Rhode Ghislaine Nguewo Ngassam, Linnea Ung, Roxana Ologeanu-Taddeï, Jorick Lartigau, P. Demoly, Isabelle Bourdon, Nicolas Molinari, A. Chiriac
Adoption and user perceptions are dominant on personal health records literature and have led to a better understanding of what individuals' behaviors and perceptions are about the adoption of personal health records. However, these insights are descriptive and are not actionable to allow creating personal health records that will overcome the adoption problems identified by users. This study uses action design research to provide actionable knowledge regarding user perceptions and adoption and their application in the case of the digital allergy card. To achieve this, we conducted interviews with patients and physicians as part of the evaluation of the digital allergy card mock-up and the first prototype. As results, we provided some research proposals regarding the benefits of, levers for, and barriers to adoption of the digital allergy card that can be tested for several other personal health records.
{"title":"An Action Design Research to Facilitate the Adoption of Personal Health Records: The Case of Digital Allergy Cards","authors":"Rhode Ghislaine Nguewo Ngassam, Linnea Ung, Roxana Ologeanu-Taddeï, Jorick Lartigau, P. Demoly, Isabelle Bourdon, Nicolas Molinari, A. Chiriac","doi":"10.4018/joeuc.288551","DOIUrl":"https://doi.org/10.4018/joeuc.288551","url":null,"abstract":"Adoption and user perceptions are dominant on personal health records literature and have led to a better understanding of what individuals' behaviors and perceptions are about the adoption of personal health records. However, these insights are descriptive and are not actionable to allow creating personal health records that will overcome the adoption problems identified by users. This study uses action design research to provide actionable knowledge regarding user perceptions and adoption and their application in the case of the digital allergy card. To achieve this, we conducted interviews with patients and physicians as part of the evaluation of the digital allergy card mock-up and the first prototype. As results, we provided some research proposals regarding the benefits of, levers for, and barriers to adoption of the digital allergy card that can be tested for several other personal health records.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"14 1","pages":"1-18"},"PeriodicalIF":6.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84326764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kahkashan Tabassum, Hadil Shaiba, Nada Ahmed Essa, Hafiza A. Elbadie
Medical sensors are implanted within the vital organs of human body to record and monitor the vital signs of pulse rate, heartbeat, electrocardiogram, body mass index, temperature, blood pressure, etc. to ensure their effective functioning. These are monitored to detect patient’s health from anywhere and at any time. The Wireless Sensor Networks are embedded in the form of Body Area Nets and are capable of sensing and storing the information on a digital device. Later this information could be inspected or even sent to a remotely located storage device specifically (server or any public or private cloud for analysis) so that a medical doctor can diagnose the present medical condition of a person or a patient. Such a facility would be of immense help in the event of an emergency such as a sudden disaster or natural calamity where communication is damaged, and the potential sources become inaccessible. The aim of this paper is to create a mobile platform using Mobile Ad hoc Network to support healthcare connectivity and treatment in emergency situations.
{"title":"An Efficient Emergency Patient Monitoring Based on Mobile Ad Hoc Networks","authors":"Kahkashan Tabassum, Hadil Shaiba, Nada Ahmed Essa, Hafiza A. Elbadie","doi":"10.4018/joeuc.289435","DOIUrl":"https://doi.org/10.4018/joeuc.289435","url":null,"abstract":"Medical sensors are implanted within the vital organs of human body to record and monitor the vital signs of pulse rate, heartbeat, electrocardiogram, body mass index, temperature, blood pressure, etc. to ensure their effective functioning. These are monitored to detect patient’s health from anywhere and at any time. The Wireless Sensor Networks are embedded in the form of Body Area Nets and are capable of sensing and storing the information on a digital device. Later this information could be inspected or even sent to a remotely located storage device specifically (server or any public or private cloud for analysis) so that a medical doctor can diagnose the present medical condition of a person or a patient. Such a facility would be of immense help in the event of an emergency such as a sudden disaster or natural calamity where communication is damaged, and the potential sources become inaccessible. The aim of this paper is to create a mobile platform using Mobile Ad hoc Network to support healthcare connectivity and treatment in emergency situations.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"433 1","pages":"1-12"},"PeriodicalIF":6.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78129472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the increasing ageing population, how can caregivers effectively provide long-term care services to meet the older adults’ needs with finite resources is emerging. In addressing this issue, nursing homes are striving to adopt smart health with the internet of things and artificial intelligence to improve the efficiency and sustainability of healthcare. This study proposed a two-echelon responsive health analytic model (EHAM) to deliver appropriate healthcare services in nursing homes under the Internet of Medical Things environment. A novel care plan revision index is developed using a dual fuzzy logic approach for multidimensional health assessments, followed by care plan modification using case-based reasoning. The findings reveal that EHAM can generate patient-centred long-term care solutions of high quality to maximise the satisfaction of nursing home residents and their families. Ultimately, sustainable healthcare services can be within the communities.
