Search Results (106)

Addressing climate change requires deeper insight into the psychological drivers of pro-environmental behavior. This study investigates how personality traits, climate-related emotions, and demographic factors can predict sustainable consumption and climate action participation using a Bayesian regression approach. Drawing from the HEXACO personality model and key emotional predictors—Climate Change Worry (CCW) and environmental empathy (EE)—we analyzed data from 604 adults in Greece to assess both private and public climate-related behaviors. This research is novel in its integrative approach, combining dispositional traits and affective states within a Bayesian analytical framework to simultaneously predict both sustainable consumption and climate action. Bayesian model testing highlighted education as the most powerful and reliable predictor of sustainable consumption, with increasing levels—namely Doctoral education—linked to more environmentally responsible action. CCW produced small but reliable effects, supporting hypotheses that moderate emotional concern will lead to sustainable behavior when linked to efficacy belief. The majority of HEXACO traits, e.g., Honesty–Humility and Conscientiousness, produced limited predictive power. This indicates in this case that structural and emotional considerations were stronger than dispositional personality traits. For climate action involvement, Bayesian logistic models found no considerable evidence of any predictor, corroborating the perspective that public participation in high effort action is most likely to rely on contextual enablers instead of internal sentiments or attributes. A significant interaction effect between education and gender also indicated that the sustainability effect of education is moderated by sociocultural identity. Methodologically, this research demonstrates the strengths of Bayesian analysis in sustainability science to make sensitive inference and model comparison possible. The results highlight the importance of affect-related structural variables in behavioral models and have applied implications for theory-informed and targeted climate education and communication interventions to enable different populations to act sustainably. Full article

Among searchable encryption techniques, multi-user dynamic searchable encryption (MUDSE) schemes are an important research direction. After the data owner transfers data to the cloud, it may be necessary to authorize different users to access some or all of the data while allowing for dynamic updates. Enabling dynamic data sharing in cloud storage while preserving users’ ability to search the data is crucial for promoting data flow and maximizing its value. This approach is particularly significant in addressing the data silo problem. However, existing security mechanisms remain imperfect, and most current scenarios assume that cloud servers are merely “curious but honest”. In reality, cloud servers may exhibit malicious behavior, such as returning incorrect or incomplete search results. Similarly, malicious users might falsify search results—for example, to avoid payment—or collude with cloud servers to steal other users’ search privacy. To address these challenges, this paper proposes an updatable multi-user dynamic searchable encryption scheme with bidirectional verification. The scheme enables secure dynamic data sharing in multi-user scenarios by constructing an index structure using homomorphic message authentication codes and bitmaps. This ensures secure updates to encrypted data without revealing the relationship between files and keyword search keys while providing forward and backward security. Regarding privilege management, the scheme employs updatable keys, ensuring that users can only generate valid search commands if they possess the latest encryption key. Additionally, blockchain technology is introduced to assist in verifying user honesty. Through actual testing and security analysis, the proposed solution demonstrates improved search speed over traditional methods while maintaining security. It also exhibits high adaptability for handling frequently changing cloud data. Full article

Stories are widely used by parents or educators to teach children the virtue of honesty. However, the existing empirical findings on the effect of story-telling on children’s honesty are limited and mixed. This study examined whether moral stories involving honesty can promote honesty in Chinese preschool children (N = 208). The Temptation Resistance Paradigm (TRP) was used to assess children’s honesty. Study 1 showed that children in the positive moral story condition were more likely to tell the truth than those in the control condition, while negative moral story-telling did not have this effect. Study 2 further examined whether combining external appeals with positive moral story-telling could further promote children’s honesty, and the results showed that the combination of the two techniques was equally as effective as moral story-telling alone. These findings have important implications for moral development and moral education. Full article

In this study, we examined the role of intellectual humility (IH) as an antecedent of individual attitude toward sustainable tourism viewed from the lens of personality trait theory, virtue ethics theory, and regenerative tourism principles within a stakeholder framework. Data were collected via Qualtrics in an online survey of 233 adults in the United States. A series of confirmatory factor analyses (CFA) were applied to the data to test the measurement model. In addition, a bifactor CFA was found to have acceptable fit and appropriate in controlling for common method variance. A series of covariance-based structural equations models (SEMs) was estimated to test the hypothesized model while controlling for common method variance in addition to individual age and gender. Using the chi-square difference test for nested model comparison, we found that intellectual humility was a significant antecedent of the negative ecological impact of tourism (β = 0.14, p < 0.01) while its relationships with economic and social impacts of travel became non-significant after controlling for common method variance. Pro-social tendency, operationalized as HEXACO Honesty–Humility, was also a significant antecedent of the negative ecological impact (β = 0.17) and positive economic impact (β = −0.34) of tourism, after controlling for common method variance. Despite its limitations due to its cross-sectional design and use of self-report data in the U.S., this study was novel in introducing intellectual humility as an important virtue to be cultivated at the individual level to achieve a holistic approach to sustainable tourism, especially in shaping destination choices. In addition, the study highlights the need to detect common method variance in self-report data via bifactor CFA to avoid erroneous reporting of significant findings, hampering our collective research efforts to address climate change and its impact. Full article

