=Paper=
{{Paper
|id=Vol-1573/Paper_2_BCSS2016
|storemode=property
|title=Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions: Work-in-progress Scoping Review of Key Components
|pdfUrl=https://ceur-ws.org/Vol-1573/Paper_2_BCSS2016.pdf
|volume=Vol-1573
|authors=Aniek Lentferink,Hilbrand Oldenhuis,Olga Kulyk,Martijn de Groot,Louis Polstra,Hugo Velthuijsen,Hermie Hermens,Lisette van Gemert-Pijnen
|dblpUrl=https://dblp.org/rec/conf/persuasive/LentferinkOKGPV16
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==Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions: Work-in-progress Scoping Review of Key Components==
https://ceur-ws.org/Vol-1573/Paper_2_BCSS2016.pdf
15 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Self-tracking and Persuasive eCoaching in Healthy
Lifestyle Interventions: Work-in-progress Scoping
Review of Key Components
Aniek Lentferink1-2-3-4, Hilbrand Oldenhuis1, Olga Kulyk2, Martijn de Groot3,
Louis Polstra1, Hugo Velthuijsen4, Hermie Hermens5, and Lisette van Gemert-Pijnen2
1
Centre of Applied Labour Market Research, Hanze University of Applied Sciences, Groning-
en, The Netherlands
{a.j.lentferink, h.k.e.oldenhuis, l.polstra}@pl.hanze.nl
2
Psychology, Health & Technology, University of Twente, Enschede, The Netherlands
{o.a.kulyk, j.vangemert-pijnen}@utwente.nl
3
Quantified Self Institute, Hanze University of Applied Sciences, Groningen, The Netherlands
{ma.degroot}@pl.hanze.nl
4
Centre of Applied Research and Innovation Entrepreneurship, Hanze University of Applied
Sciences, Groningen, The Netherlands
{h.velthuijsen}@pl.hanze.nl
5
Biomedical Signals & Systems Group, University of Twente, Enschede, The Netherlands
{h.hermens}@rrd.nl
Abstract. The combination of self-tracking and persuasive eCoaching in
healthy lifestyle interventions is a promising approach. The objective of this
study is to map the key components of existing healthy lifestyle interventions
combining self-tracking and persuasive eCoaching using the scoping review
methodology in accordance with the York methodological framework by
Arksey and O’Malley. Seven studies were included in this preliminary scoping
review. Components related to persuasive eCoaching applied only in effective
interventions were reduction of complex behavior into small steps, providing
positive motivational feedback by praise and providing reliable information to
show expertise. Concerning self-tracking, it did not seem to matter if more ac-
tion was required by the participant to obtain personal data. The first results of
this study indicate the necessity to identify the needs and problems of the spe-
cific target group of the interventions, due to differences found between various
groups of users. In addition to objective data on lifestyle and health behavior,
other factors need to be taken into account, such as the context of use, daily ex-
periences, and feelings of the users.
Keywords: persuasive eCoaching, persuasive technology, self-tracking, healthy
lifestyle intervention, scoping review.
16 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
1 Introduction
Unhealthy lifestyle is a major worldwide problem contributing to the burden of dis-
ease [1]. In line with various articles [2-4] and the latest definition of health: “…the
ability to adapt and cope…” [5], we advocate a new approach for enhancing a healthy
lifestyle, using self-tracking technology as a methodology to monitor health behavior
in combination with persuasive eCoaching. Persuasive eCoaching is defined as the
remote and automatic provision of just-in-time tailored feedback for healthy lifestyle
management, by enabling users to set personal goals and encouraging to track person-
al progress towards their goals, adapting the feedback to the usage patterns and con-
text, and encouraging long-term use. Such technological innovations enable new ways
for health promotion that could overcome some important obstacles in the uptake of
healthy lifestyle interventions [6]. Firstly, self-tracking devices allow tracking an
individual’s lifestyle pattern more reliably than estimations based on one’s personal
memory [7-9]. This objective insight into a person’s lifestyle pattern provides the
essential awareness, which is an important first step to enhance a healthy lifestyle
[10]. Secondly, the combination of self-tracking and persuasive technology has the
ability to interact 24/7 with users at the right moment with the right personal relevant
information [11]. For instance, a virtual coach engine [12] could send a personal
feedback message to the user’s mobile phone, such as: ‘Based on your accelerometer
data, you have not been exercising for more than five days. My advice is to plan an
activity within two days to accomplish your weekly exercise goal’. The ability to in-
teract 24/7 with users might positively influence the sustainable use of the health
promotion intervention [13-15]. Thirdly, nowadays most people own a device which
is applicable for eHealth [2]. Therefore, an automated healthy lifestyle intervention,
which does not require trained personnel, can reach many people at low costs [16,
17].
