Aim: This study aims to provide a comprehensive analysis of the administrative-legal assurance of the reliability and ethics of medical decision-making in wartime conditions, combining normative analysis with empirical data from a frontline Ukrainian hospital. Materials and Methods: The normative framework includes international standards of the World Health Organization, the International Committee of the Red Cross, professional medical associations, the European Charter of Patients' Rights (2002), European Union legislation, and the national healthcare and wartime legislation of Ukraine. The empirical component comprised a cross-sectional anonymous survey conducted between May and September 2025 among 40 healthcare workers at a rural hospital located near the active frontline in the Dnipropetrovsk region. The questionnaire assessed decision-making complexity, perceived probability of errors, stress impact, resource availability, preparedness, and willingness to report incidents. Results: Wartime conditions significantly increase the perceived complexity of clinical decision-making, particularly in resource allocation, evacuation prioritization, and surgical interventions. Respondents reported elevated stress levels and increased risk of errors, primarily associated with limited resources, disrupted logistics, and administrative constraints. The reliability and ethical integrity of medical decisions were found to depend on the availability of updated clinical protocols, state monitoring mechanisms, organized evacuation systems, and guaranteed minimum healthcare services. Conclusions: Effective administrative-legal support is a prerequisite for ensuring both the reliability and ethical soundness of medical decisions in wartime. Strengthening institutional safeguards, resource allocation mechanisms, and clear regulatory guidance is essential to maintain medical standards under extreme conditions.

This article seeks to reevaluate the concept and distribution of social assistance as a means to achieve distributive justice. Utilising the Tafsīr Maqāṣidī approach — an interpretation that reflects God's intentions—this study reconstructs the principles and methods of distributing social assistance to effectively realise distributive justice. The primary focus is on Qur'an Surah Al-Hashr [59]:7, which delineates the guidelines for distributing wealth collected by the government, referred to as al-Fai’. The findings indicate that the distribution of al-Fai’ in the form of social assistance is designed to prevent the concentration of wealth among affluent groups, ensuring that resources are shared with the poor and marginalised (ḍu‘afā’), thereby mitigating societal inequality. From the perspective of Maqāṣid al-Sharī‘ah, the provision of social assistance aims to safeguard religion (ḥifẓ al-dīn), life (ḥifẓ al-nafs), and the state (ḥifẓ al-Dawlah). Furthermore, social assistance embodies principles of justice (al-‘adālah), humanity (al-Insāniyyah), equality (al-Musāwāh), freedom (al-ḥurriyah), and responsibility (al-Mas’ūliyyah). Consequently, it is deemed unacceptable for the distribution of social assistance to be exploited for personal gain or to secure public office. Additionally, applying the Tafsīr Maqāṣidī approach in this context demonstrates how the maqāṣidī -based normative framework can evaluate the ethical soundness of government-initiated programs like social assistance. This research contributes to developing public policy by using the tafsir approach, in this study using Tafsīr Maqāṣidī.

This paper explores the role of African ethical philosophies, particularly Ubuntu, and interreligious dialogue in enhancing AI governance frameworks. It reveals that these philosophies provide robust principles for ethical AI development, emphasizing interconnectedness, community, and mutual respect. Interreligious dialogue synthesizes ethical principles from various religious traditions, such as stewardship, justice, and benevolence. The study concludes that integrating these diverse perspectives can significantly enhance the ethical soundness of AI systems, ensuring they uphold human dignity and social justice. These insights make an important contribution to the ongoing discourse on ethical AI governance, addressing existing gaps and providing practical strategies for inclusive policy development. Policy recommendations include developing ethical guidelines reflecting these philosophies and interfaith ethical principles.

As artificial intelligence (AI) integrates deeper into enterprise workflows, establishing trust in AI systems has become a paramount concern. This article highlights the pivotal role of data engineering in fostering responsible AI development through rigorous data quality, governance, and fairness practices. Using real-world examples from finance, healthcare, and retail, we showcase how critical data engineering techniques—such as data validation, master data management, and bias mitigation—enhance the reliability, compliance, and ethical soundness of AI solutions. We further explore emerging innovations like data mesh, Lakehouse architectures, and real-time data pipelines, emphasizing their potential to scale trustworthy AI in cloud-first environments. By treating data as a strategic asset and applying disciplined engineering principles, organizations can develop AI systems that are not only high-performing but also transparent, equitable, and aligned with regulatory and societal standards.

