Personalizing health theories in persuasive game interventions to gamer types: an African perspective

Persuasive games (PGs) informed by behaviour theories are effective tools for motivating health behaviour. It has been shown that tailoring PGs to the target audience increases their effectiveness. However, most existing studies on how to tailor PGs and gameful systems are focused on people from the Western cultures. There is a paucity of research on how to personalize PGs to the African audience. To advance research in this area, we conducted a large-scale study of 360 game players from Africa to investigate their eating habits and associated determinants of health behaviour to understand how health behaviour relates to their gamer types. We developed models showing the determinants of health behaviour for the seven gamer types identified by BrainHex. Our results show that gamer types play significant roles in the impact of various determinants on the health behaviour of Africans. People high in the achiever gamer type are motivated by perceived susceptibility (what they stand to lose), while daredevils are motivated by perceived benefit (what they stand to gain) from adopting a healthy lifestyle. Self-efficacy emerged as the most effective determinant overall, it influences health behaviour positively for all gamer types. We contribute to Human-Computer Interaction (HCI) research and practice by offering design guidelines for tailoring PGs for health to Africans based on their gamer types.

[1]  Kiemute Oyibo,et al.  Developing Culturally Relevant Design Guidelines for Encouraging Physical Activity: a Social Cognitive Theory Perspective , 2018, Journal of Healthcare Informatics Research.

[2]  Maria Letizia Jaccheri,et al.  User requirements for gamifying sports software , 2013, 2013 3rd International Workshop on Games and Software Engineering: Engineering Computer Games to Enable Positive, Progressive Change (GAS).

[3]  Keiko Yamamoto,et al.  Stand Up, Heroes! : Gamification for Standing People on Crowded Public Transportation , 2013, HCI.

[4]  I. Luginaah,et al.  Breast cancer screening among women in Namibia: explaining the effect of health insurance coverage and access to information on screening behaviours , 2019, Global health promotion.

[5]  M. Conner,et al.  Predicting health behaviour : research and practice with social cognition models , 2005 .

[6]  H. Schomer,et al.  Health Belief Model Interpretation of Compliance Factors in a Weight Loss and Cardiac Rehabilitation Programme , 1994 .

[7]  Stavros Asimakopoulos,et al.  Does Social User Experience Improve Motivation for Runners? - A Diary Study Comparing Mobile Health Applications , 2014, HCI.

[8]  K. Hepburn,et al.  Use of mobile video show for community behavior change on maternal and newborn health in rural Ethiopia. , 2014, Journal of midwifery & women's health.

[9]  Julita Vassileva,et al.  Modeling the efficacy of persuasive strategies for different gamer types in serious games for health , 2014, User Modeling and User-Adapted Interaction.

[10]  C. Koopman,et al.  Factors associated with condom use in Kenya: a test of the health belief model. , 2001, AIDS education and prevention : official publication of the International Society for AIDS Education.

[11]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .

[12]  Julita Vassileva,et al.  Tailoring persuasive health games to gamer type , 2013, CHI.

[13]  Lily Shui-Lien Chen,et al.  Subjective Well-Being: Evidence from the Different Personality Traits of Online Game Teenager Players , 2008, Cyberpsychology Behav. Soc. Netw..

[14]  S. N. Anasi,et al.  Access to and use of reproductive health information among in-school adolescent girls in Lagos State, Nigeria , 2012 .

[15]  G. Fong,et al.  Reductions in HIV risk-associated sexual behaviors among black male adolescents: effects of an AIDS prevention intervention. , 1992, American journal of public health.

[16]  Les Nelson,et al.  Online gaming motivations scale: development and validation , 2012, CHI.

[17]  Juho Hamari,et al.  "Working out for likes": An empirical study on social influence in exercise gamification , 2015, Comput. Hum. Behav..

[18]  Deborah I. Fels,et al.  Gamification in theory and action: A survey , 2015, Int. J. Hum. Comput. Stud..

[19]  Christof Weinhardt,et al.  Well-Being's Predictive Value - A Gamified Approach to Managing Smart Communities , 2013, HCI.

[20]  I. Ajzen The theory of planned behavior , 1991 .

[21]  A. Oyekale,et al.  Application of health belief model for promoting behaviour change among Nigerian single youth. , 2010, African journal of reproductive health.

