD and their caregivers.Initial search generated 356 apps with thirty-five (35) meeting the defined inclusion and exclusion criteria. After shortlisting ofmobile applications, it is observed that these existing apps generally addressed different dementia specific aspects overlying withthe identified categories in research articles. The comprehensive study concluded that mobile health apps appear as feasible ATintervention for PwD and their carers irrespective of limited available research, but these apps have potential to provide differentresources and strategies to help this community.

1. Introduction

Dementia is considered as one of the most challengingconditions in older people that affects not only the peoplewith this chronic illness but also their nonprofessional orinformal caregivers. It is a complex syndrome with pro-gressive decline in cognitive functioning such as thinking,remembering, and reasoning [1]. National Institute on Aging

(NIA) stated that dementia is a brain disorder that disturbsthe cognitive and behavioural abilities to such an extent that ithinders a person’s daily living activities [2]. A study [3] basedon the Delphi consensus technique estimated the globalprevalence of dementia. This report stated that approximately24.3 million people suffered from dementia in the year 2001and this number is expected to double in every 20 years,i.e., 42.3 million PwD in 2020 and 81.1 million in 2040.

HindawiBioMed Research InternationalVolume 2019, Article ID 7151475, 26 pageshttps://doi.org/10.1155/2019/7151475

2 BioMed Research International

Year 2001 Year 2010 Year 2020 Year 2030 Year 2040 Year 2050HIC 9.7 14.9 15.01 24.3 23.4 34.6LMIC 14.6 20.6 27.3 41.4 57.7 80.8

9.714.9 15.01

24.3 23.4

34.6

14.620.6

27.3

41.4

57.7

80.8

0

10

20

30

40

50

60

70

80

90

100

Num

ber o

f peo

ple w

ith d

emen

tia(m

illio

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Growth in number of dementia people (millions) in high income countries (HIC) Vs. low-and-middle income countries (LMIC)

Figure 1: The number of people with dementia disease (millions) in high-income countries vs. low-and-middle-income countries from theyear 2001 to the year 2050 [3, 4].

Prince et al. [4] also projected the risks of rise in dementiacases from 65.7 million to 115.4 million in the duration of2030 to 2050. The current and future estimated ratio of PwDin developing countries (low-and-middle-income countries(LMIC)) is greater than in developed countries (high-incomecountries (HIC)). Approximately 58% of the total PwD casesin 2010 were from developing countries (LMIC) and wereestimated to upsurge to 70% in 2050. The total number ofdementia people (in millions) in HIC vs. LMIC (from 2001to 2050) is exemplified in Figure 1 by using the statistics ofFerri et al. [3] and Prince et al. [4].

Although many health organizations approved differentkinds of medications for the treatment of mild to moderatedementia disease, still these medicines do not cure, reverse,or tackle the underlying root problem causing dementia.Additionally, dementia treatment consumes a large numberof resources andmoney [5].The treatment cost increases withthe severity of dementia [6]. Moreover, PwD need care asper their severity level and the majority of which is providedby their family members who are usually inexpert for thisdemanding role. Family members are commonly consideredas the main source of providing physical, emotional, social,and financial support, due to which they encounter differentchallenges like anxiety, depression, hopelessness, and poorquality of life [7]. Therefore, in the absence of a cure andlimited care skills of caregivers, more advanced strategiesneed to be developed to maximize the quality of life andpromote the independence of high need and high-costdementia patients [8].

In this context, the assistance of technology offers muchpotential and can improve the quality of life of people withdementia and their informal caregivers [9]. Recent initiativesin smart devices (i.e., smartphones, portable workstations,tablets, etc.) have made mobile applications a promisingsource for engaging people in healthcare [10], particularlyPwD with high healthcare needs [11, 12]. Mobile Health, aka

mHealth, is the provision of a healthcare facility to people byusing a mobile device. Approximately over 50,000 medicinerelated applications are available for mobile devices and themajority of these applications are free [13]. Researches [14–20]indicated that PwD can use touchscreen devices easily, andthis technology is able to provide a wide range of benefits tothem and their caregivers. It makes a valuable opportunity fordevelopers to deliver a meaningful app by adding engagingactivities for such people to live their life more independently.

The aim of this paper is to provide a comprehensivereview of existing research that supports the evidence of usingmHealth applications in dementia healthcare. The researchpaper is organized as follows: next section provides thebackground research on dementia and the role of assistivetechnology in dementia healthcare. Then, the underlyingmethodology of the research is presented and followed bythe existing research studies about mHealth apps used fordementia healthcare. Afterwards, currently available smart-phone apps in Android and iOS markets were listed. Thepaper closes with the conclusion.

2. Background and Related Work

Familiarity with dementia history is essential for healthprofessionals, informal caregivers, and health policy makers.It is also important because dementia cases are elevatingsignificantly with every passing year and intensifying theuse of national resources. Roberts and Caird [21] made acorrelation of CrichtonGeriatric behavioural rating scale [22]with their own dementia rating scale and divided subjectsinto four major categories as shown in Table 1. Later on,the global numeric scale was devised [23] to quantify theseverity of dementia symptoms and was termed as a clinicaldementia rating (CDR) system. The cognitive and functionalperformance of patient screened in six areas, such asmemory(M), orientation (O), judgment and problem solving (JPS),

BioMed Research International 3

Table 1: Categories of dementia and level of memory impairment [21, 23].

Dementia Type Memory Impairment Level0 (Normal) No mental abnormality but has a minor degree of memory impairment.1 (Mild) Definite memory impairment and calculating ability.2 (Moderate) Definite memory impairment, but also disorientation for time and/or place.3 (Severe) Definite memory impairment, but also the difficulty of self-care.

community affairs (CA), home and hobbies (HH), andpersonal care (PC). At the end of the screening, patients wereassigned with a rating ranging from 0 (normal) to 3 (severedementia).

As far as the connection of cost-dementia severity isconcerned, Jonsson and Wimo [24] estimated that the costassociated with the care of dementia patient escalates withthe severity of the disease. The findings of world Alzheimerreport 2015 [25] alsomentioned an increment in global cost ofdementia by 35% in duration of 2010 to 2015 due to increasingdementia population and the cost of per person treatment.It is observed that carers such as family members play apivotal role in providing the caregiving facility to PwD. Thischronic disease directly influences the quality of life of aperson, his/her family, and caregivers. The ratio of dementiapeople living in homes is higher as compared to hospitals orhealthcare centres [5]. The patients living at home requireextra care and monitoring [26] due to which the quality oflife and psychological health of caregivers is compromised alot [27]. To overcome this challenge, it is essential to reducethe need for the physical presence of a caregiver and stillproviding constant monitoring.

No doubt technology can assist in healthcare [28–32],but choosing the appropriate AT in dementia healthcare ischallenging and the nature of dementia can also make apersonwith dementia or carer cautious or suspicious of usingnewer devices. In this regard, McCreadie and Tinker [33]surveyed older people (aged 70 years or above) with mild tosevere mental impairments for witnessing their experienceand acceptability to a wide range of ATs. Results showedthe endorsement of participants towards the contributionof assistive technologies in assisting them with daily lifeactivities and this AT promotes independence among manyolder people with impairments. Similarly, smart technology,i.e., smartphones and/or tablets, can also act as a potentialalternative for providing healthcare solutions to dementiapatients and caretakers, also known as mHealth [34]. Studies[35, 36] affirmed that smartphones or tablets are the potentialsolutions to meet the demands of PwD by providing simpleinteractive features such as a touchscreen, motion detectionusing motion sensors, and voice recognition. It also givesthem feelings of relaxation and recreation. The qualitativeexploratory study [37] was performed to find the supportof touchscreen devices (e.g., phones and tablets) for peoplewith dementia. During the sessions, it was observed that PwDhave the capability of learning new skills via several coachinginterventions and have proficiency in comprehending newtechnologies. It is also expected that self-management abil-ities among dementia sufferers can increase by using suchapps.

Manymobile applications are incorporating the strategiesdefined byAlzheimer disease international (ADI) for improv-ing healthcare facility of dementia people; the strategies are asfollows [38]:

(1) Task Sharing: transfer of care services from specialiststo nonspecialists including family members

(2) CaseManagement: professionals responsible for coor-dinating and facilitating dementia people and theircarers lives

(3) Care Pathways: systemized planning, resourcing, anddelivery of care

It is identified that the provision of appropriate technologysupport can provide independence and improve the qualityof life of elderly people with dementia disease [39].

3. Research Methodology

3.1. Research Questions. The comprehensive review aims toidentify, appraise, and synthesize the existing evidence onthe use of mHealth apps as dementia healthcare solutionfor PwD and their carers by answering the two followingquestions:

(1) What types of mHealth apps are available for peoplewith dementia and how do these apps help them indaily living?

(2) What is the contribution of mHealth apps in support-ing informal carers of people with dementia?

