R
Rita Orji
Researcher at Dalhousie University
Publications - 165
Citations - 4545
Rita Orji is an academic researcher from Dalhousie University. The author has contributed to research in topics: Persuasive technology & Personalization. The author has an hindex of 28, co-authored 165 publications receiving 2872 citations. Previous affiliations of Rita Orji include Nnamdi Azikiwe University & University of Waterloo.
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Journal ArticleDOI
Persuasive technology for health and wellness: State-of-the-art and emerging trends.
Rita Orji,Karyn Moffatt +1 more
TL;DR: This paper provides an empirical review of 16 years (85 papers) of literature on persuasive technology for health and wellness to answer important questions regarding the effectiveness and uncover pitfalls of existing persuasive technological interventions forhealth and wellness.
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Towards an Effective Health Interventions Design: An Extension of the Health Belief Model
TL;DR: This paper extended the Health Belief Model by introducing four new variables: Self-identity, Perceived Importance, Consideration of Future Consequences, and Concern for Appearance as possible determinants of healthy behavior, showing the suitability of the extended HBM for use in predicting healthy behavior and in informing health intervention design.
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Modeling the efficacy of persuasive strategies for different gamer types in serious games for health
TL;DR: A large-scale study on 1,108 gamers is conducted to examine the persuasiveness of ten PT strategies that are commonly employed in persuasive game design, and the receptiveness of seven gamer personalities to theTen PT strategies are examined.
Proceedings ArticleDOI
Tailoring persuasive health games to gamer type
TL;DR: A large-scale survey of 642 gamers' eating habits and their associated determinants of healthy behavior to understand how health behavior relates to gamer type and developed seven different models of healthy eating behavior for the gamer types identified by BrainHex.
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Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach
TL;DR: In this article, the authors used automated extraction of COVID-19-related discussions from social media and a natural language process (NLP) method based on topic modeling to uncover various issues related to the disease from public opinions.