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作 者:Fatimah Dera M. Alshahrani Fatimah Dera M. Alshahrani(College of Computer Science, King Khalid University (KKU), Abha, KSA)
机构地区:[1]College of Computer Science, King Khalid University (KKU), Abha, KSA
出 处:《Advances in Internet of Things》2024年第2期36-52,共17页物联网(英文)
摘 要:This paper explores the integration of persuasive technology into smoking cessation efforts through the development and evaluation of a mobile app, “No-Smoke.” Leveraging compelling features like social support, tracking, planning, and motivation, the app aims to augment user engagement and support the process of quitting smoking. The efficacy of these features has been substantiated through both automated testing and user feedback, highlighting their potential to enhance awareness, motivation, and behavior modification. Despite notable successes, limitations, including a limited user base and uncertainties regarding long-term efficacy, have been acknowledged, stemming from the inherent complexities of smoking cessation. Nevertheless, based on user experiences and feedback, “No-Smoke” represents a promising advancement in the use of technology for public health interventions, particularly in the realm of smoking cessation. To address existing challenges, future research is recommended to encompass a comprehensive, long-term study involving a larger and more diverse user base. Additionally, further investigation should focus on personalization enhancements and the integration of machine learning algorithms to better understand and respond to user behavior.This paper explores the integration of persuasive technology into smoking cessation efforts through the development and evaluation of a mobile app, “No-Smoke.” Leveraging compelling features like social support, tracking, planning, and motivation, the app aims to augment user engagement and support the process of quitting smoking. The efficacy of these features has been substantiated through both automated testing and user feedback, highlighting their potential to enhance awareness, motivation, and behavior modification. Despite notable successes, limitations, including a limited user base and uncertainties regarding long-term efficacy, have been acknowledged, stemming from the inherent complexities of smoking cessation. Nevertheless, based on user experiences and feedback, “No-Smoke” represents a promising advancement in the use of technology for public health interventions, particularly in the realm of smoking cessation. To address existing challenges, future research is recommended to encompass a comprehensive, long-term study involving a larger and more diverse user base. Additionally, further investigation should focus on personalization enhancements and the integration of machine learning algorithms to better understand and respond to user behavior.
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