3.2. Study Design. This study is followed by two mainapproaches for the evaluation of mHealth apps available forPwD healthcare and their carers.

(a) The first approach is the comprehensive review ofexisting literature about mHealth apps used fordementia healthcare.

(b) The second approach is an identification of existingmHealth dementia apps that are commercially avail-able in smartphone stores.

3.3. Literature Search and Selection Approach

3.3.1. Literature Search Strategy. To identify relevant previousliterature regarding mHealth apps in dementia healthcare, akeyword search was performed on five electronic databases:MEDLINE�, PubMed, SAGE, IEEE Xplore, and Science Direct.Search terms used in all databases were “dementia AND

4 BioMed Research International

Table 2: Keywords hits in scientific databases.

Search Keywords MEDLINE� PubMed SAGE IEEE Xplore Science Directdementia ANDmobile apps 259 50 75 60 466Dementia ANDmobile technology 388 46 592 45 350dementia AND smartphone 127 31 112 48 80dementia AND tablet 114 89 380 15 172android app AND dementia 47 5 47 10 75iOS app and dementia 158 5 43 7 15mHealth app AND dementia 151 5 16 437 44mobile health app AND dementia 137 5 10 35 48dementia AND caregivers ANDmobile app 127 4 102 10 432Dementia AND carers ANDmobile app 142 9 155 15 400

mobile apps,” “dementia AND mobile technology,” “dementiaAND smartphone,” “dementia AND tablet,” “android appAND dementia,” “iOS app AND dementia,” “mHealth appANDdementia,” “mobile health app AND dementia,” “demen-tia AND caregivers AND mobile app,” and “dementia ANDcarers AND mobile app.” The hits of keywords in scientificdatabases are listed in Table 2.

3.3.2. Literature Inclusion and Exclusion Criteria. In thiscomprehensive study, we included peer-reviewed, full-textarticles published in English during last five years (from 2014to 2018) and aimed to identify such studies that specificallyassessed the implementation of using mHealth based apps onPwD and the caregivers. The initial searches based on key-words and search terms yielded a total of 6195 research arti-cles including 1650 fromMEDLINE�, 249 fromPubMed, 1532from SAGE, 682 from IEEE Xplore, and 2082 from ScienceDirect. The first step after the initial search was an exclusionof duplications, and 970 articles were excluded. Remainingresearch articles were screened by their title and abstract. Weexcluded 5060 articles due to lack of relevance in the titleand/or abstract. After applying inclusion/exclusion criteria atthe abstract level, 165 full-text articles were reviewed to checkthe appropriateness for inclusion; see Figure 2 for inclusioncriteria. For the full-text articles, we rejected 148 that did notmatch with our interest scope. We shortlisted 17 publicationsreports on the intervention of dementia apps.These includedstudies piloted and evaluated for their effects on demen-tia patients and their carers. All these shortlisted articlesrecorded useful information regarding mHealth applicationsin dementia healthcare; therefore, these are included in thereview.

3.3.3. Literature Data Synthesis. After the shortlisting ofresearch articles, the data is extracted and systematicallyorganized on the spreadsheet. It is then compared to findout correlations between studies. This process results in anidentification of categories and subcategories of mHealthapplications for PwD and their caregivers as shown inTable 3.

Table 3: Categories and subcategories of mHealth based dementiaapplications.

Categories Subcategories

Cognitive Training and Daily Living

MemoryCommunicationLogical Thinking

AttentionLanguage Abilities

Schedule

Screening Dementia DetectionCognitive Screening

Health and Safety Monitoring Fall DetectionEmergency Help

Leisure and Socialization ReminiscenceTherapySocializationTherapy

Navigation TrackingLocation Service

3.4. mHealth Based Dementia Applications Search andSelection Approach

3.4.1. App Search Strategy. During July 2018, the keywordsearch of mHealth based dementia applications was per-formed on two most common commercial stores for smart-phones: Google Play Store (developed by Google LLC, forAndroidOS devices) and App Store (developed byApple Inc.,for iOS devices). The devices used for searching the termsare LG Nexus 5 (Android OS device) and iPhone 4s (iOSdevice). Initially, the search terms for both aforementionedstores were same as the keyword search terms of literaturesection (see Section 3.3.1. for details), but these terms gener-ated maximum unrelated results, so the simple search termdementia was used to get more disease-specific app searches.

3.4.2. App Inclusion and Exclusion Criteria. The initial searchbased on dementia keyword yielded a total of 356 results,including 106 in iOS and 250 in Android. After removingthe duplicates, we screened names, ratings, and prices of

BioMed Research International 5

970 duplicate articles excluded

5060 articles excluded due to lack of relevance in title and abstract

148 articles excluded based on full-text review:Not in English language (n=4)Involved other disease conditions (n=30)Mixing Alzheimer’s disease with dementia (n=21)Limited data and no experimental results provided (n=38)

Poster presentation abstract (n=10)Other technology interventions (n=25)Literature review papers (n=15)Duplicates (n=5)

Records identified through search of five electronic databases (n=6195)1650 from MEDLINE®249 from PubMed1532 from SAGE682 from IEEE Xplore2082 from Science Direct

Articles screened for title and abstract review (n=5225)

Potentially relevant full-text articles identified for further review of research questions (n=165)

17 articles included in the comprehensive study

Figure 2: Flow diagram of literature selection.

apps generated from search keyword, as these are the promi-nent available features at the search result screen of twoselected app stores. At first stage, a total of 58 applicationswere excluded from both mobile app stores due to lack ofcompliance with our inclusion criteria 1 and 6; see Table 4for details of inclusion and exclusion criteria. AsiOS Appstore does not show download counts, so we included appsas per the inclusion criteria 1-4 of Table 4. The completeinventory of shortlisted commercial apps is listed in Table 5.In comparison to generic mHealth apps, the availability ofmobile apps geared towards dementia healthcare for bothPwD and their caregivers is relatively sparse with 35 apps byapplying inclusion/exclusion criteria.

The selection process ofmHealth based apps for dementiacare is illustrated in Figure 3. After the shortlisting ofapps, it is observed that existing apps generally addressed

different dementia specific aspects which are overlying withthe identified categories of mHealth apps in research articles(see Section 3.3.3 for categories and subcategories details).

4. Results

4.1. Literature Review of mHealth Apps Used in DementiaHealthcare. Of the seventeen (17) included articles in thisreview, seven (07) articles involved tablet assistance, two (02)focused onusing onlymobile devices, and seven (07) researcharticles used both tablets and mobile devices for mHealth.However, one study used a smart watch device with thesmartphone.

All cited studies used smartphones and tablets runningiOS and Android operating systems. Regarding the categoriesof studies as mentioned in Table 3, five (05) studies piloted

6 BioMed Research International

Table4:Inclu

sionandexclu

sioncriteria

form

Health

baseddementia

applications

inAnd

roid

Play

Storea

ndiO

SAp

psto

re.

Inclu

sionCr

iteria

Exclu

sionCr

iteria

(1)A

ppavailabilityin

English

lang

uage.

(1)A

ppun

-availabilityin

English

lang

uage.

(2)F

reea

pp.

(2)P

aidapps.

(3)S

tatesa

imed

atdementia

disease.

(3)D

oesn’tsta

tethatappisaimed

atdementia

disease.

(4)D

evelop

edin

supp

ortw

ithresearch

centre/pilo

tedatdementia

care

homes/Pop

ular

oraw

ard-winning

.(4)M

ixingdementia

andAlzh

eimer’sdisease.

(5)D

ownloads

ofapp≥1000∗ifappno

tfulfillin

gcriteria

4.(5)D

ownloads

ofapp<1000∗.

(6)R

ating≥4∗

ifappno

tfulfillin

gcriteria

4.(6)R

ating<4∗.

(7)D

uplicatea

pp.

∗ForAn

droidapps

only.

BioMed Research International 7

47 apps excluded due to:Paid apps (n=20)

263 apps excluded based inclusion/exclusion criteria:

Not in English language (n=67)Doesn’t state that app is aimed at dementia disease (n=115)Mixing dementia and Alzheimer’s disease (n=36)

Apps identified through search of Android Play Store

(n=250)

Apps remaining after duplicate removal (n=345)

Potentially relevant apps (n=298)

35 apps included in the study

Apps identified through search of iOS App Store

(n=106)

Rating <4∗ (n=27)

∗for Android Play Store

Download of apps < 1000∗ (n=45)

∗for Android Play Store

Figure 3: Selection process of mHealth based dementia apps.

and evaluated the usability of mHealth applications fromcognitive training and daily living category [40–44], five (05)studies were from screening of dementia category [45–49],one (01) study combined cognitive training and screening ofdementia categories [50], three (03) studies were from healthand safety monitoring category [51–53], two (02) studieswere from leisure and socialization category [54, 55], andone (01) study covered navigation section [56]. The dataextracted from research articles are study, study type, studyaim, study methodology, technology type (i.e., mobile, tablet,etc.), participants in the study, location, study outcome,application name, application features, and category of studyas shown in Table 6.