In addition, it is important to acknowledge the challenges in the use of self-tracking
technologies in healthy lifestyle interventions. For instance, privacy, trust, and ethics
of personal self-tracking data. Concerning privacy, safe storage of personal health
data should be assured. To date, personal health data obtained by self-tracking devices
are stored on a central server of the supplier [18]. When data are intercepted by third
parties, profiling is a risk. Profiling entails that third parties gather, analyze and com-
bine personal data to place a person in a certain category. This could lead to discrimi-
nation in the worst scenario, especially when a person is categorized wrongly due to
reliability and validity issues of the device [19]. Even if privacy is assured, trust is-
sues could still be present as people might feel uncomfortable with the fact that their
data are stored ‘somewhere out there’ [20]. As it comes to ethics, purpose limitation is
an important principle. The purpose of collecting data should be specified, explicit
and legitimate. In addition, processing of data should be in accordance with these
purposes only. Nowadays, data are stored and gathered without a clear purpose or
without a person being aware of personal data gathering [21].
It is clear that persuasive technologies in healthy lifestyle interventions could over-
come a few important obstacles, such as the lack of personally relevant feedback, the
inadequate timing of support, and issues concerning sustainable use and scalability.
17 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
However, there is, to our knowledge, no review study that combines self-tracking,
persuasive eCoaching and influence on healthy lifestyle. An overview of essential
components of self-tracking and persuasive eCoaching for enhancing a healthy life-
style is needed to make the most out of modern technologies. Also, it is worthwhile to
have knowledge about components in such interventions that might contribute to fail-
ure in the promotion of a healthy lifestyle. Therefore, this study focuses on the identi-
fication of key components of existing healthy lifestyle interventions combining self-
tracking and persuasive eCoaching by means of a scoping review. The key compo-
nents that we are aiming to map include elements of the intervention for self-tracking
and persuasive eCoaching features, and challenging and stimulating factors in the
broad sense that might influence the effectiveness of these interventions. The scoping
review method fits well with the purpose of this study, as it allows to get a relatively
quick overview of key concepts of this new and very rapidly evolving research area
by including all relevant resources of information [22]. The main research question of
this scoping review is: “What are key components of (in)effective healthy lifestyle
interventions using self-tracking and persuasive eCoaching?”.
This paper describes the first study of the 4-year overarching project ‘Quantified
Self @Work’ focusing on the development of a workplace health promotion interven-
tion combining self-tracking and persuasive eCoaching. The rest of this paper is orga-
nized in the following way. Next, we describe methods and data analysis of the first
study. Then, preliminary results are presented. Finally, we discuss research challenges
in the domain of self-tracking and persuasive eCoaching based on our preliminary
findings, as well as our future research plans.
2 Methods
Throughout the ‘Quantified Self @Work’-project, the CeHRes Roadmap is applied
[13]. This Roadmap is a holistic and systematic approach for developing and imple-
menting eHealth interventions. This study is a part of the first phase called ‘contextual
inquiry’, which aims at identification of key stakeholders, including end users, and
establishing essential requirements for the new intervention to successfully enhance a
healthy lifestyle [23]. These stakeholders include ‘everyone who affects or is affected
by the eHealth intervention’ [24]. To efficiently identify needs and problems from a
stakeholder’s perspective, it is necessary to gain state-of-the-art knowledge regarding
the key components of existing healthy lifestyle interventions combining self-tracking
and persuasive eCoaching.
The scoping review was conducted in accordance with the York methodological
framework by Arksey and O'Malley [22], including the following steps: 1) identifying
the research question, 2) identifying relevant studies, 3) study selection, 4) charting
the data, 5) collating, summarizing, and reporting the results and 6) consultation. The
additional recommendations on conducting a scoping review by Levac and
Colquhoun et al. [25] were followed.
