Impact of a TV-based Assistive Technology on Older People’s Ability to

Self-manage Their Own Health

Daniela Loi

, Silvia Macis

, Danilo Pani

, Andrea Ulgheri

, Romina Lecis

, Mauro Murgia

Marco Guicciardi

and Luigi Raffo

Department of Electrical and Electronic Engineering, University of Cagliari, Piazza dArmi, Cagliari, Italy

Department of Pedagogy, Psychology, Philosophy, University of Cagliari, Cagliari, Italy

Keywords:

Assistive Technology, Active Aging, Patient Activation, Self-management.

Abstract:

Nowadays, special emphasis is being focused on involving people on their own health and care. The use of

digital technologies in the home-care management process is increasingly contributing to the maintenance of

quality of life and preservation of functional independence in older adults. There is a huge number of available

m-health applications for self-tracking health parameters, but the majority of them are inconsistent with the

needs of older adults who do not currently use technologies such as computers, smartphones or tablets. The

aim of this work is to present a pilot study, which included 19 older adults, that was conducted to objectively

measure the effect of a TV-based assistive system on the improvement of older adults’ activation levels about

self-management of health. The correlation with the usage of speciﬁc digital services provided by the system

was also investigated. The results reveal how the impact is limited by the aspeciﬁc nature of the intervention

with respect to the participants’ health condition. At the same time, they are encouraging and indicate that

there is the potential for the system to impact on older people’ self-management skills.

1 INTRODUCTION

Encouraging people to take an active role in the man-

agement of their health condition provides several ad-

vantages: it helps achieving quality goals and im-

proved clinical outcomes, enhances people’s expe-

rience in the care process and, consequently, their

quality of life, and contributes to the reduction of

the costs of the healthcare systems (Greene and Hi-

bbard, 2012). The concept of being an informed and

activated patient refers to people’s knowledge, abil-

ity, willingness and conﬁdence to exercise indepen-

dent choices to manage their health and care (Hibbard

et al., 2004). Self-management skills include inter-

action with healthcare providers, self-monitoring of

own health conditions, dietary restrictions and healthy

choices, medication adherence, as well as manag-

ing stress and frustration which may come from liv-

ing with diseases and may impact on physical func-

tioning, psychological well-being and social relation-

ships. Self-management practices and skills offer

people an increased level of autonomy in their health,

especially in those facing age-related conditions such

as diabetes, renal and cardiac dysfunctions, hyper-

tension, cardiovascular diseases (Young et al., 2017),

(Johnson et al., 2015). Several studies have recently

shown that the use of information and communica-

tion technology (ICT) tools in the home-care manage-

ment process can help in improving patients’ activa-

tion and in inﬂuencing their attitudes and behaviours

(Kim et al., 2016), (Whitehead and Seaton, 2016).

During the last decade, there has been a trend in de-

veloping telehealth services and telemonitoring tech-

nologies to empower ordinary people to have more

knowledge and control over their own personal health

data. These technologies allow to remotely moni-

tor key physiological parameters such as blood sugar

levels, blood pressure and oxygenation levels, heart

rate and weight, as well as physical activity levels,

opening up new opportunities for self-care and self-

management. Typically, telemonitoring services are

accessible by users through PCs, smartphones and

tablets devices (Anderson et al., 2016), (Morrison

et al., 2014). An overwhelming volume of health-

related smartphone apps are available for download

today and new connected health devices are released

all the time from manufacturers such as A&D Med-

ical, Fitbit, iHealth, Medisana and Withings. How-

Loi, D., Macis, S., Pani, D., Ulgheri, A., Lecis, R., Guicciardi, M., Murgia, M. and Raffo, L.

Impact of a TV-based Assistive Technology on Older People’s Ability to Self-manage Their Own Health.

DOI: 10.5220/0006538802930299

In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 5: HEALTHINF, pages 293-299

ISBN: 978-989-758-281-3

293

ever, mobile interface are often unsuitable for older

people with limited experience or conﬁdence in using

new technologies, then missing the main target. The

use of a much more familiar and convenient interface

such as the TV, can help to address the usability needs

of the older users (Costa et al., 2017), (Raffaeli et al.,

2014).

