Trust Issues Research Articles

Readiness of and barriers for community pharmacy professionals in providing and implementing vaccination services

BackgroundCommunity pharmacy professionals are essential for healthcare delivery, particularly for administering vaccination services. However, there is a lack of substantial evidence documenting their role in vaccination within Ethiopia.ObjectivesThis study aimed to assess community pharmacy professionals’ readiness to provide vaccination services, identify barriers hindering the implementation of these services, and determine factors influencing the provision of vaccination services by community pharmacy professionals.MethodsA cross-sectional study was conducted among community pharmacy professionals in Debre Markos and Injibara Town from April 15 to May 13, 2024. The data were collected using a structured questionnaire, and descriptive statistics were used to analyze the findings.ResultsThe study revealed that a significant majority of community pharmacy professionals perceived that they had adequate vaccine knowledge and were easily accessible to the community. However, barriers such as lack of regulation, time constraints, workload concerns, patient trust issues, and infrastructure challenges hinder the implementation of vaccination services. Factors influencing the provision of vaccination services included the need for enhanced education and training, financial reimbursement, patient demand, infrastructure improvements, collaboration with other healthcare providers, and pharmacists’ special interest in vaccination.ConclusionsCommunity pharmacy professionals exhibit readiness to provide vaccination services. However, significant barriers such as regulatory constraints, time pressures, workload concerns, patient trust issues, and infrastructure challenges hinder their full participation. Addressing these barriers and leveraging pharmacists’ expertise is essential for optimizing service delivery and improving public health outcomes. Advocating for policy changes, developing comprehensive training programs, establishing clear guidelines, investing in infrastructure improvements, conducting public awareness campaigns, and fostering collaboration with other healthcare providers are recommended to facilitate the provision and implementation of vaccination services by community pharmacy professionals in Ethiopia.

Agricultural economic security under the model of integrated agricultural industry development

As globalization and technological advancements progress, the integrated agricultural industry development model has become crucial for agricultural modernization. This model fosters inter-industry integration, enhancing agricultural competitiveness and sustainability. However, it also introduces new challenges, such as increased risk spillover and outdated regulatory mechanisms. This study employs a vector autoregression (VAR) model and a directed weighted risk spillover network for a quantitative analysis of risk dynamics within agricultural markets, identifying pathways and influencers of risk transmission across industry segments. A blockchain-based regulatory framework is proposed to improve traceability, regulatory efficiency, and data security in agricultural product management. This includes the development of registration processes, smart contracts, consensus mechanisms, and data upload protocols. The research expands the theoretical base of agricultural economic security and offers practical policy guidance, with substantial academic and practical implications. It highlights how blockchain can address market trust issues, mitigate information asymmetry, and reduce potential risks, contributing to the healthier development of agricultural economy.

Artificial Intelligence in Medicine and Medical Education: Current Applications, Challenges, and Future Directions

AI's rise in medicine promises personalized care, better diagnoses, and innovative training. It analyzes images, predicts diseases, and tailors treatments. However, ethical concerns loom. Biased data can lead to unfair diagnoses, and some AI systems lack transparency, raising trust issues. The editorial proposes solutions: ethical frameworks, transparent AI, and legal regulations. It envisions a future where AI complements doctors, requiring collaboration across fields. To prepare future physicians, medical schools need to integrate AI and ethics into their curriculum. AI holds immense potential, but challenges must be addressed. Through collaboration and responsible development, AI can revolutionize medicine alongside human expertise.

A Consumer Trust Assessment Model for Online Shopping Based on Fuzzy Fusion Decision-Making

With the rapid development of e-commerce, online shopping has become an indispensable part of people's daily lives. However, consumers often face trust issues during online shopping, such as product quality and seller integrity, which directly impact their shopping experience and purchasing decisions. Therefore, accurately assessing consumer trust has become a crucial task. This study first constructs a consumer trust assessment system, analyzing and selecting key factors related to consumer trust, and establishes a model for assessing consumer trust for online shopping. Subsequently, we propose an assessment method based on text mining and deep learning sentiment analysis techniques to extract consumer sentiment information from specified consumer reviews. Furthermore, through fuzzy decision-making fusion strategy, we integrate sentiment information from the dimensions of quality assurance, reliability, and responsiveness to enhance the accuracy of the assessment.

