Pub Date : 2024-12-01DOI: 10.1016/j.chbr.2024.100525
Yvonne M. Fromm , Dirk Ifenthaler
Adaptive learning environments (ALE) provide great potential for personalizing and supporting learning processes in continuing education (CE). However, valid frameworks for designing ALE for CE have been missing so far. For example, user-centered and empirically-based guidelines for selecting indicators (i.e., information about learners and their contexts that should be collected and analyzed by ALE) and interventions for personalizing and supporting learning processes have not been established yet. Therefore, this paper aims to develop a framework of indicators and interventions for ALE for CE by investigating the perspectives of different stakeholders (i.e., learners, CE specialists, and educational technology specialists). We first conducted an interview study (N = 37) to identify indicators for ALE for CE. Subsequently, we conducted focus group interviews (N = 19) and an online survey (N = 72) to specify and evaluate possible interventions. Several indicators related to internal (e.g., prior knowledge) and external (e.g., time available for learning) conditions of learning as well as corresponding interventions (e.g., adaptation of the general difficulty level and thematic focus, recommendation of timely suitable learning resources) were identified. We developed a framework classifying interventions based on indicators and adaptivity type and providing evaluations of learners’ willingness to use these interventions, perceived learning support, and implementation effort. This framework can be used by researchers, system designers, as well as CE and educational technology specialists to design and implement user-centered and trustworthy ALE for CE.
{"title":"Designing adaptive learning environments for continuing education: Stakeholders’ perspectives on indicators and interventions","authors":"Yvonne M. Fromm , Dirk Ifenthaler","doi":"10.1016/j.chbr.2024.100525","DOIUrl":"10.1016/j.chbr.2024.100525","url":null,"abstract":"<div><div>Adaptive learning environments (ALE) provide great potential for personalizing and supporting learning processes in continuing education (CE). However, valid frameworks for designing ALE for CE have been missing so far. For example, user-centered and empirically-based guidelines for selecting indicators (i.e., information about learners and their contexts that should be collected and analyzed by ALE) and interventions for personalizing and supporting learning processes have not been established yet. Therefore, this paper aims to develop a framework of indicators and interventions for ALE for CE by investigating the perspectives of different stakeholders (i.e., learners, CE specialists, and educational technology specialists). We first conducted an interview study (<em>N</em> = 37) to identify indicators for ALE for CE. Subsequently, we conducted focus group interviews (<em>N</em> = 19) and an online survey (<em>N</em> = 72) to specify and evaluate possible interventions. Several indicators related to internal (e.g., prior knowledge) and external (e.g., time available for learning) conditions of learning as well as corresponding interventions (e.g., adaptation of the general difficulty level and thematic focus, recommendation of timely suitable learning resources) were identified. We developed a framework classifying interventions based on indicators and adaptivity type and providing evaluations of learners’ willingness to use these interventions, perceived learning support, and implementation effort. This framework can be used by researchers, system designers, as well as CE and educational technology specialists to design and implement user-centered and trustworthy ALE for CE.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100525"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743197","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}
Pub Date : 2024-12-01DOI: 10.1016/j.chbr.2024.100538
Alexander Diel , Tania Lalgi , Isabel Carolin Schröter , Karl F. MacDorman , Martin Teufel , Alexander Bäuerle
Deepfakes are AI-generated media designed to look real, often with the intent to deceive. Deepfakes threaten public and personal safety by facilitating disinformation, propaganda, and identity theft. Though research has been conducted on human performance in deepfake detection, the results have not yet been synthesized. This systematic review and meta-analysis investigates human deepfake detection accuracy. Searches in PubMed, ScienceGov, JSTOR, Google Scholar, and paper references, conducted in June and October 2024, identified empirical studies measuring human detection of high-quality deepfakes. After pooling accuracy, odds-ratio, and sensitivity (d') effect sizes (k = 137 effects) from 56 papers involving 86,155 participants, we analyzed 1) overall deepfake detection performance, 2) performance across stimulus types (audio, image, text, and video), and 3) the effects of detection-improvement strategies. Overall deepfake detection rates (sensitivity) were not significantly above chance because 95% confidence intervals crossed 50%. Total deepfake detection accuracy was 55.54% (95% CI [48.87, 62.10], k = 67). For audio, accuracy was 62.08% [38.23, 83.18], k = 8; for images, 53.16% [42.12, 64.64], k = 18; for text, 52.00% [37.42, 65.88], k = 15; and for video, 57.31% [47.80, 66.57], k = 26. Odds ratios were 0.64 [0.52, 0.79], k = 62, indicating 39% detection accuracy, below chance (audio 45%, image 35%, text 40%, video 40%). Moreover, d' values show no significant difference from chance. However, strategies like feedback training, AI support, and deepfake caricaturization improved detection performance above chance levels (65.14% [55.21, 74.46], k = 15), especially for video stimuli.