{"title":"A Two-Echelon Responsive Health Analytic Model for Triggering Care Plan Revision in Geriatric Care Management","authors":"Valerie Tang, H. Lam, Chun-Ho Wu, George T. S. Ho","doi":"10.4018/joeuc.289224","DOIUrl":"https://doi.org/10.4018/joeuc.289224","url":null,"abstract":"Due to the increasing ageing population, how can caregivers effectively provide long-term care services to meet the older adults’ needs with finite resources is emerging. In addressing this issue, nursing homes are striving to adopt smart health with the internet of things and artificial intelligence to improve the efficiency and sustainability of healthcare. This study proposed a two-echelon responsive health analytic model (EHAM) to deliver appropriate healthcare services in nursing homes under the Internet of Medical Things environment. A novel care plan revision index is developed using a dual fuzzy logic approach for multidimensional health assessments, followed by care plan modification using case-based reasoning. The findings reveal that EHAM can generate patient-centred long-term care solutions of high quality to maximise the satisfaction of nursing home residents and their families. Ultimately, sustainable healthcare services can be within the communities.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"69 1","pages":"1-29"},"PeriodicalIF":6.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86290693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Mobile Chronic Disease Management Service (MCDMS) is an emerging medical service for chronic disease prevention and treatment, but limited attention has been paid to the factors that affect users’ intention to adopt the service. Based on the unified theory of acceptance and use of technology 2 and the protection motivation theory, the authors built an MCDMS adoption model. The authors also verified the differentiating age effect on the service adoption intention from experiential distance perspective of the construal level theory. Empirical results showed that the young group focused more on the impact of effort expectancy, whereas the elderly group focused more on performance expectancy, imitating others, and perceived severity. Furthermore, the young group, however, focused more on the impact of perceived vulnerability, and offline medical habits showed no significant influence on either group’s intention to adopt, which were not consistent with the original hypotheses. The findings can aid MCDMS providers in selecting marketing strategies targeted toward different age groups.
{"title":"Factors Affecting Customer Intention to Adopt a Mobile Chronic Disease Management Service: Differentiating Age Effect From Experiential Distance Perspective","authors":"Zhangxiang Zhu, Yongmei Liu, Xianye Cao, Wei Dong","doi":"10.4018/joeuc.287910","DOIUrl":"https://doi.org/10.4018/joeuc.287910","url":null,"abstract":"The Mobile Chronic Disease Management Service (MCDMS) is an emerging medical service for chronic disease prevention and treatment, but limited attention has been paid to the factors that affect users’ intention to adopt the service. Based on the unified theory of acceptance and use of technology 2 and the protection motivation theory, the authors built an MCDMS adoption model. The authors also verified the differentiating age effect on the service adoption intention from experiential distance perspective of the construal level theory. Empirical results showed that the young group focused more on the impact of effort expectancy, whereas the elderly group focused more on performance expectancy, imitating others, and perceived severity. Furthermore, the young group, however, focused more on the impact of perceived vulnerability, and offline medical habits showed no significant influence on either group’s intention to adopt, which were not consistent with the original hypotheses. The findings can aid MCDMS providers in selecting marketing strategies targeted toward different age groups.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"8 1","pages":"1-23"},"PeriodicalIF":6.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82397883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patients’ emotions toward health IT can play an important role in explaining their usage of it. One form of health IT is self-managing care IT, such as activity trackers that can be used by chronic patients to adopt a healthy lifestyle. The goal of this study is to understand the factors that influence the arousal of emotions in chronic patients while using these tools. Past studies, in general, tend to emphasize how IT shapes emotions, underplaying the role of the individual user’s identity and, specifically, how central health is to the user’s self in shaping emotions. In this research, the authors argue that patients’ health identity centrality (i.e., the extent to which they consider health as central to their sense of self) can play an important role in forming their dependence on health IT by affecting their use of it directly and shaping their emotions around it.
