Levels Of Trustworthiness Research Articles

ChatGPT as a psychotherapist for anxiety disorders: An empirical study with anxiety patients.

Purpose: this study aims to investigate the role of ChatGPT as a psychotherapist for anxiety disorders, examining its effectiveness, acceptability, and potential benefits among individuals with anxiety disorders. Methods: a quasi-experimental design was adopted, involving a 4-week intervention where participants used ChatGPT as a therapeutic tool. The study included outpatients aged above 18 years from public hospitals in Saudi Arabia. A total of 399 participants completed a survey questionnaire that focused on their experiences with AI-based psychotherapy (six items), perceptions of ChatGPT (four items), and its role in different therapy modalities for anxiety management (seven items). Measures were taken to ensure the validity and reliability of responses by using Cronbach's alpha reliability testing (> 0.7), including the use of a translated and verified questionnaire. Results: majority received prior therapy (89.6%), reporting severe anxiety symptoms (36.1%). ChatGPT was widely used and perceived as accurate by 91.2% of users. Concerns included privacy (67.2%) and ethics (64.9%). Statistically significant differences (p < .05) in perceptions of ChatGPT for anxiety disorders were observed. While urban residents generally rated ChatGPT more positively, females consistently reported higher levels of trustworthiness, effectiveness, and coherence in guidance compared to males. Conclusion: ChatGPT has the potential to complement traditional psychotherapeutic approaches and enhance access to quality mental health care.

Uncivil communication and epistemic trustworthiness concerns in public online discussions in response to scientists during the Covid-19 pandemic

The Covid-19 pandemic illustrated important developments in science communication, with direct online interactions between scientists and the public. This study performs a content analysis of tweets (“N” = 6,000) directed at German virologists (“N” = 6) during the pandemic’s first year. It identifies substantial levels of incivility and trustworthiness concerns, which often co-occurred. These findings enhance our understanding of online communication dynamics in crises by showing how incivility and trustworthiness concerns are not only prevalent but also evolve in response to specific events and phases. This analysis provides insight into the complexities of public sentiment toward scientists during the pandemic.

Building a Scientific Foundation for Security: Multilayer Network Model Insights for System Security Engineering

AbstractTo help incorporate security into INCOSE's Systems Engineering Vision 2035, the INCOSE systems security engineering working group endorses a paradigmatic shift to reframe systems security as trustworthy, loss‐driven, and capabilities‐based. Similar research out of Sandia National Laboratories has explored cutting‐edge approaches to systems security for national security applications. Together, these efforts highlight the need for—‐and a path toward—‐a scientific foundation for security. Leveraging underlying tenets of systems theory, observed security heuristics, and the concepts emerging from INCOSE's SSE working helps triangulate a set of “first principles” as part of a scientific foundation for security as an emergent systems property that incorporates traditional physical security designs, cyber security architectures, and personnel security programs—‐as well as the (often ignored) interactions between them. These first principles, in turn, are the basis for a set of derived systems security performance axioms that support current INCOSE SSE working efforts. We have demonstrated this approach's logic and designability with a multilayer network model‐based approach for systems security. The structure of this scientific foundation for security offers additional, innovative opportunities to achieve desired levels of trustworthiness, creative mechanisms to meet needs, innovative loss‐driven approaches, and enhanced capabilities—‐all aimed at producing more efficient and effective systems security solutions against current and emerging threats, uncertainties, and complexities.

