=Paper=
{{Paper
|id=Vol-2629/2_ppt_aldenaini.pdf
|storemode=property
|title=How Effective is Personalization in Persuasive Interventions for Reducing Sedentary Behavior and Promoting Physical Activity: A Systematic Review
|pdfUrl=https://ceur-ws.org/Vol-2629/2_ppt_aldenaini.pdf
|volume=Vol-2629
|authors=Noora Aldenaini,Rita Orji,Srinivas Sampalli
|dblpUrl=https://dblp.org/rec/conf/persuasive/AldenainiOS20
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==How Effective is Personalization in Persuasive Interventions for Reducing Sedentary Behavior and Promoting Physical Activity: A Systematic Review==
https://ceur-ws.org/Vol-2629/2_ppt_aldenaini.pdf
How Effective is Personalization in Persuasive
Interventions for Reducing Sedentary Behav-
ior and Promoting Physical Activity: A Sys-
tematic Review
Noora Aldenaini1, 2, Rita Orji1, and Srinivas Sampalli1
1
Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
2
Department of Computer Science, Imam Abdulrahman Bin Faisal University, Dammam,
Saudi Arabia
nr412864@dal.ca, rita.orji@dal.ca, srini@cs.dal.ca
Abstract. The use of persuasive systems and devices to reduce sedentary lifestyles and encour-
age individuals to be more physically active is progressively gaining interest. This paper presents
a 13 years review (from 2006 to 2019) of personalized persuasive technologies (PTs) for promot-
ing physical activity (PA) and discouraging sedentary behavior (SB). Moreover, we decon-
structed the various implementations and operationalizations of the personalization in these PTs
and compared their effectiveness. Specifically, this paper aims to (1) shed light on the multiple
ways of implementing personalization in these PTs to promote PA and reducing SB, (2) evaluate
the effectiveness of personalized PTs for promoting PA and decreasing SB, (3) highlight trends
and offer suggestions for research in the area of personalizing PTs.
Keywords: Persuasive technology, Physical activity, Sedentary behavior, Personalization, Goal
recommendations, Activity recommendations, Motivation, Health
1 Introduction
Persuasive technologies (PTs) are interactive computing systems, apps, or devices that
are purposely developed to influence users to adopt healthy behaviors and attitudes and
prevent risky ones without using coercion or deception [15], [41]. PTs are mainly im-
plemented to promote healthy behavior and prevent disease or to manage diseases or
other health conditions [38], [40], but also have been used in other domains.
Persuasive 2020, Adjunct proceedings of the 15th Int. conference on Persuasive Technology.
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0).
2
Sedentary behavior (SB) is generally characterized as a long time sitting behavior –
when an individual expends lower or equal to 1.5 metabolic equivalent (£ 1.5 MET)
[57], [44]. MET “is defined as the amount of oxygen consumed while sitting at rest and
is equal to 3.5 ml O2 per kg body weight x min” [25]. Accordingly, SB and an insuffi-
cient amount of PA are global health concerns, as they lead to obesity and morbidity,
and they are the fourth leading reason for mortality globally, with an estimated 3.2
million deaths worldwide [60]. Therefore, increasing or maintaining a suitable level of
moderate-intensity PA is essential for avoiding or mitigating different diseases and
health complications such as obesity, cancer, diabetes, and cardiovascular diseases [12],
[19].
Persuasive Technology (PT) interventions are considered powerful tools for helping
people to adopt healthy behaviors such as maintaining or increasing PA levels and re-
ducing sedentary lifestyles. PTs are often deployed using various technological plat-
forms (e.g. fitness activity trackers and sensors, smartphones, websites, social network-
ing sites (SNSs), games, desktop computers, and ambient displays) [1], [41]. Activity
trackers, for instance, are often used to track and monitor personal data (e.g. the user’s
PA level, step count, heart rate, and time spent sedentary), and these activity tracker
devices are used mostly with other technology platforms (e.g. smartphones, web-based
apps) to provide users feedback about their PA progress, personalized feedback, and
personalized recommendations [1], [32], [26].
Research has suggested that personalizing PTs increases their effectiveness [39]. Thus,
personalizing PT intervention is crucial because people are different with respect to
their personal preferences, activity levels, objectives, requirements, lifestyles, and
health conditions, and even personality [42], [43], [46]. As a result, there is an increas-
ing demand for PTs to be personalized to increase their effectiveness. The personaliza-
tion strategy requires a system to provide personalized content or services to increase
relevance, motivation, and persuasion effects [22].
There is an increasing number of reviews of PTs for health and wellness. However,
most of these reviews focused on the general area of health and wellness and their gen-
eral application of various persuasive strategies, for example, see Orji and Moffat [41],
and Aldenaini et al. [1]. Research has highlighted the importance of personalizing PT,
and the personalization strategy is one of the most frequently employed persuasive
strategies [3] used in PT designs. Hence, there is a need for in-depth research into ana-
lyzing various implementations of personalization in persuasive strategies and the ef-
fectiveness of personalized PTs.
Therefore, this paper presents a 13-years review (from 2006 to 2019) of personalized
PTs for promoting PA and discouraging SB. Moreover, we deconstructed the various
implementations and operationalization of the personalization in these PTs to evaluate
and compare their effectiveness. Specifically, this paper aims to (1) shed light on the
various implementations a personalization in PT interventions for increasing PA and
reducing SB, (2) evaluate the effectiveness of personalized PTs for promoting PA and
decreasing SB, (3) highlight trends and offer suggestions for research in the area of
personalizing persuasive technologies.
3
2 Related Works
An increasing number of systematic reviews is being conducted to determine the effec-
tiveness of PTs in various domains. Ghanvatkar et al. [19] provided a scoping review
of personalization strategies employed in PA interventions. They included 49 eligible
studies in their review paper. They examined personalization strategies in the form of
feedback or recommendations. Furthermore, they identified six types of a personaliza-
tion strategy based on different forms of implementation in their reviewed studies.