Category 1: Cognitive Training and Daily Living.The first cate-gory outlines different strategies to help cognitively impaireddementia people.The included studies in this category identi-fied six (6) subcategories, i.e., memory, communication, logi-cal thinking, attention, language abilities, and schedule.Threestudies [40–42] used smart devices (i.e., tablets, smartphones,

and smart watches) with already installed applications. Konget al. [40] conducted sessions for PwD to address four majorcognitive domains, i.e., language, visual-spatial, memory, andproblem-solving.The participants rated apps on a scale of 1 to5 at the end of the session. This exploratory study stated thatapps with simple activities are more usable, whereas an appwith confusing directions and complex vocabulary resultedas least usable among PwD. Likewise, other user-centreddesign methodologies [41] addressed communication andscheduling cognitive domains by including smart watch andsmartphone device to support dementia people and theircaregivers.This study concluded that cognitive training basedmHealth apps provide a promising environment for PwDto perform better in their daily routine, whereas orientationfeature has more usability and usefulness to carers. Vahia etal. [42] also investigated the feasibility, usability, and safetyof tablet apps in managing agitated behavioural symptomsamong PwD. The 70 installed apps are reviewed and ratedas per complexity score ranging from 0 (less complex) to10 (highly complex). The results of this open-label study

8 BioMed Research International

Table5:Inventoryo

fmHealth

baseddementia

applications

inAnd

roid

Play

Storea

ndiO

SAp

psto

re.

AppNam

ePlatform

AppLink

(releaseyear)

Sing

Fit(2011)

iOS

https://itun

es.ap

ple.c

om/us/app/sin

gfit/id4

42827581

Con

stant

Therapy(

2012)

iOS

https://itun

es.ap

ple.c

om/us/app/constant-th

erapy/id575764

424

Pain

Ratin

gScales

(2015)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.etz.p

ainassessm

ent

BrainTraining

Journey(

2015)

iOS

https://itun

es.ap

ple.c

om/us/app/brain-training

-journey/id968590

641

CareT

racker

(2015)

And

roid

&iO

Shttps://play.g

oogle.c

om/store/app

s/details?id=c

om.stellacare.stella

https://itun

es.ap

ple.c

om/us/app/care-tr

acker/id914880113

Dem

entia

CareM

atters(2015)

iOS

https://itun

es.ap

ple.c

om/us/app/dementia

-care-matters/id

10023400

94Dem

entia

Test-

Risk

Calculatoro

fdem

entia

(2015)

iOS

https://itun

es.ap

ple.c

om/us/app/dementia

-test-

risk-calculator-of-d

ementia

/id1014958634

Mem

oryB

ox(2015)

And

roid

&iO

Shttps://play.g

oogle.c

om/store/app

s/details?id=c

om.sc

i.mem

orybox

https://itun

es.ap

ple.c

om/us/app/mem

ory-bo

x/id9890

93504

Dem

entia

/Digita

lDiary/Clock

(2015)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.fashmel.alzclock

Dem

entia

Clock(2015)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.wearin

gthegreen.pc.otdem

entia

clock

Care4Dem

entia

(2015)

iOS

https://itun

es.ap

ple.c

om/pk/app/care4d

ementia

/id1029281368

GreyM

atters:B

eyon

dDem

entia

(2015)

iOS

https://itun

es.ap

ple.c

om/us/app/greymatters-beyon

d-dementia

/id90

0645661

Living

andDying

WellW

ithDem

entia

(2015)

iOS

https://itun

es.ap

ple.c

om/us/app/living-and-dying-we

ll-with

-dem

entia

/id945365520

Con

sultGeri:Dem

entia

(2015)

iOS

https://itun

es.ap

ple.c

om/us/app/consultgeri-d

ementia

/id962437779

Carea

ndCon

nect:D

ementia

Friend

lyPlaces

(2015)

iOS

https://itun

es.ap

ple.c

om/gb/app/care-and

-con

nect-dem

entia

-friend

ly-places/id985980528

SeaH

eroQuest(2016)

And

roid

&iO

Shttps://play.g

oogle.c

om/store/app

s/details?id=c

om.glitchers.seaheroqu

estvrdaydream

https://w

ww.oculus.co

m/exp

eriences/gear-vr/16

39295696089857/

JigsawPu

zzle:Spider(2016)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.co

copapasoft.spiderpu

zzle

Dem

entia

Risk

Tool(2016)

And

roid

&iO

Shttps://play.g

oogle.c

om/store/app

s/details?id=c

om.dem

entia

risktoo

lhttps://itun

es.ap

ple.c

om/us/app/dementia

-risk

-tool/id

1160712531

Dem

entia

guidefor

carersandcare

providers(2016)

iOS

https://itun

es.ap

ple.c

om/gb/app/dementia

-guide-fo

r-carers-and

-care-providers/id1085813885

MindM

ate-Health

aging(2016)

iOS

https://itun

es.ap

ple.c

om/us/app/mindm

ate-for-a-healthy-brain/id1030422375

BrainS

core:C

onnectDots(2016)

iOS

https://itun

es.ap

ple.c

om/us/app/brain-score-conn

ect-d

ots/id114

6159421

Awalkthroug

hDem

entia

(2016)

And

roid

&iO

Shttps://play.g

oogle.c

om/store/app

s/details?id=c

om.alzheimersresearchu

k.walkthrou

ghdementia

https://itun

es.ap

ple.c

om/us/app/a-walk-throug

h-dementia

/id1242267344

FolsteinTest(2016)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=a

ppinventor.ai

openmylabfeed.M

MSE

Dem

oMyH

ouse

ofMem

ories(2016)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.nml.m

yhou

seofmem

ories

Dem

entia

Caregiver

Applicationv2

(2016)

iOS

https://itun

es.ap

ple.c

om/us/app/dementia

-caregiver-app

lication-v2/id

106860

1934

myP

layLife

(2017)

iOS

https://itun

es.ap

ple.c

om/us/app/myplaylife/id

1205956380

BrainTest(2017)

iOS

https://itun

es.ap

ple.c

om/us/app/braintest/id1030864

182

CogniCare-En

ablin

gperson

alized

dementia

care

(2017)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.co

gnihealth

.cogn

icare

REMEM

BERME(2017)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.cu

zzrek.remem

berm

eAlzh

eimer’sSpeedof

Processin

gGam

e-ASP

EN(2017)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.TinyH

appySteps.B

ird

Cognitiv

eRehab

inDem

entia

(2017)

And

roid

&iO

Shttps://play.g

oogle.c

om/store/app

s/details?id=c

om.co

nnectin

ternetsolutio

ns.nes.dem

entia

https://itun

es.ap

ple.c

om/gb/app/cogn

itive-rehab-in

-dem

entia

/id13164264

80eSLU

MS(2017)

iOS

https://itun

es.ap

ple.c

om/us/app/eslums/id114

1690870

Symptom

Guide�Dem

entia

(2018)

iOS

https://itun

es.ap

ple.c

om/us/app/symptom

guide-dementia

/id1357298369

Dem

entia

Respon

d(2018)

And

roid

https://play.g

oogle.c

om/store/app

s/details?id=c

om.ap

pmakr.d

ementia

respon

dYo

urCareC

ard(2018)

iOS

https://itun

es.ap

ple.c

om/us/app/your-care-card/id

1355112

732

BioMed Research International 9

Table6:Summaryof

review

edstu

dies.

Stud

y(yeara

ndcoun

try)

Stud

yTy

peStud

yAim

andMetho

dology

Participants1

mHealth

appwith

Features

Stud

yOutcomes

Stud

yCategory

Nirjjonetal.

[45],2014,USA

.UsabilityStud

y

Aim

:Toprovidec

onvenient,

automated

andeasy

toadminister

dementia

screeningtestthatcanbe

takenatho

me.

Methodology

(i)Develop

mento

fapp

lication.

(ii)U

selocaldatabasefor

displaying

wordso

nthes

creen.

(iii)Pre-processin

g,featuree

xtraction,

training

andclassifi

catio

nforc

lock

draw

ingtest.

(iv)k

-NNalgorithm

forc

lassificatio

nof

recogn

ized

digits.

7healthyadults

(3females,4

males)

age∼

25-35

MOBI-COGAp

pwith

remem

berin

gwo

rds,clock

draw

ingtestandrecalling

words.

Question

naire

ofthe

usability

study,

99.53

%accuracy

inclock

draw

ingtest.

Screening

Kong

[40],2015,

USA

.Ex

ploratory

Stud

y

Aim

:Toexplorethe

implem

entatio

nof

apps

ontheiPadto

cond

uctcognitiv

eexercises.