{"title":"Chronic Patients' Emotions Toward Self-Managing Care IT: The Role of Health Centrality and Dependence on IT","authors":"Azadeh Savoli, Mamta Bhatt","doi":"10.4018/joeuc.288550","DOIUrl":"https://doi.org/10.4018/joeuc.288550","url":null,"abstract":"Patients’ emotions toward health IT can play an important role in explaining their usage of it. One form of health IT is self-managing care IT, such as activity trackers that can be used by chronic patients to adopt a healthy lifestyle. The goal of this study is to understand the factors that influence the arousal of emotions in chronic patients while using these tools. Past studies, in general, tend to emphasize how IT shapes emotions, underplaying the role of the individual user’s identity and, specifically, how central health is to the user’s self in shaping emotions. In this research, the authors argue that patients’ health identity centrality (i.e., the extent to which they consider health as central to their sense of self) can play an important role in forming their dependence on health IT by affecting their use of it directly and shaping their emotions around it.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"9 1","pages":"1-14"},"PeriodicalIF":6.5,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90490336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent years, many online network communities, such as Facebook, Twitter, Tik Tok, Weibo, etc., have developed rapidly and become the bridge connecting physical social world and virtual cyberspace. Online network communities store a large number of social relationships and interactions between users. How to analyze diffusion of influence from these massive social data has become a research hotspot in the applications of big data mining in online network communities. A core issue in the study of influence diffusion is influence maximization. Influence maximization refers to selecting a few nodes in a social network as seeds, so as to maximize influence spread of seed nodes under a specific diffusion model. Focusing on two core aspects of influence maximization, i.e., models and algorithms, this paper summarizes the main achievements of research on influence maximization in the computer field in recent years. Finally, this paper briefly discusses issues, challenges and future research directions in the research and application of influence maximization.
{"title":"Research and Analysis of Influence Maximization Techniques in Online Network Communities Based on Social Big Data","authors":"J. Hou, Shiyu Chen, Huaqiu Long, Qianmu Li","doi":"10.4018/joeuc.308466","DOIUrl":"https://doi.org/10.4018/joeuc.308466","url":null,"abstract":"Recent years, many online network communities, such as Facebook, Twitter, Tik Tok, Weibo, etc., have developed rapidly and become the bridge connecting physical social world and virtual cyberspace. Online network communities store a large number of social relationships and interactions between users. How to analyze diffusion of influence from these massive social data has become a research hotspot in the applications of big data mining in online network communities. A core issue in the study of influence diffusion is influence maximization. Influence maximization refers to selecting a few nodes in a social network as seeds, so as to maximize influence spread of seed nodes under a specific diffusion model. Focusing on two core aspects of influence maximization, i.e., models and algorithms, this paper summarizes the main achievements of research on influence maximization in the computer field in recent years. Finally, this paper briefly discusses issues, challenges and future research directions in the research and application of influence maximization.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"46 1","pages":"1-23"},"PeriodicalIF":6.5,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80426884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As artificial intelligence technique is widely used in the automatic driving system, the safety evaluation of automatic vehicles is considered to be the most important demand. Under this context, in this paper, an evaluation system, which is composed of several important evaluation projects is proposed based on big data. These indicators reflect the performance of the automatic driving system. Besides, the principle of the evaluation index and the data management scheme are explained. In terms of the evaluation projects, the online test and the offline test are included, when the former focuses on the function design that is as expected, while the latter aims to ensure the actual driving experience of the automatic driving system. The evaluated results provide optimization direction of the algorithm index. Furthermore, based on AI technology and user big data management, the system saves lots of test cost and guarantees algorithm performance and system stability.
{"title":"An Evaluation System Based on User Big Data Management and Artificial Intelligence for Automatic Vehicles","authors":"Shan-cheng Pei, Chao Ma, Haitao Zhu, Luo Kun","doi":"10.4018/joeuc.309135","DOIUrl":"https://doi.org/10.4018/joeuc.309135","url":null,"abstract":"As artificial intelligence technique is widely used in the automatic driving system, the safety evaluation of automatic vehicles is considered to be the most important demand. Under this context, in this paper, an evaluation system, which is composed of several important evaluation projects is proposed based on big data. These indicators reflect the performance of the automatic driving system. Besides, the principle of the evaluation index and the data management scheme are explained. In terms of the evaluation projects, the online test and the offline test are included, when the former focuses on the function design that is as expected, while the latter aims to ensure the actual driving experience of the automatic driving system. The evaluated results provide optimization direction of the algorithm index. Furthermore, based on AI technology and user big data management, the system saves lots of test cost and guarantees algorithm performance and system stability.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"16 1","pages":"1-21"},"PeriodicalIF":6.5,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82485734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on rural population return management, governance theory, and information technology theory, this paper analyzes the specific performance of rural areas in managing population return, and describes the overview, quantity, life status, and demographic characteristics of rural population return, as well as the current situation of rural population return management. A method of managing rural population return based on a rural population return management model constructed by a machine learning algorithm is designed. The empirical results show that the method designed in this paper is low-cost, fast, and highly accurate, and is well suited for improving and expanding the system for managing rural return flows. The research in this paper provides a reference for further promoting the transformation strategy of rural governance in the context of new urbanization.