The rapid decline of undocumented languages in Pakistan threatens the disappearance of invaluable cultural, historical, and linguistic knowledge. Despite a rich linguistic landscape, many regional and minority languages remain poorly described, with limited textual resources or scholarly analysis. This study explores how Artificial Intelligence (AI), particularly Natural Language Processing (NLP) and machine learning techniques, can be effectively utilized to document pragmatic markers and semantic structures in these endangered languages. Pragmatic markers—words or phrases that regulate discourse and convey speaker intention—are crucial to understanding how language reflects social structure, cognition, and cultural interaction. Drawing on fieldwork conducted in multilingual regions of Pakistan, the study integrates transformer-based AI models with traditional linguistic methods to identify and categorize pragmatic markers and their functions. The research demonstrates that AI enhances the efficiency and accuracy of linguistic documentation, especially when applied to low-resource languages. However, it also reveals the irreplaceable value of human linguistic expertise and community engagement in ensuring the authenticity, interpretability, and ethical soundness of AI-generated insights. The findings challenge universalist assumptions about pragmatics, emphasizing cultural specificity and variation. By bridging technology and field linguistics, this study offers a new model for interdisciplinary collaboration in language preservation, paving the way for more inclusive, ethical, and effective documentation practices. Recommendations include developing AI models adapted to local linguistic typologies, promoting multimodal and community-led research methodologies, and ensuring equitable access to linguistic resources for marginalized language communities.

In the context of rapid development and widespread application of big data technologies, a thorough analysis of library user behavior is crucial for optimizing services and enhancing resource utilization efficiency. This study aims to construct a framework for analyzing library user behavior within a big data environment, uncovering behavioral patterns and latent needs. Utilizing literature review to establish theoretical foundations, and employing data mining and statistical analysis methods, we conduct a multidimensional analysis of behaviors such as searching, borrowing, and browsing among library users. By developing a user behavior analysis model and integrating user profiling techniques, we explore influencing factors and evolving trends in user behavior. The findings demonstrate that big data technologies can accurately capture user behavior characteristics, revealing differences in information retrieval preferences and resource usage habits. This provides data support for libraries to formulate personalized service strategies, optimize collection layouts, and enhance service processes. Additionally, the study emphasizes the importance of data security and privacy protection in user behavior analysis, ensuring compliance and ethical soundness in the analytical process.

Abstract Generative artificial intelligence (AI) has become a major research trend in the fields of education and psychology. However, several risks posed by this technology concerning the cognitive and socio‐emotional development of children and adolescents have been identified. While it would be highly useful to have a clear understanding of these potential negative effects, empirical results cannot be obtained without putting the participants of these studies in a situation that potentially endangers their development. Research fields such as the biomedical sciences utilize several measures to minimize risks, such as dose escalation and stopping rules. In addition, dynamic and flexible forms of informed consent could be adopted by our field to maximize transparency. By including methodological advancements and ethical developments in the psychological and educational research process, risks could be averted, and the ethical soundness of AI research involving children and adolescents could be maintained.

Artificial Intelligence (AI) is increasingly embedded in scientific research, transforming data analysis, automation, and decision-making. As its presence expands, AI is also intersecting with research ethics, prompting critical reflections on accountability, transparency, and fairness. Purpose: This study investigates the emerging role of AI in ethical decision-making within scientific research. It aims to explore how AI-driven tools can assist researchers, institutions, and policymakers in upholding ethical standards amidst growing research complexity. Design/Methodology/Approach: The paper adopts a conceptual and analytical approach, reviewing current and emerging AI technologies—such as ethical review systems, decision-support frameworks, and predictive models. It draws from literature and illustrative case discussions to assess ethical applications and challenges. Findings: AI shows promise in enhancing ethical governance by increasing consistency, transparency, and efficiency. However, concerns around algorithmic bias, interpretability, and accountability persist. The study advocates for a balanced AI-human collaboration to ensure responsible and adaptable ethical decisionmaking. Research Limitations/Implications: This is a conceptual study without empirical validation. Future research should evaluate AI-based ethical tools in real-world settings to understand their effectiveness and ethical soundness across diverse disciplines. Practical Implications: AI can support ethical review processes, assist decisionmakers, and encourage proactive compliance. Such tools offer scalable solutions for managing ethics in complex or high-volume research environments. Originality/Value: The paper presents a novel perspective on integrating AI into research ethics. It highlights AI’s dual potential—as a tool for ethical enhancement and a source of new ethical risks—calling for transparent, accountable, and humancentered frameworks