18 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
2.1 Identifying Relevant Studies
Pubmed, EMBASE, PsycINFO, and Scopus were the databases of choice. Pubmed
and EMBASE were chosen due to their wide coverage of scientific journals. In addi-
tion, PsycINFO fitted the specific topic of this scoping review and Scopus is multidis-
ciplinary focused which has led to the identification of studies outside of the medical
field, such as engineering. The search query consists of three components: 1) self-
tracking, 2) persuasive eCoaching and, 3) healthy lifestyle intervention. Related key-
words were identified by searching for MeSH and EMTREE terms, synonyms, key-
words of relevant articles, using PubReMiner and self-determined search terms. In-
clusion criteria were publications between the year 2013-2016, English or Dutch lan-
guage, and publications of journal articles. This specific time period is chosen due to
the fact that smart sensor and self-tracking technology is evolving rapidly. To get an
overview of the latest developments in this field, we have chosen to include publica-
tions between 2013-2016. Exclusion criteria were reviews, study populations outside
the age range of 18-66 years, and paper-based or personally reported tracking. As this
is a work-in-progress paper, these inclusion and exclusion criteria are not definite as
the scoping review methodology allows post hoc decisions of inclusion and exclusion
criteria [22].
To identify additional relevant studies, the reference list of highly relevant articles
were screened and science conference papers from important conferences were hand-
searched.
After uploading citations into the bibliographic software package Endnote, two re-
searchers independently decided upon the further inclusion of publications based on,
respectively, title, abstract and full-text articles.
2.2 Charting the Data
Together with an expert team, a data-charting form was created that includes: study
characteristics (author, year of publication, study design, participants, measuring in-
struments, variable of interest, secondary outcomes, effectiveness, study quality),
intervention characteristics (short description of the intervention, including: founda-
tion/theory used, objective of the intervention, implementation, design (co-creation,
testing/usability, medium of technology), setting/country in which the intervention
was implemented, duration, self-tracking component(s), persuasive eCoaching com-
ponent(s), and adherence), reported advantages and limitations of the intervention
according to the authors of the reviewed article and advantages and limitations of the
intervention according to the reviewer.
Effectiveness was coded according to the framework by Morrison et al. [26]. An
intervention was coded more effective when the intervention had statistically signifi-
cant better results on the majority of outcomes, was at least as effective as the com-
parison intervention and/or was more effective than waiting lists or no intervention
control group. Less effective interventions included interventions which were signifi-
cantly effective in the minority of outcomes, not necessarily as effective as compari-
son groups and/or more effective than waiting lists or no intervention control group.
19 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
An intervention was coded ineffective when no improvements were observed on any
of the outcomes and/or the intervention was not more effective than waiting lists or no
intervention control group.
Self-tracking components were extracted according to the following components:
the specific device, use of the specific device, validity of the device, measurement
outcome of the device, required action by the participant to obtain health behavior
data, duration of wearing the device and presentation of summary data.
Components of persuasive eCoaching were extracted according to the Persuasive
System Design (PSD) model [11]. The PSD model has been applied by previous stud-
ies [14, 27] to systematically categorize persuasive eCoaching components of eHealth
interventions under the following categories: primary task support, dialogue support,
system credibility support, and social support. These categories contain more specific
concepts such as tailoring or rewards. Content of the communication was only coded
when the communication was provided by technology without the inference of hu-
mans, complying with the use of the PSD model in the review of Kelders and Kok et
al. [14].
The data extraction form was tested for consistency of use by means of five rele-
vant articles by the two independent researchers.
2.3 Collating, Summarizing and Reporting the Results
By means of qualitative research methods, all data related to components of the data
extraction form were coded and analyzed with the qualitative software packaged
ATLAS.ti version 7.5. A qualitative analysis method was chosen as we were most
interested in the process of how and why components in interventions are effective or
not [28]. Descriptive numerical summary and thematic analysis were performed to
identify key components including self-tracking components, persuasive eCoaching
components and challenging and stimulating factors of (in)effective healthy lifestyle
interventions combining self-tracking and persuasive eCoaching. The descriptive
numerical summary resulted in an overview of the frequency of a self-tracking or
persuasive eCoaching component in more effective, less effective and ineffective
interventions. In addition, by means of thematic analysis, main themes were identified
on challenging and stimulating factors.
