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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Designing, Modeling and Evaluating Influence Strategies for Behavior Change Support Systems</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Anssi Öörni</string-name>
          <email>Anssi.Oorni@oulu.fi</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Saskia Kelders</string-name>
          <email>Saskia.Kelders@utwente.nl</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Lisette van Gemert-Pijnen</string-name>
          <email>J.vanGemert-Pijnen@utwente.nl</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Harri Oinas-Kukkonen</string-name>
          <email>Harri.Oinas-Kukkonen@oulu.fi</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>University of Oulu</institution>
          ,
          <country>Finland (Anssi.Oorni</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>University of Twente</institution>
          ,
          <country>The Netherlands (Saskia.Kelders</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2014</year>
      </pub-date>
      <abstract>
        <p>Behavior change support systems (BCSS) research is an evolving area. While the systems have been demonstrated to work to the effect, there is still a lot of work to be done to better understand the influence mechanisms of behavior change, and work out their influence on the systems architecture. The papers of the second BCSS workshop aim at filling this gap. They test existing influence strategies and suggest new ones, develop evaluation methods of influence strategies, and introduce systems architectures that support novel influence strategies.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        Introduction
An emphasis of research in Behavior Change Support Systems or BCSS
        <xref ref-type="bibr" rid="ref6">(OinasKukkonen 2010a, 2010b, 2013)</xref>
        is that technology, information, and people
involved in behavior change interventions shouldn’t be studied in isolation. The
three components of a BCSS combine into an entity that should be studied as a
whole to produce meaningful insight as the interaction of the components is the
gist of the behavior change support phenomenon. This also implies that should
one component change, the others will have to adjust. We are currently living
through such a major re-adjustment: Ongoing technological advances and
fundamental recent changes in the scientific picture of man, his motivations, and
behavior control mechanisms, call for continuing adjustments in the theory
behind and application of behavior change support systems.
      </p>
      <p>
        Technological advances that reduce the size of information and communication
technology (ICT) and make it globally interconnected both challenge and open up
opportunities for researchers of behavior change support systems. ICT is
becoming increasingly ubiquitous and embedded in objects of the everyday life,
contributing towards humanizing those technologies
        <xref ref-type="bibr" rid="ref6 ref8">(Oinas-Kukkonen &amp;
OinasKukkonen 2013)</xref>
        . We can carry ICT with us and can even wear it. Mobile
services, in particular, are designed to be consumed instantly, anytime, and
anywhere (Chae and Kim 2003). Technology is also becoming increasingly
aware of the context of its use
        <xref ref-type="bibr" rid="ref12">(see e.g. Wang, Huang et al. 2011)</xref>
        , which opens
up unprecedented opportunities to identify opportune situations to help people
change their adverse behaviors or maintain desired behaviors. In particular,
mobile technologies can, increasingly, connect to personal devices monitoring the
individual’s physical states. Hence, it is not surprising that there is a growing
interest in applying behavior change support systems for a variety of
interventions. This also means that there is growing demand for academic
knowledge instructing how to apply high-tech instruments for behavior changing
interventions ranging from health and security to climate change, and more.
Effective persuasion is based on deep understanding of human information
processing, and that understanding is currently undergoing profound changes.
Recent research in cognitive psychology suggests that automatic and largely
autonomous processes that interpret and select information play a leading role in
most behaviors: Perception, evaluation, and even choice have non-conscious
roots (for a recent review, see e.g. Custers and Aarts 2010). Interestingly, this
means that consciousness plays perhaps a relatively minor role in controlling
behaviors. These insights promote a shift in application of persuasive strategy: In
persuasive systems design more attention should thus be given to support more
directly behavior change rather than only attempting to influence a person’s
beliefs, attitudes, and intentions. Relative importance of information content in
persuasion is in the decline while more direct influences to behavior are in the
rise. Development of new influence strategies is badly needed. Both the theory
and practice of identifying and assessing the effectiveness of persuasion and
behavior change is in need of re-development to make them embrace the
emerging view of human information processing: In particular, measurement
techniques and instruments that rely less on personal judgment of persuasiveness
are needed.
      </p>
      <p>The aforementioned trends put increasing pressure on BCSS researchers.
Growing need for behavior change support systems means that the researchers
should start consolidating their research efforts to be able to offer easy to apply
instructions to their growing audience with limited background in BCSS. To meet
the demand, several theoretical areas should be targeted. First, the recent
developments in relevant consumer technologies (i.e. ICT, personal health
technology) and in cognitive psychology should be better integrated in the BCSS
paradigm in the form of strategies of influence. Second, BCSS design methods
and tools should be advanced to a level at which BCSS people with limited
background in the field could apply the BCSS paradigm in designing effective
behavior change support systems. Finally, evaluation tools for the BCS systems
need to be validated to ensure the performance of the systems in real-life
applications.
2</p>
      <p>Advances in BCSS research
The papers of the BCSS2014 workshop address three timely issues in design and
development of effective behavior change support systems: identification of
effective influence strategies of BCSS, evaluation methods for BCSSs, and new
tools to define and construct BCSS architectures. We will next highlight, in brief,
the key ideas behind the papers included to the Proceedings of the workshop.
3'
2.1</p>
    </sec>
    <sec id="sec-2">
      <title>Evaluation of BCSS</title>
      <p>
        In their paper, de Jong and associates (2014) evaluate constructs developed for
measuring perceived persuasiveness in technology. They find that, in general, the
different measures line up with the data obtained with Perceived Persuasiveness
Questionnaire (PPQ). However, the relationship between perceived
persuasiveness
        <xref ref-type="bibr" rid="ref4 ref5">(cf. Oinas-Kukkonen 2010b)</xref>
        and actual use rates of the persuasive
technology, obtained by analyzing log-data, appears to be much more
problematic. In sum, the authors conclude that their analysis demonstrate that the
PSD model
        <xref ref-type="bibr" rid="ref7">(Oinas-Kukkonen and Harjumaa 2009)</xref>
        generates consistent results,
when measured using different methods.