The main objective of this study is to examine and highlight the substantial impact of integrating Internet of Things (IoT) technology and biosensors in the healthcare sector, focusing on their potential to drive substantial advancements and improvements in healthcare. Emphasis is placed on tackling the global challenge posed by chronic diseases by proposing an all-encompassing healthcare system that facilitates real-time monitoring, early detection, and remote management of these conditions. Chronic diseases, distinguished by their prolonged duration and gradual progression, have emerged as a marked challenge for healthcare systems worldwide. This paper seeks to illustrate how biosensors, with the capability to identify specific biomarkers, can play a pivotal role in delivering personalized patient care, enhancing outcomes, and mitigating healthcare expenses. This review was conducted using a systematic and comprehensive approach to analyze the integration of Internet of Things (IoT) technology with biosensors for real-time monitoring and early detection of chronic diseases. Relevant literature was sourced from reputable databases, including IEEE Xplore, PubMed, and Elsevier's ScienceDirect, focusing on studies published between 2014 and 2024. Keywords such as "IoT in healthcare," "biosensors for chronic diseases," and "real-time monitoring systems" guided the selection process. This review included original research articles, review papers, and case studies, which were critically analyzed to assess current advancements, challenges, and future directions in this interdisciplinary field. The findings were synthesized to provide an in-depth understanding of how IoT-enabled biosensors are transforming healthcare, particularly in chronic disease management. This research explores the integration of IoT and biosensors for real-time monitoring of chronic diseases. The combination offers personalized healthcare, early detection, and cost reduction. Applications include remote patient monitoring, cardiac health, glucose management, and elderly care. Despite challenges, ongoing advancements promise to optimize accuracy, efficiency, and ethical soundness, ushering in a patient-centric healthcare era. The integration of IoT-enabled biosensors approach to addressing global challenges posed by chronic diseases. This study highlights the potential of this convergence in healthcare by facilitating real-time monitoring, early detection, and personalized care. By surpassing limitations of traditional monitoring systems, IoT-enabled biosensors provide continuous insights into patients' health, enabling proactive interventions. Their applications are demonstrated in diverse domains, including remote monitoring, cardiac health, glucose management, and elderly care, showcasing their role in advancing precision medicine and improving patient outcomes. Despite technical hurdles, ongoing advancements in miniaturization, edge computing, and AI-driven analytics aim to enhance accuracy, efficiency, and ethical practices, paving the way for a proactive and patient-centric healthcare era.

This paper aimed to understand the sociocultural and economic context of an unconventional TikTok marriage proposal video from 2022. By investigating the religious and ethical implications of the proposal, the study sought to expand the discourse of marriage in the age of social media, which amplifies unpopular and dissenting voices. The study analyzed one viral video of a white adult heterosexual male, using textual analysis and literature review. The video was transcribed via kome.ai and analyzed for key points made by the speaker. Findings were cross-referenced with literature on popular marriage arrangements (Judeo-Christian-Muslim and traditional arranged marriages) and less common ones (platonic marriage, civil marriage, and domestic partnership). The ethical principles of autonomy, beneficence, non-maleficence, and justice were examined to evaluate the ethical soundness of the proposal, also considering human dignity and self-determination. Results revealed that multiple commitments among mutually consenting adults challenge traditional norms but reflect diverse ways to seek fulfillment. The proposed marriage between two heterosexual males aligns with ethical principles but depends on mutual understanding. This new marriage proposal offers an unconventional approach to addressing intimacy and relationship gaps among males by emphasizing personal autonomy, freedom from traditional expectations of exclusivity, and focusing on practical benefits rather than emotional intimacy.

Hospitalized patients lacking the mental capacity to consent to treatment may demand to be discharged from the hospital against medical advice. Forced custody of these patients, including the use of restraints, may be required if the plan is to proceed with treatment. This raises ethical concerns with regard to depriving people of their liberty. The determination of the wishes and values of the patient and her best interests may sometimes vary, depending on the assessor or the clinical team entrusted to perform the evaluation. We therefore propose the following triad for clinicians when determining the best interests for this group of patients to ensure ethical and legal soundness as well as in providing consistency in approach. Firstly, the treatment should serve as a rescue response. Secondly, any restraint deployed must be proportionate with a foreseeable end. Her liberty and autonomy interests should be enhanced by the treatment. Thirdly, the patient's family must be supportive. This paper analyzes the use of the triad approach on two clinical cases, both assessed as lacking in mental capacity to decide on treatment and insisting to be discharged. Using this approach, we could justify how the contrasting outcomes, one in which the voluntary discharge was acquiesced versus the other, which was not acquiesced, were reached. We also examine the compatibility of the triad approach with the obligations under the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD).

