Various interventions have been suggested to aid in smoking cessation. However, little is known about the effects of message framing in narratives embedded in serious games. This study compares when an individual experiences unfortunate events from smoking (i.e., loss frame) versus fortunate results benefited from smoking cessation (i.e., gain frame) in a computer game through a model (i.e., virtual self-modeling) that looks like oneself or a stranger. An experiment (N = 64) using a 2 (Message framing: Gain vs. Loss) x 2 (Modeling: Self vs. Other) between-subjects design was conducted using an anti-smoking game. Results show that the gain frame induces stronger perceived susceptibility compared to the loss frame, and self-modeling is more effective than other-modeling. Results further demonstrate that the virtual misfortune experienced through one’s own face, compared to someone else’s face, is significantly more likely to increase one’s susceptibility to the negative consequences of smoking. The study also finds a significant mediating role of identification between framing and susceptibility. Overall, by demonstrating the effectiveness of the self-modeling and gain-framed messages in gameplay, the present investigation provides meaningful contributions to the use of technology for effective health communication.

In the originally published version of this manuscript, author Younbo Jung’s affiliation was incorrect. The correct affiliation should read: “Wee Kim Wee School of Communication and Information, Nanyang Technological University, 31 Nanyang Link, 637718, Singapore”. This has now been corrected online. The publisher apologizes for the error.

Abstract Expanding the theory of planned behavior (TPB) model with non-volitional factors, this study investigated determinants of purchase intention (PI) for probability-type items (PTI) in a popular mobile game. An online survey was conducted with 534 players of Summoners War. The overall results show that the PI of PTI is associated with both rational and impulsive factors. Specifically, the results of hierarchical regression analysis demonstrate that along with two TPB elements (attitude and perceived control), individual factors of self-control and general stress, as well as game-related factors of advancement, competition, purchase frequency and spending amount were all significant predictors of PTI PI. These non-volitional factors account for additional 18% of variance out of 48% total variance (R2 = .48) in PI.

ESports refers to professional video gaming that is typically broadcasted with a live commentary on TV or the Internet. Despite the rapid growth of eSports industry and its potential for a valuable advertising platform, there has not been much discussion about effective advertising strategies for the placement of virtual ads in eSports. Based on previous research, one advertisement factor (i.e. ad animation) and one in-game factor (i.e. in-game dynamics) are identified and tested in an experiment (N = 116) with a 2 (ad animation: static vs. animated ads) × 2 (in-game dynamics: battle vs. non-battle scenes) mixed design. The results show that both ad animation and in-game dynamics have a significant impact on viewers’ visual attention, in terms of fixation count and duration measured by an eye-tracking device. The results also show a significant interaction in which the impact of ad animation on fixation duration is more magnified when in-game play is less busy (i.e. non-battle scenes), compared to when it is busy (i.e. battle scenes). Theoretical implications based on the limited-capacity model, as well as practical implications for practitioners are discussed.

In this study, we investigated the effects of gender (male vs. female) and non-verbal sensitivity (high vs. low) on game experience after playing a first-person shooter videogame. The results of Experiment 2 (n=50) showed that participants with high non-verbal sensitivity experienced more positive valence and a greater level of arousal than participants with low non-verbal sensitivity. The biological sex of the participants became non-significant, after taking into consideration non-verbal sensitivity. The results of a mediation analysis showed that the emotional valence and arousal mediated the effects of non-verbal sensitivity on the enjoyment of the videogame. Implications with respect to a new understanding of gender preference for certain genres of videogames by identifying specific gender-related skills are discussed.

In this study, the effect of the user choice on social responses to computer-synthesized speech is investigated. Three previous findings about social responses to computer-synthesized speech (i.e., social identification, proximate source orientation, and similarity attraction) were tested using the choice paradigm. Social identification and proximate source orientation effects were found even when users had chosen a computer voice at their discretion. In addition, the primacy effect in the user choice prevailed: Participants were more likely to select whatever voice that they heard first between two options. The similarity attraction effect, however, was negated by the cognitive dissonance effect after user choices. The robustness of social responses, its implications for human–computer interaction, and the importance of the user choice in voice-interface designs are discussed.

In this paper, we introduce an interdisciplinary project, involving researchers from the fields of Physical Therapy, Computer Science, Psychology, Communication and Cell Neurobiology, to develop an integrated virtual reality, haptics and modern sensing technique system for post-stroke rehabilitation. The methodology to develop the system includes identification of movement pattern, development of simulated task and diagnostics. Each part of the methodology can be achieved through several sub-steps that are described in detail in this paper. The system is designed from Physical Therapy perspective that can address the motor rehabilitation needs of stroke patients. The system is implemented through stereoscopic displays, force feedback devices and modern sensing techniques that have game-like features and can capture accurate data for further analysis. Diagnostics and evaluation can be made through an Artificial Intelligence based model using collected data and clinical tests have been conducted.