Influence of protective clothing and masks on facial trustworthiness in an investment game: insights from a Chinese population study

Facial features are important sources of information about perceived trustworthiness. Masks and protective clothing diminish the visibility of facial cues by either partially concealing the mouth and nose or covering the entire face. During the pandemic, the use of personal protective equipment affected and redefined who trusts whom in society. This study used the classical investment game of interpersonal trust with Chinese participants to explore the impact of occlusion on interpersonal trust. Faces with moderate initial trustworthiness were occluded by a mask or protective clothing in Experiment 1 and were digitally occluded by a square in Experiment 2, and faces with three levels of initial trustworthiness were occluded by a mask in Experiment 3. Results showed that both undergraduates (Experiment 1a) and non-student adults (Experiment 1b) perceived the faces with protective clothing as more trustworthy than faces wearing standard masks and faces not wearing masks. Faces with the top halves showing were perceived as trustworthy as full faces, while faces with the bottom halves showing were perceived as less trustworthy. The effect of masks is weak and complex. Masks reduced participants’ trust in faces with high initial trustworthiness, had no effect on faces with low and moderate initial trustworthiness, and only slightly increased the trust of undergraduates in faces with moderate initial trustworthiness. Our findings indicate that the lack of information caused by occlusion and the social significance associated with occlusion collectively affect people’s trust behavior in Chinese society. We believe the findings of this study will be useful in elucidating the effects of personal protective equipment usage on perceptions of trustworthiness.

Decoding trust: a reinforcement learning perspective

Abstract Behavioral experiments on the trust game have shown that trust and trustworthiness are commonly seen among human beings, contradicting the prediction by assuming Homo economicus in orthodox Economics. This means some mechanism must be at work that favors their emergence. Most previous explanations, however, need to resort to some exogenous factors based upon imitative learning, a simple version of social learning. Here, we turn to the paradigm of reinforcement learning, where individuals revise their strategies by evaluating the long-term return through accumulated experience. Specifically, we investigate the trust game with the Q-learning algorithm, where each participant is associated with two evolving Q-tables that guide one’s decision-making as trustor and trustee, respectively. In the pairwise scenario, we reveal that high levels of trust and trustworthiness emerge when individuals appreciate both their historical experience and returns in the future. Mechanistically, the evolution of the Q-tables shows a crossover that resembles human psychological changes. We also provide the phase diagram for the game parameters, where the boundary analysis is conducted. These findings are robust when the scenario is extended to a latticed population. Our results thus provide a natural explanation for the emergence of trust and trustworthiness, and indicate that the long-ignored endogenous factors alone are sufficient to drive. More importantly, the proposed paradigm shows the potential to decipher many puzzles in human behaviors.

Decentralized Identity Authentication Mechanism: Integrating FIDO and Blockchain for Enhanced Security

FIDO (Fast Identity Online) is a set of network identity standards established by the FIDO Alliance. It employs a framework based on public key cryptography to facilitate multi-factor authentication (MFA) and biometric login, ensuring the robust protection of personal data associated with cloud accounts and ensuring the security of server-to-terminal device protocols during the login process. The FIDO Alliance has established three standards: FIDO Universal Second Factor (FIDO U2F), FIDO Universal Authentication Framework (FIDO UAF), and the Client to Authenticator Protocols (CTAP). The newer CTAP, also known as FIDO2, integrates passwordless login and two-factor authentication. Importantly, FIDO2’s support for major browsers enables users to authenticate their identities via FIDO2 across a broader range of platforms and devices, ushering in the era of passwordless authentication. In the FIDO2 framework, if a user’s device is stolen or compromised, then the private key may be compromised, and the public key stored on the FIDO2 server may be tampered with by attackers attempting to impersonate the user for identity authentication, posing a high risk to information security. Recognizing this, this study aims to propose a solution based on the FIDO2 framework, combined with blockchain technology and access control, called the FIDO2 blockchain architecture, to address existing security vulnerabilities in FIDO2. By leveraging the decentralized nature of the blockchain, the study addresses potential single points of failure in FIDO2 server centralized identity management systems, thereby enhancing system security and availability. Furthermore, the immutability of the blockchain ensures the integrity of public keys once securely stored on the chain, effectively reducing the risk of attackers impersonating user identities. Additionally, the study implements an access control mechanism to manage user permissions effectively, ensuring that only authorized users can access corresponding permissions and preventing unauthorized modifications and abuse. In addition to proposing practical solutions and steps, the study explains and addresses security concerns and conducts performance evaluations. Overall, this study brings higher levels of security and trustworthiness to FIDO2, providing a robust identity authentication solution.