Emerging smarter eco-cities, inherently intertwined with environmental governance, function as experimental sites for testing novel technological solutions and implementing environmental reforms aimed at addressing complex challenges. However, despite significant progress in understanding the distinct roles of emerging data-driven governance systems—namely City Brain, Smart Urban Metabolism (SUM), and platform urbanism—enabled by Artificial Intelligence of Things (AIoT), a critical gap persists in systematically exploring the untapped potential stemming from their synergistic and collaborative integration in the context of environmental governance. To fill this gap, this study aims to explore the linchpin potential of AIoT in seamlessly integrating these data-driven governance systems to advance environmental governance in smarter eco-cities. Specifically, it introduces a pioneering framework that effectively leverages the synergies among these AIoT-powered governance systems to enhance environmental sustainability practices in smarter eco-cities. In developing the framework, this study employs configurative and aggregative synthesis approaches through an extensive literature review and in-depth case study analysis of publications spanning from 2018 to 2023. The study identifies key factors driving the co-evolution of AI and IoT into AIoT and specifies technical components constituting the architecture of AIoT in smarter eco-cities. A comparative analysis reveals commonalities and differences among City Brain, SUM, and platform urbanism within the frameworks of AIoT and environmental governance. These data-driven systems collectively contribute to environmental governance in smarter eco-cities by leveraging real-time data analytics, predictive modeling, and stakeholder engagement. The proposed framework underscores the importance of data-driven decision-making, optimization of resource management, reduction of environmental impact, collaboration among stakeholders, engagement of citizens, and formulation of evidence-based policies. The findings unveils that the synergistic and collaborative integration of City Brain, SUM, and platform urbanism through AIoT presents promising opportunities and prospects for advancing environmental governance in smarter eco-cities. The framework not only charts a strategic trajectory for stimulating research endeavors but also holds significant potential for practical application and informed policymaking in the realm of environmental urban governance. However, ongoing critical discussions and refinements remain imperative to address the identified challenges, ensuring the framework's robustness, ethical soundness, and applicability across diverse urban contexts.

This paper describes a scoping review of China’s academic resource databases, relevant official websites, news reports and public accounts spanning a period from the end of 2019 to the end of 2022, to investigate the challenges in scientific integrity and ethical soundness of research conducted during and immediately after the COVID-19 pandemic in China. By conducting the scoping review with keywords related to the research questions in Chinese, relevant data were extracted and classified into four categories: challenges in research, challenges in ethics review, challenges in publishing academic work, and research ethics guidelines during and after the pandemic. The paper points out that problematic studies and findings increased with the escalation in medical research projects during the pandemic in China. The situation faced by researchers was more difficult than before the pandemic. The mode of informed consent, and ethics review and oversight systems also underwent changes. In addition, Traditional Chinese Medicine as an alternative medical treatment for COVID-19, attracted attention from the research community and became a topic of discussion. We conclude that the various challenges and concerns identified indicate a need for a proper and timely response system be formulated in preparation for possible future occurrences of new pandemics or other critical situations.

In the rapidly advancing field of Artificial Intelligence (AI), this study presents a critical evaluation of the resilience and cybersecurity efficacy of leading AI models, including ChatGPT-4, Bard, Claude, and Microsoft Copilot. Central to this research are innovative adversarial prompts designed to rigorously test the content moderation capabilities of these AI systems. This study introduces new adversarial tests and the Response Quality Score (RQS), a metric specifically developed to assess the nuances of AI responses. Additionally, the research spotlights FreedomGPT, an AI tool engineered to optimize the alignment between user intent and AI interpretation. The empirical results from this investigation are pivotal for assessing AI models’ current robustness and security. They highlight the necessity for ongoing development and meticulous testing to bolster AI defenses against various adversarial challenges. Notably, this study also delves into the ethical and societal implications of employing advanced “jailbreak” techniques in AI testing. The findings are significant for understanding AI vulnerabilities and formulating strategies to enhance AI technologies’ reliability and ethical soundness, paving the way for safer and more secure AI applications.