{"title":"Analysis of the Application of Information Technology in the Management of Rural Population Return Based on the Era of Big Data","authors":"Zhengchao Cai","doi":"10.4018/joeuc.286171","DOIUrl":"https://doi.org/10.4018/joeuc.286171","url":null,"abstract":"Based on rural population return management, governance theory, and information technology theory, this paper analyzes the specific performance of rural areas in managing population return, and describes the overview, quantity, life status, and demographic characteristics of rural population return, as well as the current situation of rural population return management. A method of managing rural population return based on a rural population return management model constructed by a machine learning algorithm is designed. The empirical results show that the method designed in this paper is low-cost, fast, and highly accurate, and is well suited for improving and expanding the system for managing rural return flows. The research in this paper provides a reference for further promoting the transformation strategy of rural governance in the context of new urbanization.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"48 1","pages":"1-15"},"PeriodicalIF":6.5,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91252620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose is to solve the problems of sparse data information, low recommendation precision and recall rate and cold start of the current tourism personalized recommendation system. First, a context based personalized recommendation model (CPRM) is established by using the labeled-LDA (Labeled Latent Dirichlet Allocation) algorithm. The precision and recall of interest point recommendation are improved by mining the context information in unstructured text. Then, the interest point recommendation framework based on convolutional neural network (IPRC) is established. The semantic and emotional information in the comment text is extracted to identify user preferences, and the score of interest points in the target location is predicted combined with the influence factors of geographical location. Finally, real datasets are adopted to evaluate the recommendation precision and recall of the above two models and their performance of solving the cold start problem.
{"title":"Global Multi-Source Information Fusion Management and Deep Learning Optimization for Tourism","authors":"Xue Yu","doi":"10.4018/joeuc.294902","DOIUrl":"https://doi.org/10.4018/joeuc.294902","url":null,"abstract":"The purpose is to solve the problems of sparse data information, low recommendation precision and recall rate and cold start of the current tourism personalized recommendation system. First, a context based personalized recommendation model (CPRM) is established by using the labeled-LDA (Labeled Latent Dirichlet Allocation) algorithm. The precision and recall of interest point recommendation are improved by mining the context information in unstructured text. Then, the interest point recommendation framework based on convolutional neural network (IPRC) is established. The semantic and emotional information in the comment text is extracted to identify user preferences, and the score of interest points in the target location is predicted combined with the influence factors of geographical location. Finally, real datasets are adopted to evaluate the recommendation precision and recall of the above two models and their performance of solving the cold start problem.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":" ","pages":""},"PeriodicalIF":6.5,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45981721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study aims to establish a platform-based enterprise credit supervision mechanism, and combined with big data, accurately evaluate the credit assets of enterprises under the influence of social stability risk, and improve the ability of enterprises to deal with risks. Using descriptive statistical methods, the study shows that most local enterprises exist in the form of micro loans, which promotes the development of local economy to a certain extent, but it is a vicious cycle of economic development; The overall prediction accuracy of the single enterprise risk assessment model under the influence of social stability risk is 65%. Compared with the single algorithm, the prediction accuracy of the integrated algorithm model is significantly improved, and the prediction accuracy can reach 83.5%, the standard deviation of data prediction is small, and the stability of the model is high.
{"title":"Research on the Risk of Social Stability of Enterprise Credit Supervision Mechanism Based on Big Data","authors":"Tao Meng, Qi Li, Zheng Dong, Feifei Zhao","doi":"10.4018/joeuc.289223","DOIUrl":"https://doi.org/10.4018/joeuc.289223","url":null,"abstract":"The study aims to establish a platform-based enterprise credit supervision mechanism, and combined with big data, accurately evaluate the credit assets of enterprises under the influence of social stability risk, and improve the ability of enterprises to deal with risks. Using descriptive statistical methods, the study shows that most local enterprises exist in the form of micro loans, which promotes the development of local economy to a certain extent, but it is a vicious cycle of economic development; The overall prediction accuracy of the single enterprise risk assessment model under the influence of social stability risk is 65%. Compared with the single algorithm, the prediction accuracy of the integrated algorithm model is significantly improved, and the prediction accuracy can reach 83.5%, the standard deviation of data prediction is small, and the stability of the model is high.","PeriodicalId":49029,"journal":{"name":"Journal of Organizational and End User Computing","volume":"45 1","pages":"1-16"},"PeriodicalIF":6.5,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81025899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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