      </p>
      <p>Caon and co-authors (2014) describe at conceptual level the Virtual Individual
Model that will be integrated to the PEGASO system through an ontology-based
virtualization. The aim of the project is to develop a system that is sensitive to
characteristics of the individual and the interaction context and capable of using
this information to dynamically select opportune tailored interventions. The
PEGASO model is integrated to the system through an ontology-based
virtualization.</p>
      <p>
        Rao (2014) reports about her work on developing evaluation tools to assist the
design of persuasive game systems. The paper argues for applying persuasive
design principles to games design when behavior change is the fundamental end
of the game. The paper suggests that it is important to include gamification in a
discussion about persuasion through games, because persuasive strategies play a
central part in gamification design. Rao suggests that the Persuasive Systems
Design (PSD) model
        <xref ref-type="bibr" rid="ref7">(Oinas-Kukkonen and Harjumaa 2009)</xref>
        can be used in game
design to identify specific characteristics of game systems that affect categories
of persuasive structures such as credibility and personal involvement.
2.2
      </p>
    </sec>
    <sec id="sec-3">
      <title>Influence Strategies of BCSS</title>
      <p>Unal and colleagues (2014) examine users’ compliance to persuasive messages in
mobile application recommendation domain and explore how persuadability of
users affects their compliance. The authors motivate their research by noting that
the rapid growth in mobile application market means a significant challenge to
find interesting and relevant applications for users. They find that subtle methods
of persuasion are more effective than obvious persuasive messages at creating
compliance. Also, persuadability is an important determinant on individual’s
compliance to recommendations.</p>
      <p>Orji (2014) explores gender effects on the strategies for persuasiveness of BCSSs.
They identify that there is a need to adapt persuasive approaches to various user
characteristics and go on to test if gender is among the characteristics that should
be taken into account when designing individualized persuasive strategies. The
author concludes that gender-dependent approaches would generally be more
appropriate for designing BCSSs that will effectively promote health behavior
changes than the one-size fits all approach.</p>
      <p>
        <xref ref-type="bibr" rid="ref2">Gkika and Lekakos (2014)</xref>
        test whether certain persuasive strategies, especially in
the form of recommendation explanations, can affect user’s adoption of
recommendations. The authors argue that explanation is an important aspect of
recommendation that may make targeted people more open to accept a
recommendation. They find that an individual’s intention to consume a
recommendation good is increased if the item is accompanied with a persuasive
explanation.
2.3
      </p>
      <p>BCSS Design
Alahäivälä and his co-authors (2014) aim at breaking out the black-box thinking
in persuasive systems design. They present a software design pattern for giving
rewards as a way of persuasive human-computer dialogue in BCSS. They argue
that by developing software architectures and software design patterns, BCSS
research can be enhanced from proof-of-concepts to concrete software
development guidelines. The paper provides BCSS research with an intricate
implementation level view of the software development aspects of BCSSs.
Wartena and company (2014) discuss the issue of bridging the healthcare and
designer point of views to intervention. They argue that social systems
development around the BCSS would benefit from better understanding of the
interaction between the user, mediator, social system and the socio-technical
system involved. They present a game-architecture inspired design approach for
BCSSs, and go on to demonstrate the benefits in the design process of combining
four archetypal modes of use: trigger, intervention, assessment, and participation.
Burrows and her colleagues (2014) discuss BCSS design in the domain of climate
change and using social and digital media technologies to influence users to
change their energy consumption behavior. They seek to understand how
information about users may be utilized within the development of persuasive
technologies and BCSSs. The authors identify how values, lifestyle aspects, and
energy consumption behaviors may be modelled to BCSS to deliver relevant and
personalized information and knowledge that can influence behavior change.
3</p>
      <p>Discussion
All in all the outlook of the BCSS field is promising. Persuasive technology and
behavior change support systems research are in the position of giving back to
practitioners and other fields of academic inquiry rather than just consume ideas
sourced from the important reference disciplines. To make this happen, though,
the field will have to amalgamate the recent findings in cognitive and other
psychology and the technological advancements in ICT in its existing body of
knowledge on how to apply information systems to persuade people change their
behaviors.
5'
Acknowledgements. We wish to thank the many people who have made the
BCSS2014 workshop possible: Bernd Ploderer for helping with the web site;
Sitwat Langrial, Bernd Ploderer and Wolfgang Reitberger for acting in the
steering committee; Liisa Kuonanoja for helping to put the proceedings together;
and the reviewers for reading through and commenting on the submissions.
1.
2.
3.
4.
5.</p>
      <p>References
Alahäivälä, T., Oduor, M., Oinas-Kukkonen, H.: A Reward Design Pattern in
BCSS, Proceedings of the Second International Workshop on Behavior
Change Support Systems (BCSS2014), Padova, Italy, May 22 (2014)
Burrows, R., Johnson, P., Johnson, H.: Influencing Behaviour by Modelling
User Values: Energy Consumption, Proceedings of the Second International
Workshop on Behavior Change Support Systems (BCSS2014), Padova,
Italy, May 22 (2014)
Chae, M., Kim, J.: What’s So Different About the Mobile Internet?
Communications of the ACM, 46 (12), 240-247 (2003).</p>
      <p>Custers, R., Aarts, H.: The unconscious will: How the pursuit of goals
operates outside of conscious awareness, Science, 329(47), 47-50 (2010)</p>
    </sec>
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