{"title":"Human performance in detecting deepfakes: A systematic review and meta-analysis of 56 papers","authors":"Alexander Diel , Tania Lalgi , Isabel Carolin Schröter , Karl F. MacDorman , Martin Teufel , Alexander Bäuerle","doi":"10.1016/j.chbr.2024.100538","DOIUrl":"10.1016/j.chbr.2024.100538","url":null,"abstract":"<div><div><em>Deepfakes</em> are AI-generated media designed to look real, often with the intent to deceive. Deepfakes threaten public and personal safety by facilitating disinformation, propaganda, and identity theft. Though research has been conducted on human performance in deepfake detection, the results have not yet been synthesized. This systematic review and meta-analysis investigates human deepfake detection accuracy. Searches in PubMed, ScienceGov, JSTOR, Google Scholar, and paper references, conducted in June and October 2024, identified empirical studies measuring human detection of high-quality deepfakes. After pooling accuracy, odds-ratio, and sensitivity (<em>d'</em>) effect sizes (<em>k</em> = 137 effects) from 56 papers involving 86,155 participants, we analyzed 1) overall deepfake detection performance, 2) performance across stimulus types (audio, image, text, and video), and 3) the effects of detection-improvement strategies. Overall deepfake detection rates (<em>sensitivity</em>) were not significantly above chance because 95% confidence intervals crossed 50%. Total deepfake detection accuracy was 55.54% (95% CI [48.87, 62.10], <em>k</em> = 67). For audio, accuracy was 62.08% [38.23, 83.18], <em>k</em> = 8; for images, 53.16% [42.12, 64.64], <em>k</em> = 18; for text, 52.00% [37.42, 65.88], <em>k</em> = 15; and for video, 57.31% [47.80, 66.57], <em>k</em> = 26. Odds ratios were 0.64 [0.52, 0.79], <em>k</em> = 62, indicating 39% detection accuracy, below chance (audio 45%, image 35%, text 40%, video 40%). Moreover, <em>d'</em> values show no significant difference from chance. However, strategies like feedback training, AI support, and deepfake caricaturization improved detection performance above chance levels (65.14% [55.21, 74.46], <em>k</em> = 15), especially for video stimuli.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100538"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757509","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}
Pub Date : 2024-12-01DOI: 10.1016/j.chbr.2024.100535
Andree Hartanto, K.T.A.Sandeeshwara Kasturiratna
Background
The integration of loot boxes has emerged as a significant factor contributing to the increasing revenue in the video gaming industry. However, this integration has also led to widespread engagement in risky loot box consumption. To understand the mechanism that drives and sustains such maladaptive behavior, we propose the FoMO-Driven Loot Boxes Spiral Hypothesis – positing that fear of missing out (FoMO) not only triggers initial engagement in risky loot box consumption but also perpetuates a self-reinforcing cycle, where such engagement intensifies subsequent FoMO, leading to further risky loot box consumption.
Method and results
We conducted a 13-week longitudinal study of 252 college students with weekly data collection to examine the bidirectional relation. Using random-intercept cross-lagged panel models, we found significant small-to-moderate cross-lagged effects from FoMO to risky loot box consumption and significant moderate-to-large cross-lagged effects from risky loot box consumption to FoMO.
Implications
Our findings support FoMO as an important trigger for initiating risky loot box consumption. Moreover, once players start engaging with risky loot box consumption, they often find themselves trapped in a reinforcing cycle of FoMO and risky loot box consumption. These findings contributes to our understanding of problematic behavior in digital gaming and have implications for the development of targeted interventions and policies aimed at reducing risky loot box consumption.
