Human Behavior and Emerging Technologies最新文献

{"title":"Behavioral Intention to Protect Customer Data in Indonesian Microenterprises: Integrating PMT and TPB Perspectives","authors":"Achmad Nizar Hidayanto,&nbsp;Belia Rida Syifa Fauzia,&nbsp;Zaenal Abidin,&nbsp;Kongkiti Phusavat,&nbsp;Binshan Lin","doi":"10.1155/hbe2/6665337","DOIUrl":"https://doi.org/10.1155/hbe2/6665337","url":null,"abstract":"<p>Microenterprises increasingly rely on social media platforms to promote products, communicate with customers, and manage transactions. However, in informal digital business environments, customer data may be exposed through everyday practices such as posting testimonials, order screenshots, or delivery information containing personal details. Previous studies have largely focused on organizational cybersecurity controls or individuals′ protection of their own data, leaving limited understanding of how microentrepreneurs decide to protect customers′ data. This study examines the behavioral drivers of customer data protection intention among Instagram-based microentrepreneurs in Indonesia by integrating protection motivation theory (PMT) and the theory of planned behavior (TPB). Data were collected through a survey of 427 microentrepreneurs and analyzed using partial least squares structural equation modeling. The results show that attitude is the strongest predictor of behavioral intention, followed by perceived vulnerability, response efficacy, perceived severity, and response cost. Response cost has a significant negative effect, whereas the other significant predictors have positive effects. Self-efficacy, subjective norm, and knowledge do not significantly influence behavioral intention. The model explains 71.5% of the variance in behavioral intention and demonstrates satisfactory predictive relevance. These findings extend behavioral cybersecurity research to third-party data protection by showing that, when entrepreneurs are responsible for protecting customers′ rather than their own data, threat appraisal and behavioral evaluation remain salient, whereas capability- and norm-related factors appear less influential. This pattern suggests that established cybersecurity motivations may operate differently when the decision maker and the primary protected party are not the same. The study also suggests that awareness alone may be insufficient unless it is translated into practical and context-specific guidance. The findings provide implications for regulators, social media platforms, and digital literacy providers seeking to strengthen microentrepreneurs′ intentions and capacity to engage in responsible customer data protection practices.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/6665337","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nexus of User and Firm Factors to Promote Cybersecurity Practices and Proactive Behavior Through a Novel SEM-Machine Learning Approach","authors":"Rao Faizan Ali,&nbsp;Kashif Ali,&nbsp;Khalifah As Almerri,&nbsp;Nosheen Malik,&nbsp;Ayed Alwadain,&nbsp;Suliman Mohamed Fati","doi":"10.1155/hbe2/2009721","DOIUrl":"https://doi.org/10.1155/hbe2/2009721","url":null,"abstract":"<p>In Industry 5.0 (I5.0), cybersecurity is a strategic priority for manufacturing firms. In the I5.0 context, human–machine collaboration requires proactive employee behavior to anticipate and mitigate cyber threats. However, existing literature largely examines user or technical factors in isolation and overlooks the joint optimization of social and technical factors. To address these, this study investigates the user-level social and firm-level technical factors to explain the cybersecurity awareness, compliance, and employee proactive behavior in the I5.0 context. Based on the socio-technical systems (STS) theory, a concept framework has been developed. A survey-based quantitative method was applied to collect data from 198 employees working in Malaysian manufacturing enterprises. A dual-stage analytical technique was used, combining partial least squares structural equation modeling (PLS-SEM) with machine learning (ML). The originality of this technique stems from the combination of PLS-SEM explanatory power with ML prediction capabilities. The PLS-SEM findings affirmed that both user-level social factors and firm-level technical factors positively drive cybersecurity compliance. Surprisingly, the relationship between cybersecurity awareness and compliance was positive but insignificant. ML outcomes highlight that user and firm factors predict (85.79%) employee proactive behavior. It reinforces the robustness and predictive capability of the integrated framework. This study provides a novel explanation of social and technical factors to employee proactive behavior through cybersecurity awareness and compliance in I5.0. The study findings provide both theoretical contributions, particularly in the advancement of STS theory, as well as practical implications for managers and policymakers seeking to improve cybersecurity frameworks.