Empowering communication strategy for safe cyberspace: insights from trust-based quality information

Purpose The recent trends of managing how to achieve communication in a safe cyberspace have attracted the particular attention from scholars worldwide. The strategic initiative of having an active organization of communication pathways is required for further scholarly elaboration to enable a subsisting safe community in cyberspace. An example of the challenges is the issue of trust in information or questionable issues denoting lack of detail and clarity. Thus, this obviously refers to a dubious circumstance that needs to explain the situation on addressing the critical issue of trust-based quality information. To respond to such an apparent situation, this paper aims to critically explore the insightful value of trust in information as essential element of quality assurance. Such arranged strategy would enable individual capacity and accountability in achieving the efficient communication management for a safe cyberspace. Design/methodology/approach The study attempted a critical review of recent literature by analysing peer-reviewed articles from journals, books, proceedings and book chapters related to theme of communication management for safe cyberspace. Findings The finding reveals that the strategic approach of enabling effective communication management for safe cyberspace is actualized through advancing trust-based quality information. Originality/value This paper aims to contribute towards enhancing communication management for safe cyberspace by addressing issues relating to trust that would lead to the quality of information.

Public Trust: Dampak Exclusion dan Inclusion Error Data Program Keluarga Harapan

The general objective of the Family Hope Program (PKH) is to reduce poverty, increase the accessibility of poor people to public services, especially education and health. PKH targeting is based on Integrated Social Welfare Data (DTKS) which is an update of the results of the Social Protection Program Data Collection (PPLS). Efforts to improve the welfare of the poor often stumble over fundamental problems related to data collection. Problems that arise from data not being in sync are inclusion errors and exclusion errors. As a result, the aid distributed is not on target and does not even fulfill the citizens' sense of justice. As a result, the level of public trust in the government decreases. This research aims to obtain an overview of the impact of data collection on public trust. This research uses a qualitative approach with data collection methods using interviews and secondary data analysis. The research results show that there are still very poor household (RTSM) in Cunca Lolos Village that have not yet become beneficiary group (KPM) PKH. This exclusion error occurs because the data collection and data updating process has not been carried out in the DTKS. The impact on the issue of public trust among citizens. Those who are eligible but are not targeted by the program consider the government to be unfair in its services and policies. Finally, citizens do not participate actively in public activities.

Influence of AI on Shopping Experience of Generation Z Customers

Artificial intelligence (AI) refers to the simulation or approximation of human intelligence in machines. AI is being used today across different industries from finance to healthcare. It is also reinventing the retail landscape. Computer vision is enabling frictionless checkout and enhancing loss prevention for brick-and-mortar stores. Retailers that harness AI to connect with customers and operate more efficiently will be better positioned to thrive in today’s AI powered world. The study is conducted with the sample size of 61 respondents by conducting survey through questionnaire in Palakkad district. This paper attempts to get an insight into the influence of AI technologies in the shopping experience of customers especially on generation Z. It is high time that customers become aware of different implications of AI and how it is contributing to their shopping life. This paper further talks about the trust issues of customers when it comes to AI and personal data sharing and how it can be improved by taking necessary measures by retailers like educating the consumers in a proper way about AI. Customers also agree that AI has made a positive impact on their shopping experience especially in customer support after purchase.

A survey of ontology-enabled processes for dependable robot autonomy.

