How Should Harm Reduction Strategies Differ for Adolescents and Adults?

Overall rates of opioid use are low in adolescents; however, recent increases in mortality from overdose in adolescents have outpaced increases in the general population. This article highlights the importance of expanding evidence-based treatment for adolescent opioid use, especially medication, while also addressing key ethical considerations of harm reduction practices and how application of such practices with adolescents may differ from adults. Concepts related to adolescent populations are discussed, including autonomy, confidentiality, and brain development. Application of harm reduction practices should be age appropriate, express respect for patients' autonomy, include social support, and be accompanied by broader aims to minimize adolescent initiation, escalation, and overall harm caused by opioid use.

PROTECTION OF CONFIDENTIAL MEDICAL INFORMATION IN UKRAINE: PROBLEMS OF LEGAL REGULATION.

The aim of the article is to analyze the legal aspects and mechanisms of confidential medical information protection about an individual in the health care sphere in Ukraine. During the scientific research, various methods of cognition of legal phenomena were used. Among the general scientific approaches, the dialectical method was primarily used, which allowed to identify trends in the development of patient information rights and formulate proposals for improving legislation in the field of medical data protection. The formal-legal method was used to provide a comprehensive characterization of the EU (European Union) and Ukrainian legislation in the sphere of confidential medical information protection. Additionally, general scientific logical methods (analysis and synthesis, comparison and analogy, abstraction, and modeling) were used in order to study the problems of information relations in the medical field and establish legal liability for violation of the confidentiality of such information. The definitions of medical data, medical information, confidential medical data, and medical confidentiality have been researched and compared. The article identified the legitimate grounds for disclosing confidential medical information about an individual in the healthcare sector. Authors revealed the gaps in Ukrainian legislation regarding the confidential medical data protection by healthcare professionals and electronic medical systems regulators. The necessity of expanding the list of subjects responsible for preserving confidential medical information has been substantiated. The study explored the case law of the European Court of Human Rights in the field of the medical data confidentiality violation. It has been outlined the potential judicial remedies and liability for violating the right to personal medical information confidentiality of an individual in the healthcare sector. The legal grounds and cases of possible lawful disclosure of confidential medical information have been analyzed. Attention has been drawn to the insufficient regulation of access to medical confidentiality during martial law. It has been emphasized that the mechanism for protecting the violated right to confidentiality of medical information involves appealing to the Ukrainian Parliament Commissioner for Human Rights or to the court. The increasing role of international legal acts in ensuring the protection of medical data in the European Union and Ukraine has been highlighted.

Moving Genomics into the Clinic: Platforms for Implementing Clinical Genomic Data-Sharing in Ways That Address Ethical, Legal and Social Implications.

This section explores the challenges involved in translating genomic research into genomic medicine. A number of priorities have been identified in the Australian National Health Genomics Framework for addressing these challenges. Responsible collection, storage, use and management of genomic data is one of these priorities, and is the primary theme of this section. The recent release of Genomical, an Australian data-sharing platform, is used as a case study to illustrate the type of assistance that can be provided to the health care sector in addressing this priority. The section first describes the National Framework and other drivers involved in the move towards genomic medicine. The section then examines key ethical, legal and social factors at play in genomics, with particular focus on privacy and consent. Finally, the section examines how Genomical is being used to help ensure that the move towards genomic medicine is ethically, legally and socially sound and that it optimises advances in both genomic and information technology.

Legal requirements for reporting clinical cases to the South African police or social services.

Medical confidentiality is the cornerstone for a trustful relationship between patients and the health professionals attending to them. However, when history or clinical findings suggest certain offenses, statutory laws (Children's Act, Older Persons Act, Mental Health Care Act, Sexual Offenses Act) establish a legal obligation for health professionals to report suspected instances of abuse to the police or alternatively, in some cases, to a designated social worker. Given the high rate of domestic violence and abuse in South Africa, health professionals are most likely to encounter such situations. Many clinicians are oblivious of the obligations, exposing themselves to possible liability and their patients to potential additional harm. This article aims to demonstrate the reporting requirements under the respective acts through case scenarios. Finally, the advantages and disadvantages of the existing legal setting are discussed briefly.

Novel model to authenticate role-based medical users for blockchain-based IoMT devices.

