Abdul Hadi, Miftachul Huda, Novel Lyndon, Badlihisham Mohd Nasir
This article aims to investigate the professional and ethical negotiation on managing cyber conflict prevention towards misuse and exploitation of massive social media adoption from the higher learners' perspective. The qualitative approach from forum discussion was made among sixty higher education learners with the selection criteria. The data gathered were analyzed using thematic basis and compared with the findings from literature analysis from relevant peer reviewed journals. All were investigated, analyzed, extracted, and proposed into the professional and ethical negotiation for cyber conflict prevention. The finding revealed the principal value of digital professional skills enhancement in online practice consisting of digital competence skills, digital practice adaptability and stability, and digital technical application skills. Moreover, the digital ethical responsibility in online practice consists of communication and information accuracy enhancement, digital manner adaptability and transparency, accountability and security. We propose a dynamic discussion that encompasses enhancing ethical commitment on information accuracy for cyber conflict management; considering ethical manner on digital manner adaptability for cyber conflict arrangement; strengthening professional skills on transparency and security information quality for cyber conflict arrangement; and empowering professional negotiation accountability for cyber conflict management.
{"title":"Managing Professional-Ethical Negotiation for Cyber Conflict Prevention","authors":"Abdul Hadi, Miftachul Huda, Novel Lyndon, Badlihisham Mohd Nasir","doi":"10.4018/ijcbpl.344022","DOIUrl":"https://doi.org/10.4018/ijcbpl.344022","url":null,"abstract":"This article aims to investigate the professional and ethical negotiation on managing cyber conflict prevention towards misuse and exploitation of massive social media adoption from the higher learners' perspective. The qualitative approach from forum discussion was made among sixty higher education learners with the selection criteria. The data gathered were analyzed using thematic basis and compared with the findings from literature analysis from relevant peer reviewed journals. All were investigated, analyzed, extracted, and proposed into the professional and ethical negotiation for cyber conflict prevention. The finding revealed the principal value of digital professional skills enhancement in online practice consisting of digital competence skills, digital practice adaptability and stability, and digital technical application skills. Moreover, the digital ethical responsibility in online practice consists of communication and information accuracy enhancement, digital manner adaptability and transparency, accountability and security. We propose a dynamic discussion that encompasses enhancing ethical commitment on information accuracy for cyber conflict management; considering ethical manner on digital manner adaptability for cyber conflict arrangement; strengthening professional skills on transparency and security information quality for cyber conflict arrangement; and empowering professional negotiation accountability for cyber conflict management.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"54 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141108616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Okina Fitriani, Rozainee Khairudin, Wan Shahrazad Binti Wan Sulaiman, Laila Meiliyandrie Indah Wardani
The study's objective was to adapt and evaluate the tool to measure parenting self-efficacy in a way that was acceptable for Indonesia's unique cyberparenting context, taking into account local customs and the growing use of digital platforms in families. A total of 202 parents were gathered as study participants, and the TOPSE was meticulously adjusted to suit the Indonesian context. The results showed a four-factor scale structure consistent with Indonesian culture. The equipment's remarkable durability emphasizes the correctness of the procedure. This study is noteworthy for its creative approach to creating a personalized assessment tool and for emphasizing the urgent need for contextualized understanding of parental self-efficacy in the digital era. This is a significant improvement in the use and integration of psychological research to improve child development and parental involvement in online learning environments, according to professionals and parents alike. It also sets a new standard for research-based, culturally aware online parenting tools.