Autonomous robots are already present in a variety of domains performing complex tasks. Their deployment in open-ended environments offers endless possibilities. However, there are still risks due to unresolved issues in dependability and trust. Knowledge representation and reasoning provide tools for handling explicit information, endowing systems with a deeper understanding of the situations they face. This article explores the use of declarative knowledge for autonomous robots to represent and reason about their environment, their designs, and the complex missions they accomplish. This information can be exploited at runtime by the robots themselves to adapt their structure or re-plan their actions to finish their mission goals, even in the presence of unexpected events. The primary focus of this article is to provide an overview of popular and recent research that uses knowledge-based approaches to increase robot autonomy. Specifically, the ontologies surveyed are related to the selection and arrangement of actions, representing concepts such as autonomy, planning, or behavior. Additionally, they may be related to overcoming contingencies with concepts such as fault or adapt. A systematic exploration is carried out to analyze the use of ontologies in autonomous robots, with the objective of facilitating the development of complex missions. Special attention is dedicated to examining how ontologies are leveraged in real time to ensure the successful completion of missions while aligning with user and owner expectations. The motivation of this analysis is to examine the potential of knowledge-driven approaches as a means to improve flexibility, explainability, and efficacy in autonomous robotic systems.

Knowledge uptake from lived experience regarding sustainable groundwater management: complementing scientific knowledge in urban policymaking

Urbanization can pose water management challenges in cities while overlooking the possibilities of residents’ lived experience and collaborative action learning. We show how the conceptual model of the Lived Experience of Sustainable Urban Groundwater Level identifies several aspects of local knowledge development through an ex-post case study in Rotterdam’s Flower Neighbourhood (The Netherlands), where too low groundwater levels threaten house foundations. Three types of local knowledge development emerged: (i) performing and monitoring well measurements by residents, (ii) environment-specific insights collected by residents and shared with civil servants, and (iii) collaboration on groundwater management experiments, resulting in empirical groundwater data. Overcoming communication barriers, trust issues, and power dynamics are crucial for effectively retrieving and integrating lived experience into collective learning for urban sustainable development.

Predictive ability of the health belief model in HIV testing and counselling uptake among youth aged 15–24 in La-Nkwantanang-Madina Municipality, Ghana

BackgroundMajority of new Human Immunodeficiency Virus (HIV)-positive persons in Ghana are aged 15–24. HIV prevalence among persons aged 15–24 years, a proxy for new infections, remained stable at 1.5% for 2017 and 2018, making it a significant public health concern. Yet only 26.4% of females and 8.6% of males aged 15–24 years know their HIV status. This study determined the predictive ability of the Health Belief Model (HBM) in HIV testing and counselling (HTC) uptake among youth (15–24 years) in the La-Nkwantanang Madina Municipality, Ghana.MethodsA cross-sectional design was adopted for the study, using a multistage sampling method to select 415 youth aged 15–24. Data were collected using a structured interviewer-administered questionnaire, and analysed using binomial logistic regression with STATA software version 16.0 at p < 0.05 significance level and at 95% confidence interval.ResultsHTC uptake was 29.2%. Perceived susceptibility, perceived barriers, and perceived self-efficacy predicted HTC uptake. Youths with a high-risk perception for contracting HIV [OR = 3.03; 95% CI = 1.46, 6.30, p = 0.003], who perceived that they can contract HIV if not protected [OR = 3.69; 95% CI = 1.47, 9.22, p = 0.005], and worry about getting HIV [OR = 3.03, 95% CI = 1.61, 5.69, p < 0.001] (perceived susceptibility) were more likely to uptake HTC. Youths who had no trust issues with health workers [OR = 3.53; 95% CI = 1.46, 8.53, p = 0.005] and those who were not afraid of positive HIV test results [OR = 5.29; 95% CI = 2.66, 10.51, p,0.001] (perceived barriers) were more likely to uptake HTC. Youths who had no difficulties in turning up for appointments (perceived self-efficacy) had higher odds of HTC uptake [OR = 11.89, 95% CI = 6.73, 20.98, P < 0.001]. For the modifying factors, being married [OR = 2.96; 95% CI = 1.65–5.33], and having knowledge of HTC [OR = 9.10; 95% CI = 2.16–38.3], significantly influenced HTC uptake.ConclusionHealth promotion interventions to increase HTC uptake should focus on heightening the perception of susceptibility to HIV, reducing the barriers to HTC uptake, and increasing the self-efficacy for HTC uptake. The interventions should also target the significant modifying factors.