With the HEXACO model of personality, this study examined the relationship between HEXACO traits (i.e., honesty–humility, emotionality, extraversion, agreeableness, conscientiousness, and openness to experience) and teaching commitment among 2031 Chinese pre-service teachers. The results show that all HEXACO traits positively predicted teaching commitment, with extraversion and agreeableness being the most pronounced predictors. Also, this study investigated whether teaching motivation, including intrinsic motivation, altruistic motivation, and extrinsic motivation, could explain the relationship between HEXACO traits and teaching commitment. The results supported the mediational role of teaching motivation, with intrinsic motivation showing the strongest mediational effect. For extraversion and openness to experience, a full mediation model was supported, while for the other four HEXACO traits, a partial mediation model was validated. The theoretical and practical implications of this study for teacher education are discussed. Full article

This systematic literature review rigorously evaluates the impact of Generative AI (GenAI) on academic integrity within higher education settings. The primary objective is to synthesize how GenAI technologies influence student behavior and academic honesty, assessing the benefits and risks associated with their integration. We defined clear inclusion and exclusion criteria, focusing on studies explicitly discussing GenAI’s role in higher education from January 2021 to December 2024. Databases included ABI/INFORM, ACM Digital Library, IEEE Xplore, and JSTOR, with the last search conducted in May 2024. A total of 41 studies met our precise inclusion criteria. Our synthesis methods involved qualitative analysis to identify common themes and quantify trends where applicable. The results indicate that while GenAI can enhance educational engagement and efficiency, it also poses significant risks of academic dishonesty. We critically assessed the risk of bias in included studies and noted a limitation in the diversity of databases, which might have restricted the breadth of perspectives. Key implications suggest enhancing digital literacy and developing robust detection tools to effectively manage GenAI’s dual impacts. No external funding was received for this review. Future research should expand database sources and include more diverse study designs to overcome current limitations and refine policy recommendations. Full article

Trust and reputation relationships among objects represent key aspects of smart IoT object communities with social characteristics. In this context, several trustworthiness models have been presented in the literature that could be applied to IoT scenarios; however, most of these approaches use scalar measures to represent different dimensions of trust, which are then integrated into a single global trustworthiness value. Nevertheless, this scalar approach within the IoT context holds a few limitations that emphasize the need for models that can capture complex trust relationships beyond vector-based representations. To overcome these limitations, we already proposed a novel trust model where the trust perceived by one object with respect to another is represented by a directed, weighted graph. In this model, called T-pattern, the vertices represent individual trust dimensions, and the arcs capture the relationships between these dimensions. This model allows the IoT community to represent scenarios where an object may lack direct knowledge of a particular trust dimension, such as reliability, but can infer it from another dimension, like honesty. The proposed model can represent trust structures of the type described, where multiple trust dimensions are interdependent. This work represents a further contribution by presenting the first real implementation of the T-pattern model, where a neural-symbolic approach has been adopted as inference engine. We performed experiments that demonstrate the capability in inferring trust of both the T-pattern and this specific implementation. Full article

This research demonstrates how confirmation and disconfirmation biases manifest based on individuals’ political affiliations when processing a self-disclosure message in the context of a political crisis. An experiment presented a crisis message in which a politician voluntarily revealed his campaign finance violations. The results revealed that confirmation bias and disconfirmation bias significantly influenced the information processing of participants based on their political affiliations. Democrat participants were significantly more open to and forgiving of the crisis message when it featured a Democrat politician. In contrast, Republican participants showed a strong tendency to be more critical and less forgiving under the same conditions. However, this pattern reversed when a Republican politician was shown in the crisis message. The research also tested moderated mediation hypotheses: the interaction effects between study participants’ political affiliations and politicians’ parties were mediated by perceived attitude toward the politician and crisis responsibility, leading to ethical perceptions about the politician. The study contributes to our understanding of the mechanisms underlying political polarization and the ways in which the biases of confirmation and disconfirmation influence individuals’ processing of political messages. Full article