{"title":"Online TOPSE","authors":"Okina Fitriani, Rozainee Khairudin, Wan Shahrazad Binti Wan Sulaiman, Laila Meiliyandrie Indah Wardani","doi":"10.4018/ijcbpl.340389","DOIUrl":"https://doi.org/10.4018/ijcbpl.340389","url":null,"abstract":"The study's objective was to adapt and evaluate the tool to measure parenting self-efficacy in a way that was acceptable for Indonesia's unique cyberparenting context, taking into account local customs and the growing use of digital platforms in families. A total of 202 parents were gathered as study participants, and the TOPSE was meticulously adjusted to suit the Indonesian context. The results showed a four-factor scale structure consistent with Indonesian culture. The equipment's remarkable durability emphasizes the correctness of the procedure. This study is noteworthy for its creative approach to creating a personalized assessment tool and for emphasizing the urgent need for contextualized understanding of parental self-efficacy in the digital era. This is a significant improvement in the use and integration of psychological research to improve child development and parental involvement in online learning environments, according to professionals and parents alike. It also sets a new standard for research-based, culturally aware online parenting tools.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"55 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140251105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In today's scenario, we all are surrounded with technologies. As the world is shifting towards technology with great pace, and technology is also showing its efficiency and strength, we must appreciate its power. Now the world is shifting towards digitalization. So, it's also important to think that ideas should lie towards e-business to get full advantage of the system. The housing sector is one of the important fields which must get the support of the technological domains to overcome many challenges. So, there is a requirement to bring a system that can direct the work of renter and customer easier. To bring this idea into the real world, the author's team has come up with the idea of a rental house portal system. This portal is a web application which acts as an e-platform to search flats, apartments, property, etc., with scientific analysis-based data. In this system, the owner provides the details of flats with its features and using ML (machine learning) technology, the price of flat is calculated and the customer can check the availability of flat according to his/her requirement and to provide benefits to both parties. As the details of the flat are available on site, there is no need to explain the features of the house to the owner. Customers also have the benefits of searching for the desired house in less time and at a very reasonable price. Therefore, the rental house system is a very nice step towards the finding of flats online. The present manuscript has new thoughts of prediction of house rent price according to the features provided using statistical techniques and has come as one of the best platforms to search the property at a reasonable price.
{"title":"Examining Rental House Data With MRL Analysis","authors":"Rohit Rastogi","doi":"10.4018/ijcbpl.333474","DOIUrl":"https://doi.org/10.4018/ijcbpl.333474","url":null,"abstract":"In today's scenario, we all are surrounded with technologies. As the world is shifting towards technology with great pace, and technology is also showing its efficiency and strength, we must appreciate its power. Now the world is shifting towards digitalization. So, it's also important to think that ideas should lie towards e-business to get full advantage of the system. The housing sector is one of the important fields which must get the support of the technological domains to overcome many challenges. So, there is a requirement to bring a system that can direct the work of renter and customer easier. To bring this idea into the real world, the author's team has come up with the idea of a rental house portal system. This portal is a web application which acts as an e-platform to search flats, apartments, property, etc., with scientific analysis-based data. In this system, the owner provides the details of flats with its features and using ML (machine learning) technology, the price of flat is calculated and the customer can check the availability of flat according to his/her requirement and to provide benefits to both parties. As the details of the flat are available on site, there is no need to explain the features of the house to the owner. Customers also have the benefits of searching for the desired house in less time and at a very reasonable price. Therefore, the rental house system is a very nice step towards the finding of flats online. The present manuscript has new thoughts of prediction of house rent price according to the features provided using statistical techniques and has come as one of the best platforms to search the property at a reasonable price.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135136474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emotion detection from voice signals is needed for human-computer interaction (HCI), which is a difficult challenge. In the literature on speech emotion recognition, various well known speech analysis and classification methods have been used to extract emotions from signals. Deep learning strategies have recently been proposed as a workable alternative to conventional methods and discussed. Several recent studies have employed these methods to identify speech-based emotions. The review examines the databases used, the emotions collected, and the contributions to speech emotion recognition. The Speech Emotion Recognition Project was created by the research team. It recognizes human speech emotions. The research team developed the project using Python 3.6. RAVDEESS dataset was also used since it contained eight distinct emotions expressed by all speakers. The RAVDESS dataset, Python programming languages, and Pycharm as an IDE were all used by the author team.