Digital Defiance’s Affecting Use of Information Communication Technology Deployed for Prevention and Detection of Crime in Community Policing in Malawi

ICTs digital space has modernized citizen socialization amongst citizens to enhance security and is augmenting for lack of resource constraints as well as promoting less agents on ground thereby strengthening internal security through community policing. Availability of ICT gadgets, applications, and initiatives make simple and influential crime reporting and crime control. This study examines factors that affect the use of information communication technology deployed for crime prevention and detection in community policing. Mixed methods exploratory sequential design was used to collect data. Qualitative purposive sampling targeted four focus group discussions of 10 participants each and one key informant interview of 10 participants, interview guide instrument was utilized. Quantitative household survey used Yamene (1969) formular to identify 432 respondents who were randomly distributed into 10 locations of Muloza and used structured questionnaire. Qualitative data analysis follows transcribing, coding, and grouping into sub-themes, themes that answer research objectives aided by NVivo application. Quantitative analysis used descriptive statistics in SPSS version 20. Under pragmatics paradigm guided by democratic participation, social-disorganization and broken window theories, results show that the majority of ICTs are mobile telephones, which play an important role in the storage, dissemination, and replication of security information in community policing. Dominated by married persons at 56.5% in the youth category of 57.2% respondents. The police are faced with the technical challenge of installing and maintaining ICTs. The police have no ICT resources deployed for the prevention, detection, and investigation of crime in Muloza. Hence, the police rely on personal mobile phones, which are operated on do it yourself as convenience by victim or law enforcement agent to follow an issue. Regression when tested at confidence interval 95.0% showed that some factors have significance value on use of ICTs deployed for prevention and detection of crime in community policing (i) Age at p=.001 (ii) Education at p=.000 (iii) Income at p=.000 (iv) Knowledge expertise at p=.000 (v) Cost of accessing technologies at p=.009 and (vi) Trust issues between police and people at p=.009. The importance of ICTs is that they have revolutionized monitoring and surveillance that may improve prevention, detection, and investigation of crime in community policing, and allow for storage, dissemination, and replication of security information. Proper use of ICTs for prevention and detection of crime may improve police investigations. Citizens’ wide use of ICTs in formal and non-formal ways may help reduce corruption through wide information storage replication and dissemination.

Trust Issues? Article 99 RoP Reasoned Orders in the Preliminary Reference Procedure

Trust Issues? Article 99 RoP Reasoned Orders in the Preliminary Reference Procedure

Do Humans Trust AI in HRM? Why Do? Why Not? — Insights from a Decade of Research

This literature review investigates the complex issue of trust in the context of Artificial Intelligence (AI) applications in Human Resource Management (HRM). Adopting the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically reviewed 43 research articles published between 2013 and 2023 to examine the attitudes towards AI as a disruptive technology in HRM practices, the ethical and legal challenges that influence trust, and the strategies for building a trustworthy future. The findings reveal a mixed picture of trust, with growing adoption of AI in various HRM practices, such as recruitment, selection, performance management, and employee development, accompanied by significant concerns related to bias, transparency, privacy, and job displacement. The review identifies key factors that affect trust in AI, including perceived usefulness, ease of use, and fairness, as well as the ethical and legal challenges that erode trust, such as data privacy, algorithmic bias, and lack of explainability. Furthermore, it discusses the implications for HRM professionals and proposes strategies for enhancing trust, such as ensuring human oversight, promoting transparency, and developing AI literacy skills. This review contributes to the research on AI in HRM by providing a nuanced understanding of the trust dynamics, challenges, and opportunities associated with this disruptive technology, offering valuable insights for both researchers and practitioners.