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/2009721","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring ChatGPT Adoption in Higher Education: The Mediating Roles of Information Accuracy and Learning Value in the UTAUT Framework","authors":"Rasheda Akter Rupa,&nbsp;Afruza Haque,&nbsp;Faharia Sultana,&nbsp;Afrin Sultana,&nbsp;Rana Al Mosharrafa,&nbsp;Md Al Amin","doi":"10.1155/hbe2/8847712","DOIUrl":"https://doi.org/10.1155/hbe2/8847712","url":null,"abstract":"<p>The widespread use of ChatGPT across sectors underscores the need to assess the factors that drive students to use it for learning. Therefore, this study investigates the factors influencing the adoption intentions for ChatGPT in academic settings by applying the Unified Theory of Acceptance and Use of Technology. Integrating information accuracy and learning value as dual mediators, the research examines how performance expectancy, effort expectancy, social influence, and facilitating conditions shape users′ behavioral intentions. Responses from 619 university students have been analyzed using PLS-SEM. The findings reveal that, except for effort expectancy, all the variables significantly impact students′ behavioral intentions regarding the uptake of ChatGPT. Moreover, the study outcomes also reveal that information accuracy and learning value are the significant mediating factors in the relationships among performance expectancy (partial), effort expectancy (full), social influence (partial), facilitating conditions (partial), and students′ use intentions. This study substantially contributes to the ChatGPT adoption literature through mediating information accuracy and learning value, highlighting their significance in driving students′ adoption intentions. Moreover, this study provides insights for academicians, administrators, and policymakers, encouraging the adoption and ethical use of ChatGPT in higher education, with an emphasis on content reliability and educational benefits in developing countries.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/8847712","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validated Instruments for Problematic Digital Media Use in Elementary School Children: A Systematic Literature and Network Analysis","authors":"Triana Lestari,&nbsp;Ratna Jatnika,&nbsp;Hendriati Agustiani,&nbsp;Fredrick Dermawan Purba,&nbsp;Muh. Asriadi AM","doi":"10.1155/hbe2/7571166","DOIUrl":"https://doi.org/10.1155/hbe2/7571166","url":null,"abstract":"<p>The term “brain rot” is increasingly used to describe concerns about excessive consumption of low-quality digital content and its cognitive, behavioral, and educational effects in children. However, brain rot is not an established clinical construct, and no validated instruments have been specifically designed to measure it. Existing studies instead use related constructs, such as digital addiction, problematic internet use, gaming disorder, smartphone addiction, and problematic media use. This study is aimed at evaluating validated instruments assessing problematic digital media use among children aged 6–13 years and to map broader research trends using a Systematic Literature and Network Analysis (SLNA). A systematic review was conducted following PRISMA guidelines using four databases: Scopus, APA PsycInfo, ERIC, and PubMed, covering studies published from 2015 to 2025. Bibliometric analysis using VOSviewer examined keyword co-occurrence, thematic evolution, and research gaps. Study quality was assessed using modified COSMIN criteria. A total of 24 studies involving 17,991 participants were included. Results showed that instruments for children aged 9–12 years had strong psychometric properties, including excellent reliability (Cronbach′s <i>α</i> = 0.88–0.96), strong construct validity, and adequate stability over time. The Digital Addiction Scale for Children (DASC) was the most comprehensive instrument, whereas the Internet Addiction Test-6 (IAT-6) was effective for brief screening. In contrast, very limited evidence was found for children aged 6–8 years, showing an important measurement gap. Future research should prioritize age-appropriate instruments for younger children and improve clinical use of existing tools.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/7571166","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Benefiting From Video Chat Limits Negative Experiences","authors":"Lauren E. Knox,&nbsp;Jean E. Fox Tree","doi":"10.1155/hbe2/8366678","DOIUrl":"https://doi.org/10.1155/hbe2/8366678","url":null,"abstract":"<p>Previous research on video chat experiences typically center the negative experiences of users. However, there are many benefits as well, particularly for people who may not be able to participate without video chat. We tested how highlighting the benefits of video chat affected college student perceptions and experiences with these platforms. We also examined how explicitly benefiting from video chat platform use related to video chat perceptions and experiences. We did not find evidence supporting the hypothesis that highlighting the benefits of video chat changes perceptions or experiences with these platforms. However, we did find that identifying with two or more groups who benefit from video chat platform use (e.g., people with disabilities, people with long commute times) was associated with better video chat experiences (i.e., less Zoom fatigue, greater social presence, more conversation enjoyment) compared with identifying with one group or fewer.