2.4 Consultation
The final step ‘consultation’ is planned as an interactive discussion with researchers
and experts from several fields during the workshop on Behavior Change Support
Systems (BCSS 2016): Epic for Change, the Pillars for Persuasive Technology for
Smart Societies. Input for this discussion are the preliminary results of this scoping
review. The aim of this consultation is to bring meaning and applicability of the re-
sults to a higher level by getting insights into other perspectives concerning prelimi-
nary results, beyond the perspectives of the research team [22, 25]. Participants in the
20 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
workshop will be asked for permission to record the discussion. This recording will
then be transcribed and analyzed within ATLAS.ti.
3 Preliminary Results and Discussion
The search resulted in 297 publications. After the title selection, 181 publications
remained. For this preliminary scoping review, seven relevant publications29-35 were
selected on the basis of abstracts, which revealed inclusion of all three components:
self-tracking, persuasive eCoaching, and healthy lifestyle. During the writing of this
work-in-progress paper, consensus between the two researchers (AL and HO) on the
abstract selection had to be reached, based on the inclusion criteria. From these seven
publications, six publications29-32,34,35 were applicable for the descriptive numerical
summary analysis as these studies tested the effectiveness of an intervention combin-
ing self-tracking and persuasive eCoaching. Two out of these six publications showed
more effectiveness29,31, one showed less effectiveness32, and three showed ineffec-
tiveness30,34,35. A summary of the extracted data on interventions characteristics is
shown in Appendix A, Table 1.
The seventh publication comprised a qualitative study on the usability of self-
monitoring and provision of feedback by mobile devices among HIV-patients and
mothers33. For the purpose of this scoping review, we extracted only information on
the usability by mothers as we are aiming for the development of a healthy lifestyle
intervention in which users will mostly comprise healthy adults.
It is important to note that only a few publications are included in the analysis
which limits our ability to provide statements on key components in (in)effective
interventions. However, a few prudent trends can be presented.
3.1 Key Components of Persuasive eCoaching
Firstly, more effective interventions29,31 made an effort on reducing complex behavior
into simple tasks, defined as the persuasive component reduction by the PSD model
[11], unlike less effective32 and ineffective interventions30,34,35. For example, Adams
and Sallis et al.29 applied this component by setting personal goals based on extending
the average steps the participant performed during the past nine days in order to even-
tually reach the ultimate goal of 10.000 steps during five or more days a week. In
addition, praise (e.g. providing positive motivational feedback [11]) was a persuasive
component more and less effective interventions29,31,32 had applied whereas ineffec-
tive interventions did not30,34,35. Finally, the component expertise only appeared in
more effective interventions29,31. Expertise refers to the provision of reliable infor-
mation to show knowledge, experience, and competence of the system [11]. No com-
ponents were observed that might have affected ineffectiveness of the interventions.
21 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
3.2 Key Components of Self-tracking
Firstly, it did not seem to matter if more action was required by the participant to get
the personal data into the system. Participants of the more effective interventions were
asked to perform the most effort, e.g. personally calculating and importing weekly
averages concerning steps as input for the system. Secondly, no clear trend is ob-
served in the way summary data is presented between effective interventions and
ineffective interventions. Thirdly, all interventions in which the duration of self-
tracking was performed longer than three months were more or less effective29,31,32.
Table 2 in Appendix B displays a summary of self-tracking and persuasive eCoaching
components in more effective, less effective and ineffective interventions.
3.3 Challenging and Stimulating Key Components
From the thematic analysis, adherence and usability appeared to be main themes.
Adherence. Adherence refers to “the extent to which individuals experience the con-
tent of an intervention” [14]. Overall, adherence to the usage of self-tracking devices
was high29,34,35. Among participants who did not adhere to usage of the self-tracking
device, Adams and Sallis et al.29 investigated the reasons. These reasons mainly re-
ferred to aesthetic reasons: the self-tracking device did not fit with the wardrobe or
participants did not like to wear the self-tracking device. One publication reported on
adherence to a website-based intervention31. Although a high percentage of the partic-
ipant made use of the website for advice (86%), the intervention group was more
likely to drop-out than the comparison group (which comprised no intervention at all).
A suggestion was made to explain this by the fact that the website did not contain
many interactive features which made it less attractive to return to the website31.