In this open letter, members of the Global Forum for Research Ethics and Integrity [GFREI] – an open, independent collaborative involving 80+ individuals in 30+ countries – report on and extend arguments made during a workshop conducted at the Oxford Global Health and Bioethics International Conference (June 26–27, 2023). Ten GFREI presenters from nine countries used a case study approach to present and discuss an emerging model to integrate diverse global voices in engaging open public consultation opportunities – sometimes termed calls for input, calls for public comment, requests for information (RFIs). A key form of public consultation invites observations and ideas on, and specific edits to, draft versions of policies, guidance, regulations, and other formats under a specific deadline. Based on our experience, we posit that engagement of public consultation opportunities is a matter of transnational civic responsibility; that such engagement can add substantive value to public discourse and the realization of public good; that engaging voices and views from all global regions, and respecting and integrating diverse contributions from varying experience, expertise and forms of knowledge significantly strengthens public consultation responses; and that sustaining and extending GFREI’s independent global voice, and building its diversity and the range of disciplines represented, is worthy of robust support from the global community. Finally, we call on the ethics/bioethics community to engage these calls as an important strategy in advancing the ethical soundness of the laws, regulations, policies, guidelines presented for public consultation.

This study delves into the immediate critical response to Samuel Richardson‟s 1740 novel “Pamela,” which became highly popular for portraying a maidservant embodying peak levels of moral purity. Henry Fielding stands out as a significant critic of “Pamela,” and this paper scrutinizes his counter-narratives, “Shamela” (1741) and “Joseph Andrews” (1742). Fielding, along with other critics, perceived “Pamela” as a disruption to the established norms of master-servant and upper-lower class dynamics prevalent during the 18th century. Utilizing a variety of literary techniques, Fielding compels the reader to question the sincerity and integrity of their beloved character, Pamela. In his works, Fielding recasts Pamela as a strategic social climber, who is manipulative in her attempts to marry her employer. He meticulously unpacks Richardson‟s narrative to expose its artificiality and pretence. By aligning his narrative with Richardson‟s, Fielding seeks to instil skepticism among “Pamela” enthusiasts about the work‟s ethical soundness. Further extending his critique, Fielding introduced “Joseph Andrews” as a subsidiary narrative aimed at demystifying the elevated notions of virtue and moral purity

Health technology assessment (HTA) is a conventional method for evaluating reasonable use of health technologies in many countries. To investigate the ethical soundness of HTA studies in Islamic Republic of Iran. All HTA reports published by the HTA office until 2020 were reviewed using the HTA Core Model and the Q-SEA questionnaires. We evaluated 91 reports for ethical soundness. The research question, literature search and inclusion/exclusion criteria were included in 91.2%, 83.5% and 82.4% of the HTA reports, respectively. Only 13.2% of the reports explicitly stated the objective of the analysis and 6.6% stated the ethics framework. Only 2.2%, 4.4%, 9.9%, 9.9%, 14.3%, and 2.2%, respectively, of the reports, complied with the completeness, bias, policy implications, other implications, conceptual clarification, and conflicting values. HTA reports in the Islamic Republic of Iran require coordinated and integrated framework acceptable to all stakeholders to ensure their compliance with sound ethical requirements.

Health professions education research (HPE-R) must be ethically sound. Ethical review decisions and other ethical considerations should be clearly reported in journal articles to allow readers to assess the ethical soundness of the research. We explored and evaluated how ethical review decisions and ethical considerations for HPE-R are reported in health professions education (HPE) journal articles. We identified a 1-year sample, for 2020, of eight HPE journals. We systematically assessed the reporting of ethical review and key ethical considerations in the articles in the sample. The search yielded 2004 articles, of which 955 articles (47.7%) were eligible and were thus assessed. Most (83.4%) of the assessed articles mentioned a review by an ethical review board (ERB). In the category 'research articles', 92% articles reported the outcome of the ethical review. In the category 'other articles' (e.g. educational case reports), reporting of ethical processes was less common (32%). Overall, the reporting of key ethical considerations was limited, although these considerations were more reported in 'research articles' compared with 'other articles'. ERB assessments and HPE-R approval was reported in most research articles. This finding is an improvement compared with previous evaluations of ethical research practice in HPE-R. All studies, particularly those that are exempted or not fully reviewed, should describe their key ethical considerations clearly to enable the HPE community to assess the ethical soundness. Our review revealed that the reporting of ethical considerations was limited and deserves attention from the research community.