The psychometric properties of the lifelong learning measurement scale (LLMS): the study of validation in higher education setting

In the dynamic world of higher education, lifelong learning is important to both individuals and institutions, and measuring it can provide insightful data for both. The purpose of this study is therefore to refine and validate the psychometric qualities of the Lifelong Learning Measurement Scale (LLMS), created to measure academic staff’s engagement with lifelong learning in higher education institutions. Using a cross-sectional study design, the current study validated the scale using rigorous psychometric procedures. The study involved 396 participants, who were selected using a simple random sampling technique. The collected data were analysed using factorial analysis methods. The results provide a theoretically based four-factor structure consisting of 16 items of the LLMS. Strong evidence for the validity of the scale comes from its content validity, construct-related validity, and criterion-related validity. In addition, the scale and its factors demonstrate excellent levels of trustworthiness, according to estimates of composite reliability and internal consistency. The impartial and fair use of the scale is further supported by strong evidence for measurement invariance across gender groups. In conclusion, these results confirm that the LLMS is a legitimate and trustworthy tool that can be used in a variety of research and practices related to lifelong learning in a higher education setting. Furthermore, it is important to note that further research is needed to examine its applicability in different contexts. Subsequent research on its longitudinal stability and sensitivity to different cultural characteristics could also confirm LLMS as a reliable and integrative assessment tool for lifelong learning.

Secrecy Enhancement of relay cooperative NOMA network based on user behavior

From the perspective of information security, relays exhibit varying levels of trustworthiness when forwarding information. For screening and eliminating the malicious users of cooperative NOMA relay networks, a reputation-based algorithm is proposed, in which the user relays (URs) are categorized into three types based on their behaviors—malicious users, speculative users, and honest users. Meanwhile, in order to minimize information leakage at the relay, cooperative interference signals are transmitted by far user (FU) and near user (NU) via the uplink while the base station (BS) is also transmitting signals to the relay. This approach increases inter-user interference (IUI) to confuse the eavesdropping capability of the relay. To verify the superiority of the proposed scheme, an asymptotic lower bound expression for the ergodic secrecy rate (ESR) of the downlink is derived to characterize the secrecy performance of the proposed scheme. Furthermore, in the case of limited system power, a joint power allocation algorithm based on the golden section method is also proposed to further enhance the security performances of the system. The simulation results validate the accuracy of the derived analysis results and demonstrate that the proposed scheme has a significant improvement in the ESR compared with the traditional scheme.

Smartphone use decreases trustworthiness of strangers

Trust is crucial for social, economic, and political relationships. Evidence shows the importance of trust in distinct areas, from the day-to-day forming of personal relations to the stability of democracies. In this paper, we ask how new technologies that compete for our attention affect the formation of trust between strangers. To that end, we study how smartphone use affects interactions with, and subsequent trust in, strangers. In our experiment, we had participants wait in groups of six for approximately 20 minutes, allowing them to interact as they wished. In one treatment, participants could use their smartphones during the wait time, while in the other they did not have access to their phones. We then randomly paired participants within each group to play a trust game and answer a brief survey. As predicted, we find that limiting phone access resulted in higher levels of trustworthiness.

When being unattractive is an advantage: effects of face perception on intuitive culpability judgments

This experiment explored the influence of facial attractiveness and trustworthiness on guilty judgments. We recruited 128 participants, randomly assigned to high and low time pressure conditions to act as judges in a simulated blind-date swindle case. Participants judged nine male faces from the Chicago Face Database with three attractiveness levels (unattractive, neutral and attractive), featuring a 2 × 3 mixed factorial design, with consistent standardized average levels of face trustworthiness. We also assessed participants’ self-reported processing styles (rational vs. experiential) using the Rational Experiential Inventory. Notably, participants predominantly judged unattractive faces as innocent, indicating an ugly leniency effect. Our results suggest the primacy of perceived face trustworthiness over attractiveness in guilt judgments for cases where the accused’s physical appearance might facilitate the crime’s success. This highlights the importance of examining the contribution of perceived trustworthiness to guilt judgment biases, and adds to growing evidence exploring extrajudicial factors in criminal verdicts.

