Persuasive technology Redirected from Persuasion technology

Persuasive technology is broadly defined as technology that is designed to change attitudes or behaviors of the users through persuasion and social influence, but not necessarily through coercion.[1] Such technologies are regularly used in sales, diplomacy, politics, religion, military training, public health, and management, and may potentially be used in any area of human-human or human-computer interaction. Most self-identified persuasive technology research focuses on interactive, computational technologies, including desktop computers, Internet services, video games, and mobile devices,[2] but this incorporates and builds on the results, theories, and methods of experimental psychology, rhetoric,[3] and human-computer interaction. The design of persuasive technologies can be seen as a particular case of design with intent.[4]


Functional triad

Persuasive technologies can be categorized by their functional roles. B. J. Fogg proposes the functional triad as a classification of three "basic ways that people view or respond to computing technologies": persuasive technologies can function as tools, media, or social actors – or as more than one at once.[5]

  • As tools, technologies can increase people's ability to perform a target behavior by making it easier or restructuring it.[6] For example, an installation wizard can influence task completion – including completing tasks not planned by users (such as installation of additional software).
  • As media, interactive technologies can use both interactivity and narrative to create persuasive experiences that support rehearsing a behavior, empathizing, or exploring causal relationships.[7] For example, simulations and games instantiate rules and procedures that express a point of view and can shape behavior and persuade; these use procedural rhetoric.[3]
  • Technologies can also function as social actors.[8] This "opens the door for computers to apply ... social influence".[9] Interactive technologies can cue social responses, e.g., through their use of language, assumption of established social roles, or physical presence. For example, computers can use embodied conversational agents as part of their interface. Or a helpful or disclosive computer can cause users to mindlessly reciprocate.[10] Fogg notes that "users seem to respond to computers as social actors when computer technologies adopt animate characteristics (physical features, emotions, voice communication), play animate roles (coach, pet, assistant, opponent), or follow social rules or dynamics (greetings, apologies, turn taking)."[11]

Direct interaction v. mediation

Persuasive technologies can also be categorized by whether they change attitude and behaviors through direct interaction or through a mediating role:[12] do they persuade, for example, through human-computer interaction (HCI) or computer-mediated communication (CMC)? The examples already mentioned are the former, but there are many of the latter. Communication technologies can persuade or amplify the persuasion of others by transforming the social interaction,[13][14] providing shared feedback on interaction,[15] or restructuring communication processes.[16]

Persuasion design

Persuasion design is the design of messages by analyzing and evaluating their content, using established psychological research theories and methods. Andrew Chak[17] argues that the most persuasive web sites focus on making users feel comfortable about making decisions and helping them act on those decisions. The comfort that a user feels is generally registered subconsciously.[18]

Persuasion by social motivators

Previous research has also utilized on social motivators like competition for persuasion. By connecting a user with other users,[19] his/her coworkers,[20] friends and families,[21] a persuasive application can apply social motivators on the user to promote behavior changes. Social media such as Facebook, Twitter also facilitate the development of such systems. It has been demonstrated that social impact can result in greater behavior changes than the case where the user is isolated.[22]

Persuasive strategies

Halko and  Kientz[23] made an extensive search in the literature for persuasive strategies and methods used in the field of psychology to modify health-related behaviors. Their search concluded that there are eight main types of persuasive strategies, which can be grouped into the following four categories, where each category has two complementary approaches.

Instruction style


This persuades the technology user through an authoritative agent, for example, a strict personal trainer who instructs the user to perform the task that will meet their goal.


This persuades the user through a neutral agent, for example, a friend who encourages the user to meet their goals. Another example of instruction style is customer reviews; a mix of positive and negative reviews together give a neutral perspective on a product or service.[24]

Social feedback


This persuades the user through the notion of cooperating and teamwork, such as allowing the user to team up with friends to complete their goals.


This persuades the user through the notion of competing. For example, users can play against friends or peers and be motivated to achieve their goal by winning the competition.

Motivation type


This persuades the user through external motivators, for example, winning a trophy as a reward for completing a task.


This persuades the user through internal motivators, such as the good feeling a user would have for being healthy or for achieving a goal.