Aims: This study determined the extent of implementation of ecological solid waste management activities: waste generation and storage, waste processing and resources recovery, collection and transportation, and disposal of solid wastes in communities in a component city in Negros Occidental as assessed by the city implementers, barangay implementers, and residents when taken as a whole and when barangays are grouped according to geographical location, population, land area, and income classification. Lastly, the findings of the study were utilized in the formulation of a strategic plan for enhanced implementation of the city's comprehensive solid waste management program. 
 Study Design: The study utilized the quantitative design particularly the descriptive-comparative approach.
 Place and Duration of Study: The study was conducted in the barangays of a component city in Southern part of Negros Occidental Philippines during school year 2022.
 Methodology: The study used a descriptive-comparative research design utilizing a survey questionnaire for data collection. Only Five hundred thirteen (513) respondents participated in the study and the seven (7) others refused to answer the survey questionnaire. Total enumeration was employed for city implementers. Stratified random sampling was used to identify the respondents for barangay and community leaders for each stratum to be well represented. Purposive sampling was used in data collection. In the same way, purposive sampling was used in the conduct of interviews. To analyze the descriptive data, Mean, Standard Deviation, and Frequency Count were also used. Kruskal Wallis and Mann-Whitney U tests were utilized for comparative analysis. More so, general moral principles of respect for persons, beneficence, and justice to ensure the ethical soundness of the study are addressed in the study.
 Results: The result shows no significant difference in the implementation when communities are grouped according to population. However, a significant difference was found when communities were grouped according to location, land area, and income. When it comes to demographics of the respondents in the component city in Southern Negros. In terms of respondents, 1.8% (f=9) were city implementers, 25.0% (f=128) were barangay implementers, and 73.3% (f=193) were community leaders. Among the three (3) implementers, the majority were the community leaders in the component city. Meanwhile, in regards to location, 40.0% (f=205) of respondents came from upland location, 37.6% (f=193) stayed at mainland, and 22.4% (f=115) lived in coastal location. Dominantly, respondents from the upland location obtained the highest percentage among the location. When it comes to population, 73.9% (f=379) belonged to the smaller population with 5933 and below, and 26.1% (f=134) was from a bigger population with 5934 and above. The majority belonged to a smaller population that dominated the study. Similarly, in terms of land area, 73.9% (f=379) of the respondents were from a smaller area (1931 and below), while 26.3% (f=135) were from a bigger area (1932 and up). Finally, in terms of income classification, 68.6% (f=352) of respondents belonged to the barangays with a lower income of 806880 and below, while 31.4% (f=68.4) belonged to the barangays with a higher income of 8068808 and up. Respondents residing in lower-income areas have fewer sources of living, income, and resources.

BackgroundAlthough apps are becoming increasingly relevant in healthcare, there is limited knowledge about how healthcare professionals perceive “quality” in this context and how quality principles that can aid them in assessing health-related apps may be prioritised.The objective was to investigate physicians’ views of predefined (general) quality principles for health apps and to determine whether a ranking algorithm applied to the acquired data can provide stable results against various demographic influences and may thus be appropriate for prioritisation.MethodsParticipants of an online survey of members of two German professional orthopaedics associations conducted between 02/12/2019 and 02/01/2020 were asked about their perception of a set of quality principles for health apps (i.e., “practicality,” “risk adequacy,” “ethical soundness,” “legal conformity,” “content validity,” “technical adequacy,” “usability,” “resource efficiency,” and “transparency”). Structured as a Kano survey, for each principle, there were questions about its perceived relevance and opinions regarding the presence or absence of corresponding characteristics. The available data were evaluated descriptively, and a newly developed method for prioritisation of the principles was applied overall and to different demographic strata (for validation).ResultsThree hundred eighty-two datasets from 9503 participants were evaluated. Legal conformity, content validity, and risk adequacy filled ranks one to three, followed by practicability, ethical soundness, and usability (ranks 4 to 6). Technical adequacy, transparency, and resource efficiency ranked last (ranks 7 to 9). The ranking based on the proposed method was relatively stable, irrespective of demographic factors. The principles were seen as essential, with one exception (“resource efficiency”). Only those with little to no interest in digitisation (22/382, 5.8%) rated the nine principles indifferently.ConclusionsThe specified quality principles and their prioritisation can lay a foundation for future assessments of apps in the medical field. Professional societies build upon this to highlight opportunities for digital transformations in medicine and encourage their members to participate.