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/8366678","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence Acceptance in Akan Literacy Among University Students: Does AI Guilt Affect Behavioral Intentions and Actual Usage?","authors":"Love Kafui Mensah,&nbsp;Fred Oware Gyimah,&nbsp;Daniel Bafour-Koduah,&nbsp;Abdul-Rahman Mutawakil,&nbsp;Ernest Nyamekye","doi":"10.1155/hbe2/8086861","DOIUrl":"https://doi.org/10.1155/hbe2/8086861","url":null,"abstract":"<p>Developments in recent AI models such as ChatGPT, Claude, and Khaya AI have demonstrated enhanced capacity for processing and generating Akan language data, opening new pathways for Akan language learning, teaching, translation and digital content generation. However, students′ practical use of AI may be hampered by feelings of guilt associated with reliance on AI for academic learning. This study, therefore, examined Akan language students′ acceptance and use of AI tools for learning and how AI guilt (AIG) influences intention and usage. It was underpinned by the Technology Acceptance Model (TAM). A cross-sectional survey design was employed for this investigation. Using a census method, data were collected from 150 Akan language students. Partial least squares structural equation modeling was used to analyze the data. The results revealed that perceived usefulness (PU) of AI influenced students′ AI use intentions (BI). BI was also found to be a statistically significant predictor of actual use of AI (AU). Surprisingly, PEOU did not significantly predict students′ AI use intentions. In addition, AIG did not moderate the relationships between BI and AU, PEOU and BI and, PU and BI. We, therefore, recommend that policymakers should focus on training students on the responsible use of AI tools while considering ethical issues and imparting knowledge about how valuable it is to employ AI tools in learning.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/8086861","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gaming Behavior Associations Between Sleep, Occupational Balance, and Self-Regulation Among Students of Allied and Healthcare Professions in Karnataka, India","authors":"B. Deepak,&nbsp;Vinita A. Acharya,&nbsp;R. Vani Lakshmi,&nbsp;Deena Dimple Dsouza","doi":"10.1155/hbe2/6314594","DOIUrl":"https://doi.org/10.1155/hbe2/6314594","url":null,"abstract":"<p>The increasing popularity of gaming among healthcare professionals has raised concerns about its potential influence on health and well-being. Despite the growing number of international studies, there is limited evidence among students of allied and healthcare professions in India. This study examined the correlations between gaming behavior, sleep quality, self-regulation, and occupational balance among 210 undergraduate students of allied and healthcare professions in India, using a cross-sectional design. Descriptive statistics and Spearman′s rank-order correlations were used for data analysis. No significant correlations were found between gaming behavior and sleep quality, self-regulation, or occupational balance. However, a significant negative correlation was observed between occupational balance and sleep quality (<i>ρ</i> = −0.196, <i>p</i> = 0.004), indicating that better occupational balance is associated with improved sleep quality. Gaming behavior showed nonsignificant trends toward poor sleep and occupational balance. Gaming was a balanced leisure activity among this population.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/6314594","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148849171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human Behavioral Adaptation to Artificial Intelligence Across Emerging Industries: A Multisector Analysis","authors":"Neelu Jain,&nbsp;Amit Verma,&nbsp;Preeti Singh,&nbsp;Prabhjot Kaur,&nbsp;Shalini Yadav","doi":"10.1155/hbe2/8413791","DOIUrl":"https://doi.org/10.1155/hbe2/8413791","url":null,"abstract":"<p>Sustainable development demands a total transformation of traditional industries made possible through artificial Intelligence (AI), which also creates new business methods and operational systems. The research examines AI′s effects on productive manufacturing, healthcare services finance business, renewable energy production, and the creative industry. Modern business environments drive organizations to deploy AI as an automated system for repetitive work alongside analytic and decisional enhancement as well as cost reduction. Medical technology leveraging AI brings significant improvements to modern healthcare operations, particularly with its diagnostic capabilities and personalized treatment plans, as well as its ability to manage patients remotely. These algorithms