Strategic social decision making undergoes significant changes in typically developing and autistic early adolescents.

Information sampling about others' trustworthiness prior to cooperation allows humans to minimize the risk of exploitation. Here, we examined whether early adolescence or preadolescence, a stage defined as in between childhood and adolescence, is a significant developmental period for strategic social decisions. We also sought to characterize differences between autistic children and their typically developing (TD) peers. TD (N=48) and autistic (N=56) 8- to 12-year-olds played an online information sampling trust game. While both groups adapted their information sampling and cooperation to the various trustworthiness levels of the trustees, groups differed in how age and social skills modulated task behavior. In the TD group social skills were a stronger overall predictor of task behavior. In the autistic group, age was a stronger predictor and interacted with social skills. Computational modeling revealed that both groups used the same heuristic information sampling strategy-albeit older TD children were more efficient as reflected by decreasing decision noise with age. Autistic children had lower prior beliefs about the trustee's trustworthiness compared to TD children. These lower priors indicate that children believed the trustees to be less trustworthy. Lower priors scaled with lower social skills across groups. Notably, groups did not differ in prior uncertainty, meaning that the priors of TD and autistic children were equally strong. Taken together, we found significant development in information sampling and cooperation in early adolescence and nuanced differences between TD and autistic children. Our study highlights the importance of deep phenotyping of children including clinical measures, behavioral experiments and computational modeling. RESEARCH HIGHLIGHTS: We specified how early adolescents with and without an autism diagnosis sampled information about their interaction partners and made cooperation decisions in a strategic game. Early adolescence is a significant developmental period for strategic decision making, marked by significant changes in information sampling efficiency and adaptivity to the partner's behavior. Autistic and non-autistic groups differed in how age and social skills modulated task behavior; in non-autistic children behavior was more indicative of overall social skills. Computational modeling revealed differences between autistic and non-autistic groups in their initial beliefs about cooperation partners; autistic children expected their partners to be less trustworthy.

Beauty in the eyes of the beholder

We investigate the unconscious influence of beauty on perceptions of commonly-sought employee traits. To do this, we develop a set of photos rated for “societal attractiveness” and use eye-tracking technology to measure participants' pupil sizes while they rate the same set of photos on perceived levels of competence, friendliness, and trustworthiness. We find that the same autonomic response to attractiveness occurs even when participants are asked to rate individuals on traits other than attractiveness. Each additional millimeter of pupil dilation results in about a seven percentage point increase in the perception of rated characteristics. Our data also suggest that societal and personal perceptions of beauty are substitutes rather than complements. These findings contribute to our understanding of the unconscious biases underlying the beauty premium and highlight the importance of considering both personal and societal perceptions of beauty in evaluating individuals. These results are important for labor market outcomes and suggest the need for further research on the unconscious role of beauty in shaping economic opportunities.

The Paradox of Information Control Under Authoritarianism: Explaining Trust in Competing Messages in China

To steer public opinion, autocracies prioritize state media reports of political news while marginalizing commercial and foreign media. Can this dominance guarantee people’s trust in state media news? We contend that rumors, circulated via informal channels and resistant to state information control, present a formidable challenge to public trust in state media news. Our two survey experiments in China pitted news of varying information quality (e.g. informative/detailed reports vs cursory mentions of events) from state media sources against rumors, showing that state media news can retain high levels of trustworthiness only if its information quality is high; however, low-quality state media news resulting from information control diminishes its trustworthiness and prompts people to believe rumors. Low-quality rumors have more negative effects than high-quality rumors on news trustworthiness and citizens’ satisfaction with government policies. Thus, information control can paradoxically erode trust in state media, which often represent the government in autocracies.

