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"Artificial intelligence"

Original Articles
Purpose
This study compared healthy lifestyle (HLS) practices and awareness regarding the use of chatbots (A-uC) for health management between childhood and adolescent cancer survivors (CACSs) and their parents, with the aim of assessing the feasibility of tailored artificial intelligence (AI) chatbot-based interventions for holistic survivorship care.
Methods
A descriptive comparative design was employed involving 80 CACSs and 80 parents (N=160) recruited through the Korean Pediatric Cancer Foundation. HLS practices were assessed using a validated seven-domain instrument encompassing physical activity, nutrition, interpersonal relations, stress management, positive life perspective, health responsibility, and spiritual health. A-uC was evaluated using an extended technology acceptance model-based tool. Responses to the open-ended question addressing unmet HLS practices were analyzed using latent Dirichlet allocation topic modeling.
Results
No significant differences were observed between CACSs and parents in overall HLS (CACSs: 3.16±0.80; parents: 3.18±0.36, p=.74). While perceptions across most A-uC domains did not differ significantly, parents demonstrated a significantly higher “intention to use” chatbots for health management than CACSs (p=.03). The mean A-uC scores exceeded 4 (out of 5) in both groups, reflecting positive perceptions of chatbot-based HLS support. Topic modeling identified “exercise,” “healthy diet,” and “regular lifestyle” as common unmet areas.
Conclusion
CACSs and their parents share largely concordant views on HLS and A-uC, with a strong interest in chatbot interventions. These findings underscore the potential of tailored AI chatbot programs to address unmet lifestyle needs and promote holistic survivorship care.

Citations

Citations to this article as recorded by  
  • What do we want to know from a chatbot? Identifying inquiries among adult survivors of childhood and adolescent cancer in South Korea
    Min Ah Kim, Mirae Kim, Yehwi Park, Chaerim Park, Chungyeon Lee, Kyubum Hwang, Hayoung Oh
    European Journal of Oncology Nursing.2026; 82: 103202.     CrossRef
  • What do cancer patients discuss online regarding CINV management? A social media-based topic modeling study
    Hongzhan Jiang, Wanting Shen, Meng Zhou, Yinyin Lyu, Meiqi Meng, Dan Yang, Xuejing Li, Bohan Zhang, Yufang Hao
    Frontiers in Oncology.2026;[Epub]     CrossRef
  • 1,129 View
  • 93 Download
  • 2 Crossref
Development of a chatbot for school violence prevention among elementary school students in South Korea: a methodological study
Kyung-Ah Kang, Shin-Jeong Kim, Byoung-doo Oh, Yu-Hyeon Kim
Child Health Nurs Res 2024;30(1):45-53.   Published online January 31, 2024
DOI: https://doi.org/10.4094/chnr.2023.054
Purpose
This study develops a chatbot for school violence prevention (C-SVP) among elementary school students.
Methods
Among the analysis, design, development, implementation, and evaluation (ADDIE) models, ADD phases were applied to develop a C-SVP. Students’ learning needs were identified by constructing content with a design that attracted their attention. Subsequently, a formative evaluation was conducted on the developed C-SVP to test its applicability by ten elementary school students targeting the 5th and 6th grades.
Results
The chatbot was designed using KakaoTalk and named “School Guardian Angel.” The formative evaluation revealed that the developed C-SVP was easily accessible and useful for elementary school students.
Conclusion
The developed C-SVP is expected to be effective in preventing violence among elementary school students. However, further research involving children of various age groups is required.