These personalization types are summarized as shown in Table 1.
There are other interesting review papers on PT interventions in the area of PA and/or
SB in general – not focus specifically on personalization. For example, Almutari and
Orji [2] provided a systematic review of articles that focused on PT for promoting PA.
They analyzed the effectiveness of PT that employed social influence strategies such
as comparison, cooperation, and competition only. Their findings revealed that PTs
employing social support strategies to promote PA are promising in motivating users
to be physically active.
Similarly, Aldenaini et al. [1] conducted a 16-years systematic review (from 2003 to
2019) of PTs and their effectiveness for promoting PA and discouraging SB. They high-
lighted trends in their outcomes such as research methods, behavioral theories, persua-
sive strategies and different ways of implementing each strategy, system design, and
employed technologies. Their findings revealed that employing PTs were effective and
promising in promoting a desirable behavior change among different populations when
employed with a suitable persuasive strategy. They also provided a list of interesting
recommendations for advancing PTs’ future research.
Furthermore, Wang et al. [58] conducted a systematic review of studies targeted at re-
ducing SB in the work environment. They used the persuasive system design (PSD)
model [22] to evaluate the effectiveness and utilization of PT in discouraging prolonged
SB among office works. Their findings showed that a reminder was the most frequently
employed PSD strategy. They also found that coupling a reminder strategy with educa-
tion sessions was more promising than hourly reminders alone.
Our systematic review paper included studies that employed a personalization strategy
in their PT design to promote PA and/or reduce SB. In contrast, many existing studies
tend to focus only on either promoting PA or reducing SB, and hardly on both. We also
aimed at examining various ways of implementing personalization in different PTs.
Again, our review specifically focused on PTs employing a personalization strategy in
the area of SB and PA.
Table 1: Types of Personalization [19].
Type of Personalization Meaning/Definition
Goal Recommendations Quantified goals such as step count, floor count,
duration of exercise, calorie burn rate.
4
Activity Recommendations Recommending a specific type of PA or behavior
such as standing, walking, running, cycling.
Fitness Partner Recommendations Matching a user of a system to other users who are
similar and have the same target goals for motivat-
ing them in maintaining or increasing their PA lev-
els.
Educational Content Increasing users' knowledge and awareness by
sending personalized feedback about the health
benefits of PA or some techniques and tips for im-
proving PA.
Motivational Content Motivating users to improve their PA by sending
personalized motivational feedback and reinforce-
ment messages.
Intervention Timing Finding the right and suitable time to send a rec-
ommendation or feedback to the users such as
sending a notification reminder to a user at a suita-
ble time and opportune moments
3 Methods and Coding Scheme
As this paper aims to evaluate and analyze PT interventions (e.g. systems, apps, or
websites) that implemented a personalization strategy, we used quantitative content
analysis to classify data into different categories and compare between different out-
comes [48].
We used Google Scholar, ACM Digital Library, Springer, PubMed, Elsevier Scopus,
and EBSCOHost databases to search for and select relevant studies. We searched the
terms “Persuasive Technology and Physical Activity”, “Persuasive Technology and
Sedentary Behavior”, “Technology and Physical Activity Interventions”, “Technology
and Sedentary Behavior Interventions”, “Fitness and Persuasive Technology”, “Pro-
longed Sitting and Sedentary Lifestyles”, “Physical Activity Apps or Applications”,
and “Sedentary Behavior Apps or Applications”. We also searched through the relevant
references from the reviewed studies. We used Mendeley, a reference manager, to or-
ganize the obtained articles.
After searching through different databases, we identified 534 unique titles, of which
315 articles were excluded by title, while 219 articles were considered eligible based
on title examinations. We investigated each title to check whether it falls within the
scope of the review or not. We excluded those titles that targeted other health domains
– domains not related to PA and/or SB (e.g. dental health, smoking cessation, unwanted
pregnancy, eating habits, risky sexual behavior, alcohol drinking, etc.). After examin-
ing the abstract of the 219 remaining articles, we excluded 181 articles, and we included
a total of 38 articles. The included articles: were published in English between 2006
and 2019; implemented any form of a personalization strategy, included personalized
5
recommendations or feedback to promote PA and/or reducing SB; and were targeted at
PA or SB, or both. We summarized the search and exclusion process, as shown in Fig-
ure 1.
We coded the 38 relevant articles by adapting the coding scheme created by Orji and
Moffat [41] and validated by many other researchers, including [1], [3], [2]. As shown
in Table 2, the coding sheet contains the study author(s), year of publication, domains,
technology platforms, duration of a study, evaluation methodology, persuasive strate-
gies, theories, targeted outcomes, audience age demographic, number of participants,
results, and country of a study. We added a new identification to the coding sheet, which
is the type of personalization as we adapted from Ghanvatkar et al. [19]. The types of
personalization refer to the different ways of implementing a personalization strategy
throughout the PT interventions. Appendix 1 provides a comprehensive overview of
our coding sheet.
Fig. 1. The Studies Selection Workflow.
Table 2: Coding Scheme Analysis- Adapted from Orji and Moffat [41].
S/N Identification Example
1 Author(s)/Year Name of author(s) and year of publication.
2 Domain PA, SB, Mental Health, etc.
3 Technology Mobile, Web, Computer applications, etc.
4 Evaluation Methods Quantitative, Qualitative, and Mixed.
6
5 Types of Personalization Goal, activity, or fitness partner recommendations, educa-
(Ways of implementa- tional or motivational content feedback, and intervention tim-
tions) ing.
6 Persuasive Strategies Motivational strategies employed.
7 Duration of Evaluation Weeks, months, years, etc.
8 Theories Theories implemented either on the system design of a PT or
on the evaluation of a study.
9 Targeted Outcomes Behavior, Motivation, Attitudes, Awareness, etc.
10 Audience Age De- Children, Adults, Old People, etc.
mographics
11 Number of Participants How many participants involved in the study assessment?
12 Results Successful or not.
13 Country Country of a study where conducted.
4 Results
Our analysis of existing PT interventions that applied personalization in their system
designs for PA promotion and/or SB reduction revealed interesting outcomes. This sec-
tion presents our findings from the reviewed studies in detail.