This paper presents the results of a four-month pi-

lot study aimed at investigating the effect of a TV-

based assisted living system on older people’s activa-

tion and on their self-care behaviors. The system has

been developed in the framework of the HEREiAM

European project, ﬁnanced by the Active and Assisted

Living (AAL) Programme (www.aal-europe.eu, call

5). The system has been designed speciﬁcally for

older people and exploits an Android set-top-box, a

smart card and a simpliﬁed remote control device,

to offer a combination of health, social, comfort and

safety services (Macis et al., 2017). The assessment

was mainly based on the different services usage and

on the patient activation measure (PAM) question-

naire, adopted to measure the level of activation of

participants toward their care management. In partic-

ular, the expected outcomes were an improved PAM

score over time and a signiﬁcant correlation with the

use of the different services provided by the system.

2 MATERIALS AND METHODS

This section provides information on the technology

adopted and on the methodologies followed in the

study for the evaluation of its impact on the users. It

includes a description of the system architecture, an

overview of the population study and of the experi-

mental setup, and an outline of the tools and methods

used for data collection and analysis.

2.1 System architecture

The system in its entirety consists of three main com-

ponents:

• a Home based kit (Figure 1), which includes an

Android set-top-box with installed a set of appli-

cations reﬂecting the interests and the needs of

each user, a personal smart card, a custom remote

control, a portable webcam, some proximity in-

frared sensors and two personal self-care devices

(body scale and non-invasive blood pressure me-

ter);

• a cloud-based infrastructure, called Remote Ser-

vices Platform, that centralizes both the user pro-

ﬁle management and access control (authentica-

tion, authorization, user’s relationships) and the

interoperability services (data and information

sharing, messages exchanging, resources plan-

ning);

• a Web Portal, available for external individuals

such as family members, informal and profes-

sional caregivers, that allows accessing shared

information (health status data, room presence,

usage statistics), according to user authorization

rules.

Webcam

Smart card

Remote control

Android set-top-box

Proximity sensors

Medical devices

Figure 1: Home based kit.

2.1.1 Supported Services

The system basically assists older adults in their daily

life activities by offering a combination of different

digital home-based care services. Using the system

through their own television, older adults are able to:

• Make or receive video calls from a personalized

network of caregivers (Videocall service);

• Get notiﬁcations for upcoming appointments or

events that are scheduled for a speciﬁc time of the

day (Agenda service);

• Access a grocery shopping service from home and

get products delivered right to the door (Shopping

service);

• See the latest news and events happening around

their city, insert events in their Agenda or share

them with friends (News & Events service);

• Receive health coaching and reminder messages

for medication intake, and register how they feel

or behave in relation to a health condition and its

therapy (Coaching service);

• Self-monitor their health status by measuring

blood pressure, heart rate and body weight using

the integrated Bluetooth medical devices with the

TV interface (Health service);

• Be monitored by pre-authorized caregivers in

their day-time and night-time mobility trends

HEALTHINF 2018 - 11th International Conference on Health Informatics

294

around the house through the integrated network

of motion sensors (Tracking service).

All these services were offered with the purpose of

motivating older adults to be more involved in their

health care and to remain independent and socially

active for as long as possible.

2.2 Population Study

A group of 19 older adults (8 males, 11 females)

was recruited for the study by the local Municipal-

ity of Cagliari among the subjects enrolled in the so-

cial services department activities. Inclusion crite-

ria were: participant’s age of 65 years or over, abil-

ity to live independently and engage in normal ver-

bal communication, and familiarity with basic TV

functionalities. Exclusion criteria were: participant’s

age less than 65 years, any kind of cognitive impair-

ments or serious visual or hearing impairments, any

severely limited dexterity in one or both hands. The

study was performed following the principles outlined

in the Helsinki Declaration of 1975, as revised in

2000. Subjects were asked to read and sign an in-

formed consent form prior to their participation in the

study and to complete a pre-participation question-

naire, which inquired about basic demographic as-

pects, background information and medical history.