run on AI enablement to safeguard financial institutions from fraud, reduce their business risks and provide real-time and data-driven support to their clients. When combined with AI′s ability to optimize renewable energy production, the system can deliver high accuracy in forecasting energy demand. The AI system′s ability to optimize renewable energy production contributes to the high accuracy of energy demand forecasting. In the technological era, it is essential that the industries that lead the way incorporate cognitive technologies and data analysis, which is powered by AI, to stay at the forefront of the game. There are several challenges arising from the swift adoption of AI as data protection issues and ethical issues clash yet need to be addressed alongside regulatory considerations and job redesign. These should be addressed appropriately to ensure a fair global development in the context of upholding the principles of society. Analysis is done to understand the potential applications of AI in deployment management, resource enhancement, and environmentally friendly operations. Organizations obtain successful AI implementation through the identification of business transformation opportunities and solutions to implementation issues. Companies maintain social responsibility alongside innovative practices by developing equitable measures between standards of ethics and law alongside technological progress.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/8413791","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Nostalgia to Noir: AI and the Genre Fluidity in Ruskin Bond’s Works","authors":"Padmasri Bodi,&nbsp;Prasanna Lakshmi Narra","doi":"10.1155/hbe2/1477133","DOIUrl":"https://doi.org/10.1155/hbe2/1477133","url":null,"abstract":"<p>The rapid advancement of artificial intelligence (AI) in literature has sparked ethical debates on creativity, authorship, and human interpretation. AI-driven tools increasingly shape literary analysis, creative writing, and textual interpretation, raising concerns about bias, loss of emotional depth, and ethical governance. As AI becomes more embedded in humanities research, a responsible framework for ethical AI development is essential. This paper explores the intersection of Buddhist philosophy, scientific inquiry and AI ethics in literature, proposing that Buddhist principles mindfulness (sati), wisdom (prajna) and ethical conduct (sila) offer a valuable foundation for addressing these challenges. Drawing from Buddhist epistemology, this study examines how scientific inquiry and AI ethics benefit from mindfulness-based decision-making, emphasizing human oversight in AI-driven literary analysis. It explores Buddhist thought’s role in fostering responsible AI development, compassion-driven technological progress, and ensuring AI serves as an augmentation tool rather than a replacement. Additionally, it analyzes Ruskin Bond’s works through a Buddhist lens, highlighting his meditative storytelling, ecological consciousness and themes of mindfulness, impermanence and simplicity. Bond’s evocative prose, capturing the transient beauty of nature and human experience, raises a critical question: Can AI truly replicate the mindfulness inherent in human literary expression? By integrating literature, philosophy and AI ethics, this study argues that Buddhist ethical principles provide a guiding framework for AI governance in humanities research. It advocates for a balanced AI–human collaboration one that respects cultural, ethical and intellectual literary traditions while leveraging AI’s analytical strengths.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/1477133","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence (AI) in Forensic Psychology: An Umbrella Review of Potentials and Pitfalls","authors":"Ysabel A. Guevarra,&nbsp;Eva M. Hisham,&nbsp;Andree Hartanto","doi":"10.1155/hbe2/6547352","DOIUrl":"https://doi.org/10.1155/hbe2/6547352","url":null,"abstract":"<p>Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web of Science. Across the reviewed literature, our umbrella review suggests that AI is positioned as offering several potential benefits for forensic psychological work, including improved predictive accuracy, real-time threat monitoring, more optimised resource allocation, enhanced analysis of complex behavioural data and more objective decision-making. At the same time, the present review highlights persistent pitfalls that may constrain the reliability and defensibility of current applications. These include the reinforcement of bias and disparities, limited transparency and explainability, over-reliance that may undermine human judgement, data constraints and overfitting, ethical and legal risks and substantial implementation and computational demands that may inhibit real-world application. Overall, this review underscores the need for rigorous safeguards to ensure that AI enhances rather than compromises forensic decision-making.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/6547352","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}