4.1 Persuasive Technology for Physical Activity and Sedentary Behavior by
Year and Country
Based on our inclusion and exclusion criteria, Figure 2 shows that most of the articles
were published between 2016 and 2019. Three articles (8%) were published in each of
2010, 2012, 2013, and 2014. One article (3%) was published in each of 2006, 2007,
2008, and 2011.
7
Fig. 2. Persuasive Technologies for Physical Activity Promotion and Sedentary Behavior Re-
duction Trends by Year.
Figure 3 shows that the reviewed studies were conducted in 16 countries. The USA had
the largest number of studies with a total of 17 (45%). The UK followed the USA with
a total of 4 studies (11%). Netherlands and Canada were in third place with a total of 3
studies (8%) each.
Fig. 3. Persuasive Technologies for Physical Activity Promotion and Sedentary Behavior Re-
duction Trends by Country.
8
4.2 Targeted Domains
All the studies included in this review were targeted at either promoting PA and/or
discouraging SB. We categorized the targeted health domains into three groups: PA,
SB, and mixed (the studies that focused on both PA promotion and SB reduction).
Thirty-two studies (84%) were targeted at maintaining or increasing PA, while four
studies (11%) focused on decreasing SB. Only two studies (5%) targeted both the PA
and SB domains. Figure 4 presents the targeted health domains covered in this review
paper.
Fig. 4. Targeted Health Domains.
4.3 Evaluation Methodologies Used for Promoting Physical Activity and
Reducing Sedentary Behavior
Figure 5 shows the percentage of the total number of studies employing in each evalu-
ation methodology. The evaluation methodologies covered in the reviewed studies are
categorized into three main methods: qualitative, quantitative, and mixed (methods that
include both qualitative and quantitative methodologies). The evaluation approach
most commonly used in the studies was mixed methods with a total of 17 studies (45%).
The qualitative methodology ranked second with a total of eight studies (21%). This is
followed by the quantitative methodology with a total of five studies (13%). Eight stud-
ies (21%) did not evaluate their PT designs.
9
Fig. 5. Evaluation Methods Used in the Reviewed Studies.
4.4 Effectiveness of Personalized PT based on Evaluation Methods
Figure 6 shows that out of the 17 studies that employed a mixed-methods approach, ten
studies (59%) reported fully successful outcomes, and seven studies (41%) reported
partially successful outcomes. Fully successful outcomes mean those studies that re-
ported all positive outcomes with respect to achieving their design objectives, as re-
ported by the authors in their papers. By partially successful outcomes, we mean that
the results of the PT evaluation show a mixture of both positive and negative outcomes
respect to achieving their design objectives. The negative outcome means studies that
were totally unsuccessful at achieving their design objectives. Out of the eight studies
that employed a qualitative methodology, five studies (63%) were fully successful, two
studies (25%) were partially successful, and only one study (12%) did not specify its
outcomes. All five studies that employed only a quantitative methodology to evaluate
their PT designs reported fully successful outcomes.
10
Fig. 6. Comparative Effectiveness of PTs Based on Evaluation Methods.
4.5 Target Audience of Personalized PTs
The number of participants in the evaluation of the PT interventions for promoting PA
and discouraging SB varies significantly across the reviewed studies. The number of
participants ranged from 4 to 129,010. For the reviewed studies that had multiple
phases, we combined the number of participants from all phases.
As represented in Figure 7, sixteen studies (42%) were targeted at adults (31–54 years
old), while six studies (16%) were targeted at young adults (18–30 years old). Children
and elderly people were targeted in five studies (13%) for each. Four studies (11%)
targeted teenagers, and only six studies (16%) did not specify their target population.
Fig. 7. Target Audience of Personalized PTs.
11
4.6 Effectiveness of Personalized PTs Across Various Age Groups
Figure 8 shows the effectiveness of personalized PTs based on the population age de-
mographic. Out of the 16 studies targeted at adults, six studies (38%) reported fully
successful outcomes, seven studies (44%) reported partially successful outcomes, two
studies (12%) did not evaluate their PT designs, and only one study (6%) did not specify
its outcomes.
All six studies that targeted at young adults reported fully successful outcomes. For
children, out of the five studies targeted at them, three studies (60%) showed fully suc-
cessful outcomes, one study (20%) was partially successful, and one study (20%) did
not evaluate its PT design. Out of the five studies targeted at elderly people, four studies
(80%) were fully successful, and only one study (20%) did not provide an evaluation
for its design. Three studies (75%) targeted at teenagers reported fully successful out-
comes, and only one study (25%) targeted at teenagers was partially successful. Out of
the six studies that did not specify their target population, two studies (33%) were fully
successful, and four studies (67%) had no evaluation.
Fig. 2. Effectiveness of Personalized PTs Across Various Age Groups.
4.7 Personalization Implementations in PT for PA and SB
Most reviewed PTs implemented a personalization strategy as personalized feedback
and personalized recommendations. With respect to feedback, the personalization strat-
egy was mostly employed as personalized educational or personalized motivational
content. However, for the recommendations, personalization was employed as person-
alized activity recommendations, personalized goal recommendations, or personalized
fitness partner recommendations in line with Ghanvatkar et al. [19].
According to Ghanvatkar et al. [19], there are six types of a personalization strategy, as
shown in Table 1. Thus, we adapted their categorizations of personalization and used it
12
in analyzing the personalization approaches employed in the reviewed studies. The
comprehensive details about each type/category of personalization and their definitions
can be found in Ghanvatkar et al. [19].
Figure 9 shows that out of the 38 reviewed studies, twenty-three studies (61%) imple-
mented personalization strategy as personalized motivational feedback to users. Nine-
teen (50%) of the total studies implemented the personalization strategy as personalized
goal recommendations. Personalized activity recommendations and personalized inter-
vention timing ranked third with a total of ten studies (26%) for each. Just five studies
(13%) implemented a personalization strategy as personalized educational feedback.