Usability. The participants in the qualitative study33 reported goal-setting, monitoring
progress, and problem-solving support as main components of an intervention that
would make the intervention interface attractive. Goal-setting can be a helpful tool in
tailoring, a persuasive component of the PSD model [11]. Information can be tailored
to the needs and interests of the participant when the system is aware of the goal a
participant is aiming for. In addition, monitoring progress by means of self-tracking
was also an important feature mentioned by the participants, comprising healthy
adults, in the usability evaluation in the study by Bickmore and Schulman et al.30.
However, the mothers from the qualitative study found it important that the effort of
self-tracking was in balance with its added value, for example, guidance by the sys-
tem in the problem-solving process33. To expand on this, just receiving summary data
about their health behavior was not perceived attractive33, although the comparison of
presentation of summary data between effective and ineffective interventions did not
reveal a clear trend. The mothers preferred to receive more in-depth information
showing patterns33, which can be accomplished by reducing efforts of the participant
to discover these patterns, and, therefore, making it easier for participants to perform
22 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
the intended behavior and reach goals. This relates to the persuasive component re-
duction in the PSD model [11].
In addition, the acceptable number of messages per day was around 3-4 times ac-
cording to participants in the qualitative study33. However, it was important that con-
tent was divergent and participants could decide at what time they would receive mes-
sages33. The latter can be seen as a personalized service and is, therefore, a form of
the persuasive component personalization of the PSD model [11]. The number of
acceptable messages per day contrasts to reportings by participants in the study of
Wang and Cadmus-Bertram et al.35, in which three text messages per day were too
many. This difference might be explained by the fact that the content of the messages
was not tailored in the intervention of Wang and Cadmus-Bertram et al.35.
Other findings on usability where that differences existed between studies concern-
ing preference of the platform for the intervention. The mothers reported to prefer a
cell-phone application33 in contrast to the study by Haggerty and Huepenbecker et
al.32, in which a website was more in favor than a cell-phone application among obese
women with endometrial cancer. In addition, resulting from the usability study of
Bickmore and Schulman et al.30, the virtual coach was perceived as a suitable applica-
tion type for the participants, especially because of her nice and personal appearance,
relating to the persuasive component social role of the PSD model. Users indicated
that the virtual coach was someone participants could relate to, which links to the
persuasive component similarity of the PSD model. In addition, participants believed
that reminders helped them to attain their goal30. A persuasive component that was
not perceived as stimulating was social comparison33, the ability to compare your
self-tracking data with others according to the PSD model [11]. Finally, the partici-
pants in the qualitative study33 reported that they were not so concerned with privacy
issues. A password for the app would even be a burden to interact with the app33.
4 Conclusion and Future Research
This paper presents preliminary results of the scoping review into the identification of
key components of existing healthy lifestyle interventions using self-tracking and
persuasive eCoaching. Although we acknowledge the fact that identification of key
components on the basis of only a few studies was frail, we presented some prudent
trends.
In summary, reduction of complex behavior into small steps, providing positive
and motivational feedback by praise and providing reliable information to show ex-
pertise of the system might contribute to the effectiveness of the intervention as these
persuasive eCoaching components were discovered in effective interventions but not
in ineffective interventions. The persuasive components praise and expertise were
also acknowledged as important components of an eCoach by respondents in a quali-
tative study [12]. Concerning self-tracking, it did not seem to matter if more action
was required by the participant to obtain objective data into the system. What did
seem to matter was the duration of the self-tracking: longer than three months of self-
tracking was performed in effective intervention but not in ineffective interventions.
23 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
In addition, monitoring progress was mentioned as an important intervention compo-
nent by users. It appeared that adherence to self-tracking devices was good. Partici-
pants reported mostly aesthetic reasons for non-adherence. Other attractive compo-
nents in such interventions were goal-setting and support in the problem-solving pro-
cess. Usability issues on the number of acceptable messages per day seemed to de-
pend on relevant content for the user. In addition, the importance of personalization in
the timing of feedback messages was in line with previous research [12]. This also
accounts for the desire of variation in feedback messages and the fact that the virtual
coach was perceived as a suitable application type for the participants [12]. Further-
more, differences were observed between studies29,33 on preference for transmission
of the intervention through a cell-phone application or a website. Finally, on the basis
of a qualitative study into usability33, privacy issues were not necessarily an issue for
every group of users.