Methodology

(i)Ke

ywordbasedappselectionfro

miTun

es.

(ii)Q

uestion

naire

todeterm

inethe

familiarity

ofthep

artic

ipantw

ithtechno

logy.

(iii)Finalizethe

apps

basedon

aqu

estio

nnaire.

10Pw

D(6

males,4

females)

age∼

64-84

MoC

A:15.74

(diagn

osed

with

early

-stage

dementia

)

Free

Apps

(iTun

es)w

ithvisual-spatia

l,mem

oryand

prob

lem-solving

.

Participants’

ratin

gof

exercise,C

linicians

respon

seforfurther

implem

entatio

nof

apps.

Cognitive

training

anddaily

living

Zorlu

ogluetal.

[47],2015,

Turkey.

NovelStud

y

Aim

:Toevaluatethec

ognitiv

eskills

byinvolvingdifferent

tests

forc

ognitiv

efunctio

nsassessment.

Methodology

(i)Ex

perim

entalstudy

tocond

uct33

tests

in14

different

cogn

itive

skills.

(ii)D

isplayther

adar

charttoshow

progress.

23participantswith

CG+P

wD

ControlG

roup

9healthypeop

leage∼

63-95

Females

=78.78%

,Males=

22.22%

Avg.MoC

Ascore:24.55±

3.08

PwDGr

oup

14dementia

peop

leage∼

73-89

Females

=78.57%

,Males=

22.43%

Avg.MoC

Ascore:13.57±5.61

Mobile

Cognitive

Screening

(MCS

)App

with

trail

making,clockdraw

ing,

attention,visual,shape

similarity,shapem

atching,

arith

metic,proverb,

naming,nu

mbers,

colourfulshapes,market,

date,and

story

recalltest.

Correlatio

nbetweenMCS

andMoC

Ascores

was

r2=0

.57;thiscorrelation

was

meaning

ful(p<0.01).

Screening

10 BioMed Research International

Table6:Con

tinued.

Stud

y(yeara

ndcoun

try)

Stud

yTy

peStud

yAim

andMetho

dology

Participants1

mHealth

appwith

Features

Stud

yOutcomes

Stud

yCategory

Sind

ietal.[46],

2015,Finland

.CA

IDEStud

y

Aim

:Topredictthe

riskof

dementia

throug

hCA

IDE(cardiovascularrisk

factor,ageingandincidenceo

fdementia

)Risk

Scorea

pp.

Methodology

(i)Develop

mento

fapp

basedon

CAID

Edementia

riskscoreb

yinvolvinginform

ationon

age,

educationallevel,hypertension,

hypercho

leste

rolemia,obesity,and

physicalinactiv

ity.

Four

independ

ent

popu

latio

n-basedrand

omsamples

ParticipantsMMSE

score≤

24

CAID

ERisk

ScoreA

ppwith

graphicaldisp

layof

riskscores,

riskof

developing

dementia

estim

ation,gu

idance

and

suggestio

nsto

users,the

recommendatio

nof

ahealth

practitioner.

Receiver

operating

characteris

tics(RO

C)curved

emon

strated

the

dementia

riskscore

predictedeffectiv

ely.

95%confi

denceinterval

(0.71-0

.83).

Screening

Thorpe

etal.

[41],2016,

Denmark.

UCD

case

Aim

:AUCD

(User-centreddesig

n)to

investigatethea

doptionof

pervasive

assistiv

etechn

olog

yamon

gmild

dementia

peop

le.

Methodology

(i)Selectionof

keysupp

ortfeatures.

(ii)U

sertestin

gof

selected

applications.

5Dyads

with

PwDof

MCI

PwD:3

males,2

females

age∼

61-73

11Free

AndroidAp

pswith

schedu

ling,navigatio

n,commun

ication,

emergencyh

elp,

mon

itorin

gand

orientation.

Syste

mUsabilityScores

(SUS)

inusability

testing

andfield

testing

.

Cognitive

training

anddaily

living+

Naviga

tion+

Health

andSafety

Monito

ring

Vahiae

tal.[42],

2016,U

SA.

Open-Label

Stud

y

Aim

:Toinvestigatethefeasib

ility,

usability

andsafety

oftabletapps

inmanagingagitatio

nam

ongdementia

patie

nts.

Methodology

(i)Person

alizationof

tablet

applications

(rates

electedapps

asper

complexity

).(ii)F

indthec

orrelatio

nalanalysis

betweentabletusea

nddemograph

iccharacteris

ticso

fthe

grou

p.

36participants(n)w

ithMild

toSevere

dementia

(females:61.1%,m

ales:38.9%

)Mild

lyim

paire

dMoC

Ascore:18

to25;n

=23

Mod

erately

Impaire

dMoC

Ascore:10

to17;n

=7SeverelyIm

paire

dMoC

Ascore

<10;n

=16

Age∼avg79.9

70Free

iTun

esAp

pswith

commun

ication,games,

musicandmusical

instr

uments,

video,

entertainm

entand

recording,we

bbrow

sera

ndnews,and

picture/ph

otograph

-view

ing

apps.

WellU

tilizationof

app.

Agitatio

nredu

ctionin

the

mild

lyim

paire

dgrou

pas

comparedto

severe

impaire

d=p=0

.02.

Cognitive

training

anddaily

living

Boyd

etal.[50],

2017,Ireland

.UsabilityStud

y

Aim

:Todevelopandevaluatethe

usability

ofEn

Cared

iagn

ostic

s(EC

D)

andBrainFitP

lan(BFP

)app

.Methodology

(i)SelectAnd

roid

apps.

(ii)D

esigntrails-basedstu

dy.

(iii)Usabilityassessmento

fapp

s.

Inclu

des0

2trials:

Trial1:

11healthypeop

le(age>60

)Females:9,M

ales:2

4oldera

dults

with

physical

impairm

ent

Trail2:

8oldera

dults

Females:4,M

ales:4

MMSE

score:21-26

Diagn

osed

with

early

-stage

dementia

ECDAp

pwith

screeningof

dementia

.BF

PAp

pwith

logical

thinking

basedon

existing

apps

(chess,jigsawetc.)

.

75%drop

outatT

rail1for

BFPtesting

duetoin

familiarity

with

techno

logy

andlack

ofcarersup

port.

Highacceptabilityin

ECD.

Nousability

issue

inEC

D.

Screening(EC

D)

Cognitive

training

anddaily

living

(BFP

)

BioMed Research International 11

Table6:Con

tinued.

Stud

y(yeara

ndcoun

try)

Stud

yTy

peStud

yAim

andMetho

dology

Participants1

mHealth

appwith

Features

Stud

yOutcomes

Stud

yCategory

Dethlefse

tal.

[43],2017,

England.

PilotS

tudy

Aim

:Toprovidee

lderlypeop

leand

PwDcompu

ter-basedcogn

itive

simulationvias

pokennatural

lang

uage.

Methodology

(i)Wizard-of-O

zinterface.

(ii)T

oprocessinp

utspeech

ofparticipantand

respon

daccordingly.

23participantswith

Health

yand

PwD

Health

yPeople:13

Avg.age∼

84.33

PwD:10

Avg.age∼

78.20

Wizard-of-O

zSystem

with

sorting,naming,recall,

quizandproverb.

Enjoym

entand

wantedto

useitagain.

Cognitive

training

anddaily

living

(Mem

ory&

Commun

icatio

n)

Bayenetal.[51],

2017,U

SA.

PilotS

tudy

Aim

:Toanalyseh

owcontinuo

usvideo

mon

itorin

gandreview

offalls

ofPw

Dcansupp

orta

bette

rqualityof

care.

Methodology

(i)Measurethec

ount

offalls

occurring

inthev

ideo

coveredarea.

(ii)E

valuatethe

useo

fvideo

recording

andreplay

possibilitie

sfor

care

practic

e.

Overall38

PwDwith

10participantsallowingwrittenand

oralconsentfor

videorecording

intheirp

rivater

ooms.

SafetyYou

Appwith

video

view

featurefrom

past72

hours,livev

ideo

view

ona

smartpho

nefro

meach

insta

lledcamera.

Dropin

fallrate.

Positiveimpacton

quality

ofcare.

Health

andSafety

Monito

ring

(FallD

etectio

n)

Mulvenn

aetal.

[54],2017,

England.

FeasibilityStud

y

Aim

:Toinvestigatethee

ffectso

findividu

al-specific

reminisc

ence

activ

ityprovided

byusingthea

pp.

Methodology

(i)Anagile

developm

entapp

roachfor

prototype

(ii)L

ocaldatabase

forthe

storage

ofmultim

ediacontent.

28Dyads

Inspire

DAp

pto

enable

PwDandtheirc

arer

gather

together,store

selected

generic

andperson

alized

mem

orabilia.

Engagement.

Use

forp

ersonal

multim

ediacontent.