Trustworthy and collaborative traceability management: Experts’ feedback on a blockchain‐enabled framework

AbstractBlockchain technology has attracted significant attention in both academia and industry. Recently, the application of blockchain has been advocated in software engineering. The global software engineering paradigm exacerbates trust issues, as distributed and cross‐organizational teams need to share software artifacts. In such a context, there is a need for a decentralized yet reliable traceability knowledge base to keep track of what/how/when/by whom software artifacts were created or changed. This study presents a blockchain‐enabled framework for trustworthy and collaborative traceability management and identifies benefits, challenges, and potential improvements based on the feedback of software engineering experts. A qualitative approach was followed in this study through semistructured interviews with software engineering (SE) experts. Transcripts were analyzed by applying the content analysis technique. The results indicated the emergence of five categories, further grouped into three main categories: experts' perceptions, blockchain‐based software process improvement, and experts' recommendations. In addition, the findings suggested four archetypes of organizations that may be interested in blockchain technology: distributed organizations, organizations with contract‐based projects, organizations in regulated domains, and regulators who may push the use of this technology. Further efforts should be devoted to the integration of the proposal with tools used throughout the software development lifecycle and leveraging the potential of smart contracts in validating the implementation of requirements automatically.

Community notes increase trust in fact-checking on social media.

Community-based fact-checking is a promising approach to fact-check social media content at scale. However, an understanding of whether users trust community fact-checks is missing. Here, we presented Americans with 36 misleading and nonmisleading social media posts and assessed their trust in different types of fact-checking interventions. Participants were randomly assigned to treatments where misleading content was either accompanied by simple (i.e. context-free) misinformation flags in different formats (expert flags or community flags), or by textual "community notes" explaining why the fact-checked post was misleading. Across both sides of the political spectrum, community notes were perceived as significantly more trustworthy than simple misinformation flags. Our results further suggest that the higher trustworthiness primarily stemmed from the context provided in community notes (i.e. fact-checking explanations) rather than generally higher trust towards community fact-checkers. Community notes also improved the identification of misleading posts. In sum, our work implies that context matters in fact-checking and that community notes might be an effective approach to mitigate trust issues with simple misinformation flags.

Identifying Community-Based Entrustable Professional Activities for Medical Students Through a Modified Delphi Process.

Recognition of the need for medical education to train physicians who are skilled at supporting population health and work beyond traditional health care settings is growing. Entrustable professional activities (EPAs) for medical students typically have centered around activities taking place in the clinical workplace; however, EPAs that involve working with community members in community contexts have not been clearly established. We used a three-stage online modified-Delphi method to identify community-based EPAs for University of Wisconsin School of Medicine and Public Health medical students. We recruited key stakeholders to participate and asked them, based on their experience, to generate a list of community-based tasks that they believed graduates should be trusted to perform. Subsequently, using a five-point anchored Likert scale (1=strongly disagree to 5=strongly agree), we asked participants to rate their level of agreement with each identified task becoming an EPA. An a priori definition of consensus was established. Twenty-two tasks reached consensus as potential community-based EPAs. The tasks with the highest mean ratings were "addressing trust issues with the medical community amongst the local population" (mean=4.71), "meeting with community members around a health topic" (mean=4.64), "identifying opportunities for disease prevention" (mean=4.64), and "identifying policies that impact community outcomes" (mean=4.57). The identified community-based tasks can support the augmentation of existing community-based curriculum and help identify areas for novel curriculum and assessment development. Lessons learned from this local effort could be helpful to other programs seeking to establish and refine community-based curricula.