The IoT (Internet of Things) has played a promising role in e-healthcare applications during the last decade. Medical sensors record a variety of data and transmit them over the IoT network to facilitate remote patient monitoring. When a patient visits a hospital he may need to connect or disconnect medical devices from the medical healthcare system frequently. Also, multiple entities (e.g., doctors, medical staff, etc.) need access to patient data and require distinct sets of patient data. As a result of the dynamic nature of medical devices, medical users require frequent access to data, which raises complex security concerns. Granting access to a whole set of data creates privacy issues. Also, each of these medical user need to grant access rights to a specific set of medical data, which is quite a tedious task. In order to provide role-based access to medical users, this study proposes a blockchain-based framework for authenticating multiple entities based on the trust domain to reduce the administrative burden. This study is further validated by simulation on the infura blockchain using solidity and Python. The results demonstrate that role-based authorization and multi-entities authentication have been implemented and the owner of medical data can control access rights at any time and grant medical users easy access to a set of data in a healthcare system. The system has minimal latency compared to existing blockchain systems that lack multi-entity authentication and role-based authorization.

Unlocking Public Health Data: Navigating New Legal Guardrails and Emerging AI Challenges.

Here, we analyze the public health implications of recent legal developments - including privacy legislation, intergovernmental data exchange, and artificial intelligence governance - with a view toward the future of public health informatics and the potential of diverse data to inform public health actions and drive population health outcomes.

Ethical dimensions in telemedicine - balancing technology, responsible care, and patient protection.

Telemedicine, defined as the practice of delivering healthcare services remotely using information and communications technologies, raises a plethora of ethical considerations. As telemedicine evolves, its ethical dimensions play an increasingly pivotal role in balancing the benefits of advanced technologies, ensuring responsible healthcare practices within telemedicine environments, and safeguarding patient rights. Healthcare providers, patients, policymakers, and technology developers involved in telemedicine encounter numerous ethical challenges that need to be addressed. Key ethical topics include prioritizing the protection of patient rights and privacy, which entails ensuring equitable access to remote healthcare services and maintaining the doctor-patient relationship in virtual settings. Additional areas of focus encompass data security concerns and the quality of healthcare delivery, underscoring the importance of upholding ethical standards in the digital realm. A critical examination of these ethical dimensions highlights the necessity of establishing binding ethical guidelines and legal regulations. These measures could assist stakeholders in formulating effective strategies and methodologies to navigate the complex telemedicine landscape, ensuring adherence to the highest ethical standards and promoting patient welfare. A balanced approach to telemedicine ethics should integrate the benefits of telemedicine with proactive measures to address emerging ethical challenges and should be grounded in a well-prepared and respected ethical framework.

Principles of digital professionalism for the metaverse in healthcare.

BACKGROUND: Experts are currently investigating the potential applications of the metaverse in healthcare. The metaverse, a groundbreaking concept that arose in the early 21st century through the fusion of virtual reality and augmented reality technologies, holds promise for transforming healthcare delivery. Alongside its implementation, the issue of digital professionalism in healthcare must be addressed. Digital professionalism refers to the knowledge and skills required by healthcare specialists to navigate digital technologies effectively and ethically. This study aims to identify the core principles of digital professionalism for the use of metaverse in healthcare. METHOD: This study utilized a qualitative design and collected data through semi-structured online interviews with 20 medical information and health informatics specialists from various countries (USA, UK, Sweden, Netherlands, Poland, Romania, Italy, Iran). Data analysis was conducted using the open coding method, wherein concepts (codes) related to the themes of digital professionalism for the metaverse in healthcare were assigned to the data. The analysis was performed using the MAXQDA software (VER BI GmbH, Berlin, Germany). RESULTS: The study revealed ten fundamental principles of digital professionalism for the metaverse in healthcare: Privacy and Security, Informed Consent, Trust and Integrity, Accessibility and Inclusion, Professional Boundaries, Evidence-Based Practice, Continuous Education and Training, Collaboration and Interoperability, Feedback and Improvement, and Regulatory Compliance. CONCLUSION: As the metaverse continues to expand and integrate itself into various industries, including healthcare, it becomes vital to establish principles of digital professionalism to ensure ethical and responsible practices. Healthcare professionals can uphold these principles to maintain ethical standards, safeguard patient privacy, and deliver effective care within the metaverse.

Ethical considerations during Mpox Outbreak: a scoping review.