{"title":"Longitudinal bidirectional relation between fear of missing out and risky loot box consumption: Evidence for FoMO-Driven loot boxes spiral hypothesis","authors":"Andree Hartanto, K.T.A.Sandeeshwara Kasturiratna","doi":"10.1016/j.chbr.2024.100535","DOIUrl":"10.1016/j.chbr.2024.100535","url":null,"abstract":"<div><h3>Background</h3><div>The integration of loot boxes has emerged as a significant factor contributing to the increasing revenue in the video gaming industry. However, this integration has also led to widespread engagement in risky loot box consumption. To understand the mechanism that drives and sustains such maladaptive behavior, we propose the FoMO-Driven Loot Boxes Spiral Hypothesis – positing that fear of missing out (FoMO) not only triggers initial engagement in risky loot box consumption but also perpetuates a self-reinforcing cycle, where such engagement intensifies subsequent FoMO, leading to further risky loot box consumption.</div></div><div><h3>Method and results</h3><div>We conducted a 13-week longitudinal study of 252 college students with weekly data collection to examine the bidirectional relation. Using random-intercept cross-lagged panel models, we found significant small-to-moderate cross-lagged effects from FoMO to risky loot box consumption and significant moderate-to-large cross-lagged effects from risky loot box consumption to FoMO.</div></div><div><h3>Implications</h3><div>Our findings support FoMO as an important trigger for initiating risky loot box consumption. Moreover, once players start engaging with risky loot box consumption, they often find themselves trapped in a reinforcing cycle of FoMO and risky loot box consumption. These findings contributes to our understanding of problematic behavior in digital gaming and have implications for the development of targeted interventions and policies aimed at reducing risky loot box consumption.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100535"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743198","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}
Pub Date : 2024-12-01DOI: 10.1016/j.chbr.2024.100546
Nirit Yuviler-Gavish, Rotem Halutz, Liad Neta
With the advent of large language models, a spotlight has been turned onto chatbots. Utilizing the Technology Acceptance Model (TAM), we investigated whether whatsappization of the chatbot – making the conversation more resemble a WhatsApp conversation – improves Perceived Ease of Use, Perceived Usefulness, and Attitude Toward Using. In today's world, given that WhatsApp conversations sometimes substitute for face-to-face communication, borrowing this format for use in another framework was reasonable. Participants, assigned a drive-sharing task, communicated with a textual chatbot via WhatsApp and had to decide whether to take a lift to college with a driver suggested by the chatbot. Whatsappization of the chatbot was done in two ways: Through a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing …” (Indicators versus No Indicators). The research was full factorial, with a 2 by 2 design. 120 participants were randomly assigned to one of the four groups, with 30 participants in each group. The results, using one-way ANOVAs, demonstrated that the interaction with the chatbot was longer under the Dialog compared to the No Dialog condition, and participants in the Dialog condition had a lower rating for Attitude Toward Using. In addition, both for the Perceived Ease of Use and Perceived Usefulness constructs, participants' ratings were lower under the Indicators compared to the No Indicators condition. Our findings signal that whatsappization of the chatbot decreased user's motivation to use the system. Hence, the current study suggests that a non-human agent should not try to imitate a WhatsApp conversation.
{"title":"How whatsappization of the chatbot affects perceived ease of use, perceived usefulness, and attitude toward using in a drive-sharing task","authors":"Nirit Yuviler-Gavish, Rotem Halutz, Liad Neta","doi":"10.1016/j.chbr.2024.100546","DOIUrl":"10.1016/j.chbr.2024.100546","url":null,"abstract":"<div><div>With the advent of large language models, a spotlight has been turned onto chatbots. Utilizing the Technology Acceptance Model (TAM), we investigated whether whatsappization of the chatbot – making the conversation more resemble a WhatsApp conversation – improves Perceived Ease of Use, Perceived Usefulness, and Attitude Toward Using. In today's world, given that WhatsApp conversations sometimes substitute for face-to-face communication, borrowing this format for use in another framework was reasonable. Participants, assigned a drive-sharing task, communicated with a textual chatbot via WhatsApp and had to decide whether to take a lift to college with a driver suggested by the chatbot. Whatsappization of the chatbot was done in two ways: Through a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing …” (Indicators versus No Indicators). The research was full factorial, with a 2 by 2 design. 120 participants were randomly assigned to one of the four groups, with 30 participants in each group. The results, using one-way ANOVAs, demonstrated that the interaction with the chatbot was longer under the Dialog compared to the No Dialog condition, and participants in the Dialog condition had a lower rating for Attitude Toward Using. In addition, both for the Perceived Ease of Use and Perceived Usefulness constructs, participants' ratings were lower under the Indicators compared to the No Indicators condition. Our findings signal that whatsappization of the chatbot decreased user's motivation to use the system. Hence, the current study suggests that a non-human agent should not try to imitate a WhatsApp conversation.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100546"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759666","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}
