Evaluating the Effect of Adapting Virtual Humans Based on Individual Differences in Users

被引:0
|
作者
Zalake, Mohan [1 ]
De Siqueira, Alexandre Gomes [2 ]
Vaddiparti, Krishna [2 ]
Antonenko, Pavlo [2 ]
Lok, Benjamin [2 ]
机构
[1] Univ Illinois, Chicago, IL 60607 USA
[2] Univ Florida, Gainesville, FL USA
来源
DIGITAL HUMAN MODELING AND APPLICATIONS IN HEALTH, SAFETY, ERGONOMICS AND RISK MANAGEMENT, PT I, DHM 2024 | 2024年 / 14709卷
关键词
Virtual humans; Health; Behavior change; Adaptive systems; STUDENTS; IMPACT;
D O I
10.1007/978-3-031-61060-8_28
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This paper investigates the effects of adapting a virtual human's persuasion strategy based on users' personalities and prior beliefs regarding recommended behavior in the context of promoting mental health coping skills among college students. The paper uses the Theory of Planned Behavior (TPB) as the theoretical model to study how a virtual human's persuasion strategies impact behavior change. The paper also employs Cialdini's six persuasion strategies - Reciprocity, Scarcity, Authority, Commitment, Likability, and Consensus - to manipulate the virtual human's dialog. The paper develops a user model that predicts the effectiveness of different persuasion strategies based on user data from a previous study. The paper then evaluates the user model in an empirical study with 292 undergraduate students, comparing three experimental conditions - a matched condition where the virtual human used a more effective persuasion strategy, a mismatched condition where the virtual human used a less effective persuasion strategy, and a control condition where the virtual human did not use any persuasion strategy. The paper finds that adapting the virtual human's persuasion strategy can positively influence users who have low self-efficacy to perform the recommended behavior, but can negatively influence users who already have high self-efficacy. The paper also finds that persuasion strategies may not be sufficient to induce behavior change, and suggests accounting for users' perceived barriers and benefits of the recommended behavior. The paper contributes to the Human-Computer Interaction research by providing evidence for the importance of individual differences in designing virtual human health interventions.
引用
收藏
页码:405 / 423
页数:19
相关论文
共 50 条
  • [1] ADAPTING TO INDIVIDUAL-DIFFERENCES
    GLASER, R
    SOCIAL POLICY, 1977, 8 (02) : 27 - 33
  • [2] Adapting a Virtual Agent to Users' Vocabulary and Needs
    Mendes, Ana Cristina
    Prada, Rui
    Coheur, Luisa
    INTELLIGENT VIRTUAL AGENTS, PROCEEDINGS, 2009, 5773 : 529 - 530
  • [3] Proactively adapting interfaces to individual users for mobile devices
    Hartmann, Melanie
    Schreiber, Daniel
    ADAPTIVE HYPERMEDIA AND ADAPTIVE WEB-BASED SYSTEMS, 2008, 5149 : 300 - 303
  • [4] The Impact of Adapting Content for Students with Individual Differences
    Flores, Raymond
    Ari, Fatih
    Inan, Fethi A.
    Arslan-Ari, Ismahan
    EDUCATIONAL TECHNOLOGY & SOCIETY, 2012, 15 (03): : 251 - 261
  • [5] Adapting Instruction in the Social Studies to Individual Differences
    不详
    NERVOUS CHILD, 1945, 4 (04): : 413 - 414
  • [6] Individual and group behaviours for virtual humans
    Thalmann, D
    COMPUTER ANIMATION 2000, PROCEEDINGS, 2000, : 122 - 124
  • [7] Individual differences in virtual environments
    Sas, C
    COMPUTATIONAL SCIENCE - ICCS 2004, PT 3, PROCEEDINGS, 2004, 3038 : 1017 - 1024
  • [8] Evaluating the Uncanny Valley Effect in Dark Colored Skin Virtual Humans
    de Andrade Araujo, Victor Flavio
    Costa, Angelo Brandelli
    Musse, Soraia Raupp
    2023 36TH CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES, SIBGRAPI 2023, 2023, : 1 - 6
  • [9] Individual differences among cocaine users
    Gunnarsdóttir, ED
    Pingitore, RA
    Spring, BJ
    Konopka, LM
    Crayton, JW
    Milo, T
    Shirazi, P
    ADDICTIVE BEHAVIORS, 2000, 25 (05) : 641 - 652
  • [10] Individual differences in frontoparietal plasticity in humans
    Austin L. Boroshok
    Anne T. Park
    Panagiotis Fotiadis
    Gerardo H. Velasquez
    Ursula A. Tooley
    Katrina R. Simon
    Jasmine C. P. Forde
    Lourdes M. Delgado Reyes
    M. Dylan Tisdall
    Dani S. Bassett
    Emily A. Cooper
    Allyson P. Mackey
    npj Science of Learning, 7