Reinforcement type

Negative reinforcement

This persuades the user by removing an unpleasant stimulus. For example, a brown and dying nature scene might turn green and healthy as the user practises more healthy behaviors.

Positive reinforcement

This persuades the user by adding a positive stimulus. For example, adding flowers, butterflies, and other nice-looking elements to an empty nature scene as a user practises more healthy behaviors.

More recently, Lieto and  Vernero[25][26] have also shown that arguments reducible to logical fallacies are a class of widely adopted persuasive techniques in both web and mobile technologies. These techniques have also shown their efficacy in large-scale studies about persuasive news recommendations.[27]

Reciprocal equality

One feature that distinguishes persuasion technology from familiar forms of persuasion is that the individual being persuaded often cannot respond in kind. This is a lack of reciprocal equality. For example, when a conversational agent persuades a user using social influence strategies, the user cannot also use similar strategies on the agent.[28]

Health behavior change

While persuasive technologies are found in many domains, considerable recent attention has focused on behavior change in health domains. Digital health coaching is the utilization of computers as persuasive technology to augment the personal care delivered to patients, and is used in numerous medical settings.[29]

Numerous scientific studies show that online health behaviour change interventions can influence users' behaviours. Moreover, the most effective interventions are modelled on health coaching, where users are asked to set goals, educated about the consequences of their behaviour, then encouraged to track their progress toward their goals. Sophisticated systems even adapt to users who relapse by helping them get back on the bandwagon.[30]

Maintaining behavior change long term is one of the challenges of behavior change interventions. For instance, as reported, for chronic illness treatment regimens non-adherence rate can be as high as 50% to 80%. Common strategies that have been shown by previous research to increase long-term adherence to treatment include extended care, skills training, social support, treatment tailoring, self-monitoring, and multicomponent stages. However, even though these strategies have been demonstrated to be effective, there are also existing barriers to implementation of such programs: limited time, resources, as well as patient factors such as embarrassment of disclosing their health habits.[31]

To make behavior change strategies more effective, researchers also have been adapting well-known and empirically-tested behavior change theories into such practice. The most prominent behavior change theories that have been implemented in various health-related behavior change research has been self-determination theory, theory of planned behavior, social cognitive theory, transtheoretical model, and social ecological model. Each behavior change theory analyses behavior change in different ways and consider different factors to be more or less important. Research has suggested that interventions based on behavior change theories tend to yield better result than interventions that do not employ such theories. The effectiveness of them vary: social cognitive theory proposed by Bandura, which incorporates the well-known construct of self-efficacy, has been the most widely used method in behavior change interventions as well as the most effective in maintaining long-term behavior change.[32]

Even though the healthcare discipline has produced a plethora of empirical behavior change research, other scientific disciplines are also adapting such theories to induce behavior change. For instance, behavior change theories have also been used in sustainability, such as saving electricity,[33] and lifestyle, such as helping people drinking more water.[34] These research has shown that these theories, already effectively proven useful in healthcare, is equally powerful in other fields to promote behavior change.

Interestingly, there have been some studies that showed unique insights and that behavior change is a complex chain of events: a study by Chudzynski et al.[35] showed that reinforcement schedule has little effect on maintaining behavior change. A point made in a study by Wemyss et al.[33] is that even though people who have maintained behavior change for short term might revert to baseline, their perception of their behavior change could be different: they still believe they maintained the behavior change even if they factually have not. Therefore, it is possible self-report measures would not always be the most effective way of evaluating the effectiveness of the intervention.

Promote sustainable lifestyles

Previous work has also shown that people are receptive to change their behaviors for sustainable lifestyles. This result has encouraged researchers to develop persuasive technologies to promote for example, green travels,[36] less waste,[20] etc.

One common technique is to facilitate people's awareness of benefits for performing eco-friendly behaviors. For example, a review of over twenty studies exploring the effects of feedback on electricity consumption in the home showed that the feedback on the electricity consumption pattern can typically result in a 5–12% saving.[37] Besides the environmental benefits such as CO2 savings, health benefit, cost are also often used to promote eco-friendly behaviors.[36]

Research challenges

Despite the promising results of existing persuasive technologies, there are three main challenges that remain present.