Consumer trust in organic food producers and its influence on consumers’ attitudes toward food reformulation and its sensory consequences

In Europe, high targets of 25 % are set for the expansion of organic agriculture farmland by 2030. As organic food is a credence good, consumer trust is of particular importance. In this research, it is examined to what extent consumers differ in their trust in organic food producers and whether consumers have different attitudes toward reformulation measures in Germany. The sample consists of 1038 participants. Confirmatory factor analysis in combination with latent profile analysis was used to analyze the data. The results show that three segments exist. The first segment (9.15 %) does not trust, the second segment (63.87 %) shows neither trust nor distrust, while the third segment (26.97 %) shows a high level of trust toward organic food producers. The findings about the different levels of trustworthiness among the different consumer profiles can be used by food producers to design communication strategies specifically targeted at each segment.

Reexamining health messages in the political age: The politicization of the COVID‐19 pandemic and its detrimental effects on vaccine hesitancy

AbstractOur work investigates the extent to which the politicization of health science may have impacted consumers' vaccine hesitancy during the COVID‐19 pandemic. This inter‐disciplinary, multi‐method manuscript reports the results of three empirical investigations designed to examine how the consumers' political leanings and the sources they rely on for information might influence their decisions to receive a COVID‐19 vaccine. We explore how radically opposing viewpoints regarding the pandemic may have eroded public trust in government institutions and health science during the months leading up to the 2020 U.S. presidential election. In addition, we examine how consumers with opposing political leanings may be differentially influenced by promotional messages that represent the two dominant contrasting viewpoints regarding the COVID‐19 pandemic. Importantly, we find that low vaccine‐hesitant Trump voters can be successfully targeted for pro‐vaccination interventions using highly credible spokespeople, perceived to have high levels of expertise and trustworthiness.

Relating Facial Trustworthiness to Antisocial Behavior in Adolescent and Adult Men.

Here, we investigate how facial trustworthiness-a socially influential appearance variable-interrelates with antisocial behavior across adolescence and middle adulthood. Specifically, adolescents who look untrustworthy may be treated with suspicion, leading to antisocial behavior through expectancy effects. Alternatively, early antisocial behaviors may promote an untrustworthy appearance over time (Dorian Gray effect). We tested these expectancy and Dorian Gray effects in a longitudinal study that followed 206 at-risk boys (90% White) from ages 13-38 years. Parallel process piecewise growth models indicated that facial trustworthiness (assessed from photographs taken prospectively) declined during adolescence and then stabilized in adulthood. Consistent with expectancy effects, initial levels of facial trustworthiness were positively related to increases in antisocial behavior during adolescence and also during adulthood. Additionally, higher initial levels of antisocial behavior predicted relative decreases in facial trustworthiness across adolescence. Adolescent boys' facial appearance may therefore both encourage and reflect antisocial behavior over time.

Investment strategies and coordination for green food supply chain: a further research considering the inputs of the blockchain-based traceability system