Citations

Citations to this article as recorded by  
  • Effects of School Violence Prevention Education Using a Chatbot (SVPE-C) on Sixth-Grade Students in South Korea
    Shin-Jeong Kim, Sunyeob Choi, Kyung-Ah Kang
    The Journal of School Nursing.2026; 42(2): 113.     CrossRef
  • Implementation of the ADDIE Model in Chatbot Development using Diagramflow
    Fadhil Mureno Ega Nugraha , Muhammad Setiyawan
    Journal of Technology and System Information.2025; 2(2): 9.     CrossRef
  • Intelligent conversational agent as an active strategy for school safety management
    Martha Vidal-Sepúlveda, Cristian Olivares-Rodríguez, Alejandro Sanhueza
    Journal of Risk Research.2025; 28(9-10): 1010.     CrossRef
  • Essential Elements for Implementing AI Tools in Elementary School: A Systematic Literature Review
    Jorge Arriola-Mendoza, Gabriel Valerio-Ureña
    Education Sciences.2024; 14(12): 1292.     CrossRef
  • 8,006 View
  • 143 Download
  • 4 Crossref
Awareness of using chatbots and factors influencing usage intention among nursing students in South Korea: a descriptive study
So Ra Kang, Shin-Jeong Kim, Kyung-Ah Kang
Child Health Nurs Res 2023;29(4):290-299.   Published online October 31, 2023
DOI: https://doi.org/10.4094/chnr.2023.29.4.290
Purpose
Artificial intelligence (AI) has had a profound impact on humanity; in particular, chatbots have been designed for interactivity and applied to many aspects of daily life. Chatbots are also regarded as an innovative modality in nursing education. This study aimed to identify nursing students' awareness of using chatbots and factors influencing their usage intention.
Methods
This study, which employed a descriptive design using a self-reported questionnaire, was conducted at three university nursing schools located in Seoul, South Korea. The participants were 289 junior and senior nursing students. Data were collected using self-reported questionnaires, both online via a Naver Form and offline.
Results
The total mean score of awareness of using chatbots was 3.49±0.61 points out of 5. The mean scores of the four dimensions of awareness of using chatbots were 3.37±0.60 for perceived value, 3.66±0.73 for perceived usefulness, 3.83±0.73 for perceived ease of use, and 3.36±0.87 for intention to use. Significant differences were observed in awareness of using chatbots according to satisfaction with nursing (p<.001), effectiveness of using various methods for nursing education (p<.001), and interest in chatbots (p<.001). The correlations among the four dimensions ranged from .52 to .80. In a hierarchical regression analysis, perceived value (β=.45) accounted for 60.2% of variance in intention to use.
Conclusion
The results suggest that chatbots have the potential to be used in nursing education. Further research is needed to clarify the effectiveness of using chatbots in nursing education.