Intervention timing is a type of personalization that uses the context of the feedback or
recommendation to find the right and suitable time to deliver it to the user [19]. Only
one study (3%) implemented a personalization strategy as a personalized fitness partner
recommendation.
Fig.3. Personalization Implementations in Persuasive Technologies for PA and SB.
Besides the above personalization approaches, other implementations of a personaliza-
tion strategy were identified in the reviewed studies. For instance, Dantzing et al.[10]
implemented personalization in the form of context-aware coaching, as users got a daily
personalized step goal, and they were coached through a custom-design smartphone
application to achieve their targeted goal by receiving personalized messages in real-
time. Thus, the work of Dantzing et al.[10] provided an example of three types of per-
sonalization: goal recommendations, educational content, and motivational content.
Another example implementation of the personalization as goal recommendations and
motivational content was found in Bounce [31], a smartphone app for breast cancer
13
survivors that encourages them to engage in more PA. The Bounce app reminds users
of their PA goals. It also provides personalized and customizable reinforcements and
virtual rewards such as badges and trophies once users achieve progress towards ac-
complishing their goals and sends pop-up messages to congratulate users on their PA
progress.
Schafer et al. [50] delivered personalization as personalized motivational content. They
provided personalized gamified feedback through a smartphone application. This feed-
back was delivered by providing a simple visualization of the activity level through a
personalized animated avatar and represented them based on the gender of children.
Francillette et al. [17] showed an example of implementing personalization as person-
alized goal recommendations and intervention timing. They designed a smartphone ex-
ergame app to motivate individuals with severe mental health conditions to integrate
PA into their daily lives. The app enables players to plan and set their PA goals based
on the players’ profiles, which allows the system to generate different PA choices with
different difficulty levels according to the players’ predetermined choices as personal-
ized goal recommendations. These PA choices were delivered to the players at suitable
times as personalized intervention timing.
The PRO-Fit application [11] showed an example of implementing personalization as
personalized fitness partner recommendations, goal recommendations, activity recom-
mendations, and intervention timing. PRO-Fit is a personalized smartphone fitness ap-
plication that recommends personalized PA sessions based on the user’s calendar and
availability, fitness goals, and preferences. Furthermore, the app integrates with the
user’s social networks, and, based on them, the app suggests “fitness buddies/partners”
that have similar fitness goals, preferences, and availability.
Table 3 provides a summary of different ways of implementing a personalization strat-
egy in our reviewed studies based on the types of personalization that have been clas-
sified, defined, and validated by Ghanvatkar et al. [19] in their scoping review study.
Table 3: Implementation of A Personalization Strategy.
Personalization Strategy
Implementation
Categories
Personalized Goal Recom- Sending personalized messages and notifications to re-
mendations mind users about their target quantified goals (e.g. per-
sonalized context-aware coaching, generating different
PA choices and sessions based on the users’ goals and
preferences). For example of implementations, see
[31], [10], [11], and [17], etc.
Personalized Activity Rec- Sending personalized suggestions of suitable type of
ommendations physical activities to users (e.g. biking, running, aero-
bic, yoga, cycling, stretching, walking). For example,
see [11], and [23], etc.
14
Personalized Fitness Partner Matching users of a PT system to a similar partner who
Recommendations have the same target goals to increase their motivations
(e.g. suggesting “fitness buddies/partners” that have
similar fitness goals, preferences, and availability). For
example, see [11].
Personalized Motivational Sending personalized feedback or messages that aim to
Content motivate users to change their behavior of engaging in
more PA (e.g. context-aware coaching that encourages
users to continue maintaining a good levels of practic-
ing PA, personalized gamified and visual feedback of
the user’s activity level through a personalized ani-
mated avatar). For example, see [10], [31], and [50],
etc.
Personalized Educational A personalized feedback that targeted at increasing the
Content awareness and knowledge of the users by providing
them with different tips and instructions (e.g. context-
aware coaching that educate users in how to specific
type of PA). For example, see [10], and [14], etc.
Personalized Intervention Intervention timing is a type of personalization that
Timing uses the context of the feedback or recommendation
and finds the right and suitable time to deliver it to the
user (e.g. recommending PA choices PA to be deliv-
ered to the players at their suitable times and availabil-
ity). For instance, see [11], and [17], etc.
4.8 Effectiveness of Personalization in Physical Activity and Sedentary
Behavior Domains
Figure 10 summarizes the effectiveness of the reviewed studies, all of which employed
some form of personalization in their persuasive intervention design. Out of the total
38 reviewed studies, twenty studies (52%) reported fully successful outcomes, nine
studies (24%) were partially successful, eight studies (21%) did not evaluate their PT
designs, and only one study (3%) did not specify its evaluation outcomes. Overall,
forty-seven (76%) of the total reviewed studies reported successful outcomes, whether
fully or partially successful.
Figure 11 shows the effectiveness of various implementations of a personalization strat-
egy. Out of the 23 studies that employed motivational feedback, 16 studies (69%) re-
ported fully successful outcomes, five studies (22%) reported partially successful out-
comes, and only two studies (9%) had no evaluation of their PT designs. Out of the 19
studies that implemented a personalization strategy as goal recommendations, eight
studies (42%) were fully successful, four studies (21%) were partially successful, six
studies (32%) did not evaluate their system, and only one study (5%) did not specify its
outcomes.
15
Out of the ten studies that applied activity recommendations, six studies (60%) showed
fully successful outcomes, two studies (20%) reported partially successful outcomes,
and two studies (20%) had no evaluation.
Of the ten studies that employed the personalized intervention timing as an implemen-
tation of persuasive strategy, five studies (50%) reported fully successful outcomes,
three studies (30%) were partially successful, and just two studies (20%) were not eval-
uated. Finally, out of the five studies that implemented educational feedback as a form
of personalization, three studies (60%) were fully successful, one study (20%) was par-
tially successful, and one study (20%) had no evaluation. Only one study employed a
fitness partner recommendation as a form of personalization, and this study did not
evaluate its PT design.