PurposeTo study these issues, the authors chose a GFSC with one producer and one material supplier as research object, the supplier will offer green material to the producer and the producer will make green food using green production technology. Then, the authors proposed that consumers' perceived value was determined by the trustworthiness levels of the related green and quality-safety information provided by the supplier and the producer. Then, considering the trustworthiness levels of the green and quality information provided by the supplier and the producer, the authors improved the demand function. Afterwards, we constructed four investment models and their income models are built and then a cost-sharing and revenue-sharing contract (hereafter, CSRS) was adopted to coordinate the GFSC.Design/methodology/approachWith the growth of consumers environmental awareness and life level, consumers' requirements for green and high quality food are growing. In recently years, to increase consumers' perceived trustworthiness on the product greenness and quality levels, stakeholders in green food supply chain (hereafter, GFSC) start to adopt the blockchain-based traceability system (hereafter, BLTS). For investors, they need to know the investment conditions and how to coordinate the GFSC.Findings(1) When the revenue-sharing coefficient is less than three-fourths and higher then a certain vaule, the cost-sharing and revenue-sharing contract can make the GFSC coordinate. (2) The investment cost threshold of the BLTS has a positive relationship with the trustworthiness improvement levels of the green and quality information, the green degree of food products and the quality of food products. (3) In the proposed four investment situations, as the growth of consumers perceived credibility coefficient about the greenness information and the quality information, chain members' revenues will increase. In addition, comparing with co-investing the BLTS, benefits of chain members are lower than them in the sole investment model.Originality/value(1) The demand function we proposed can help chain members forecast market demand to support production or ordering decisions. (2) The investment decision policies can offer a theoretical reference for chain members to use the BLTS. (3) The CSRS will offer the theoretical reference for coordinating the supply chain after using the BLTS. Furthermore, our study method can be referenced by other scholars. (4) The study method can offer a method reference for researchers who do a similar discussion in a manufacturing supply chain. Although, our research cannot guide the industrial practices, it can serve as a reference of the similar research in industry.

Shared Nationality in Social Exchange: A Trust Vignette Experiment in the United States, South Africa, and Switzerland

Empirical research suggests that societies that are diverse as a result of international migration have lower levels of social trust, but little is known about the mechanisms underlying this relationship. The authors test one possible mechanism: that conationality increases interpersonal trust and the willingness to reciprocate trust. As part of large-scale surveys in the United States, South Africa, and Switzerland, respondents were presented with trust vignettes in which information about the nationality of the interaction partner was systematically varied. Despite overall country-level differences in levels of trust and trustworthiness, no in-group bias associated with conationality was found in these types of interactions. This suggests that the negative association between ethnic diversity and social trust cannot be explained by differences in relational trust conditional on sharing the same nationality.

Analyzing the Impacts of Diversity on Organizational Resilience: Analytical Review and Formulation

The successful implementation of diversity to structure organizational resilience (OR) requires the leadership's ability to recognize and study the controlling elements of the phenomena that can guarantee organizations to have a greater ability to respond to crises facing them provided there has been an establishment of a solid foundation and the essential group of people, funding, decapitation plans, and technology. This study primarily focuses on three major elements, such as the structure of an organization, the system setup of such organization, and the existence of diversity within that organization under study. Within these elements, we discuss subfactors evolving around them while emphasis is placed mostly on diversity and further discussion will be needed on other subfactors highlighted in this study. The work is presented in the following fundamental requirements that define OR in a diverse environment. The OR system structure presents the levels of preparedness, collaboration, trustworthiness, responsibility, and adaptability that allow organizations to measure their agility; the technical framework of OR shows the ability to improve individual management disciplines of organizations to manage risks; and the protocol will implement OR systems into the reliable, attainable, and successful system.

Multi-Objective Big Data View Materialization Using NSGA-III

Present day applications process large amount of data that is being produced at brisk rate and is heterogeneous with levels of trustworthiness. This Big data largely consists of semi-structured and unstructured data, which needs to be processed in admissible time so that timely decisions are taken that benefit the organization and society. Such real time processing would require Big data view materialization that would enable faster and timely processing of decision making queries. Several algorithms exist for Big data view materialization. These algorithms aim to select Big data views that minimize the total query processing cost for the query workload. In literature, this problem has been articulated as a bi-objective optimization problem, which minimizes the query evaluation cost along with the update processing cost. This paper proposes to adapt the reference point based non-dominated sorting genetic algorithm, to design an NSGA-III based Big data view selection algorithm (BDVSANSGA-III) to address this bi-objective Big data view selection problem. Experimental results revealed that the proposed BDVSANSGA-III was able to compute diverse non-dominated Big data views and performed better than the existing algorithms..