Besides the fact that statements had to be made on the basis of only a few studies,
another limitation comprises the data extraction on persuasive eCoaching and self-
tracking on the basis of the information described in the article. One can expect that
some components are described more comprehensive than other components. For
example, feedback is more likely described in detail, such as tailoring feedback to
personal needs, than the visualization, such as the provision of images that attracts the
user, referred to the persuasive component liking of the PSD model [11]. For the full
scoping review, we will make an attempt to request screenshots of the intervention by
the authors of the reviewed articles.
A third limitation of this scoping review is the restricted ability to make statements
about separate components and the impact on effectiveness as components influence
each other. This is acknowledged by another review into the effectiveness of online
healthy lifestyle interventions [36]. However, the identification of components in
effective and ineffective interventions might provide some direction. Based on the
results of the full scoping review, future experimental research into the evaluation of
isolated components can be advised.
As mentioned above, the knowledge obtained from this scoping review will be
used for our next study into the identification of needs and problems from a key
stakeholder perspective. Based on the findings of the qualitative study33, which indi-
cated large differences in preferences between two different populations (HIV-
patients vs. mothers), it is useful to put effort into the identification of needs and prob-
lems in the specific population of the “Quantified Self @Work”-project: the working
population.
Another important challenge for future research into tracking a person’s lifestyle
pattern using self-tracking devices and persuasive eCoaching, is the attention to other
factors (psychological and sociological), besides objective data on health behavior.
These other factors need to be taken into account in order to understand, predict and
prevent high-risk health behavior (e.g., high stress) [37]. In future research, we will
apply a promising method called ‘Ecological momentary assessment’ (EMA). EMA
can be used to systematically collect data about daily experience and feelings of the
users, as well as the context of use, for instance, through a user-friendly smartphone
application [38, 39].
24 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Finally, future research should study the issue of privacy, trust, and ethics related
to healthy lifestyle intervention using self-tracking and persuasive eCoaching. As
indicated by this preliminary scoping review, not all users are concerned about priva-
cy issues33. However, one might expect privacy issues within the workplace setting
due to the hierarchical relation between employer and employees. For instance, access
to personal data by the employer might be issued by the employee as their employer
has an indication of activities performed during spare time. This also raises ethical
issues. For instance, to which extent is an employer allowed to influence the employ-
ee’s health behavior or time spent outside working hours. In addition, a risk might
exist for judging an employee’s capability to perform proper work when health issues
are identified. We will collaborate with experts in other multidisciplinary fields within
connected projects, in order to account for privacy, trust, and ethics in relation to self-
tracking of lifestyle patterns during the development of the intervention.
25 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Appendix A
Table 1. Summary of extracted data on intervention characteristics of included publications.
Study Intervention, comparison intervention Effectiveness Self-tracking components Persuasve eCoaching
and population components
Adams and Intervention: A one-day goal was presented every More effective Device: Omron HJ-720ITC pedome- Tailoring
Sallis et day on an nth percentile criterion over the past (valid) ter (OMRON Healthcare Europe Praise
al.[29] nine days. This resulted in a goal that was higher B.V., Hoofddorp, the Netherlands). Rewards
than the daily average of the nine days. Participants Reminders
received a short message (<160 characters) every 9 Effort by participant: Daily sending Expertise
days by email or mobile phone, based on the partici- of steps. Reduction
pant’s preference. Feedback messages were never
negative and were tailored to the successfulness of Summary data: No summary data
the person in reaching goals. In addition, partici- were sent to participants.
pants received points for uploading data and accom-
plishing goals. These points could be exchanged for Duration wearing: Daily for 170 days
items and services.
Comparison: Participants in the comparison group
were motivated by a static goal (10,000 steps each
day) and static feedback messages.
Population: Inactive overweight adults.
Bickmore Intervention: “The ontology-based design approach Ineffective Device: Omron HJ-720ITC pedome- Tailoring
and Schul- is used to develop an animated conversational agent ters (OMRON Healthcare Europe Social role
man et that plays the role of a health counselor that can B.V., Hoofddorp, the Netherlands). Similarity
al.[30] promote both physical activity (ACT) and fruit and Reminder
vegetable consumption (DIET) through a series of Personalization
26 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Table 1 (Continued). Summary of extracted data on intervention characteristics of included publications.