Leisu

rean

dSocia

lization

(Rem

iniscence

Therapy)

Meggese

tal.

[56],2017,

Germany.

PilotS

tudy

Aim

:Toevaluatetheu

sere

xperience

regardingprototypelocatingsyste

min

homed

ementia

care

tobette

run

derstand

then

eeds

andpreferences

ofPw

Dandtheirc

arers.

Methodology

(i)Use

oflocatin

gsyste

mfor4

weeks.

(ii)M

easureusability,produ

ctfunctio

nsandfeatures.

(iii)Measurecaregiverb

urden

perceivedself-effi

cacy,the

frequ

ency

ofuse,andwillingn

esstopu

rchase

the

prototype.

18Dyads

PwDCo

unt

3MCI

,6Mild

diseases

everity,9

mod

erated

iseases

everity

Avg.age∼

71.94

CarersCo

unt

10hu

sbands,6

wives,2

daug

hters

PrototypeL

ocatingSyste

mwith

acall,alarm,location

tracking

andservice

hotline.

Sub-Features:

Zone

mapping

Zone

Sharing

Usabilityratin

gdeclined,

prod

uctfun

ctions

rated

positively

.Nodifferenceincaregiver

burden

andperceived

self-effi

cacy.

Mod

eratefrequ

ency

ofuse,

andhigh

willingn

essto

purchase.

Naviga

tion

12 BioMed Research International

Table6:Con

tinued.

Stud

y(yeara

ndcoun

try)

Stud

yTy

peStud

yAim

andMetho

dology

Participants1

mHealth

appwith

Features

Stud

yOutcomes

Stud

yCategory

Tyacketal.[44

],2017,E

ngland

.

Quantitativ

eandQualitative

Stud

y

Aim

:Toexplorew

hether

art-b

ased

interventio

ncanbe

delivered

viaa

touchscreentabletdevice

displaying

artimages.

Methodology

(i)Th

equantitativ

edatafollo

weda

quasi-e

xperim

entalrepeatedmeasures

desig

n.(ii)C

ompare

before

andaft

eruseo

fthetableto

nwe

ll-being.

(iii)Th

equalitatived

atac

ollected

durin

ginterviewsw

asanalysed

using

them

aticanalysis.

12Dyads

PwD

Males:8,Fem

ales:4

Avg.age∼

75Diagn

osed

dementia

with

4years

Carer

Males:2,Fem

ales:10

Avg.age∼

66

ArtView

ingAp

pfor

presentin

gchoiceso

fart

genretoview

from

museumsa

ndarea

artists.

Improvem

entinwe

ll-being

andenthusiasm

.

Cognitive

training

anddaily

living

(Stim

ulating,

Remem

berin

g,Attention)

Docking

etal.

[52],2017,

England.

Qualitative

Stud

y

Aim

:Toim

provethe

pain

assessment

ofPw

Dandmanagem

entinthis

vulnerablepo

pulatio

n.Methodology

(i)cond

uctin

gusability

testing

ofan

appto

assesspain

inadultswith

dementia

treated

byparamedics.

(ii)e

valuatethe

approp

riatenessof

the

algorithm

used

inan

app.

(iii)identifying

areasfor

further

developm

entand

respon

seto

recommendatio

ns.

24paramedicstu

dentsfrom

two

EnglandAmbu

lances

ervices.

Females:11,Males:13

7Delp

hiPanelE

xperts

Females:1,

Males:6

Pain

Assessm

entA

ppwith

theA

bbey

Pain

Scaleb

ased

questio

nnaire.

Positiveu

sabilitytesting

.ParamedicsS

tudentsa

ndDelp

hipanelofexp

erts

stateitas

ausefultoo

lina

pre-ho

spita

lsettin

g.

Health

andSafety

Monito

ring

(EmergencyHelp

,Pa

inassessm

ent)

Huang

etal.

[48],2017,

Taiwan.

Experim

ental

Stud

y

Aim

:Todevelopap

sychom

etric

ally

valid

touchscreentablet-based

cogn

itive

testbatte

ryto

identifyearly

cogn

itive

impairm

entd

ueto

dementia

inoldera

dults.

Methodology

(i)To

cond

uct8

tests

with

13subscores

forthe

measuremento

fdifferent

cogn

ition

skills.

120participants(n)

CDR=

0;n=

41;age∼64

-88

CDR=

0.5with

MCI

;n=4

3;age

∼59-91

CDR=

1;n=

36;age∼56-91

Attention,VisualMem

ory,

Visuospatia

l,Re

actio

nTime,Fine

Motor

Con

trol.

(App

namen

otmentio

ned)

Mann–

Whitney

Utests

were

significantfor

CDR=

0versus

0.5,andCD

R=0

versus

1.Con

firmationof

the

four-fa

ctor

mod

elby

Con

firmatoryfactor

analysis(C

FA).

Screening

BioMed Research International 13

Table6:Con

tinued.

Stud

y(yeara

ndcoun

try)

Stud

yTy

peStud

yAim

andMetho

dology

Participants1

mHealth

appwith

Features

Stud

yOutcomes

Stud

yCategory

Welsh

etal.[55],

2018,E

ngland

.Ex

perim

ental

Stud

y

Aim

:Toencouragec

onversation

betweenyoun

gerp

eoplea

ndtheiro

ldrelativ

eslivingwith

dementia

.Methodology

(i)Ex

tend

thep

reviou

sworkby

developing

anapplicationthat

incorporatesthefollowingfour

desig

nrequ

irements:

(1)S

ettin

gup

aprofile.

(2)Inspiratio

n(m

ediato

usefor

talk).

(3)C

ollectingmedia.

(4)P

reparin

gac

onversation.

Deploym

entw

ith02

families

ofPw

D.

Deploym

entincare

home

involves

3volun

teerstomaintain

acon

versationwith

10resid

ents,

age∼

80-95with

mod

erateto

severedementia

.9olderp

eoplew

ithperson

al/professionaldem

entia

experie

ncefor

expertcritiqu

e.

TicketTo

TalkAp

pto

create

aprofilefor

anolder

person

,prompt

carersto

collectmedia(aud

ios,

videos,and

images

etc.)

,helpsc

arerstoorganize

media,u

semediaas

prom

ptsa

ndconversatio

nsta

rters

Prom

otingandmanaging

reminisc

ence,Startingand

maintaining

conversatio

n,Re

distr

ibutingAgency.

Leisu

rean

dSocia

lization

(Rem

iniscence

Therapy,

Relaxatio

n)

Shibatae

tal.

[49],2018,

Japan.

Experim

ental

Stud

y

Aim

:Torepo

rtthatMCI

patie

ntsh

ave

asignificantly

larger

vocabu

lary

than

healthyelderly

peop

le.

Methodology

(i)Use

automaticspeech

recogn

ition

form

easurin

glang

uage

abilitie

s.(ii)A

nalyze

narratives

peechandfin

dfour

lang

uage

abilitie

sscores.

18participants

PwD:8

with

MCI

CG:9

VocabC

hecker

Appto

calculatethe

numbero

ftokens,n

umbero

ftypes,

tokentype

ratio

,potentia

lvocabu

lary

size.

p-values

int-testsho

wthat

tokentype

ratio

ofPw

Dis

high

erthan

CG(p<0.05,

high

lysig

nificant)

Screening(langua

geabilitiesb

ased)

Atee

etal.[53],

2018,Italy.

NovelStud

y

Aim

:Todescrib

eano

velsystem

called

PainCh

ek�focusin

gon

itsconceptual

foun

datio

n,clinicalandtechnical

contents,

clinicaluse,andpractic

altip

sforu

sein

clinicalsetting

s.Methodology

(i)Fo

llowingthings

toconsider

while

developing

anapplication:

(a)S

ubjectiven

atureo

fpain.

(b)C

omplexity,and

dynamicity

ofpain

asac

onstr

uct.

(c)A

nob

jectived

escriptio

nof

key

pain

behaviou

rs.

(d)Th

etem

poralityo

fpainandrelated

behaviou

rs.

(ii)S

imples

corin

gmechanism

.

12Dyads

PwD

Males:8,Fem

ales:4

Avg.age∼

75Diagn

osed

dementia

with

4years

Carer

Males:2,Fem

ales:10

Avg.age∼

66

PainCh

ek�Ap

pto

testpain

scale(

42itemsa

cross6

domains),to

displaypain

assessmentlog,Painchart

andlocalp

atient

database,

toprovidem

edications

and

therapiesa

ndcomments

section.

Soun

dpsycho

metric

prop

ertie

s.Ex

cellent

concurrent

valid

ity,interrater

reliability,internal

consistency,and

excellent

testre-te

streliability.