Sociodemographic and clinical characteristics of the

selected sample can be summarized as follows:

• Age, years (range): 73.15 ± 6.36, (65 − 87);

• Marital status: 65% married, 30% widowers and

5% separated;

• Educational level: 15% completed a primary

school, 40% completed middle school, 30% had

a high school diploma and 15% graduation;

• Health problems in the last 6 months: 80% suf-

fered from some disease;

• Drugs assumptions: 75% reported regular intake

of drugs for conditions such as type 2 diabetes,

hypertension, heart problems, musculoskeletal

problems.

2.3 Study Design

Subjects who consented to the study were contacted

by the research team to schedule a home installation

appointment. The Home based kit was installed in

each house by a technician, assuring that everything

was fully functional and properly working. All partic-

ipants received a user’s manual with all the necessary

information for the proper use of the system. Partic-

ipants with no broadband Internet connection in their

homes were provided with a TP-LINK 4G Wi-Fi don-

gle. The Android TV-box was connected to the HDMI

port of the participant’s TV and to the Internet. Par-

ticipants accessed all the functionalities of the system

by simply inserting their personal smart card, with-

out the need to remember and type any passwords. A

dedicated remote control was entrusted to them in or-

der to control the Android TV-box and navigate the

different services. A portable webcam with built-in

microphone was connected to the TV-box, to exploit

videocall functionalities. The set of medical devices

to monitor the participants’ physical conditions was

conﬁgured and the network of environmental sensors

providing information about participants movements

around the house was installed. The sensors were

connected to the Android TV-box via Bluetooth or

ZigBee. For the whole duration of the study, each

TV-box collected all the different types of data gath-

ered from the network of sensors and instruments in-

stalled at home, and transmitted them to the Remote

Services Platform using the latest medical and secu-

rity standards. These data were made available on the

Internet through the Web portal for remote monitor-

ing purposes. At least one informal caregiver for each

older adult participant was invited to take part in the

study. In total, a sample of 26 informal caregivers (9

males, 17 females, age 43± 7.85 years) expressed in-

terest in participating and in accessing up-to-date in-

formation about their relatives. They received login

credentials and instructions to access the Web portal.

2.4 Assessment Plan

The assessment focused on ﬁnding out if the proposed

services could help in incorporating self-management

support into the daily routine of older adults. The

PAM questionnaire was employed to measure the

level of participants’ activation toward their care man-

agement. All older adult participants were asked to

ﬁll in the PAM questionnaire three times during the

study period: baseline (T

), midterm (T

) and ﬁnal

evaluation (T

). Moreover, the assessment investi-

gated potential correlations between the PAM scores

and the usage time of speciﬁc services (in minutes).

2.4.1 Activation Assessment

The PAM consists of 13 items that are related to pa-

tients’ knowledge of their health condition or disease,

skills and conﬁdence in their management of health

related tasks, and personal beliefs about health care

(Hibbard et al., 2005). For each statement, there are

four response options which are assigned scores from

1 to 4: (1) “Strongly Disagree”, (2) “Disagree”, (3)

“Agree” and (4) “Strongly Agree”. If all questions are

Impact of a TV-based Assistive Technology on Older People’s Ability to Self-manage Their Own Health

295

answered, the total raw score is calculated by adding

all the responses to the 13 items. The range of PAM

raw scores is 13 to 52. In the case of PAM items with

missing data, the total raw score is calculated by di-

viding the sum of the all the responses by the number

of items answered (excepting non-applicable items),

and by multiplying the result by 13. The higher the

PAM scores, the higher patient activation.

2.4.2 Services Usage and Trends Assessment

The system allows collecting statistics related to us-

age of the offered services. The following informa-

tion can be obtained from each Android TV box:

• number of times each service was used;

• total time and the mean time of usage by the single

participant.