Study Intervention, comparison intervention Effectiveness Self-tracking components Persuasive eCoaching
and population components
Bickmore simulated conversations with users on their home Effort by participant: Weekly upload Suggestion
and Schul- computers.” Feedback is tailored to participant’s of data from the pedometer. Tunneling
man et pedometer data. The intervention of interest in this
al.[30] scoping review: ACT. Summary data: The virtual coach
shows the participants their progress
Comparison: As this study included a 4-arm ran- with the steps chart every time they
domized trial, the comparison interventions were the had a conversation with her.
interventions other than the ACT-intervention:
DIET, ACT-DIET, and no intervention. Duration wearing: Daily for 60 days
Participants: Adults somewhat motivated to change
health behavior (precontemplation or contemplation
phase of the Transtheoretical Model).
Compernol- Intervention: Participants in the intervention re- More effective Device: Omron HJ-203-ED pedome- Tailoring
le and Van- ceived computer-tailored step advice based on their ter (OMRON Healthcare Europe Reduction
delanotte et self-tracking data. The advice consisted of three B.V., Hoofddorp, the Netherlands). Suggestion
al.[31] parts: 1) a general introduction, 2) personalized Tunneling
feedback including a scheme how to reach the goal Effort by participant: Calculate daily Expertise
of 10,000 steps per day with their referenced in- average each week and recording Praise
crease per week (1000 or 500 steps), 3) recommen- non-walking activities and activities Personalization
dations and suggestions how to increase daily step when the pedometer was not worn.
counts.
Summary data: Progress feedback
Comparison: Participants in the control condition was provided by comparing the
did not receive an intervention. previous step level with the current
27 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Table 1 (Continued). Summary of extracted data on intervention characteristics of included publications.
Study Intervention, comparison intervention Effectiveness Self-tracking components Persuasive eCoaching
and population components
Compernol- Participants: Employees who were not physically step level. In addition, a chart was
le and Van- active during the day. presented with bars for the previous
delanotte et number of steps, the current number
al.[31] of steps and the ultimate goal com-
prising 10,000 steps.
Duration wearing: Daily for 90 days
Haggerty Intervention: 3-5 daily personalized text messages Less ef- Device: WiFi scale Withings (With- Praise
and were sent to the participant. “The messages included fective ings, Inc., Cambridge, MA, USA) Personalization
Huepenbeck different types of interaction, such as encouraging Suggestion
er et al. [32] statements and yes/no or multiple choice questions. Effort by participant: Weekly sending Tailoring
The SMS engine used data (rules, participant infor- of weight.
mation, the day of the week, behavioral topic, etc.)
to determine the appropriate SMS to send to each Summary data: It is not clear if partic-
user.” WiFi scales from Withings were used for self- ipants in the intervention group re-
tracking. ceive summary data. In the compari-
son group, the WiFi scale graphed
Comparison intervention: Counseling by an inter- participants' weights through an in-
ventionist. Data of the Withings WiFi scale was ternet platform.
used as input for the counseling.
Duration wearing: Unclear. Interven-
Participants: Obese women (BMI ≥ 30 kg/m2) with tion duration was 180 days.
endometrial cancer.
28 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Table 1 (Continued). Summary of extracted data on intervention characteristics of included publications.
Study Intervention, comparison intervention Effectiveness Self-tracking components Persuasive eCoaching
and population components
Tabak and Intervention: The physical activity data obtained by Ineffective Device: Accelerometer MTx-W sen- Tailoring
Vollen- the accelerometer were shown on the mobile phone sor (Xsens Technologies, Enschede, Suggestion
broek- in a graph showing both the current activity and the The Netherlands). Normative influence
Hutten et activity the participant is aiming for (10,000 steps
al.[34] per day). Feedback messages included “(1) a short Effort by participant: Nothing.
summary of activity behavior and (2) advice on how
to improve or maintain the activity behavior.” Summary data: The smartphone
showed the measured activity cumu-
Comparison: Usual care which mostly included latively in a graph, together with the
weekly (group) training sessions at the local physio- cumulative activity the users should
therapy practices. aim for.
Population: Patients diagnosed with COPD Duration wearing: A minimum of
four days a week, from waking till
22.00 hours, during 28 days.
