Journal of Foresight and Health Governance

The future is undergoing astonishing transformations. Technologies are reshaping the structure and nature of our world at a tremendous pace every day. Artificial intelligence and blockchain can be regarded as two of the most significant future technologies, whose full scope of influence remains not only unknown but is also triggering waves of remarkable changes, catching many businesses off guard and transforming numerous processes and chains. Today, achieving a comprehensive product information chain from production to sale is a critical issue that matters greatly to consumers. This is especially emphasized in the food industry. Knowing the components of a product, who produced it, on what date, the transportation systems and methods used, and the time taken to reach the customer are all crucial elements in service quality. In this context, the use of blockchain technology proves highly efficient. Blockchain is capable of decentralized and immutable storage of verified data and has the potential to render current financial payment methods obsolete by replacing them entirely. At present, many large organizations such as Walmart chain stores are utilizing this technology, particularly in the management of their supply chains. This article investigates the application of blockchain technology in the product supply chains of chain stores using the Futures Wheel method, an exploratory tool for examining the consequences and impact of this technology in the retail industry. The implications of blockchain in the retail sector and chain stores were studied across 18 dimensions, based on expert opinions and global experiences. Given the many unknown aspects of this technology, experts participated in two specialized panels in a brainstorming-friendly environment and identified 18 positive consequences of blockchain for product tracking and traceability. The most important contribution of this study for consumers is the confidence it provides regarding their purchases.

Appropriate organizational responses to environmental variables have oriented strategic planning toward novel approaches such as strategic foresight. The purpose of this study is the qualitative development of the External Factors Evaluation (EFE) Matrix affecting Iran’s sports industry using scenario planning. This research is developmental–applied in terms of purpose, mixed-method in nature, and follows a survey path incorporating cross-impact analysis and scenario planning. The statistical population included associate professors and full professors in the field of sports management, selected through a mixed sampling method in four phases. The results indicated that, based on different states of key uncertainties in the Scenario Wizard software, four feasible scenarios with high internal consistency were identified. Based on the occurrence probabilities of their various assumptions, the EFE matrix can be developed. Therefore, the proposed matrix of this study can assist in formulating more resilient strategies in the uncertain environment of Iran's sports industry by enabling more precise identification and evaluation of external factors. The innovation of the present research lies in integrating the EFE matrix—as one of the most important tools in strategic management—with scenario planning, one of the most significant methods in futures studies. Hence, the use of the evolved EFE matrix extracted from this research is recommended not only for managers of organizations active in the sports industry but also for long-term planners in other sectors and organizations.

The present study was conducted with the aim of identifying athletic talent using the adaptive method of core indicators in professional athletes. This research is applied in terms of purpose and descriptive-analytical in terms of nature and method, utilizing a mixed-methods approach (qualitative-quantitative). The statistical population in the qualitative section included selected scientific articles from domestic and international databases, as well as academic experts and elite athletes. Sampling was conducted purposively, and data were collected through semi-structured interviews and analyzed using thematic analysis. In the quantitative section, the statistical population consisted of 36 professional and elite athletes selected using purposive sampling. Data were collected using a researcher-made questionnaire and analyzed using a one-sample t-test. The results indicated that athletic talent identification through the adaptive method of core indicators includes seven main dimensions (genetic, physiological, anthropometric, psychological, biological, living environment, and lifestyle) and 53 indicators. Of these, 46 indicators were in a favorable condition, while 7 indicators (having athlete parents, sitting height, lower limb length, pelvic width, thoracic circumference, abdominal circumference, and the use of university-educated professionals in talent identification centers) were in an unfavorable condition. The highest means were related to the indicators of intrinsic interest in competitive sports (4.47), physical health (4.42), and mental toughness (4.39). Athletic talent identification is a complex and multidimensional process that requires attention to a range of genetic, physiological, anthropometric, psychological, biological, and environmental indicators. To succeed in this process, a comprehensive and scientific talent identification system must be designed and implemented with the participation of academic experts and by considering all these indicators. Furthermore, special attention should be given to the indicators that are in an unfavorable condition, and appropriate plans should be developed to improve them.