{"title":"Emotion Detection via Voice and Speech Recognition","authors":"Rohit Rastogi, Tushar Anand, Shubham Kumar Sharma, Sarthak Panwar","doi":"10.4018/ijcbpl.333473","DOIUrl":"https://doi.org/10.4018/ijcbpl.333473","url":null,"abstract":"Emotion detection from voice signals is needed for human-computer interaction (HCI), which is a difficult challenge. In the literature on speech emotion recognition, various well known speech analysis and classification methods have been used to extract emotions from signals. Deep learning strategies have recently been proposed as a workable alternative to conventional methods and discussed. Several recent studies have employed these methods to identify speech-based emotions. The review examines the databases used, the emotions collected, and the contributions to speech emotion recognition. The Speech Emotion Recognition Project was created by the research team. It recognizes human speech emotions. The research team developed the project using Python 3.6. RAVDEESS dataset was also used since it contained eight distinct emotions expressed by all speakers. The RAVDESS dataset, Python programming languages, and Pycharm as an IDE were all used by the author team.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"122 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135136473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the current world, where diabetes is day by day becoming a very common and fatal disease, it's important that proper measures be taken in order to deal with it. As per the studies, early prediction of diabetes can lead to improved treatment to avoid further complications of the disease, and in order to do so efficiently, machine learning techniques are a great deal. In this study, various factors are taken into consideration, like blood pressure, pregnancy, glucose level, age, insulin, skin thickness, and diabetes pedigree function, which together can be useful to predict whether a person has a risk of developing diabetes or not and help society with the early diagnosis of diabetes. This model is trained using three main classification algorithms, namely support vector, random forest, and decision tree classifiers. The prediction results of each of the classifiers are summarized in this study, and the decision tree gives 78.89% accuracy.
{"title":"Integrating Machine Learning for Accurate Prediction of Early Diabetes","authors":"Kailash Chandra Bandhu, Ratnesh Litoriya, Aditi Rathore, Alefiya Safdari, Aditi Watt, Swati Vaidya, Mubeen Ahmed Khan","doi":"10.4018/ijcbpl.333157","DOIUrl":"https://doi.org/10.4018/ijcbpl.333157","url":null,"abstract":"In the current world, where diabetes is day by day becoming a very common and fatal disease, it's important that proper measures be taken in order to deal with it. As per the studies, early prediction of diabetes can lead to improved treatment to avoid further complications of the disease, and in order to do so efficiently, machine learning techniques are a great deal. In this study, various factors are taken into consideration, like blood pressure, pregnancy, glucose level, age, insulin, skin thickness, and diabetes pedigree function, which together can be useful to predict whether a person has a risk of developing diabetes or not and help society with the early diagnosis of diabetes. This model is trained using three main classification algorithms, namely support vector, random forest, and decision tree classifiers. The prediction results of each of the classifiers are summarized in this study, and the decision tree gives 78.89% accuracy.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"84 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135270654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cyberbullying may create psychological well-being problems and several coping strategies can augment the strength between cyberbullying and psychological well-being issues. The current study endeavors to investigate the association between cyberbullying victimization and feelings of loneliness among adolescents and also the role of coping strategies and emotional intelligence between cyberbullying and loneliness. Various coping strategies can alleviate the strength between cyberbullying victimization and loneliness. Through a survey questionnaire, data were collected from 451 adolescents in India. The findings reveal that coping strategies (seeking support, active coping, and avoidant coping) diminish loneliness and act as a mediator between cyberbullying victimization and loneliness. Seeking support and active coping strategies ease the loneliness resulting from cyberbullying victimization, while avoidant coping strategy is found to be non-significant. Emotional intelligence is found to alleviate the negative effects of cyberbullying on loneliness. The research can augment existing knowledge of cyberbullying and the mental well-being of adolescents concerning loneliness and emotional intelligence. The contributions of the study on the linkages among these variables and the psychological well-being concerns of adolescent victims of cyberbullying are highlighted.