This is possible thanks to a dedicated application in-

stalled in the TV box that exploits an internal database

and a service running in background to save statistics

of the actions performed by the older adults using the

system’s applications. When a system application is

opened by the user, the system automatically saves the

following information in the database of the monitor-

ing application:

• name of the launched application;

• a sequence of encoded information identifying

when the event occurred;

• a sequence of encoded information identifying the

user logged on the platform.

The recorded information is saved in real time and a

daily log ﬁle is sent, every 24 hours, to the Remote

Services Platform.

2.5 Data Analysis Methods

All the daily usage information stored in the server

were retrievable through the Web Portal. At the end

of the study, these records were exported on a Mi-

crosoft Excel sheet for statistical analysis. False pos-

itives (applications launched by mistake and closed

after no more than 30 seconds) were manually dis-

carded and the quantitative data obtained were coded

and exported from Excel into SPSS Release 18.

Data related with the system usage were analyzed

with descriptive statistics, in order to identify the av-

erage time and frequency of usage. For each service,

the average session duration was calculated by divid-

ing the total duration of all the sessions performed by

the population study (measured in seconds) by the to-

tal number of sessions, as shown in (1):

Avg Session Duration =

Total Duration

Number of sessions

(1)

A statistical analysis was also performed on the

questionnaires data to describe the psychosocial char-

acteristics of the study population. All variables were

checked about univariate and multivariate normality.

Since data have shown a normal distribution, para-

metric analyses were used. An analysis of variance

(ANOVA) on repeated measures was performed to

analyze the changes of PAM scores from baseline.

The signiﬁcance level was set at p < 0.05. Pearson’s

correlation coefﬁcient was used to assess the correla-

tion between average PAM scores and average time

use of the services: Videocall, Agenda, Shopping,

News&Events, Health.

3 RESULTS

Descriptive statistics on the usage of the proposed ser-

vices are shown in ﬁgures 2, 3 and 4.

Videocall

Agenda

Shopping

News &

Events

Health

Average number of sessions

Figure 2: Average number of sessions for each service. Er-

ror bars represent one standard deviation.

Table 1 details the descriptive statistics for the

PAM scores in each phase of the assessment (T

, T

and T

). The repeated measures ANOVA shows no

signiﬁcant differences between PAM raw scores from

baseline to 4 months, F

2,17

= 1.55, p = 0.24. This

is partially due to the limited trial duration and sam-

ple size. However, it is also worth noting that the

high baseline PAM levels among participants may

have determined a “ceiling effect” in the reported re-

sults. Furthermore, the aspeciﬁc nature of the inter-

vention, with respect to the participants’ health con-

dition, could have determined an underestimation of

the system usefulness, with a consequent limited im-

pact on the subject’s activation. However, a general

improvement in the mean values of PAM, despite the

absence of statistical signiﬁcance, supports the cur-

rent search for eHealth solutions for patient empower-

ment, i.e., the delivery or enhancement of health care

HEALTHINF 2018 - 11th International Conference on Health Informatics

296

00:00:00

00:30:00

01:00:00

01:30:00

02:00:00

02:30:00

03:00:00

03:30:00

04:00:00

Videocall

Agenda

Shopping

News &

Events

Health

Average total duration in hours

Figure 3: Average total duration in hours of all sessions.

Error bars represent one standard deviation.

0,00

1,00

2,00

3,00

4,00

5,00

6,00

7,00

8,00

Videocall

Agenda

Shopping

News &

Events

Health

Average session duration in minutes

Figure 4: Average session duration in minutes for each ser-

vice.

Table 1: Comparisons of PAM scores (Mean and Standard

Deviation) obtained in the three phases of the study: T

, T

and T

Patient Activation Measure

43 (SD 4.9)

43.1 (SD 6.9)

45.2 (SD 4.4)

services or health care information through the Inter-

net and related technologies (Lettieri et al., 2015).