Health

andSafety

Monito

ring

(EmergencyHelp

,Pa

inassessm

ent)

1

PwD:Peoplew

ithDem

entia

;CG:C

ontro

lGroup

;MoC

A:M

ontre

alCognitiv

eAssessm

ent;Dyad:Pw

Dandcarers;M

MSE

:Mini-M

entalStateEx

amination;

MCI

:Mild

Cognitiv

eIm

pairm

ent.

14 BioMed Research International

demonstrated the positive impact of the tablet as a nonphar-macological intervention for reducing agitation among olddementia patients.

Other three included studies [43, 44, 50] developed appli-cations for engaging PwD in different cognitive exercises.Dethlefs et al. [43] used cognitive stimulation technique toinvolve dementia people in cognitive activities and socialfunctioning, i.e., the conversation about childhood, puz-zles, or memory activities. This study used “Wizard-of-Oz”setup to support elderly people with CDR less than 3. Theexperiment involved human wizards (informal carers) withprevious experiences of providing cognitive stimulation on ahuman-to-human basis. The human wizard was responsibleto understand the natural spoken language of the dementiapatient and respond through prespecified text templatesprovided by an app.The off-the-shelf text-to-speech softwareconverted the text response of wizards into speech. Boyd etal. [50] developed EnCare diagnostics (ECD) app and brainfit plan (BFP) app and evaluated the usability on healthyand cognitively and physically impaired older adults. TheEnCare diagnostics (ECD) app is used to access the cognitivestate of individual (discussed in screening category) whilebrain fit plan (BFP) is used to suggest PwD different tasksto perform daily. Tyack et al. [44] performed an exploratorystudy to check three cognitive domains, i.e., stimulation,remembering, and attention of PwD. They developed an artviewing app to display paintings and photographic images ofhistoric places. The quantitative and qualitative findings ofstudy approved touchscreen-based art interventions as well-being benefits for PwD.

Category 2: Screening. Screening technology is intended tohelp elderly people by giving them an early awareness of anysymptoms that may lead to cognitive impairment. It is alsohelpful for carers by identifying the risks of dementia amongtheir family members. Dementia detection and cognitivescreening based subcategories emerged from the selectedarticles. Two articles [46, 49] are focused on predicting therisk of dementia among people by using the mobile app. Theearliest of these two articles [46] developed an app to predictthe late-life dementia risks based on CAIDE (CardiovascularRisk Factors, Aging, and Incidence of Dementia) risk score,whereas Shibata et al. [49] developed an mHealth app withnatural language processing (NLP) technique to detect thedementia symptoms as the change in language ability isconsidered as one of the early signs of having dementia.The app examines the free narrative speech of a personand calculates four language abilities such as the number ofwords in speech segment (tokens), the number of differentwords in speech segment (types), type-token ratio (TTR),and potential vocabulary size (PVS). The results validatedsignificant difference in language ability between PwD andhealthy elderly people.

Four (04) studies [45, 47, 48, 50] designed and developedcognitive screening of dementia apps. MOBI-COG app [45]allowed people to take dementia screening tests at homeby incorporating convenient, automated, and easy measuresto administer features. The user is asked to perform threetasks, i.e., remembering words, clock drawing, and recalling

words and at the end displays an automated assessmentof these tasks. The experimental setup involved normalpeople while the other three included articles [47, 48, 50]included dementia people to validate the effectiveness ofmobile app as a screening application. Zorluoglu et al. [47]proposed a mobile cognitive screening (MCS) app. This appfeatured 33 tests in fourteen (14) different types for theassessment of cognitive functions. The eight (08) targetedcognitive functions are memory, attention, language, orienta-tion, arithmetic, visual, abstraction, and executive functions.To check the effectiveness of MCS test, all participants in thisstudy are tested by using this app and Montreal cognitiveassessment (MoCA)—an eminent assessment technique forcognitive screening—to compare the results of two tests.The scores of the same participants revealed the correlationbetween MCS and MoCA score. Another study [48] alsoused touchscreen tablet-based mHealth app to identify earlycognitive impairment in older adults. This study concludedthat the cognitive battery test is a cost-effective solution forthe screening of early MCI and AD among dementia people.However, Boyd et al. [50] developed EnCare diagnostics appto access the cognitive state of individuals with dementia. Theapp is proposed as an alternative to the mini-mental stateexamination (MMSE)which is another well-known cognitivescreening test.The participants of this study stated limitationsin using BFP, a cognitive training based mHealth app asexplained earlier in category 1, but they showed a positiveresponse in using ECD.

Category 3: Health and Safety Monitoring. The third categoryincorporates the monitoring of health and safety conditionsof dementia patients. Based on our included studies, thiscategory is subdivided into two subcategories: fall detectionand emergency help. For emergency situations, two apps[52, 53] help in assessing the pain of elderly dementiapatients. Pain Assessment app [52] is designed and developedon the basis of the Abbey pain scale (a one-minute painassessment questionnaire for people with severe dementia),whereas PainChek� [53] is also used to access the painby incorporating 42 items from 6 different domains (face,voice, movement, behaviour, activity, and body). Smartphonecamera at front-end and artificial intelligence (AI) algorithmat the back-end are used to detect the facial expressionsof dementia patient from already classified nine (09) facialexpressions. The other five (05) domains required manualinput from the user. After the completion of input in sixdifferent domains, the app generates a numerical pain scoreranging from no pain (Score: 0-6) to severe pain (Score ≥16).These studies postulated that mHealth tools are useful in theprehospital settings and emergency situations and these appshave a potential to transform the pain assessment of PwDwho are unable to communicate and express their feelings toothers.

On the other hand, Bayen et al. [51] provided safety mon-itoring app to detect the falls of a dementia patient in a carefacility. The experimental setup used wall-mounted camerasto record the falls and smartphone device for continuouschecking of PwD. The smartphone-based app featured livevideo view from mounted cameras and video review service

BioMed Research International 15

to staff of care facility to ensure the better quality of careprovision.This observational pilot study concluded that videoreview facility is helpful in screening the severity of fallsand injuries occur due to falls. The study also highlightedthat video replay can be helpful in identifying deficienciesof cognitive behaviour and environmental circumstancescontributing to the fall.

Category 4: Leisure and Socialization. This category “leisureand socialization” of included studies provides reminis-cence and socialization therapy to PwD. mHealth basedapp InspireD [54] investigated the effects of reminiscenceactivity on PwD. The main functions of the app are thefollowing: (1) to bring people living with dementia and theircaregivers together and (2) to store generic and personalizedmemorabilia in the form of audio, video, and photos.This fea-sibility study showed that PwD interacted with this app morethan their caregivers in reminiscence section. Additionally,dementia people preferred to view personalized multimediacontent than generic videos or photos. Welsh et al. [55]designed and developed mobile and tablet-based app Ticketto Talk to promote intergenerational interactions betweenyoung relatives and dementia individuals. The application isevaluated through the trials of two families, a care home andan elder people group.The thematic analysis of obtained datafrom participants revealed that Ticket to Talk promotes andmanages reminiscence and helped young people to start andmaintain a conversation.

Category 5: Navigation. The last category relates to providing“navigation facility” and it is very useful for caregivers as theycan track the location of patients. A pilot study [56] presentedthe mobile-based locating system with four major functions:locating, call, alarm, and hotline, and two subfunctions: zonemapping and zone sharing. The outcomes of the proposedapplication are measured in terms of usability and rating ofapp features. The usability score decreased over time due totechnical deficiencies of a prototype system. Regardless ofthe technical discrepancies, it is noticed that PwD and theircaregivers are more receptive about the assistance of mHealthtechnology in home dementia care. It is also found out thatmale caregivers were more willing to purchase this prototypethan female caregivers.

4.2. ExistingmHealth BasedCommercial AppsUsed inDemen-tia Healthcare. Out of 35 identified mHealth dementia apps,eleven (11) apps belong to cognitive training and daily livingcategory, four (04) apps are from screening category, four (04)apps are from health and safety monitoring category, six (06)apps are from leisure and socialization category, one (1) appis from navigation category, and nine (09) apps are for thesupport of carers.The following data are extracted from apps:app name, app release year, app rating (if any), app reviewcount (if any), platform, the app offered by, app category,privacy policy (provided or not), and features of apps. Thedetails of identified apps fromAndroid and iPhone platformsare mentioned in Table 7.