Citations

Citations to this article as recorded by  
  • Applications, attitudes and ethical considerations of Generative Artificial Intelligence (Gen AI) in nursing education: a scoping review
    Philip Hardie, Andrew Darley, Rosemarie Derwin, Jessica Eustace-Cook, Sean Kearns, Barry Mc Brien, Aysha Siddiquee, David Zheng, Mary Mooney
    BMC Nursing.2026;[Epub]     CrossRef
  • Adoption of AI in nursing education- A systematic review of factors influencing student intentions
    Abdulaziz Mofdy Almarwani
    Applied Nursing Research.2026; 88: 152068.     CrossRef
  • Educational Applications of AI-Based Chatbots in Nursing: A Scoping Review
    Francisco Fernandes, Rúben Encarnação, José Alves, Carla Pais-Vieira, Suzinara Beatriz Soares de Lima, Paulo Alves
    Nursing Reports.2026; 16(3): 87.     CrossRef
  • The effect of using a chatbot integrated with the ARCS motivation model in physiology education: a mixed-methods study
    Yasin Ali Cimen, Gunes Bolatli
    Frontiers in Physiology.2026;[Epub]     CrossRef
  • Conceptual analysis of Chatbots in nursing education applications
    Lianhua Li, Xia Chen, Shaoyong Ma, Zhengxia Yang, Yingying Wang
    Nurse Education Today.2026; 166: 107188.     CrossRef
  • Importance of AI Chatbot in Nursing Education: A Systematic Review
    Tahira Ghaffar, Rajan Balakrishnan, Mian Adnan Aslam Javaid
    Biological and Clinical Sciences Research Journal.2026; 7(4): 37.     CrossRef
  • Predicting nursing students’ behavioral intentions to use AI: The interplay of ethical awareness, digital literacy, moral sensitivity, attitude, self-efficacy, anxiety, and social influence
    Mohammad Abuadas, Zainab Albikawi
    Journal of Human Behavior in the Social Environmen.2025; : 1.     CrossRef
  • Integrating artificial intelligence ethically in nursing education
    Dawn L. Riess
    Nursing.2025; 55(4): 56.     CrossRef
  • The Turkish Version of the Technology Acceptance Model-Based Scale TAME-ChatGPT: A Validity and Reliability Study
    Ebru Küçük, Buket Meral, Kıymet Yesilçiçek Çalık, Cantürk Çapık
    International Journal of Human–Computer Interactio.2025; 41(23): 14734.     CrossRef
  • A Study of Student Demographic Variables as Predictors of Intentions to Adopt Computer-Based Testing in Nursing School Clinical Examination
    Olusegun Ojo Bakare, Adebola Arike Bolarinwa
    ETDC: Indonesian Journal of Research and Education.2025; 4(2): 376.     CrossRef
  • The use of generative artificial intelligence (AI) in nursing education
    Mollie Ostick, Bette Mariani, Catherine Lovecchio
    Teaching and Learning in Nursing.2025; 20(4): e1296.     CrossRef
  • Development and effects of a scenario-based labor nursing simulation education program using an artificial intelligence tutor: a quasi-experimental study
    Seo-A Park, Hye Young Kim
    Women's Health Nursing.2025; 31(2): 143.     CrossRef
  • Driving AI chatbot adoption: A systematic review of factors, barriers, and future research directions
    Norah Alharbi, Fareed Ud Din, David Paul, Edmund Sadgrove
    Journal of Open Innovation: Technology, Market, an.2025; 11(3): 100590.     CrossRef
  • Applying the technology acceptance model to examine factors influencing chatbot use in HPV prevention education among nursing students
    Ching-Yi Lai, Wei-Sho Ho
    BMC Nursing.2025;[Epub]     CrossRef
  • Integrating a knowledge-based artificial intelligence chatbot into nursing training programs: a comparative quasi-experimental study in Egypt and Saudi Arabia
    Eman A. Shokr
    BMC Nursing.2025;[Epub]     CrossRef
  • Nursing Students' Perceptions and Attitudes on the Application of Artificial Intelligence in Nursing Education: A Mixed‐Methods Systematic Review
    Yuhang Li, Shi Chen, Xiaohui Dong, Xianying Lu, Xinyu Chen, Dingxi Bai, Wen Luo, Ting Cao, Zihao Song, Chaoming Hou, Jing Gao
    Journal of Advanced Nursing.2025;[Epub]     CrossRef
  • Effect of using artificial intelligence chatbot about electronic fetal monitoring on maternity nursing students’ performance
    Amal Mohamed Talaat Abdelwahab, Marwa Ibrahim Hamdy Aboraiah, Hanan Elsayed Mohamed Elsayed
    BMC Medical Education.2025;[Epub]     CrossRef
  • Evolution of Chatbots in Nursing Education: Narrative Review
    Fang Zhang, Xiaoliu Liu, Wenyan Wu, Shiben Zhu
    JMIR Medical Education.2024; 10: e54987.     CrossRef
  • The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care
    Hyewon Shin, Jennie C. De Gagne, Sang Suk Kim, Minjoo Hong
    CIN: Computers, Informatics, Nursing.2024; 42(10): 704.     CrossRef
  • Artificial intelligence tools utilized in nursing education: Incidence and associated factors
    Samar Thabet Jallad, Khitam Alsaqer, Baker Ishaq Albadareen, Duaa Al-maghaireh
    Nurse Education Today.2024; 142: 106355.     CrossRef
  • The association of artificial intelligence ethical awareness, attitudes, anxiety, and intention-to-use artificial intelligence technology among nursing students
    Moh''d Khair Migdadi, Islam Ali Oweidat, Mohammad R. Alosta, Khalid Al-Mugheed, Amany Anwar Saeed Alabdullah, Sally Mohammed Farghaly Abdelaliem
    DIGITAL HEALTH.2024;[Epub]     CrossRef
  • UNLOCKING THE TRANSFORMATIVE POWER OF ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE DEVELOPMENT IN HIGHER EDUCATION
    TIJJANI MUHAMMAD, MARY DAVID
    Innovare Journal of Social Sciences.2024; : 19.     CrossRef
  • 9,405 View
  • 226 Download
  • 22 Crossref
Purpose
This study aimed to identify students' awareness of the use of a chatbot (A-uC), a type of artificial intelligence technology, for violence prevention among elementary school students.
Methods
The participants comprised 215 students in the fourth to sixth grades in Chuncheon, South Korea, and data were collected via a self-reported questionnaire.
Results
The mean A-uC score was 3.43±0.83 out of 5 points. The mean scores for the 4 sub-dimensions of the A-uC tool were 3.48±0.80 for perceived value, 3.44±0.98 for perceived usefulness, 3.63±0.92 for perceived ease of use, and 3.15±1.07 for intention to use. Significant differences were observed in A-uC scores (F=59.26, p<.001) according to the need for the use of chatbots in violence prevention education. The relationships between intention to use and the other A-uC sub-dimensions showed significant correlations with perceived value (r=.85, p<.001), perceived usefulness (r=.76, p<.001), and perceived ease of use (r=.64, p<.001).
Conclusion
The results of this study suggest that chatbots can be used in violence prevention education for elementary school students.