From Digital Philanthropy to Sustainable Empowerment: Dompet Dhuafa Riau’s Mechanisms in Fundraising and Trust Building

Dompet Dhuafa Riau’s transition to digital philanthropic management has significantly increased voluntary donations, addressing the concerns of digital philanthropy scholars about the impact of technology on philanthropic interactions. This research aims to uncover the practical mechanisms employed by Dompet Dhuafa Riau in transforming into a digital media-utilizing philanthropic institution. Using a qualitative method with a phenomenological approach, the study reveals a well-established transition pattern that integrates elements of traditional philanthropy into digital activities. Digital media serves as a tool to facilitate voluntary donations from donors, effectively addressing trust issues commonly associated with transitioning to online platforms by ensuring fund allocation emphasizes sustainability. Service, mentoring, and training mechanisms further enhance Dompet Dhuafa Riau’s credibility as a reliable philanthropic institution, strengthening donor confidence and encouraging continued donations. This shift demonstrates that incorporating media into the management of philanthropic organizations creates a complex relationship between philanthropic institutions and the public, mediated by the unique dynamics of digital platforms.

Communicating the cultural other: trust and bias in generative AI and large language models

Abstract This paper is concerned with issues of trust and bias in generative AI in general, and chatbots based on large language models in particular (e.g. ChatGPT). The discussion argues that intercultural communication scholars must do more to better understand generative AI and more specifically large language models, as such technologies produce and circulate discourse in an ostensibly impartial way, reinforcing the widespread assumption that machines are objective resources for societies to learn about important intercultural issues, such as racism and discrimination. Consequently, there is an urgent need to understand how trust and bias factor into the ways in which such technologies deal with topics and themes central to intercultural communication. It is also important to scrutinize the ways in which societies make use of AI and large language models to carry out important social actions and practices, such as teaching and learning about historical or political issues.

THE INTERPLAY BETWEEN E-COMMERCE OPTIMIZATION, CONSUMER TRUST, AND IMPULSIVE BUYING: A COMPREHENSIVE ANALYSIS

This study investigates the burgeoning e-commerce market in Thailand, focusing on consumer trust, e-commerce optimization, and impulsive buying behaviors among Generation Z. With a significant portion of Thailand's population engaging in online shopping, the study aims to understand the factors influencing consumer trust and the impact of e-commerce optimization on impulsive buying. Using a quantitative approach, data were collected from 721 respondents aged 18-28 and data analysis using SEM-PLS. The main findings show that e-commerce optimization has a significant positive correlation with consumer trust (R² = 0.965) and impulsive buying (R² = 0.988). This research provides practical contributions for e-commerce practitioners to enhance their marketing and operational strategies based on these findings The results indicate a strong positive correlation between consumer trust and e-commerce optimization, The practical implications of these findings suggest that e-commerce platforms should focus on enhancing their security features and user-friendliness to foster consumer trust, which in turn can lead to increased impulsive buying. Additionally, businesses can utilize these insights to design more effective marketing strategies that leverage consumer trust to drive impulsive purchases. This research provides practical contributions for e-commerce practitioners to enhance their marketing and operational strategies based on these findings. Despite challenges such as consumer trust issues and logistical inefficiencies, the potential for e-commerce growth in Thailand remains substantial, driven by government support and private sector innovation.

Cognitivism as the Basis of Artificial Intelligence

The article examines the main issues of cognitivism as the basis of artificial intelligence (AI) in a modern philosophical interpretation of these entities. A classification of AI is given according to the level of cognitivism of basic functions. We consider the issues of the evolution of the cognitive capabilities of artificial intelligence. The problems of predictability of the negative impact of AI on society are raised. The article highlights the main cognitive distortions that are possible when using artificial intelligence in research, namely, the illusion of research breadth. The authors provide recommendations for researchers and editors of academic journals regarding a competent use of AI in scientific experiments. This work also raises the issue of trust in the field of cybersecurity of AI systems. The authors consider the hypothesis about the presence of consciousness in chatbots and draw clear conclusions about its absence.