[22]  Stoyan R. Stoyanov,et al.  Gamification for health and wellbeing: A systematic review of the literature , 2016, Internet interventions.

[23]  Oren Zuckerman,et al.  Deconstructing gamification: evaluating the effectiveness of continuous measurement, virtual rewards, and social comparison for promoting physical activity , 2014, Personal and Ubiquitous Computing.

[24]  A. Kagee,et al.  Acceptability of routine HIV counselling and testing among a sample of South African students: Testing the Health Belief Model , 2013, African journal of AIDS research : AJAR.

[25]  Sameer Deshpande,et al.  Factors Influencing Healthy Eating Habits Among College Students: An Application of the Health Belief Model , 2009, Health marketing quarterly.

[26]  Deborah I Thompson,et al.  Serious Video Games for Health: How Behavioral Science Guided the Development of a Serious Video Game , 2010, Simulation & gaming.

[27]  Rita Orji,et al.  Persuasive technology for health and wellness: State-of-the-art and emerging trends , 2018, Health Informatics J..

[28]  K Witte,et al.  A theoretically based evaluation of HIV/AIDS prevention campaigns along the trans-Africa highway in Kenya. , 1998, Journal of health communication.

[29]  H. Kaiser A second generation little jiffy , 1970 .

[30]  Adrian Leguina,et al.  A primer on partial least squares structural equation modeling (PLS-SEM) , 2015 .

[31]  Brian Wansink,et al.  Mindless Eating: Why We Eat More Than We Think , 2001 .

[32]  R. Croyle,et al.  Theory at a glance: a guide for health promotion practice (Second edition). , 2005 .

[33]  Julita Vassileva,et al.  Improving the Efficacy of Games for Change Using Personalization Models , 2017, ACM Trans. Comput. Hum. Interact..

[34]  B. Fogg The ethics of persuasive technology , 2003 .

[35]  Julita Vassileva,et al.  Towards an Effective Health Interventions Design: An Extension of the Health Belief Model , 2012, Online journal of public health informatics.

[36]  Nick Yee,et al.  Motivations for Play in Online Games , 2006, Cyberpsychology Behav. Soc. Netw..

[37]  Rebecca E. Grinter,et al.  Let's play!: mobile health games for adults , 2010, UbiComp.

[38]  Elke E. Mattheiss,et al.  From Classes to Mechanics: Player Type Driven Persuasive Game Development , 2015, CHI PLAY.

[39]  Julita Vassileva,et al.  LunchTime: a slow-casual game for long-term dietary behavior change , 2013, Personal and Ubiquitous Computing.

[40]  Melissa Densmore,et al.  Designing with Community Health Workers: Enabling Productive Participation Through Exploration , 2016, AfriCHI.

[41]  I. Rosenstock Why people use health services. , 1966, The Milbank Memorial Fund quarterly.

[42]  A. Daftary,et al.  Using mHealth for HIV/TB Treatment Support in Lesotho: Enhancing Patient–Provider Communication in the START Study , 2016, Journal of acquired immune deficiency syndromes.

[43]  N. Modeste,et al.  Attitudes toward Condom Use among High School and University Students in Zimbabwe , 2006, International quarterly of community health education.

[44]  Julita Vassileva,et al.  Providing for Impression Management in Persuasive Designs , 2012 .

[45]  E. Kupek,et al.  Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders , 2006, BMC medical research methodology.

[46]  H. Kelley Attribution theory in social psychology , 1967 .

[47]  P. White The concept of diseases and health care in African traditional religion in Ghana , 2015 .

[48]  Chrysanne Di Marco,et al.  Towards Personality-driven Persuasive Health Games and Gamified Systems , 2017, CHI.

[49]  Rik Crutzen,et al.  Effects of a Web-Based Computer-Tailored Game to Reduce Binge Drinking Among Dutch Adolescents: A Cluster Randomized Controlled Trial , 2016, Journal of Medical Internet Research.

[50]  Wei Peng,et al.  Design and Evaluation of a Computer Game to Promote a Healthy Diet for Young Adults , 2009, Health communication.

[51]  J. Cafazzo,et al.  Design of an mHealth App for the Self-management of Adolescent Type 1 Diabetes: A Pilot Study , 2012, Journal of medical Internet research.