Technical challenges

Persuasive technologies developed relies on self-report or automated systems that monitor human behavior using sensors and pattern recognition algorithms. Several studies in the medical field have noted that self-report is subject to bias, recall errors and low adherence rates. The physical world and human behavior are both highly complex and ambiguous. Utilizing sensors and machine learning algorithms to monitor and predict human behavior remains a challenging problem, especially that most of the persuasive technologies require just-in-time intervention.

Difficulty in studying behavior change

In general, understanding behavioral changes require long-term studies. As multiple internal and external factors can influence these changes, such as personality type, age, income, willingness to change and more. For that, it becomes difficult to understand and measure the effect of persuasive technologies.

Ethical challenges

The question of manipulating feelings and desires through persuasive technology remains an open ethical debate. User-centered design guidelines should be developed encouraging ethically and morally responsible designs, and provide a reasonable balance between the pros and cons of persuasive technologies.[38]

In addition to encouraging ethically and morally responsible designs, Fogg believes education, such as through the journal articles he writes, is a panacea for concerns about the ethical challenges of persuasive computers.[39] Fogg notes two fundamental distinctions regarding the importance of education in engaging with ethics and technology: "First, increased knowledge about persuasive computers allows people more opportunity to adopt such technologies to enhance their own lives, if they choose. Second, knowledge about persuasive computers helps people recognize when technologies are using tactics to persuade them."[11]

Another ethical challenge for persuasive technology designers is the risk of triggering persuasive backfires, where the technology triggers the bad behavior that it was designed to reduce.[40]

See also

Other subjects which have some overlap or features in common with persuasive technology include:


  1. ^ Fogg 2002
  2. ^ Oinas-Kukkonen et al. 2008
  3. ^ a b Bogost 2007
  4. ^ Lockton et al. 2010
  5. ^ Fogg 1998
  6. ^ Fogg 2002, ch. 3
  7. ^ Fogg 2002, ch. 4
  8. ^ Reeves & Nass 1996, Turkle 1984
  9. ^ Fogg 2002, p. 90
  10. ^ Fogg 1997b, Moon 2000
  11. ^ a b Fogg, BJ (1998). "Persuasive Computers: Perspectives and Research Directions". Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI '98. New York, NY, USA: ACM Press/Addison-Wesley Publishing Co.: 225–232. doi:10.1145/274644.274677. ISBN 9780201309874. S2CID 14818487.
  12. ^ Oinas-Kukkonen & Harjumaa 2008
  13. ^ Licklider 1968
  14. ^ Bailenson et al. 2004
  15. ^ DiMicco 2004
  16. ^ Winograd 1986
  17. ^ Chak 2003
  18. ^ Spahn, Andreas (December 2012). "And Lead Us (Not) into Persuasion…? Persuasive Technology and the Ethics of Communication". Science and Engineering Ethics. 18 (4): 633–650. doi:10.1007/s11948-011-9278-y. ISSN 1353-3452. PMC 3513602. PMID 21544700.
  19. ^ de Oliveira, Rodrigo; Cherubini, Mauro; Oliver, Nuria (2010-01-01). MoviPill: Improving Medication Compliance for Elders Using a Mobile Persuasive Social Game. Proceedings of the 12th ACM International Conference on Ubiquitous Computing. UbiComp '10. New York, NY, USA: ACM. pp. 251–260. doi:10.1145/1864349.1864371. ISBN 9781605588438. S2CID 75742.
  20. ^ a b Thieme, Anja; Comber, Rob; Miebach, Julia; Weeden, Jack; Kraemer, Nicole; Lawson, Shaun; Olivier, Patrick (2012-01-01). "We've Bin Watching You": Designing for Reflection and Social Persuasion to Promote Sustainable Lifestyles. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI '12. New York, NY, USA: ACM. pp. 2337–2346. doi:10.1145/2207676.2208394. ISBN 9781450310154. S2CID 8776002.
  21. ^ Caraban, Ana; Ferreira, Maria José; Gouveia, Rúben; Karapanos, Evangelos (2015-01-01). Social Toothbrush: Fostering Family Nudging Around Tooth Brushing Habits. Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers. UbiComp/ISWC'15 Adjunct. New York, NY, USA: ACM. pp. 649–653. doi:10.1145/2800835.2809438. ISBN 9781450335751. S2CID 24178634.
  22. ^ Chiu, Meng-Chieh; Chang, Shih-Ping; Chang, Yu-Chen; Chu, Hao-Hua; Chen, Cheryl Chia-Hui; Hsiao, Fei-Hsiu; Ko, Ju-Chun (2009-01-01). Playful Bottle: A Mobile Social Persuasion System to Motivate Healthy Water Intake. Proceedings of the 11th International Conference on Ubiquitous Computing. UbiComp '09. New York, NY, USA: ACM. pp. 185–194. doi:10.1145/1620545.1620574. ISBN 9781605584317. S2CID 207175275.
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  27. ^ Gena, Cristina; Grillo, Pierluigi; Lieto, Antonio; Mattutino, Claudio; Vernero, Fabiana (2019-09-26). "When Personalization Is Not an Option: An In-The-Wild Study on Persuasive News Recommendation". Information. 10 (10): 300. doi:10.3390/info10100300.
  28. ^ Fogg, 2002
  29. ^ Elton 2007
  30. ^ Cugelman et al. 2011
  31. ^ Middleton, Kathryn R.; Anton, Stephen D.; Perri, Michal G. (14 June 2013). "Long-Term Adherence to Health Behavior Change". American Journal of Lifestyle Medicine. 7 (6): 395–404. doi:10.1177/1559827613488867. PMC 4988401. PMID 27547170.
  32. ^ Joseph, Rodney P.; Daniel, Casey L.; Thind, Herpreet; Benitez, Tanya J.; Pekmezi, Dori (8 July 2016). "Applying Psychological Theories to Promote Long-Term Maintenance of Health Behaviors". American Journal of Lifestyle Medicine. 10 (6): 356–368. doi:10.1177/1559827614554594. PMC 5313056. PMID 28217036.
  33. ^ a b Wemyss, Devon; Cellina, Francesca; Lobsiger-Kägi, Evelyn; de Luca, Vanessa; Castri, Roberta (January 2019). "Does it last? Long-term impacts of an app-based behavior change intervention on household electricity savings in Switzerland". Energy Research & Social Science. 47: 16–27. doi:10.1016/j.erss.2018.08.018.
  34. ^ Dhar, Rhavi; Putnam-Farr, Eleanor (2017). "Sustaining Sustainable Hydration: the Importance of Aligning Information Cues to Motivate Long Term Consumer Behavior Change". ACR North American Advances. NA-45.
  35. ^ Chudzynski, Joy; Roll, John M.; McPherson, Sterling; Cameron, Jennifer M.; Howell, Donelle N. (13 February 2015). "Reinforcement Schedule Effects on Long-Term Behavior Change". The Psychological Record. 65 (2): 347–353. doi:10.1007/s40732-014-0110-3. PMC 4484864. PMID 26139942.
  36. ^ a b Froehlich, Jon; Dillahunt, Tawanna; Klasnja, Predrag; Mankoff, Jennifer; Consolvo, Sunny; Harrison, Beverly; Landay, James A. (2009-01-01). UbiGreen: Investigating a Mobile Tool for Tracking and Supporting Green Transportation Habits. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI '09. New York, NY, USA: ACM. pp. 1043–1052. doi:10.1145/1518701.1518861. ISBN 9781605582467. S2CID 10819791.
  37. ^ Fischer, Corinna (2008-02-01). "Feedback on household electricity consumption: a tool for saving energy?". Energy Efficiency. 1 (1): 79–104. doi:10.1007/s12053-008-9009-7. ISSN 1570-646X. S2CID 18804506.
  38. ^ IJsselsteijn, Wijnand; Kort, Yvonne de; Midden, Cees; Eggen, Berry; Hoven, Elise van den (2006-05-18). Persuasive Technology for Human Well-Being: Setting the Scene. Persuasive Technology. Lecture Notes in Computer Science. 3962. pp. 1–5. CiteSeerX doi:10.1007/11755494_1. ISBN 978-3-540-34291-5.
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