{"title":"Association Between Cyberbullying Victimization and Loneliness Among Adolescents","authors":"Abhishek Shukla, Vikram Singh Chouhan","doi":"10.4018/ijcbpl.330586","DOIUrl":"https://doi.org/10.4018/ijcbpl.330586","url":null,"abstract":"Cyberbullying may create psychological well-being problems and several coping strategies can augment the strength between cyberbullying and psychological well-being issues. The current study endeavors to investigate the association between cyberbullying victimization and feelings of loneliness among adolescents and also the role of coping strategies and emotional intelligence between cyberbullying and loneliness. Various coping strategies can alleviate the strength between cyberbullying victimization and loneliness. Through a survey questionnaire, data were collected from 451 adolescents in India. The findings reveal that coping strategies (seeking support, active coping, and avoidant coping) diminish loneliness and act as a mediator between cyberbullying victimization and loneliness. Seeking support and active coping strategies ease the loneliness resulting from cyberbullying victimization, while avoidant coping strategy is found to be non-significant. Emotional intelligence is found to alleviate the negative effects of cyberbullying on loneliness. The research can augment existing knowledge of cyberbullying and the mental well-being of adolescents concerning loneliness and emotional intelligence. The contributions of the study on the linkages among these variables and the psychological well-being concerns of adolescent victims of cyberbullying are highlighted.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136130947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Newspapers are a rich informational source. A headline of an article sparks an interest in the reader. So, news providing agencies tend to create catchy headlines to attract the reader's attention onto them, and this is how sarcasm manages to find its way into news headlines. Sarcasm employs the use of words that carry opposite meaning with respect to what needs to be conveyed. This leads to the need of developing methods by which we can correctly predict whether a piece of text, or news for that matter, truthfully means what it says or is simply being sarcastic about it. Here, the authors have used a dataset containing 55,329 tuples consisting of news headlines from The Onion and the Huffington Post, which was taken from Kaggle, on which they applied feature extraction techniques such as Count Vectorizer, TF-IDF, Hashing Vectorizer, and Global Vectorizer (GloVe). Then they applied seven classifiers on the obtained dataset. The experimental results showed that the highest accuracies among the ML models were 81.39% for LR model with Count Vectorizer, 79.2% for LR model with TF-IDF Vectorizer, and 78% for SVM model with Count Vectorizer. They also obtained the best accuracy of 90.7% using the Bi-LSTM Deep Learning Model. They have trained the seven models and compared them based on their respective accuracies and F1-Scores.
{"title":"Comparison of Artificial Decision Techniques for Detection of Sarcastic News Headlines","authors":"Tarun Jain, Horesh Kumar, Payal Garg, Abhinav Pillai, Aditya Sinha, Vivek Kumar Verma","doi":"10.4018/ijcbpl.330131","DOIUrl":"https://doi.org/10.4018/ijcbpl.330131","url":null,"abstract":"Newspapers are a rich informational source. A headline of an article sparks an interest in the reader. So, news providing agencies tend to create catchy headlines to attract the reader's attention onto them, and this is how sarcasm manages to find its way into news headlines. Sarcasm employs the use of words that carry opposite meaning with respect to what needs to be conveyed. This leads to the need of developing methods by which we can correctly predict whether a piece of text, or news for that matter, truthfully means what it says or is simply being sarcastic about it. Here, the authors have used a dataset containing 55,329 tuples consisting of news headlines from The Onion and the Huffington Post, which was taken from Kaggle, on which they applied feature extraction techniques such as Count Vectorizer, TF-IDF, Hashing Vectorizer, and Global Vectorizer (GloVe). Then they applied seven classifiers on the obtained dataset. The experimental results showed that the highest accuracies among the ML models were 81.39% for LR model with Count Vectorizer, 79.2% for LR model with TF-IDF Vectorizer, and 78% for SVM model with Count Vectorizer. They also obtained the best accuracy of 90.7% using the Bi-LSTM Deep Learning Model. They have trained the seven models and compared them based on their respective accuracies and F1-Scores.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135879015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The relationship between the obsessive-compulsive disorder and the gaming disorder is investigated. A total of 345 undergraduates completed a survey that included demographic information, responses to the obsession-compulsive inventory-revised scale and the internet gaming disorder test. While initial findings showed the obsessive-compulsive disorder can predict the gaming disorder, deeper probe carried the potential of changing how this relationship is conceptualized. Only the checking subtype predicted the internet gaming disorder within the disordered gaming group. A corollary to this finding is that symptoms of the checking subtype of the compulsions component can predict having gaming disorder. Also, there was a significant strong association between a counting symptom and the internet gaming disorder scores of the disordered gaming group. This study indicated that the identified significant impact of the obsessive-compulsive disorder on the gaming disorder is rooted in shared mental functions by a gamer.