Fig.4. Overall Effectiveness of Personalized PT for PA and SB.
16
Fig. 5. Effectiveness of Personalized PT Based on How a Personalization Strategy was Imple-
mented.
5 Discussion
We found that many of the reviewed studies (45%) employed a mixed-methods evalu-
ation, which is a combination of qualitative and quantitative evaluation methodologies.
We highly recommend researchers to apply the mixed evaluation methodology to fully
reveal the comprehensive impact of their PT design and its effectiveness rather than
employing either the qualitative method alone or a quantitative method alone.
The majority of the reviewed studies targeted adults and young adults with a total of 22
studies (58%). Thus, we recommend that researchers design more PT for promoting PA
and discouraging SB targeting other populations such as the elderly, teenagers, and
children. Our findings showed that the studies targeted at adults and young adults re-
ported the largest number of successful outcomes, whether fully or partially successful.
This is perhaps because adults and young adults are at an active age, and they can prac-
tice moderate-intensity PA easily more than older populations. Similarly, adults and
young adults are more aware of the benefits of PA and the consequences of a sedentary
lifestyle than teenagers and children [1], [2].
Based on the reviewed studies, we found that personalizing PT for promoting PA and
discourage SB among users is an effective and promising approach of increasing the
effectiveness of PTs, with a total of 29 (76%) of the entire reviewed studies (38) report-
ing successful outcomes, both fully and partially successful outcomes.
17
We included studies that implemented any form of personalization in the PT design for
PA and SB domains. The results of our analysis revealed that personalization was de-
livered and implemented differently from one study to another based on the user’s pro-
file, preferences, predetermined goals, and availability. We found that the most com-
mon and effective way of implementing a personalization strategy based on the re-
viewed studies emerged to be personalized motivational content. We believe this is
because motivation is one of the most crucial factors for persuading users to achieve a
particular objective [37], such as, in our case, increasing PA levels and reducing SB.
Thus, personalized feedback that aims to motivate users to change their behavior of
engaging in more PA and reducing SB plays an essential role in improving users’ mo-
tivation and commitment.
The second most frequently employed and effective type of personalization implemen-
tation is the goal recommendations. Personalized goal recommendations were delivered
to users based on the PA goals they set on the PT system. It is important to mention that
goal recommendations describe quantified goals such as step counts, calories burned,
and duration of activity [19]. Users appreciated systems that reminded them of their
personal goals and objectives.
Based on our findings, personalized activity recommendations and intervention timing
ranked as the third most commonly employed and effective implementation of person-
alization in PTs for promoting PA and decreasing SB. Activity recommendation entails
prescribing different types of activities for achieving a set goal such as running, walk-
ing, or cycling. Intervention timing focuses on sending feedback or recommendations
to users at a suitable and available time for them because users may ignore or forget
feedback sent when they are busy with other primary tasks that take greater priority
[19].
Although educational content and fitness partner recommendations seem to be the least
commonly employed types of personalization implementation, they are considered ef-
fective tools to increase the awareness of the users about the benefits of PA for health
and general well-being and the consequences of SB and to provide external motivations
through matching users with partners who have similar goals and objectives to assist
them in maintaining their PA level [19]. Therefore, we recommend researchers to em-
ploy a personalization strategy and deliver it to users using different types of imple-
mentation based on the users’ needs and combine it with other complementary persua-
sive strategies to achieve a desired behavior change objective.
Since most of the reviewed studies employ more than one persuasive strategy, this
makes it challenging to know which of the employed persuasive strategies contributed
to the effectiveness of a PT and lead to the observed behavior change, such as increasing
PA levels and reducing SB. Therefore, we cannot attribute the observed results on the
effectiveness of the PTs to their use of a personalization strategy only.
18
6 Conclusion
This paper presented some interesting trends on various implementations of a person-
alization strategy and provided a general overview of personalized PT interventions for
promoting PA and discouraging SB. We uncovered various ways of implementing per-
sonalization in different PTs and compared their effectiveness, including personalized
motivational and educational content feedback, personalized goal and activity recom-
mendations, personalized intervention timing, and personalized fitness partner recom-
mendations. Finally, our findings revealed that PT interventions for promoting PA and
decreasing SB are effective and promising when they are personalized.
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APPENDIX 1
Appendix 1. A Comprehensive Overview of PT for Physical Activity and/or Sedentary Behavior
# Authors Do- Technol- Applica- Persuasive Strategies Theo- Evalua- Types of Per- Duration Targeted Audience No. of Results Country
of Arti- main ogy tion / Pro- /Affordances ries tion sonalization Outcomes Age Partici- of Study
cles, ject Name Method (Ways of imple- Group pants
Year, mentation)
Refer-
ence
1 Foster et PA Smartphon StepMatron Tracking, Personalization, none Mixed motivational 3 Weeks Behavior Adults 10 Fully Suc- UK
al.(2010), e mobile, Goal Setting, Self-Moni- content and goal cessful
[16] Computer, toring, Social Support (So- recommendation
Pedometer cial Learning, Compari-
sons, Competition, Rank-
ings Recognition, Giving
Comments)
2 He and SB Smartphon On11 Tracking, Reduction, Tun- none Qualita- activity recom- 2 Weeks Behavior, Adults 8 Partially USA
Agu e mobile neling, Tailoring, Person- tive mendations, and Awareness Successful
(2014), alization, Goal Setting, intervention tim-
[23] Self-Monitoring (Self-Re- ing
flection), Reminder, Sug-
gestion, Liking
3 Fahim et SB Smartphon Alert Me Tracking, Personalization, none Quantita- educational con- Unspeci- Behavior, Unspeci- 0 Fully Suc- Russia
al.(2017) e mobile Self-Monitoring, Re- tive tent, activity fied Awareness fied cessful
, [14] minder recommenda-
tion, interven-
tion timing
4 Mohadis PA Smartphon WargaFit Tracking, Reduction, Tun- none Mixed goal recommen- Unspeci- Behavior Elderly 8 Fully Suc- Malaysia
and Ali e mobile neling, Tailoring, Person- dations, and ac- fied cessful
(2016), alization, Self-Monitoring, tivity recom-
[34] Simulation, Rehearsal, mendation
Praise, Reminders, Sug-
gestions, Similarity, Ex-
pertise, Real world feel,
Third-Party Endorsement,
Verifiability, Social Sup-
port (Social Learning, So-
cial Comparison, Norma-
tive influence, Social fa-
cilitation, Competition,
Recognition)
Persuasive 2020, Adjunct proceedings of the 15th Int. conference on Persuasive Technology. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution
4.0 International (CC BY 4.0).
2
Appendix 1. (continued)
# Au- Do- Technology Applica- Persuasive Strategies /Af- Theo- Evalua- Types of Per- Duration Targeted Audi- No. of Results Country
thors of main tion / fordances ries tion sonalization Outcomes ence Partici- of Study
Arti- Project Method (Ways of imple- Age pants
cles, Name mentations) Group
Year,
Refer-
ence
5 Cambo SB Smartphone BreakSe Tracking, Personalization, none Mixed intervention tim- 8 Days Behavior Adults 6 Partially USA
et mobile, nse Self-Monitoring, Rewards, ing, and activity Successful
al.(2017 Smartwatch Reminder recommendation
), [7]
6 Mansart PA Smartphone- Go Run Tracking, Tunneling, Per- none Mixed motivational Unspecified Behavior Adults 10 Fully Suc- Thailand
et and based mobile Go sonalization, Self-Monitor- content cessful
al.(2015 SB exergame ing, Rewards, Social Sup-
), [30] port (Sharing)
7 Lin et PA Smartphone Motivate Tracking, Reduction, Per- none Mixed motivational 5 Weeks Behavior, Adults 6 Fully Suc- Nether-
al.(2011 mobile appli- sonalization, Feedback content, inter- Awareness cessful lands
), [29] cation, web from users (Self-Report), vention timing,
application Reminder, Suggestion activity recom-
mendations
8 Dharia PA Smartphone PRO-Fit Tracking, Reduction, Per- none none goal recommen- none Behavior Un- 0 none USA
et mobile appli- sonalization, Self-Monitor- dations, activity speci-
al.(2016 cations ing, Reminder, Suggestion, recommenda- fied
), [11] Authorization, Social Sup- tions, fitness
port partner recom-
mendations, in-
tervention tim-
ing
9 Klein et PA Smartphone Ac- Tracking, Reduction, Tai- MBR, Qualita- motivational 3 Months Behavior, Young 100 Fully Suc- Nether-
al.(2017 mobile appli- tive2Get loring, Personalization, TTM, tive content, inter- Awareness Adults cessful lands
), [26] cation, Web her Goal Setting, Self-Monitor- DCM, vention timing,
page, Face- ing, Simulation, Reminder, SCT, activity recom-
book, Weara- Suggestion, Liking, Social SRT, mendations
ble activity Role, Surface Credibility, HAPA
tracker (Fit- Social Support (Social
bit) Comparison)
3
Appendix 1. (continued)
# Authors Do- Technol- Application / Persuasive Theories Evaluation Types of Per- Duration Targeted Audience No. of Results Country
of Arti- main ogy Project Strategies /Af- Method sonalization Outcomes Age Group Partici- of Study
cles, Name fordances (Ways of imple- pants
Year, mentations)
Refer-
ence
10 Arteaga PA Smartph Mobile App Tracking, Re- TPB, Qualitative activity recom- 1 Month Behavior Teenagers 5 Fully Suc- USA
et one mo- duction, Per- TMB, mendations, mo- Motiva- cessful
al.(2010) bile sonalization, PRT tivational con- tion
, [5] game ap- Self-Monitor- tent
plication ing, Reward,
Social Support
(Competition)
11 Luca PA Smartph LocoSnake Tracking, Re- none Mixed motivational 5 Minutes Attitude Young 15 Fully Suc- Italy
Chittaro one mo- game duction, Per- content Adults cessful
and Ric- bile ex- sonalization,
cardo ergame Self-monitor-
Sioni ing, Simula-
(2012), tion, Rewards
[8]
12 Haque et PA Mobile iGO Personaliza- SDT Qualitative motivational 1 Week Behavior Young 26 Fully Suc- Finland
al.(2016) to web tion, Self-Mon- content Adults cessful
, [21] applica- itoring, Re-
tion (An- wards, Re-
droid) minder, Social
Support (Com-
petition,
Recognition)
13 Bond et SB Smartph B-MOBILE Tracking, Per- none Quantita- goal recommen- 16 Behavior, dults 30 Fully Suc- USA
al.(2014) one ap- sonalization, tive dations, inter- Months Motiva- cessful
, [6] plication, Goal Setting, vention timing tion
Weara- Self-Monitor-
ble sen- ing, Praise, Re-
sor wards, Re-
minder
4
Appendix 1. (continued)
# Au- Do- Technol- Application Persuasive Strategies Theories Evalua- Types of Per- Dura- Targeted Audience No. of Results Coun-
thors of main ogy / Project /Affordances tion sonalization tion Outcomes Age Group Partici- try of
Arti- Name Method (Ways of imple- pants Study
cles, mentations)
Year,
Refer-
ence
14 Skriloff PA Smartpho FitPlay Tracking, Personaliza- none none intervention tim- none Behavior, Unspecified 0 none USA
et ne mobile Games plat- tion, Social Support (Co- ing, and activity Motivation
al.(2016 applica- form operation, Competition) recommendation
), [51] tion (An-
droid),
Wearable
activity
tracker
(Fitbit)
15 McMah PA Smartpho Ready~Stea Reduction, Personaliza- WMT, none goal recommen- none Behavior Elderly 0 none USA
on et ne mobile dy tion, Goal Setting, Self- USS, dations
al.(2013 applica- Monitoring, Simulation, TDP
), [33] tion Praise, Rewards, Social
Role
16 Rama- PA and Mobile to ohmage Tracking, Personaliza- none none goal recommen- none Behavior Unspecified 0 none USA
nathan Experi- web plat- tion, Self-Monitoring, dations, motiva-
et ence form Feedback from users tional content
al.(2012 Sam- (Self-Report), Praise,
), [47] pling Surface Credibility, So-
cial Support