Pub Date : 2024-12-01DOI: 10.1016/j.chbr.2024.100540
Tuğçe Özbek , Martin Daumiller , Aida Roshany-Tabrizi , Tobias Mömke , Ingo Kollar
Computer-supported peer feedback offers great potential to enhance students' learning. Yet, students sometimes do not use computer-supported peer feedback opportunities, which partially can be the result of low technology acceptance. The UTAUT-model specifies performance expectancy, effort expectancy, and facilitating conditions as decisive factors for the intention to use a technology. From a motivational perspective, however, it can be expected that also students' achievement goals have an impact on the intention to use an online peer feedback tool. Therefore, we investigated the effects of learning approach, appearance approach, appearance avoidance, work avoidance and relational goals (besides performance expectancy, effort expectancy and facilitating conditions) on 155 computer science students' intentions and actual use of an online peer feedback tool and their performance in an end-of-course exam. Results of path modelling the longitudinal, student and log-data informed data showed that students' intentions predicted actual use, which predicted exam performance. Learning approach goals positively predicted the intention to use the tool, while performance and work avoidance goals did not predict intentions. Relational goals, however, negatively predicted intentions and end-of-course performance, shedding light on the importance of students' social motivations when using online peer feedback tools in their studies (e.g., peer feedback might be perceived as a social threat). Thus, the results point to the importance of an appropriate framing of online peer feedback tool use in educational settings as a learning opportunity and to reduce students’ possible concerns about their social relationships when using online peer feedback tools.
{"title":"Friendship or feedback? – Relations between computer science students’ goals, technology acceptance, use of an online peer feedback tool, and learning","authors":"Tuğçe Özbek , Martin Daumiller , Aida Roshany-Tabrizi , Tobias Mömke , Ingo Kollar","doi":"10.1016/j.chbr.2024.100540","DOIUrl":"10.1016/j.chbr.2024.100540","url":null,"abstract":"<div><div>Computer-supported peer feedback offers great potential to enhance students' learning. Yet, students sometimes do not use computer-supported peer feedback opportunities, which partially can be the result of low technology acceptance. The UTAUT-model specifies performance expectancy, effort expectancy, and facilitating conditions as decisive factors for the intention to use a technology. From a motivational perspective, however, it can be expected that also students' achievement goals have an impact on the intention to use an online peer feedback tool. Therefore, we investigated the effects of learning approach, appearance approach, appearance avoidance, work avoidance and relational goals (besides performance expectancy, effort expectancy and facilitating conditions) on 155 computer science students' intentions and actual use of an online peer feedback tool and their performance in an end-of-course exam. Results of path modelling the longitudinal, student and log-data informed data showed that students' intentions predicted actual use, which predicted exam performance. Learning approach goals positively predicted the intention to use the tool, while performance and work avoidance goals did not predict intentions. Relational goals, however, negatively predicted intentions and end-of-course performance, shedding light on the importance of students' social motivations when using online peer feedback tools in their studies (e.g., peer feedback might be perceived as a social threat). Thus, the results point to the importance of an appropriate framing of online peer feedback tool use in educational settings as a learning opportunity and to reduce students’ possible concerns about their social relationships when using online peer feedback tools.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100540"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743308","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}
Pub Date : 2024-12-01DOI: 10.1016/j.chbr.2024.100545
Francisco J. Sanmartín , Judith Velasco , Fátima Cuadrado , Juan A. Moriana
Loot boxes (LBs) are microtransactions within video games that offer players the opportunity to acquire virtual items randomly. LBs shared structural and psychological features with gambling, especially slot machines. However, one potential shared feature that has been scarcely explored in LBs, is the level of arousal experienced by players. This study explores changes in electrodermal activity (EDA), heart rate (HR) and respiratory rate (RR) during the opening of LBs in FIFA and during simulated slot machine spin in gamblers (n = 14, M = 19.93 years), LB users (n = 13, M = 19.62 years) and a control group (n = 13, M = 21.92 years). Additionally, the study aimed to compare psychophysiological activation levels produced by both dynamics in each group. Results indicated that both gamblers and LB users showed increased EDA during LB opening and slot machine spins, while HR or RR did not exhibit significant changes. The control group showed increased EDA during the slot machine spin, with no changes during LB opening or in other psychophysiological measures. The comparison between LB opening and slot machine spin revealed similar levels of psychophysiological activation for gamblers and LB users. These findings suggest a potential link between gambling and LBs, which could inform the development of policies for safer gaming environments.