Wang and Intervention: This study tested the utility of a wear- Ineffective Device: Fitbit One (Fitbit Inc., San Personalization
Cadmus- able sensor/device and short message service (SMS) Francisco, CA, USA) Suggestion
Bertram et text-messaging prompts to increase PA. The mes-
al. [35] sages were sent automatically without tailoring. Effort by participant: Daily upload of
data from the activity tracker.
Comparison: Self-monitoring with Fitbit One only.
Summary data: Participants received
Participants: overweight and obese adults. summary feedback by the Fitbit ap-
plication. The Fitbit application is
29 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Table 1 (Continued). Summary of extracted data on intervention characteristics of included publications.
Study Intervention, comparison intervention Effectiveness Self-tracking components Persuasive eCoaching
and population components
Wang and capable of showing a graph with the
Cadmus- number of steps per day, week, month
Bertram et or year and the intended goal.
al. [35]
Duration wearing: Daily for 42 days.
30 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Appendix B
Table 2. Persuasive eCoaching and Self-tracking components by the effectiveness of the intervention.
Persuasive eCoaching or More effective (studies n=2) Less effective (studies n=1) Ineffective (studies n=3)
Self-tracking component
Persuasive eCoaching Expertise (n=2) Personalization Normative influence
(n=frequency of component in Personalization Praise Personalization (n=2)
studies) Praise (n=2) Suggestion Reminder (n=1)
Reduction (n=2) Tailoring Similarity
Reminders Social role
Rewards Suggestion (n=3)
Suggestion Tailoring (n=2)
Tailoring (n=2) Tunneling
Tunneling
Self-tracking – Device Omron HJ-720ITC pedometer WiFi scale Withings (Withings, Inc., MTx-W sensor accelerometer
(OMRON Healthcare Europe B.V., Cambridge, MA, USA) (Xsens Technologies, Enschede, The
Hoofddorp, the Netherlands) Netherlands)
Omron HJ-203-ED pedometer Omron HJ-720ITC pedometer
(OMRON Healthcare Europe B.V., (OMRON Healthcare Europe B.V.,
Hoofddorp, the Netherlands) Hoofddorp, the Netherlands)
Fitbit One (Fitbit, Inc., San Francis-
co, CA, USA)
31 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Table 2 (Continued). Persuasive eCoaching and Self-tracking components by the effectiveness of the intervention.
Persuasive eCoaching or More effective (studies n=2) Less effective (studies n=1) Ineffective (studies n=3)
Self-tracking component
Self-tracking – Effort by partici- Daily sending of steps. Weekly sending of weight. Nothing.
pant
Calculate daily average each week and Weekly upload of data from the
recording non-walking activities and pedometer.
activities when the pedometer was not
worn. Daily upload of data from the activi-
ty tracker.
Self-tracking – Presentation of No summary data were sent to partici- It is not clear if participants in the The smartphone showed the meas-
summary data pants. intervention group receive summary ured activity cumulatively in a
data. In the intervention group, the graph, together with the cumulative
Progress feedback was provided by WiFi scale graphed participants' activity the users should aim for.
comparing the previous step level weights through an internet plat-
with the current step level. In addi- form. The virtual coach shows them their
tion, a chart was presented with bars progress with the steps chart every
for the previous number of steps, the time they had a conversation with
current number of steps and the ulti- her.
mate goal comprising 10,000 steps.
Participants received summary feed-
back by the Fitbit application. The
Fitbit application is capable of
showing a graph with the number of
steps per day, week, month or year
and the intended goal.
32 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
Self-tracking and Persuasive eCoaching in Healthy Lifestyle Interventions:
Work-in-progress Scoping Review of Key Components
Table 2 (Continued). Persuasive eCoaching and Self-tracking components by the effectiveness of the intervention.
Persuasive eCoaching or More effective (studies n=2) Less effective (studies n=1) Ineffective (studies n=3)
Self-tracking component
Self-tracking – Duration Daily for 170 days. Unclear. Intervention duration was A minimum of four days a week,
180 days. from waking till 22.00 hours, during
Daily for 90 days. 28 days.
Daily for 60 days.
Daily for 42 days.
33 Fourth International Workshop on Behavior Change Support Systems (BCSS’16):
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Work-in-progress Scoping Review of Key Components
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