Health tourism is a dynamic global phenomenon; however, notable knowledge gaps remain concerning its development in emerging nations characterized by unique geopolitical and economic contexts. This research investigates the development of health tourism in Iran through a qualitative methodology, employing semi-structured interviews with 23 experts, comprising 9 healthcare providers, 8 tourism facilitators, and 6 representatives from regulatory bodies. We employed Braun and Clarke's six-step framework for thematic analysis. The findings revealed three primary themes derived from the 45 codes: (1) strategic positioning considerations, which include healthcare service excellence, cost advantage, and destination appeal; (2) operational challenges and solutions, addressing regulatory barriers, service delivery gaps, and marketing and reputation management; and (3) imperatives of innovation and sustainability, including technology integration, ecosystem development, and quality and sustainability frameworks. Iran exhibits considerable potential due to its specialized medical expertise and competitive pricing, notwithstanding the challenges posed by international sanctions and prevailing perception issues. The integrated framework of the study demonstrates the interrelationships among these dimensions, enhancing both theoretical comprehension of emerging destination development and practical implementation strategies. Future research should integrate quantitative methods, undertake longitudinal studies to assess the impacts of technological innovation, conduct comparative analyses with regional competitors, and explore outcomes that prioritize patients from the perspectives of international health tourists. This analysis examines the interplay between geopolitical constraints and healthcare service delivery, providing insights for stakeholders in healthcare, tourism, and regulatory sectors.

This study explores the ethical, social, and policy implications of artificial intelligence (AI) in public health. This qualitative study employed semi-structured interviews with 32 experts in AI research, public health policy, bioethics, and healthcare administration. Participants were recruited through online announcements and professional platforms, ensuring a diverse representation of viewpoints. Data collection continued until theoretical saturation was achieved. Interviews were transcribed verbatim and analyzed using NVivo software through thematic analysis, following an inductive coding approach to identify key ethical, social, and policy concerns. The analysis revealed three main themes: ethical scenarios, social scenarios, and policy scenarios. Ethical concerns included bias in AI models, privacy and data security risks, and trust in AI-driven healthcare, with participants emphasizing the need for bias mitigation strategies and transparent AI governance. Socially, the findings highlighted AI’s impact on the healthcare workforce, disparities in AI accessibility, and the evolving patient-doctor relationship, raising concerns about public trust and the digital divide. Policy challenges centered on the lack of standardized AI regulations, unclear accountability mechanisms, and the need for global collaboration in AI governance, with participants advocating for clearer compliance frameworks and cross-border AI policy alignment. While AI holds transformative potential in public health, its successful integration requires ethical safeguards, inclusive social adaptation, and comprehensive policy frameworks. Addressing algorithmic bias, strengthening data security, fostering public trust, and establishing robust governance structures are essential for ensuring that AI-driven public health interventions align with ethical principles, social equity, and regulatory standards.

This study explores future scenarios of antimicrobial resistance (AMR). This qualitative research employed semi-structured interviews with 19 participants, including experts in public health, epidemiology, healthcare policy, and AMR research. Participants were recruited through online announcements and professional platforms. Theoretical saturation was used to determine the sample size. Data were collected through virtual interviews, transcribed verbatim, and analyzed using NVivo software. A grounded theory approach was applied, with open and axial coding used to identify key themes related to AMR governance, public health preparedness, technological developments, and societal factors. The study identified four major themes influencing AMR’s future trajectory: policy and governance challenges, public health preparedness gaps, technological and scientific barriers, and societal and behavioral factors. Policy inconsistencies, weak enforcement mechanisms, and inadequate surveillance systems were key governance issues. Public health preparedness remained insufficient, with limited healthcare capacity, delayed policy responses, and inadequate community engagement in AMR mitigation. Technological advancements, such as artificial intelligence and antimicrobial alternatives, were seen as promising but hindered by regulatory and financial constraints. Societal drivers of AMR included antibiotic misuse, pharmaceutical marketing influence, and public misconceptions. Participants emphasized the need for coordinated policy interventions, improved surveillance, and increased investment in research and innovation. Addressing AMR requires a globally coordinated response that integrates governance reforms, enhanced public health preparedness, technological advancements, and behavior change strategies. Strengthening regulatory frameworks, increasing funding for AMR initiatives, and promoting international collaboration are essential for mitigating future risks.