This study aimed to explore the influence of different types of moral stories on the honest behaviour of children aged 7–11 using a field experiment. The research findings are as follows: 1. Compared to the control condition, moral stories with positive consequences of honesty significantly promote honest behaviour in children and suppress their tendency to lie. 2. The impact of different types of moral stories on honest behaviour in children varies with age. Specifically, compared to the control condition, moral stories with positive consequences of honesty significantly promote the honest behaviour of children aged 7–10. 3. Moral stories with positive consequences of honesty significantly promote honest behaviour in children because they convey positive and encouraging messages to children that “speaking the truth leads to positive consequences”. This study suggests that teachers should utilize moral stories with positive consequences of honesty more frequently to enhance students’ honest behaviour, particularly for 7–10-year-old children. Full article

This pilot study investigated how viewers perceive Monica Geller’s personality using three evidence-based personality models: Big Five, HEXACO, and Cloninger’s Biopsychosocial Model. Additionally, it examined how these perceptions are associated to audiences’ engagement in parasocial relationships with this iconic character from the sitcom Friends. A sample of sixty-three participants assessed Monica’s personality by responding to the Big Five Inventory (BFI), the HEXACO-60, and the Temperament and Character Inventory (TCI-60). Participants also completed the Multidimensional Measure of Parasocial Relationships (MMPR). Personality scores were contextualized against U.S. population norms (N_BFI = 711, N_HEXACO = 1126, N_TCI = 1948) and Pearson correlations were conducted to explore associations between personality traits and the Affective, Behavioral, Cognitive, and Decisional dimensions of parasocial engagement. Normative comparisons revealed Monica’s perceived Openness and Agreeableness in the Big Five and her Openness and Agreeableness in the HEXACO as significantly below average, while her Big Five Neuroticism and her HEXACO Conscientiousness were significantly above average. In the Biopsychosocial Model, Monica’s Persistence was significantly higher than population norms, while Cooperativeness was significantly lower. Big Five Agreeableness showed correlations across all parasocial engagement dimensions. HEXACO Emotionality was strongly linked to the Affective and Behavioral dimensions, while Honesty–Humility was associated with Cognitive parasocial engagement. In the Biopsychosocial Model, Reward Dependence and Cooperativeness were associated with Cognitive and Affective parasocial engagement, while Self-Directedness was linked to the Behavioral dimension. The Biopsychosocial Model offered the most comprehensive insights, capturing the multidimensional nature of viewer–character engagement. The Big Five and HEXACO models added valuable perspectives, particularly in explaining that traits associated with trust and kindness are linked to decision making. These findings emphasize the importance of integrating multiple personality frameworks to advance the understanding of parasocial relationship engagement, shedding light on the nuanced ways personality traits shape audience perceptions and relationships with media characters, with significant implications for media psychology and personality research. Limitations and avenues for future developments are discussed, building on the insights from this pilot study. Full article

Academic integrity is a cornerstone of education systems, yet the rise of contract cheating poses significant challenges for higher education institutions. Current approaches to managing contract cheating often lack the comprehensive structure needed to address the complexities of modern cheating methods. The primary objective of this study is to investigate the effectiveness of the proposed Three-Tier Framework (TTF), designed in our previous study to combat contract cheating. The proposed framework comprises three tiers: awareness, monitoring, and evaluation. It engages stakeholders within the system and encourages a proactive and collaborative stance against contract cheating while reinforcing a culture of academic honesty. The evaluation focuses on three key aspects: the clarity of the framework’s functions and objectives, the potential challenges in implementing the proposed monitoring process, and the perceived limitations in detecting and mitigating contract cheating through this framework. Supervised and unsupervised assignments are considered, excluding the option of e-proctoring, as some students encountered difficulties setting up necessary tools and software for online exams. Survey results reveal a broad consensus among respondents, who expressed strong confidence in the clarity and effectiveness of the framework and its monitoring procedures. These positive perceptions were consistent across respondents, regardless of their prior experience or familiarity with contract cheating. Although the overall feedback was positive, concerns were raised regarding implementing the framework in current educational settings. Specific challenges cited include tight timelines and the increased workload associated with the new procedures, emphasising a need for additional guidance, training, and institutional support to ensure effective adoption. The proposed framework incorporates an instructor dashboard designed to streamline academic workflow and simplify the monitoring process introduced in this framework. The survey results confirm that the framework can be adopted to address the unique needs of academics and diverse educational environments; however further research is needed to explore its applicability across the broader higher education community. Full article