[52]  Boris E. R. de Ruyter,et al.  Adaptive Persuasive Systems: A Study of Tailored Persuasive Text Messages to Reduce Snacking , 2012, TIIS.

[53]  Helen H. Jensen,et al.  An Evaluation of the Health Belief Model for Predicting Perceived and Actual Dietary Quality1 , 1998 .

[54]  Tracy A. Dennis,et al.  Mental Health on the Go , 2014, Clinical psychological science : a journal of the Association for Psychological Science.

[55]  Rita Orji,et al.  STD PONG: A Personalized Persuasive Game for Risky Sexual Behaviour Change in Africa , 2018, PPT@PERSUASIVE.

[56]  Silvia Riva,et al.  Interactive Sections of an Internet-Based Intervention Increase Empowerment of Chronic Back Pain Patients: Randomized Controlled Trial , 2014, Journal of medical Internet research.

[57]  Saskia M. Kelders,et al.  'This Is Your Life!' - The Design of a Positive Psychology Intervention Using Metaphor to Motivate , 2014, PERSUASIVE.

[58]  R. Orji,et al.  DESIGN FOR BEHAVIOUR CHANGE: A MODEL-DRIVEN APPROACH FOR TAILORING PERSUASIVE TECHNOLOGIES , 2014 .

[59]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[60]  STD PONG : An African-Centric Persuasive Game for Risky Sexual Behaviour Change , 2018 .

[61]  Melissa Densmore,et al.  Exploring Co-design with Breastfeeding Mothers , 2018, CHI.

[62]  Regan L. Mandryk,et al.  BrainHex: A neurobiological gamer typology survey , 2014, Entertain. Comput..

[63]  Peter Johannes Schulz,et al.  The Effect of Social Support Features and Gamification on a Web-Based Intervention for Rheumatoid Arthritis Patients: Randomized Controlled Trial , 2015, Journal of medical Internet research.

[64]  Juho Hamari,et al.  Does Gamification Work? -- A Literature Review of Empirical Studies on Gamification , 2014, 2014 47th Hawaii International Conference on System Sciences.

[65]  B. J. Fogg,et al.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[66]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[67]  H. Hoffman,et al.  Virtual Reality Pain Control During Burn Wound Debridement in the Hydrotank , 2008, The Clinical journal of pain.

[68]  H. Jensen,et al.  Evaluation of the Health Belief Model for Predicting Perceived and Actual Dietary Quality (An) , 1998 .

[69]  D. Bangsberg,et al.  Short message service (SMS) reminders and real-time adherence monitoring improve antiretroviral therapy adherence in rural Uganda , 2016, AIDS.

[70]  David W. McDonald,et al.  Theory-driven design strategies for technologies that support behavior change in everyday life , 2009, CHI.

[71]  Ross Shegog,et al.  Application of behavioral theory in computer game design for health behavior change , 2010 .

[72]  J. Prochaska,et al.  In Search of How People Change: Applications to Addictive Behaviors , 1992, The American psychologist.

[73]  Romin W. Tafarodi,et al.  Individualism–collectivism, life events, and self‐esteem: a test of two trade‐offs , 1999 .

[74]  H. Carabin,et al.  Towards an understanding of barriers to condom use in rural Benin using the Health Belief Model: A cross sectional survey , 2005, BMC public health.

[75]  Hadi Kharrazi,et al.  Healthcare Game Design: Behavioral Modeling of Serious Gaming Design for Children with Chronic Diseases , 2009, HCI.

[76]  Traci Mann,et al.  Approach/avoidance motivation, message framing, and health behavior: understanding the congruency effect , 2006, Motivation and emotion.

[77]  Elke E. Mattheiss,et al.  Using Player Type Models for Personalized Game Design - An Empirical Investigation , 2016, IxD&A.

[78]  Lennart E. Nacke,et al.  The neurobiology of play , 2010, Future Play.

[79]  John C. Norcross,et al.  In search of how people change: Applications to addictive behaviors. , 1992 .

[80]  Pearl Pu,et al.  HealthyTogether: exploring social incentives for mobile fitness applications , 2014, Chinese CHI '14.

[81]  G. Hofstede,et al.  Cultures and Organizations: Software of the Mind , 1991 .

[82]  James Noble,et al.  Fine Tuning the Persuasion in Persuasive Games , 2007, PERSUASIVE.