17 Stanley PA and Smartpho PiNiZoRo Tracking, Reduction, none Qualita- activity recom- Unspeci- Behavior, Children 4 Fully Canada
et Obesity ne mobile Personalization, Simula- tive mendations fied Awareness Suc-
al.(2010 game ap- tion cessful
), [54] plication
5
18 Toscos PA Mobile Mobile App Tracking, Personaliza- none Mixed motivational 3 Weeks Behavior Teenagers 8 Par- USA
et phone ap- tion, Goal Setting, Self- content tially
al.(2008 plication, Monitoring, Praise, Re- Suc-
), [56] Pedometer minder, Social Support cessful
(Comparison, Competi-
tion, Sharing)
Appendix 1. (continued)
# Au- Do- Technology Applica- Persuasive Strategies /Af- Theo- Evaluation Types of Person- Dura- Targeted Audience No. Results Coun-
thors of main tion / Pro- fordances ries Method alization (Ways tion Outcomes Age of try of
Arti- ject Name of implementa- Group Par- Study
cles, tion) tici-
Year, pant
Refer- s
ence
19 Mutsud PA Mobile text Mobile Tailoring, Personalization, Goal TTM Mixed goal recommen- 3 Behavior Young 30 Fully USA
di and messaging phone text Setting, Self-Monitoring, Praise, dations, motiva- Months Adults Success-
Con- app, Pedom- messaging Reward, Reminder, Suggestion, tional content ful
nelly eter app Social Support (Sharing)
(2012),
[35]
20 Toscos Eating Cell-phone Chick Tracking, Reduction, Personali- none Mixed motivational con- 6 Days Behavior, Female 10 Fully USA
et and PA application, Clique zation, Self-Monitoring, Praise, tent Aware- Teenagers Success-
al.(2006 Pedometer Social Support (Cooperation, ness ful
), [55] Competition, Sharing)
21 Sohn PA and PDA text UP Health Tracking, Personalization, Goal none Qualitative goal recommen- 1 week Behavior, Adults 5 Partially South
and Lee Smok- messaging, Setting, Self-Monitoring, Re- dations Aware- Success- Korea
(2007), ing Instant Mes- ward or Punishment, Reminder, ness ful
[52] saging (IM) Social Support (Cooperation,
system, Mo- Competition)
bile device
22 Glynn PA smartphone, Accupedo Tracking, Personalization, Goal none Qualitative goal recommen- 2 Behavior Adults 80 Unspeci- Ireland
et Pedometer Setting, Self-Monitoring, Social dations Months fied
al.(2013 Support (Sharing)
), [20]
6
23 Marcu PA Smartphone Bounce Reduction, Tunneling, Personali- TTM, Qualitative motivational con- 3 Weeks Behavior, Adults 4 Fully USA
et al. mobile zation, Goal Setting, Self-Moni- SCT tent , goal recom- Attitude, Success-
(2018), toring, Praise, Rewards, Re- mendations Aware- ful
[31] minders, Social Role, Trustwor- ness, Mo-
thiness, Expertise, Authority, tivation
Social Support (Normative In-
fluence, Cooperation, Social In-
teraction)
Appendix 1. (continued)
# Au- Domain Technol- Applica- Persuasive Strategies Theories Evaluation Types of Per- Dura- Targeted Audience No. of Results Country
thors of ogy tion / Pro- /Affordances Method sonalization tion Outcomes Age Partici- of Study
Arti- ject Name (Ways of imple- Group pants
cles, mentations)
Year,
Refer-
ence
24 Zhang PA Mobile ap- PennFit Tracking, Personalization, SCT Quantitative motivational 3 Months Behavior, Young 91 Fully USA
and plication, Self-Monitoring, Re- content, inter- Aware- Adults Suc-
Jemmot Activity minder, Social Support vention timing ness cessful
t Tracker (Comparison, Social Inter-
(2019), (Fitbit) action ( messages with
[59] chatting tool))
25 Lee et PA and Smartphon Puzzle Tunneling, Personaliza- unspeci- none goal recommen- none Behavior, Adults 34 none USA
al. SB e applica- Walk tion, Goal Setting, Self- fied dations Motiva-
(2018), tion Monitoring, Praise, Re- tion
[28] wards, Reminder, Liking
26 Lane et PA, Smartphon BeWell+ Tracking, Personalization, none Quantitative motivational 19 Days Behavior, Unspeci- 27 Fully UK
al.(2014 Sleep, e applica- Self-Monitoring, Simula- content Social In- fied (Gen- Suc-
), [27] Social tion, and tion, Rewards, Liking, So- teraction eral) cessful
Interac- ambient cial Support (Social Inter-
tion display on action)
the
smartphone
wallpaper
7
27 Hong et PA A mobile to iCanFit Tracking, Reduction, Tun- none Mixed goal recommen- 11 Behavior, Elderly 112 Fully USA
al.( web appli- neling, Tailoring, Person- dations, motiva- months Motiva- Suc-
2013), cation alization, Goal Setting, tional content , tion cessful
[24] (desktop Self-Monitoring, Sugges- educational con-
version as a tion, Praise , Trustworthi- tent
web, iPh- ness, Expertise, Surface
one ver- Credibility, Real-world
sion) Feel, Authority, Third-
party Endorsements, Veri-
fiability, Social Support (
Normative Influence, So-
cial Interaction)
Appendix 1. (continued)
# Au- Domain Technol- Applica- Persuasive Strate- Theories Evaluation Types of Person- Duration Targeted Audience No. Results Country
thors of ogy tion / Pro- gies /Affordances Method alization (Ways Outcomes Age Group of of Study
Arti- ject Name of implementa- Par-
cles, tions) tici-
Year, pant
Refer- s
ence
28 Francil- PA A An Reduction, Tailoring, none Mixed goal recommen- 30 Behavior, Adults 15 Partially Canada