Impulsive buying is a growing problem in modern society with significant financial and psychological consequences, and it is necessary to examine the mechanisms underlying it. Understanding the mechanisms driving this behavior is crucial. Impulsive buying consists of two key aspects: a cognitive aspect, characterized by a lack of planning and reflection, and an affective aspect, involving emotional responses that can occur before, during, or after a purchase. This study aims to explore the relationship between personality traits, as measured by the HEXACO model, and tendencies toward impulsive buying. Specifically, it examines how the HEXACO traits differentially predict the cognitive and affective components of impulsive buying tendencies. Data were collected from a sample of 420 students, with 32 excluded due to incomplete responses, resulting in a final sample of 388 students (155 men, 233 women) with an average age of 22.8. Hierarchical regression analyses revealed that HEXACO personality domains significantly predicted overall impulsive buying tendencies. As expected, Honesty–Humility and Conscientiousness were negatively associated with impulsive buying, while Emotionality and Extraversion positively predicted impulsive buying tendencies. Moreover, Honesty–Humility, Conscientiousness, and Extraversion significantly predicted the cognitive component of impulsive buying, while Honesty–Humility and Emotionality were significant predictors of the affective component. These findings suggest the importance of educating individuals, from an early age, on the negative consequences of impulsive buying, effective money-saving strategies, and the principles of mental accounting. Full article

Climate change is an irreversible crisis that urgently calls for social transformation to protect human livelihood and environmental stability. Establishing awareness, building environmental literacy, and citizens’ mobilization are the steps toward sustainable change in giving a legacy of hope to future generations. This research explores major psychological and social drivers of pro-environmental behavior, considering the influence of HEXACO personality traits, climate anxiety (CCW), and social media engagement (SMI) on sustainable consumption (SC) and climate action intentions (CCI). Our findings revealed th eco-guilt (EGQ) and environmental empathy (EE) are immediate drivers for climate action, while long-term nurturance of eco-grief (ECOG) leads to engagement, supporting the notion that different emotions uniquely contribute to pro-environmental intentions. In terms of personality predictors, HEXACO’s traits of emotionality (E), honesty-humility (HH), and openness (O) are revealed to be significant, with emotionality also moderating the relationship between eco-grief and climate change action. The results reveal that connectedness to nature (CTN) and moderate levels of climate anxiety synergistically promote sustainable consumption intentions, while demographic factors such as gender, education levels, and exposure to social media moderate these intentions. Females also show a higher level of climate action intention in response to eco-guilt and eco-grief, while individuals with higher levels of education are more responsive to climate-related social media content, increasing their sustainable consumption behaviors. In exploring such interactions, this study aims to add to the understanding of what drives people toward valued environmental behaviors and, in turn, to inform effective climate advocacy, education, and personality-driven strategies to promote environmental engagement. Full article

Most decision-making models, including the pairwise comparison method, assume the honesty of the decision-maker. However, it is easy to imagine a situation where the decision-maker tries to manipulate the ranking results. This problem applies to many decision-making methods, including the pairwise comparison method. This article proposes three simple algorithmic methods for manipulating data using the pairwise comparison method. The proposed solutions try to mimic the behavior of a dishonest decision-maker who, acting under time pressure, chooses a simple strategy that leads to pushing through a given alternative. We also test the susceptibility to detection of the proposed manipulation strategies. To this end, we propose a convolutional neural network architecture, which we train based on generated data consisting of the original random pairwise comparison matrices and their manipulated counterparts. Our approach treats the pairwise comparison matrices as two- or three-dimensional images specific to the decision situation. In the latter case, the matrices are initially transformed into a three-dimensional map of local inconsistencies, and only data processed in this way are subjected to analysis using neural networks. The experiments indicate a significant level of detection of the proposed manipulations. In numerical tests, the effectiveness of the presented solution ranges from 88% to 100% effectiveness, depending on the tested algorithm and test parameters. The measured average computation time for the single case analyzed oscillated below one millisecond, which is a more than satisfactory result of the performance of the built implementation. We can successfully use the neural networks trained on synthetic data to detect manipulation attempts carried out by real experts. Preliminary tests with respondents also indicated high effectiveness in detecting manipulation. At the same time, they signaled the difficulty of distinguishing actual manipulation from a situation in which an expert strongly prefers one or more selected alternatives. Full article

Ethical practice is a universal concern for healthcare professionals, independent of their social, cultural, or religious background. This study aimed to assess and categorise statements published in codes of ethics for pharmacists from three diverse societies within the wider European area. The study followed a qualitative exploratory and triangular design, comparing the leading professional and ethical statements between three geographically apart countries (Portugal, Lithuania, and Turkey) and using the International Pharmaceutical Federation Code of Ethics proposal as a gold standard. Common core values such as honesty, integrity, and professional autonomy were identified across the countries’ codes, suggesting that shared recognised core values underpin pharmacists’ practice and policies in culturally diverse settings. None of the codes fully correspond to the framework the International Pharmaceutical Federation proposed. The analysis elicited significant inconsistencies between the codes for analogous practice models within the same continent. Further studies are needed to gain a more profound and comprehensive understanding of the underlying reasons for these discrepancies so that ethical weaknesses can be improved and harmonisation towards best-practice principles can benefit patients and healthcare systems. Full article