战利品箱（LBs）是电子游戏中的微交易，让玩家有机会随机获得虚拟道具。LBs与赌博（尤其是老虎机）具有相同的结构和心理特征。然而，LBs有一个潜在的共同特征却很少被挖掘，那就是玩家体验到的兴奋程度。本研究探讨了《FIFA》中LB开业期间和模拟老角机旋转期间赌徒（n = 14, M = 19.93岁）、LB使用者（n = 13, M = 19.62岁）和对照组（n = 13, M = 21.92岁）的皮电活动（EDA）、心率（HR）和呼吸频率（RR）的变化。此外，该研究旨在比较两种动力在每组中产生的心理生理激活水平。结果表明，赌徒和LB使用者在LB打开和老虎机旋转时EDA增加，而HR或RR没有明显变化。对照组在老虎机旋转过程中显示EDA增加，而在LB打开或其他心理生理测量中没有变化。LB打开和老虎机旋转之间的比较表明，赌徒和LB使用者的心理生理激活水平相似。这些发现表明赌博和LBs之间存在潜在的联系，这可以为制定更安全的游戏环境政策提供信息。
{"title":"The thrill of chance: Psychophysiological responses in loot boxes and simulated slot machines","authors":"Francisco J. Sanmartín , Judith Velasco , Fátima Cuadrado , Juan A. Moriana","doi":"10.1016/j.chbr.2024.100545","DOIUrl":"10.1016/j.chbr.2024.100545","url":null,"abstract":"<div><div>Loot boxes (LBs) are microtransactions within video games that offer players the opportunity to acquire virtual items randomly. LBs shared structural and psychological features with gambling, especially slot machines. However, one potential shared feature that has been scarcely explored in LBs, is the level of arousal experienced by players. This study explores changes in electrodermal activity (EDA), heart rate (HR) and respiratory rate (RR) during the opening of LBs in FIFA and during simulated slot machine spin in gamblers (<em>n</em> = 14, <em>M</em> = 19.93 years), LB users (<em>n</em> = 13, <em>M</em> = 19.62 years) and a control group (<em>n</em> = 13, <em>M</em> = 21.92 years). Additionally, the study aimed to compare psychophysiological activation levels produced by both dynamics in each group. Results indicated that both gamblers and LB users showed increased EDA during LB opening and slot machine spins, while HR or RR did not exhibit significant changes. The control group showed increased EDA during the slot machine spin, with no changes during LB opening or in other psychophysiological measures. The comparison between LB opening and slot machine spin revealed similar levels of psychophysiological activation for gamblers and LB users. These findings suggest a potential link between gambling and LBs, which could inform the development of policies for safer gaming environments.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100545"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743306","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}
Pub Date : 2024-11-24DOI: 10.1016/j.chbr.2024.100530
Cristian Opariuc-Dan , Alexandra Maftei , Ioan-Alex Merlici
The present study examined the relations between two facets of Instagram addiction symptoms (i.e., Instagram Feed Addiction – IFA and Instagram Stories Addiction – ISA), anti-mattering, loneliness, and life satisfaction. More specifically, we explored the potential moderating roles of loneliness and life satisfaction on the link between anti-mattering and Instagram addiction symptoms. The sample involved 280 Romanian adults aged 18 to 57 (M = 22.58, SD = 4.62, 72.86% females, mostly from rural residential areas. Findings showed that the higher the age, the lower the scores on both IFA and ISA. Male participants reported higher IFA and ISA than females. Anti-mattering was positively associated with loneliness, Instagram feed, and stories addiction symptoms and negatively associated with life satisfaction. A moderated linear regression with residual centering suggested that both loneliness and life satisfaction moderated the links relations between anti-mattering and Instagram feed and stories addiction symptoms. These findings are discussed in relation to their practical implications for preventing and managing digital addictions among adults.