{"title":"The Relationship Between Obsessive-Compulsive Disorder and Gaming Disorder","authors":"Nazir Hawi, Maya Samaha","doi":"10.4018/ijcbpl.330133","DOIUrl":"https://doi.org/10.4018/ijcbpl.330133","url":null,"abstract":"The relationship between the obsessive-compulsive disorder and the gaming disorder is investigated. A total of 345 undergraduates completed a survey that included demographic information, responses to the obsession-compulsive inventory-revised scale and the internet gaming disorder test. While initial findings showed the obsessive-compulsive disorder can predict the gaming disorder, deeper probe carried the potential of changing how this relationship is conceptualized. Only the checking subtype predicted the internet gaming disorder within the disordered gaming group. A corollary to this finding is that symptoms of the checking subtype of the compulsions component can predict having gaming disorder. Also, there was a significant strong association between a counting symptom and the internet gaming disorder scores of the disordered gaming group. This study indicated that the identified significant impact of the obsessive-compulsive disorder on the gaming disorder is rooted in shared mental functions by a gamer.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Screen media technologies (SMTs) has become an essential part of human life and almost everybody, irrespective of their age group, uses one or the other screen media technologies. Increased dependency on SMTs is raising concerns over their ill effect on the psychological health of its users. The present work aims to study the impact of social media usage and laptop/computer on psychological and physical health. This is a cross-sectional study of the middle management employees of a major Indian telecom organization. The analyses were carried out using structural equation modelling (SEM) approach. Results suggested that neck pain is directly related to cognitive stress, somatic stress, and laptop/computer usage. Cognitive stress was indirectly related to Instagram and WhatsApp use. Behavioural stress had no direct or indirect relationship with social media or laptop/computer use. Using a laptop/computer is found to be the most critical factor contributing to neck pain in Indian middle-aged adults working in an office environment.
{"title":"Effect of Screen Media Technologies on Physical and Psychological Well Being in Middle Aged Adults","authors":"Priya Singh, Prabhas Bhardwaj, Sushil Kumar Sharma, Anil Kumar Agrawal","doi":"10.4018/ijcbpl.330132","DOIUrl":"https://doi.org/10.4018/ijcbpl.330132","url":null,"abstract":"Screen media technologies (SMTs) has become an essential part of human life and almost everybody, irrespective of their age group, uses one or the other screen media technologies. Increased dependency on SMTs is raising concerns over their ill effect on the psychological health of its users. The present work aims to study the impact of social media usage and laptop/computer on psychological and physical health. This is a cross-sectional study of the middle management employees of a major Indian telecom organization. The analyses were carried out using structural equation modelling (SEM) approach. Results suggested that neck pain is directly related to cognitive stress, somatic stress, and laptop/computer usage. Cognitive stress was indirectly related to Instagram and WhatsApp use. Behavioural stress had no direct or indirect relationship with social media or laptop/computer use. Using a laptop/computer is found to be the most critical factor contributing to neck pain in Indian middle-aged adults working in an office environment.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135981899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed at investigating the potential effect of emotional regulation on the medical staff in Algerian hospitals. A cross-sectional approach based on survey design was used in this study in order to answer the research questions. Data were collected by a questionnaire administered to a sample consisting of 153 randomly selected medical staff working at Algerian hospitals. The results revealed that the risk of COVID-19 transmission affected the emotional regulation of the medical staff in Algerian hospitals. It was also found that there were differences among participants in their emotional regulation that could be attributed to the variables of profession and workplace. The results highlighted the contributions of the positive and negative emotional regulation strategies, profession, and workplace as mediating variables in predicting the emotional regulation of medical staff. The results have important implications for how best to help the medical staff fulfill their emotions, thus being better qualified for the response to the COVID-19 pandemic.
{"title":"The Risk of COVID-19 Transmission","authors":"Yasmina Tichabet","doi":"10.4018/ijcbpl.329598","DOIUrl":"https://doi.org/10.4018/ijcbpl.329598","url":null,"abstract":"This study aimed at investigating the potential effect of emotional regulation on the medical staff in Algerian hospitals. A cross-sectional approach based on survey design was used in this study in order to answer the research questions. Data were collected by a questionnaire administered to a sample consisting of 153 randomly selected medical staff working at Algerian hospitals. The results revealed that the risk of COVID-19 transmission affected the emotional regulation of the medical staff in Algerian hospitals. It was also found that there were differences among participants in their emotional regulation that could be attributed to the variables of profession and workplace. The results highlighted the contributions of the positive and negative emotional regulation strategies, profession, and workplace as mediating variables in predicting the emotional regulation of medical staff. The results have important implications for how best to help the medical staff fulfill their emotions, thus being better qualified for the response to the COVID-19 pandemic.","PeriodicalId":38296,"journal":{"name":"International Journal of Cyber Behavior, Psychology and Learning","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83445807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：