Citations

Citations to this article as recorded by  
  • Effects of School Violence Prevention Education Using a Chatbot (SVPE-C) on Sixth-Grade Students in South Korea
    Shin-Jeong Kim, Sunyeob Choi, Kyung-Ah Kang
    The Journal of School Nursing.2026; 42(2): 113.     CrossRef
  • Parental and child perspectives on healthy lifestyles and artificial intelligence chatbot use among childhood and adolescent cancer survivors: a descriptive comparative study in South Korea
    Kyung-Ah Kang, Shin-Jeong Kim, In-Hye Song, Hee-Jin Yoon
    Child Health Nursing Research.2026; 32(1): 27.     CrossRef
  • Scientific Mapping of Chatgpt Usage in Education: A Bibliometric Perspective
    İsmail Eray Dursun, Mustafa Taktak
    Sınırsız Eğitim ve Araştırma Dergisi.2025; 10(1): 123.     CrossRef
  • Unpacking artificial intelligence in elementary education: A comprehensive thematic analysis systematic review
    Taoufik Boulhrir, Mahmoud Hamash
    Computers and Education: Artificial Intelligence.2025; 9: 100442.     CrossRef
  • A systematic literature review of the acceptability of the use of Metaverse in education over 16 years
    Hui Wen Chua, Zhonggen Yu
    Journal of Computers in Education.2024; 11(2): 615.     CrossRef
  • Development of a chatbot for school violence prevention among elementary school students in South Korea: a methodological study
    Kyung-Ah Kang, Shin-Jeong Kim, Byoung-doo Oh, Yu-Hyeon Kim
    Child Health Nursing Research.2024; 30(1): 45.     CrossRef
  • ความตระหนักรู้ในการใช้ปัญญาประดิษฐ์เพื่อการเรียนรู้สำหรับนักศึกษาระดับปริญญาตรี คณะศึกษาศาสตร์ มหาวิทยาลัยรามคำแหง
    หนึ่งฤทัย ดิษฐ์โรจน์, วศิน นุชคง , จุฑาภรณ์ มาสันเทียะ
    Interdisciplinary Academic and Research Journal .2024; 4(6): 43.     CrossRef
  • Essential Elements for Implementing AI Tools in Elementary School: A Systematic Literature Review
    Jorge Arriola-Mendoza, Gabriel Valerio-Ureña
    Education Sciences.2024; 14(12): 1292.     CrossRef
  • Awareness of using chatbots and factors influencing usage intention among nursing students in South Korea: a descriptive study
    So Ra Kang, Shin-Jeong Kim, Kyung-Ah Kang
    Child Health Nursing Research.2023; 29(4): 290.     CrossRef
  • 6,733 View
  • 173 Download
  • 9 Crossref
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