{"title":"I Don't matter anyway. Will more Instagram change that? Anti-mattering and Instagram Feed vs. stories addiction symptoms: The moderating roles of loneliness and life satisfaction","authors":"Cristian Opariuc-Dan , Alexandra Maftei , Ioan-Alex Merlici","doi":"10.1016/j.chbr.2024.100530","DOIUrl":"10.1016/j.chbr.2024.100530","url":null,"abstract":"<div><div>The present study examined the relations between two facets of Instagram addiction symptoms (i.e., Instagram Feed Addiction – IFA and Instagram Stories Addiction – ISA), anti-mattering, loneliness, and life satisfaction. More specifically, we explored the potential moderating roles of loneliness and life satisfaction on the link between anti-mattering and Instagram addiction symptoms. The sample involved 280 Romanian adults aged 18 to 57 (<em>M</em> = 22.58, <em>SD</em> = 4.62, 72.86% females, mostly from rural residential areas. Findings showed that the higher the age, the lower the scores on both IFA and ISA. Male participants reported higher IFA and ISA than females. Anti-mattering was positively associated with loneliness, Instagram feed, and stories addiction symptoms and negatively associated with life satisfaction. A moderated linear regression with residual centering suggested that both loneliness and life satisfaction moderated the links relations between anti-mattering and Instagram feed and stories addiction symptoms. These findings are discussed in relation to their practical implications for preventing and managing digital addictions among adults.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100530"},"PeriodicalIF":4.9,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707266","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}
Pub Date : 2024-11-24DOI: 10.1016/j.chbr.2024.100529
Jackie Zhanbiao Li , Janet Yuen-Ha Wong , Doreen Wing-Han Au , Yiyao Chen , Yingqian Lao , Mengmeng Zhang
This study aims to examine the impact of social media reports (SMR) on nurses' job satisfaction (NJS) and investigate the moderating effect of nurse manager overconfidence (NMO). Focusing on nurses in tertiary public hospitals in Guilin, China, we constructed an analytical dataset using survey data from January to June 2024 and social media comments collected through web scraping technology. Results reveal a significant positive correlation between SMR and NJS, indicating that increases in social media reports are associated with higher job satisfaction among nurses. However, when NMO acts as a moderating factor, the positive effect of SMR on NJS is attenuated, suggesting that overconfidence among nurse managers may diminish the influence of social media feedback. Furthermore, the study employs robustness tests, including the Replace Variables Method, Entropy Balancing Method, Instrumental Variable Method (IV-2LS), and Other Methods, effectively addressing endogeneity issues and confirming the reliability of these findings. This research offers theoretical support for enhancing hospital management and extends the literature on the moderating role of managerial characteristics on job satisfaction, providing practical insights for promoting high-quality hospital development.
{"title":"The impact of social media reports on nurses’ job satisfaction: A cross-section suvery","authors":"Jackie Zhanbiao Li , Janet Yuen-Ha Wong , Doreen Wing-Han Au , Yiyao Chen , Yingqian Lao , Mengmeng Zhang","doi":"10.1016/j.chbr.2024.100529","DOIUrl":"10.1016/j.chbr.2024.100529","url":null,"abstract":"<div><div>This study aims to examine the impact of social media reports (SMR) on nurses' job satisfaction (NJS) and investigate the moderating effect of nurse manager overconfidence (NMO). Focusing on nurses in tertiary public hospitals in Guilin, China, we constructed an analytical dataset using survey data from January to June 2024 and social media comments collected through web scraping technology. Results reveal a significant positive correlation between SMR and NJS, indicating that increases in social media reports are associated with higher job satisfaction among nurses. However, when NMO acts as a moderating factor, the positive effect of SMR on NJS is attenuated, suggesting that overconfidence among nurse managers may diminish the influence of social media feedback. Furthermore, the study employs robustness tests, including the Replace Variables Method, Entropy Balancing Method, Instrumental Variable Method (IV-2LS), and Other Methods, effectively addressing endogeneity issues and confirming the reliability of these findings. This research offers theoretical support for enhancing hospital management and extends the literature on the moderating role of managerial characteristics on job satisfaction, providing practical insights for promoting high-quality hospital development.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100529"},"PeriodicalIF":4.9,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707265","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}
Pub Date : 2024-11-22DOI: 10.1016/j.chbr.2024.100533
Raluca Alexandra Fulgu, Valerio Capraro
We present eight experiments exploring gender biases in GPT. Initially, GPT was asked to generate demographics of a potential writer of fourty phrases ostensibly written by elementary school students, twenty containing feminine stereotypes and twenty with masculine stereotypes. Results show a strong bias, with stereotypically masculine sentences attributed to a female more often than vice versa. For example, the sentence “I love playing fotbal! Im practicing with my cosin Michael” was constantly assigned by GPT-3.5 Turbo to a female writer. This phenomenon likely reflects that while initiatives to integrate women in traditionally masculine roles have gained momentum, the reverse movement remains relatively underdeveloped. Subsequent experiments investigate the same issue in high-stakes moral dilemmas. GPT-4 finds it more appropriate to abuse a man to prevent a nuclear apocalypse than to abuse a woman. This bias extends to other forms of violence central to the gender parity debate (abuse), but not to those less central (torture). Moreover, this bias increases in cases of mixed-sex violence for the greater good: GPT-4 agrees with a woman using violence against a man to prevent a nuclear apocalypse but disagrees with a man using violence against a woman for the same purpose. Finally, these biases are implicit, as they do not emerge when GPT-4 is directly asked to rank moral violations. These results highlight the necessity of carefully managing inclusivity efforts to prevent unintended discrimination.