lette et smartphone smartphone Personalization, Goal dations, interven- minutes Motivation Successful
al.(2018 exergame exergame Setting, Self-Moni- tion timing
), [17] application app toring, Rewards, Re-
minder, Liking
29 Dantzig PA A A digital Tracking, Personali- none Mixed goal recommen- 1 Month Behavior, Adults 70 Partially Nether-
et smartphone smartphone zation, Self-monitor- dations, educa- Motivation Successful lands
al.(2018 application coaching ing, Praise, Reminder, tional content,
), [10] , wearable system Suggestion motivational con-
activity tent
tracker de-
vice
30 Alt- PA A gamified A gamified Tracking, Personali- SDT Mixed motivational con- 1 Month Behavior, Adults 12 Partially Germany
meyer system in- mobile app zation, Self-Monitor- tent Motivation, Successful
et cludes fit- ing, Rewards, Re- Usability
al.(2018 ness minder, Similarity,
), [4] tracker, Social Support (Com-
mobile app, parison, Normative
website as a Influence)
8
public dis-
play
31 Schafer PA A gamified A gamified Tracking, Personali- none Mixed motivational con- 1 Month Behavior, Children 61 Partially Germany
et smartphone smartphone zation, Self-Monitor- tent Awareness, Successful
al.(2018 app app ing, Praise, Rewards, Motivation,
), [50] Liking Acceptance,
Attitude
32 Cirave- PA Mobile Active 10 Tracking, Reduction, unspeci- Quantita- goal recommen- 1 year and Behavior, Unspeci- 749,0 Fully Suc- UK
gna et phone ap- Personalization, Self- fied tive dations and moti- 11 months Adherence fied 10 cessful
al.(2019 plication monitoring, Goal-Set- vational content
), [9] ting, Praise, Rewards,
Reminders, Expertise,
Real-world feel
Appendix 1. (continued)
# Au- Do- Technology Applica- Persuasive Strategies Theories Evalua- Types of Duration Targeted Audience No. of Results Country
thors of main tion / Pro- /Affordances tion Personaliza- Outcomes Age Partici- of Study
Arti- ject Name Method tion (Ways Group pants
cles, of imple-
Year, mentations)
Refer-
ence
33 Oyibo PA Mobile BEN’FIT Tailoring, Personalization, SCT Mixed goal recom- 1 Months Behavior, Adults 120 Partially Canada,
et phone appli- Goal-Setting, Self-Moni- mendations, Motivation Success- USA,
al.(2019 cation toring, Rewards, Social motivational ful and Ni-
), [45] Support (Social Learning, content geria
Social Comparison, Coop-
eration)
34 Samar- PA Mobile ap- KidLED Tracking, Personalization, none none goal recom- none Motivation, Children none none USA
iya et plication, mobile ap- Goal-Setting, Self-Moni- mendations Awareness
al.(2019 Wearable plication toring, Social Support (So-
), [49] LED Color cial Learning, Social Com-
Light Dis- parison)
play, Activ-
ity Tracker
9
35 Oliveira PA Mobile ap- PersonalFit Tracking, Reduction, Per- none none goal recom- none Self-man- Unspeci- none none Portugal
et plication sonalization, Social Role mendations agement fied
al.(2016
), [36]
36 Econo- PA and Gamified PhytoCloud Tracking, Tailoring, Per- none none educational none Behavior Adults none none UK
mou et Eating Mobile Web sonalization, Goal-Setting, content , mo-
al.(2017 (Diet) App Self-Monitoring, Sugges- tivational
), [13] tions, Trustworthiness, Ex- content
pertise, Surface Credibil-
ity, Authority, Third-Party
Endorsement, Social Sup-
port (Social Learning, Nor-
mative Influence, Recogni-
tion (Ranking), Sharing )
Appendix 1. (continued)
# Au- Domain Technol- Application Persuasive Theories Evaluation Types of Person- Duration Targeted Audience No. of Results Country
thors of ogy / Project Strategies Method alization (Ways Outcomes Age Partici- of Study
Arti- Name /Affordances of implementa- Group pants
cles, tion)
Year,
Refer-
ence
37 Geurts PA Mobile Walk- Tracking, GST Mixed goal recommen- 10 Weeks Behavior, Elderly 13 Fully Suc- Belgium
et applica- WithMe Tunneling, dations, educa- Motivation cessful
al.(2019 tion Tailoring, tional content,
), [18] Personaliza- motivational con-
tion, Goal- tent
Setting, Self-
Monitoring,
Praise, Exper-
tise, Social
Support
(Sharing)
10
38 Spies- PA A gami- Woody Tracking, Per- none Mixed motivational con- 12 Days Behavior, Children 38 Fully Suc- Austria
berger fied sonalization, tent Awareness, cessful
et smartphon Simulation, Motivation
al.(2015 e app Reminder,
), [53] Rewards, Lik-
ing, Expertise
ABBREVIATIONS
MBR: Model-Based Reasoning
TTM: Transtheoretical Model
DCM: Dynamic Computational Model
SCT: Social Cognitive Theory
SRT: Self-Regulation Theory
HAPA: Health Action Process Approach
TPB: Theory of Planned Behavior
TMB: Theory of Meaning Behavior
PRT: Personality Theory
SDT: Self-Determination Theory
WMT: Wellness Motivation Theory
USS: User-Specific Strategies
TDP: Theoretical Design Principles
GST: Goal-Setting
Persuasive 2020, Adjunct proceedings of the 15th Int. conference on Persuasive Technology. Copyright © 2020 for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).