5. Discussion

mHealth has become the fast-growing assistive technologythat supports the broad range of healthcare services includingmental healthcare [57].ThemHealth applications for demen-tia are divided into two broad categories:

(1) Apps used by dementia sufferers for the improvementin their quality of life

(2) Apps used by the health care providers (health profes-sionals or informal caregivers) to perform a variety offunctions or services for PwD

The aim of this comprehensive study is to identify,appraise, and synthesize the existing evidence of usingmHealth based dementia apps as a healthcare resource forpeople with dementia. Secondly, this study also contributesto finding out the influence of mHealth apps in supportinginformal caregivers. In this study, seventeen (17) articles arereviewed and a total of thirty-five (35) apps are shortlisted.All included articles in this comprehensive study provideda clear description of the experimental methodology andoutcomes of using mHealth apps for dementia people andtheir caregivers. The systematic data analysis of includedstudies and review of commercial apps resulted in theidentification of five categories and subcategories of mHealthbased dementia applications. These categories of dementiamobile applications can help in finding out the existing appsand planning of new mHealth based interventions for PwDand their carers. Regarding the participants of the includedstudies, seven (07) studies recruited PwD and their profes-sional and informal carers, five (05) studies engaged PwDonly, three (03) studies involved control groups (healthy olderpeople) and PwD, one (01) study performed experimentalstudy on healthy adults, and one study conducted a usabilitystudy on care professionals.

All articles are evaluated as providing useful and relevantinformation regarding mHealth apps in dementia care yetthere were some limitations in the studies. Majority of thesestudies were focused on testing the feasibility and usability ofexisting or developed mobile applications for PwD. However,only one study adopted a user-centered design methodologyin development of mobile application by involving dementiapeople. User feedback in a systemic manner can deliver aneffective application as few studies highlighted the reluctanceof moderate to severe CDR people in using assistive tech-nology due to complex features of applications. Other thanthis, the most apparent gap in the literature is the lack ofawareness or training applications for informal caregivers butthe exploration of commercially available apps acknowledgedin the availability of applications to support caregiver byproviding knowledge about dementia healthcare.

This review concluded that the convenience and unifor-mity of using mHealth based dementia apps make it likeableto use by dementia people in daily routine. It is also validatedthat smartphone-based assistive technology is psychomet-rically valid in evaluating the cognitive skills of dementiapeople. The adoption of mHealth apps among dementiapeople is highly correlated with the simple features of appsand can be used as a nonpharmacological intervention. The

16 BioMed Research International

Table7:Listof

mHealth

baseddementia

applications

inAnd

roid

andiPho

neplatform

s.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

Sing

Fit(2011)

MedicalHealth

Techno

logies

iOS

(i)Provides

musictherapy.

Leisu

reandSo

cialization

No

63review

s(4.0)

Con

stant

Therapy

(2012)

Con

stant

Therapy,Inc.

iOS

(i)Use

person

alized

exercisesa

thom

e(ii)G

etup

to4tim

esmore

practic

ewith

immediate

feedback.

(iii)Pairs

perfe

ctlywith

cliniccogn

itive

speech

therapy.

Cognitiv

eTraining

(Com

mun

ication,

Lang

uage

Abilitie

s)Yes

300review

s(4.5)

Pain

Ratin

gScales

(2015)

ETZ

And

roid

(i)To

accessthep

ainin

dementia

patie

nts.

Health

andSafety

Mon

itorin

gNo

1000

+do

wnloads

(4.2)

BrainTraining

Journey

(2015)

Jarrod

Kanizay

iOS

(i)En

dlessg

amelevelsto

perfo

rmsim

plee

xercise

s.(ii)M

emoryo

riented

game.

Cognitiv

eTraining

(Mem

ory)

No

Nodatagiven

CareT

racker

(2015)

StellaCareA

pSAnd

roid

&iO

S(i)

Tohelpcarersin

tracking

dementia

patie

nts

Navigation

Yes

1000

+do

wnloads

(4.7)

Dem

entia

Care

Matters

(2015)

AppsmeL

tdiO

S

(i)Organizationalproject.

(ii)P

ushno

tificatio

nenabled.

(iii)Integrated

Facebo

okandTw

itter

feeds.

DailyLiving

Activ

ities

(Scheduling)

No

Nodatagiven

BioMed Research International 17

Table7:Con

tinued.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

Dem

entia

Test-

Risk

Calculatoro

fdementia

(2015)

PearsH

ealth

Cybers.r.o.

iOS

(i)Dem

entia

risktest.

(ii)D

iseaseinformation.

(iii)Optionto

send

test

results

viae

mail.

(iv)N

exttestd

aterem

inder.

(v)T

ipsa

ndtricks

toredu

cether

iskof

dementia

.

DailyLiving

Activ

ities,

Dem

entia

Screening

No

Nodatagiven

Mem

oryB

ox(2015)

Swedish

Care

International

AB

And

roid

&iO

S(i)

Provided

aily

interactions

between

caregivers,fam

ilyandPw

D.

Leisu

reandSo

cialization

Yes

1000

+do

wnloads

(4.9)

Dem

entia

/Digita

lDiary/C

lock

(2015)

Fashmel

And

roid

(i)Provided

igita

l/analog

clockdisplay.

(ii)L

ivea

ndremotely

confi

guredcalend

ar.

DailyLiving

Activ

ities

Yes

1000

+do

wnloads

(4.4)

Dem

entia

Clock

(2015)

Wearin

gthe

Green

And

roid

(i)Disp

layinteractivec

lock

forP

wD.

DailyLiving

Activ

ities

No

1000

+do

wnloads

(4.5)

Care4Dem

entia

(2015)

University

ofNew

South

Wales

iOS

(i)Provideinformationand

supp

ortfor

carersin

their

roleof

carin

gforP

wD.

Carer

Supp

ort

No

1000

+do

wnloads

(4.2)

18 BioMed Research International

Table7:Con

tinued.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

GreyM

atters:

Beyond

Dem

entia

(2015)

GreyM

atters

CareL

LCiO

S

(i)Cr

eatesp

ersonalized

life

storybo

ok.

(ii)R

ecordandshare

mem

ories.

(iii)Liste

nto

musicand

play

games.

(iv)C

ollabo

ratewith

family.

(v)R

ecordandsharen

ewmem

ories.

Leisu

reandSo

cialization

(Rem

inisc

ence

Therapy)

Yes

18review

s(4.5)

Living

andDying

WellW

ithDem

entia

(2015)

Footsqueek

iOS

(i)Develop

edby

expertsin

thefi

eldinclu

ding

from

the

Alzh

eimer’sSo

cietyUK,

GoldStandardsF

ramew

ork

andtheE

ndof

Life

Partnership

(ii)P

rovide

supp

ortto

carersandidentifykey

issuesinDem

entia

andEn

dof

LifeCare

Carer

Supp

ort

No

Nodatagiven

Con

sultGeri:

Dem

entia

(2015)

New

York

University

iOS

(i)Jointp

rojectwith

Hartfo

rdInstitutefor

GeriatricNursin

g(H

IGN).

(ii)G

uide

forc

aregiverso

fPw

D.

Carer

Supp

ort

No

Nodatagiven

Carea

ndCon

nect:

Dem

entia

Friend

lyPlaces

(2015)

University

ofNew

castleu

pon

Tyne

iOS

(i)Develop

edas

partof

aresearch

projectat

New

castleU

niversity.

(ii)F

inddementia

friend

lyplaces

andleaver

eviews.

Leisu

reandSo

cialization

Yes

Nodatagiven

BioMed Research International 19

Table7:Con

tinued.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

SeaH

eroQuest(2016)

GLITT

ERSLL

DAnd

roid

&iO

S(i)

Agamefor

tracking

the

navigatio

ndata.

Health

andSafety

Mon

itorin

gYes

2.8k

review

s(4.6)

JigsawPu

zzle:Spider

(2016)

CoC

oPaPaS

oftAnd

roid

(i)50

freep

uzzle

images

ofspider

tosolve.

(ii)A

llowto

zoom

-in,

zoom

-out,m

ove-in

screen.

Cognitiv

eTraining

(Problem

Solving)

No

1000

+do

wnloads

(4.8)

Dem

entia

Risk

Tool

(2016)

RISE

SISC

And

roid

&iO

S

(i)Develop

edwith

Ageing

Research

Centera

tKa

rolin

skaInstitute.

(ii)T

oestim

atethe

risks

ofdeveloping

dementia

inthe

future.

Dem

entia

Screening

Yes

100+

downloads

(4.8)

Dem

entia

guidefor

carersandcare

providers

(2016)

TextMattersLtd

iOS

(i)Centre

forInformation

DesignRe

search,

University

ofRe

ading

Project.

(ii)T

oun

derstand

dementia

.(iii)Day-to

-day

living.

(iv)T

osupp

ortcaregivers.

(v)T

oprovideL

egaland

Mon

eyInform

ation.

(vi)To

provides

ymptom

sandbehaviou

rs.

(vii)

Togive

know

ledge

abou

tmedicalterm

s.

Carer

Supp

ort

Yes

Nodatagiven

20 BioMed Research International

Table7:Con

tinued.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

MindM

ate-Health

ageing

(2016)

MindM

ateL

tdiO

S

(i)Brainwo

rkou

t.(ii)N

utrition.

(iii)Ex

ercise.

(iv)R

eminder.

(v)G

ames

basedon

:Prob

lem-solving

.Speed.