我们介绍了探索 GPT 中性别偏见的八项实验。起初，我们要求 GPT 生成一个潜在作者的人口统计数据，这些数据包含 40 个表面上由小学生书写的短语，其中 20 个包含女性刻板印象，20 个包含男性刻板印象。结果显示出强烈的偏差，刻板的男性化句子被归于女性的频率高于反之。例如，句子 "I love playing fotbal！I love playing fotbal! Im practicing with my cosin Michael"（我和我的朋友迈克尔一起练习）这句话经常被 GPT-3.5 Turbo 归于女性作者。这一现象很可能反映出，虽然让女性融入传统男性角色的举措已经取得了一定的进展，但反向运动仍然相对落后。随后的实验研究了高风险道德困境中的同一问题。GPT-4 发现，与虐待女性相比，虐待男性来防止核启示更为合适。这种偏差延伸到了性别均等辩论中的其他重要暴力形式（虐待），但没有延伸到那些不那么重要的暴力形式（酷刑）。此外，在为更大利益而实施男女混合暴力的情况下，这种偏见会加剧：GPT-4 同意女性为防止核灾难而对男性施暴，但不同意男性为同样目的对女性施暴。最后，这些偏差是隐性的，因为当直接要求 GPT-4 对违反道德的行为进行排序时，这些偏差并没有出现。这些结果凸显了谨慎管理包容性工作以防止意外歧视的必要性。
{"title":"Surprising gender biases in GPT","authors":"Raluca Alexandra Fulgu, Valerio Capraro","doi":"10.1016/j.chbr.2024.100533","DOIUrl":"10.1016/j.chbr.2024.100533","url":null,"abstract":"<div><div>We present eight experiments exploring gender biases in GPT. Initially, GPT was asked to generate demographics of a potential writer of fourty phrases ostensibly written by elementary school students, twenty containing feminine stereotypes and twenty with masculine stereotypes. Results show a strong bias, with stereotypically masculine sentences attributed to a female more often than vice versa. For example, the sentence “I love playing fotbal! Im practicing with my cosin Michael” was constantly assigned by GPT-3.5 Turbo to a female writer. This phenomenon likely reflects that while initiatives to integrate women in traditionally masculine roles have gained momentum, the reverse movement remains relatively underdeveloped. Subsequent experiments investigate the same issue in high-stakes moral dilemmas. GPT-4 finds it more appropriate to abuse a man to prevent a nuclear apocalypse than to abuse a woman. This bias extends to other forms of violence central to the gender parity debate (abuse), but not to those less central (torture). Moreover, this bias increases in cases of mixed-sex violence for the greater good: GPT-4 agrees with a woman using violence against a man to prevent a nuclear apocalypse but disagrees with a man using violence against a woman for the same purpose. Finally, these biases are implicit, as they do not emerge when GPT-4 is directly asked to rank moral violations. These results highlight the necessity of carefully managing inclusivity efforts to prevent unintended discrimination.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100533"},"PeriodicalIF":4.9,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707269","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}
Pub Date : 2024-11-21DOI: 10.1016/j.chbr.2024.100537
Jan Olav Christensen , Stein Knardahl , Morten Birkeland Nielsen
Information and Communication Technology (ICT) at work can cause distress and frustration, commonly labeled ”technostress”. Nevertheless, few, if any, studies have examined the impact of ICT factors on sickness absence due to mental distress. We investigated effects of ”ICT-hassles” - disruption of work due to ICT-problems - on low or medium-level and high level sickness absence due to psychological diagnoses (LMSA-P/HSA-P). We also determined the mitigating influences of ICT-training and ICT-support. We surveyed 8620 workers in Norway, linking responses to official registry data of medically certified absence due to psychological complaints during 12 months following the survey. We used Bayesian multilevel multinomial logistic regression and analyzed ICT-variables at the individual level as well as averaged over employees within work-units. Moderated regressions determined whether effects of ICT-hassles varied with levels of support and training. Individual level ICT-hassles predicted HSA-P (OR 1.20, 95% CI 1.01,1.42) and work-unit level hassles LMSA-P (OR 1.47, 95% CI 1.11,1.94). ICT-support at both levels predicted lower risk of LMSA-P (individual: OR 0.84, 95% CI 0.74,0.97, work-unit: OR 0.63, 95% CI 0.50,0.80). Insufficient training appeared to have the most marked effects, with ORs ranging from 1.66 to 5.12. Effects were strongest at the work-unit level and persisted after adjustment for job demands and -control. No moderation of the effect of hassles by training and support was observed. In conclusion, ICT-hassles may promote absence whereas support and training prevent it. However, offering support after hassles have occurred may not be sufficient, suggesting that prevention is more effective than repair.