Table 2 displays the correlations between the

mean PAM scores and time use (minutes) of differ-

ent services. The correlations analysis showed a pos-

itive relationship between the use of the applications

Videocall and News&Events. There is some evidence

that participants with higher levels of activation in

managing health care have spent more time using

these two applications. According to these ﬁndings,

greater contact and interaction with friends and rela-

tives and higher interest in local news and city activi-

ties can be associated with higher patient activation.

4 DISCUSSION

The aim of the study was to assess the level of ac-

tivation of the elderly toward their care management

when using a multi-purpose TV-based assistive tech-

nology. An improved PAM score over time was ex-

pected, correlated with the use of the services embed-

ded in the system.

However, after 4 months, there was only a slight

improvement in PAM scores, not reaching statistically

signiﬁcant values. Main limitations of the study were:

the short duration due to the project schedule, the re-

duced number of subjects limiting, among the other

things, any gender-speciﬁc analysis, the absence of

speciﬁc disease whose quantitative monitoring was

perceived by the elderly as worthy of attention. Due

to such study limitations, it is difﬁcult to draw a ﬁ-

nal conclusion on the PAM changes, but the overall

high scores at baseline may have limited the potential

increase in participants’ activation. Moreover, the as-

peciﬁc nature of the intervention, with respect to the

users’ health condition, may have determined an un-

derestimation of the system usefulness, with a conse-

quent limited impact on the subject’s activation. This

makes the achieved results not comparable to those

of studies involving chronic patients (diabetes, heart

failure, etc.), where a telemonitoring is perceived as a

need primarily by the patients themselves.

Descriptive statistics on the usage time high-

lighted that Health was the service most used by par-

ticipants during the study, followed by News&Events,

Videocall, Shopping and Agenda. The Health ser-

vice result is particularly encouraging, taking into ac-

count that there was no supervision on the health data

by professional caregivers. Over the reported period,

participants spent on average a total of 1 hour and 42

minutes in self-monitoring their health data. This is

not a very long amount of time, but considering that

the time needed to complete a measurement session

ranged from 1 to 2 minutes, this result indicates that

on average each participant accessed the Health ser-

vice between two and three times per week. Such

regular self-monitoring of physiological parameters

gave participants some degree of responsibility for

their own care during the trial, and a more tangible

understanding of their health status. Results also re-

vealed that the more engaging services with longer

sessions were VideoCall, News&Events and Shop-

ping. The average amount of time a participant spent

in the VideoCall service during a single session was

about 7.5 minutes.

Impact of a TV-based Assistive Technology on Older People’s Ability to Self-manage Their Own Health

297

Table 2: Correlations matrix between variables.

Variables Health Videocall Agenda Shopping News&Events

PAM −0.23 0.60 (p <0.01) 0.25 0.17 0.43

Health −0.17 −0.26 0.40 0.18

Videocall 0.20 0.16 0.32

Agenda −0.02 0.18

Shopping −0.04

5 CONCLUSIONS

In this paper, the results of a 4-month pilot study, in

which a TV-based system and a set of home-care ser-

vices were introduced into the daily life of 19 older

adults, were presented. Assessment was carried out

with the objective of evaluating how a digital system

developed speciﬁcally for older people changes the

PAM scores, and to understand how the PAM scores

are related to the system usage. The approach, and

the achived results, are important for the development

of similar projects, enabling to address at the time of

the study design some criticalities. Results reveal a

non-intensive use of the system and negligible corre-

lation between the access to the health service provide

within the platform and the PAM score.

In the light of presented results, future investiga-

tions will be performed on people living with speciﬁc

chronic conditions, including asthma, diabetes, and

hypertension. These patients must have an active role

in making decisions about their health, under the su-

pervision of the family doctor or the specialist. To

avoid a ceiling effect, patients whose scores at base-

line are already fairly high will be excluded from the

study.

ACKNOWLEDGEMENTS

This work is part of a project ﬁnanced by the AAL

Programme (AAL-2012-5-064). The authors would

like to thank all the partners involved in the project

for their contribution, and the elderly citizens of the

Municipality of Cagliari who took part in the trial, for

their time and willingness to complete questionnaires

over the lifetime of this study.

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