Mem

ory.

Attention.

Cognitiv

eTrainingand

DailyLiving

Activ

ities

Yes

425review

s(4.7)

BrainS

core:C

onnect

Dots(2016)

DAEM

YEONG

KONG

iOS

(i)Mem

orytraining

app

with

checking

attention

skillso

fadementia

patie

nt.

Cognitiv

eTraining

(Atte

ntion,Mem

ory)

No

Nodatagiven

Awalkthroug

hDem

entia

(2016)

Alzh

eimer’s

Research

UK

And

roid

&iO

S

(i)Providev

irtual

reality

-based

experie

nceo

fdementia

toun

derstand

PwDbette

r.

Health

&Safety

Mon

itorin

g,DailyLiving

Activ

ities

No

5000

+do

wnloads

(4.9)

FolsteinTest

(2016)

Openm

ylab

And

roid

(i)MMSE

orFo

lsteintestto

measure

cogn

itive

impairm

ent.

(ii)D

atas

avingop

tions.

(iii)Au

diorecord

observations.

Dem

entia

Screening

Yes

1000

+do

wnloads

(4.6)

BioMed Research International 21

Table7:Con

tinued.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

MyH

ouse

ofMem

ories

(2016)

National

Museums&

Gallerie

son

Merseyside

And

roid

(i)Ex

ploreob

jectsfrom

the

1920sto1980s.

(ii)S

hare

Mem

ories,

Experie

ncem

usic

(iii)Ac

tivities

todo

together

bycarera

nddementia

patie

nt.

Leisu

reandSo

cialization

(Relaxation,

Reminisc

ence

Therapy)

Yes

1000

+do

wnloads

(4.2)

Dem

entia

Caregiver

Applicationv2

(2016)

Melv

ynZh

ang

Weibin

iOS

(i)Jointp

rojectwith

the

University

ofNew

castle

Scho

olof

Nursin

g.(ii)P

rovide

caregiving

tips

andcurrentstre

ssindexof

carers.

Carer

Supp

ort

No

Nodatagiven

myP

layLife

(2017)

myP

layLife

Ltd

iOS

(i)Pilotedin

16ho

mec

ares.

(ii)C

reatea

private

networkof

family

mem

bers.

(iii)Sh

arep

hotos,videos

andaudios.

Leisu

reandSo

cialization

(Rem

inisc

ence

Therapy)

Yes

Nodatagiven

BrainTest

(2017)

BrainTestInc.

iOS

(i)To

detectcogn

itive

changesa

ssociatedwith

dementia

andMCI

.Dem

entia

Screening

Yes

56review

s(4.6)

CogniCare-En

ablin

gperson

alized

dementia

care

(2017)

Cognihealth

And

roid

(i)Mon

itorsym

ptom

s,record

care

challenges.

(ii)E

nabletocommun

icate

bette

rwith

thec

arew

orker.

Health

&Safety

Mon

itorin

gYes

1000

+do

wnloads

(5)

REMEM

BERME

(2017)

Cuzzrek

And

roid

(i)Help

sPwDto

remem

ber

then

ameo

ffam

ilymem

bers.

Cognitiv

eTraining

(Rem

ember)

No

1000

+do

wnloads

(4.9)

22 BioMed Research International

Table7:Con

tinued.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

Alzh

eimer’sSpeedof

Processin

gGam

e-ASP

EN(2017)

Tiny

Happy

Steps

And

roid

(i)Cognitiv

etrainingapp.

Cognitiv

eTraining(Logical

Thinking

,Mem

ory)

No

1000

+do

wnloads

(4.3)

Cognitiv

eRehab

inDem

entia

(2017)

NHSEd

ucation

forS

cotland

And

roid

&iO

S

(i)NHSEd

ucationfor

Scotland

(NES

)Project.

(ii)P

rovide

twosections:

LearnSection:

Provides

educationalinformationin

cogn

ition

,cognitiv

eim

pairm

entand

processo

fcogn

itive

rehabilitation.

RehabSection:

Guide

users

throug

hthep

rocessof

cogn

itive

rehabilitationfor

apersonwith

early

-stage

dementia

.

Carer

Supp

ort

No

100+

downloads

eSLU

MS

(2017)

Chew

yLo

gic,

LLD

iOS

(i)SaintL

ouisUniversity

Scho

olof

Medicine.

Project.

(ii)E

asttestadm

inistratio

nof

iPad/iP

hone.

(iii)Au

tomaticScoring.

(iv)Q

uicklyseetrend

sin

testscores.

(v)A

dark

andlig

htthem

efore

asyratin

g.(vi)Outlin

e/Offline

functio

ns.

(vii)

View

ingresults

on-th

e-go

with

aniPho

ne.

(viii)V

iewandmanage

patie

nthisto

ry.

Dem

entia

Screening

No

22review

s(4.2)

BioMed Research International 23

Table7:Con

tinued.

AppNam

e(releaseyear)

Offeredby

Platform

Features

Category

PrivacyPo

licyMentio

ned

(Yes/N

o)

Dow

nloads/Reviews

(Raring),

Ifany

Symptom

Guide�

Dem

entia

(2018)

DGIC

linical

iOS

(i)DGIC

linicalProject.

(ii)H

elpcaregiversin

learning

abou

tdem

entia

.Carer

Supp

ort

No

Nodatagiven

Dem

entia

Respon

d(2018)

Academ

yfor

Professio

nal

Excellence

And

roid

(i)Ac

adem

yfor

Professio

nalE

xcellence's

SanDiego

project.

(ii)T

oprovidec

arerstoget

inform

ationabou

tdementia

disease.

Carer

Supp

ort

No

10+do

wnloads

(5)

Your

CareC

ard

(2018)

TheM

emory

Kit,LL

CiO

S

(i)Con

nectallthe

care

team

mem

bers

(ii)D

esignedto

helpcarer

bette

rund

ersta

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24 BioMed Research International

gradual improvement in the well-being of dementia people indaily living is witnessed by using mobile apps. The impact ofwell-being manifests in the form of their behaviour, emotion,cognition, and relationship with carers.

It is found out that informal care places a high amountof mental, emotional, physical, and financial stress to thecarers. Using a mobile app with navigation feature makesit possible to address one of the significant stress factorsfor carers, i.e., the disorientation of PwD while outside theenvironment. Similarly, the video monitoring-based appli-cations have the tendency to provide a promising assistivetool to support carers. These apps with video monitoringhelp carers to detect any falls or accidents of PwD in dailyliving to prevent them from serious injuries. The care is lessburdensome when carers have information and educationabout dementia so that the health-related problems of PwDare well managed and well addressed. Mobile apps make painassessment process of dementia people simpler and easier.The tools are useful in emergency situations and have thecapability to transform the pain of PwD especially for thosewho are unable to communicate or express their feelingsto others. Many mHealth based apps are now working onunderstanding the language abilities of PwD so that theprovision of better care and quality of life can be ensured.Lastly, this review also recommends that the quality of life ofPwDcan also be improved by using reminiscence therapy andsocialization among family members and dementia people.It can be achieved by using such mHealth based dementiaapps that engage dementia people in a series of daily livingactivities and provide carers with a starting point to makeconversation with the dementia sufferer.

5.1. Limitations. In this paper, only studies published inEnglish during the last five years (from 2014 to 2018) offive databases were included which may not take account ofpapers published in other languages and other years.

6. Conclusion

The purpose of this comprehensive study is to identify,evaluate, and synthesize the existing evidence on the use ofmHealth based applications (apps) as a healthcare resourcefor people with dementia and assistance to carers. A reviewof both peer-reviewed and full-text literature was under-taken along with mHealth based dementia applicationsfrom commercial mobile stores. The results of this reviewhave identified five major areas of mHealth based dementiaapplications. To date, applications for dementia healthcareare used in cognitive training, screening, health and safetymonitoring, leisure and socialization, and navigation. Thecognitive training and leisure and socialization of PwDare attained by engaging them in a variety of activities indaily living such as memory, attention, logical thinking,scheduling, and communication. For informal caregivers,the applications are focused on providing awareness andeducation about dementia. The carer support in the form ofnavigation and health and safetymonitoring is also noticeablein mobile applications. The purpose of mobile applications

is to assist carers in understanding the dementia peoplewith the objective of providing a better quality of life. Thisreview concluded that mHealth based assistive technologyhas the potential to provide efficient healthcare facility toPwD and support caregivers as this technology providessimple interactive features and promotes independence.

Data Availability

Please contact authors for data requests.

Disclosure

This article does not contain any studies with human partici-pants or animals performed by any of the authors.

Conflicts of Interest

All the authors declare that they have no conflicts of interest.

Authors’ Contributions

All the authors contributed equally.

Acknowledgments

This work was supported by AI and Data Analytics (AIDA)Lab, Prince Sultan University, Riyadh, Saudi Arabia.

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