工作中的信息与传播技术（ICT）会造成困扰和挫折，通常被称为 "技术压力"。然而，很少有研究（如果有的话）探讨过信息和通信技术因素对因精神压力而缺勤的影响。我们调查了 "信息和通信技术麻烦"--信息和通信技术问题导致的工作中断--对因心理诊断（LMSA-P/HSA-P）导致的中低水平和高水平病假的影响。我们还确定了信息与通信技术培训和信息与通信技术支持的缓解作用。我们对挪威的 8620 名工人进行了调查，并将答复与调查后 12 个月内经医学证明的心理投诉缺勤的官方登记数据联系起来。我们采用贝叶斯多层次多叉逻辑回归法，分析了个人层面的信息和通信技术变量，以及工作单位内员工的平均信息和通信技术变量。调节回归确定了信息和通信技术障碍的影响是否随支持和培训水平的变化而变化。个人层面的信息和通信技术麻烦预示着 HSA-P（OR 1.20，95% CI 1.01,1.42），工作单位层面的麻烦预示着 LMSA-P（OR 1.47，95% CI 1.11,1.94）。两个层面的信息和通信技术支持预示着较低的 LMSA-P 风险（个人：OR 0.84，95% CI 0.74,0.97；工作单位：OR 0.63，95% CI 0.50,0.80）。培训不足的影响似乎最为明显，OR 值从 1.66 到 5.12 不等。在工作单位层面的影响最大，在对工作要求和控制进行调整后，影响依然存在。没有观察到培训和支持对麻烦影响的调节作用。总之，信息和通信技术带来的麻烦可能会导致缺勤，而支持和培训则会防止缺勤。然而，在麻烦发生后提供支持可能还不够，这表明预防比修复更有效。
{"title":"IT really matters: Associations of computer hassles and technical support with medically certified sickness absence due to mental health complaints","authors":"Jan Olav Christensen , Stein Knardahl , Morten Birkeland Nielsen","doi":"10.1016/j.chbr.2024.100537","DOIUrl":"10.1016/j.chbr.2024.100537","url":null,"abstract":"<div><div>Information and Communication Technology (ICT) at work can cause distress and frustration, commonly labeled ”technostress”. Nevertheless, few, if any, studies have examined the impact of ICT factors on sickness absence due to mental distress. We investigated effects of ”ICT-hassles” - disruption of work due to ICT-problems - on low or medium-level and high level sickness absence due to psychological diagnoses (LMSA-P/HSA-P). We also determined the mitigating influences of ICT-training and ICT-support. We surveyed 8620 workers in Norway, linking responses to official registry data of medically certified absence due to psychological complaints during 12 months following the survey. We used Bayesian multilevel multinomial logistic regression and analyzed ICT-variables at the individual level as well as averaged over employees within work-units. Moderated regressions determined whether effects of ICT-hassles varied with levels of support and training. Individual level ICT-hassles predicted HSA-P (OR 1.20, 95% CI 1.01,1.42) and work-unit level hassles LMSA-P (OR 1.47, 95% CI 1.11,1.94). ICT-support at both levels predicted lower risk of LMSA-P (individual: OR 0.84, 95% CI 0.74,0.97, work-unit: OR 0.63, 95% CI 0.50,0.80). Insufficient training appeared to have the most marked effects, with ORs ranging from 1.66 to 5.12. Effects were strongest at the work-unit level and persisted after adjustment for job demands and -control. No moderation of the effect of hassles by training and support was observed. In conclusion, ICT-hassles may promote absence whereas support and training prevent it. However, offering support after hassles have occurred may not be sufficient, suggesting that prevention is more effective than repair.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100537"},"PeriodicalIF":4.9,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707268","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号