BACKGROUND: Historically, epidemics have been accompanied by the concurrent emergence of stigma, prejudice, and xenophobia. This scoping review aimed to describe and map published research targeting ethical values concerning monkeypox (mpox). In addition, it aimed to understand the research gaps related to mpox associated stigma. METHODS: We comprehensively searched databases (PubMed Central, PubMed Medline, Scopus, Web of Science, Ovid, and Google Scholar) to identify published literature concerning mpox ethical issues and stigma from May 6, 2022, to February 15, 2023. The key search terms used were "monkeypox", "ethics", "morals", "social stigma", "privacy", "confidentiality", "secrecy", "privilege", "egoism", and "metaethics". This scoping review followed the framework proposed by Arksey and O'Malley in 2005 and was further improved by the recommendations of Levac et al. in 2010. RESULTS: The search strategies employed in the scoping review yielded a total of 454 articles. We analyzed the sources, types, and topics of the retrieved articles/studies. The authors were able to identify 32 studies that met inclusion criteria. Six of the 32 included studies were primary research. The study revealed that the ongoing mpox outbreak is contending with a notable surge in misinformation and societal stigma. It highlights the adverse impacts of stigma and ethical concerns associated with mpox, which can negatively affect people with the disease. CONCLUSION: The study's findings underscore the imperative need to enhance public awareness; involve civil society; and promote collaboration among policymakers, medical communities, and social media platforms. These collective endeavors are crucial for mitigating stigma, averting human-to-human transmission, tackling racism, and dispelling misconceptions associated with the outbreak.

Reducing privacy risks of China's healthcare big data through the policy framework.

While healthcare big data brings great opportunities and convenience to the healthcare industry, it also inevitably raises the issue of privacy leakage. Nowadays, the whole world is facing the security threat of healthcare big data, for which a sound policy framework can help reduce privacy risks of healthcare big data. In recent years, the Chinese government and industry self-regulatory organizations have issued a series of policy documents to reduce privacy risks of healthcare big data. However, China's policy framework suffers from the drawbacks of the mismatched operational model, the inappropriate operational method, and the poorly actionable operational content. Based on the experiences of the European Union, Australia, the United States, and other extra-territorial regions, strategies are proposed for China to amend the operational model of the policy framework, improve the operational method of the policy framework, and enhance the operability of the operational content of the policy framework. This study enriches the research on China's policy framework to reduce privacy risks of healthcare big data and provides some inspiration for other countries.

Collaborative learning from distributed data with differentially private synthetic data.

BACKGROUND: Consider a setting where multiple parties holding sensitive data aim to collaboratively learn population level statistics, but pooling the sensitive data sets is not possible due to privacy concerns and parties are unable to engage in centrally coordinated joint computation. We study the feasibility of combining privacy preserving synthetic data sets in place of the original data for collaborative learning on real-world health data from the UK Biobank. METHODS: We perform an empirical evaluation based on an existing prospective cohort study from the literature. Multiple parties were simulated by splitting the UK Biobank cohort along assessment centers, for which we generate synthetic data using differentially private generative modelling techniques. We then apply the original study's Poisson regression analysis on the combined synthetic data sets and evaluate the effects of 1) the size of local data set, 2) the number of participating parties, and 3) local shifts in distributions, on the obtained likelihood scores. RESULTS: We discover that parties engaging in the collaborative learning via shared synthetic data obtain more accurate estimates of the regression parameters compared to using only their local data. This finding extends to the difficult case of small heterogeneous data sets. Furthermore, the more parties participate, the larger and more consistent the improvements become up to a certain limit. Finally, we find that data sharing can especially help parties whose data contain underrepresented groups to perform better-adjusted analysis for said groups. CONCLUSIONS: Based on our results we conclude that sharing of synthetic data is a viable method for enabling learning from sensitive data without violating privacy constraints even if individual data sets are small or do not represent the overall population well. Lack of access to distributed sensitive data is often a bottleneck in biomedical research, which our study shows can be alleviated with privacy-preserving collaborative learning methods.

GEN-RWD Sandbox: bridging the gap between hospital data privacy and external research insights with distributed analytics.

BACKGROUND: Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand for access to diverse data from clinical practice and daily life for research, posing challenges due to the sensitive nature of medical information, including genetics and health conditions. Regulations like the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in Europe aim to strike a balance between data security, privacy, and the imperative for access. RESULTS: We present the Gemelli Generator - Real World Data (GEN-RWD) Sandbox, a modular multi-agent platform designed for distributed analytics in healthcare. Its primary objective is to empower external researchers to leverage hospital data while upholding privacy and ownership, obviating the need for direct data sharing. Docker compatibility adds an extra layer of flexibility, and scalability is assured through modular design, facilitating combinations of Proxy and Processor modules with various graphical interfaces. Security and reliability are reinforced through components like Identity and Access Management (IAM) agent, and a Blockchain-based notarisation module. Certification processes verify the identities of information senders and receivers. CONCLUSIONS: The GEN-RWD Sandbox architecture achieves a good level of usability while ensuring a blend of flexibility, scalability, and security. Featuring a user-friendly graphical interface catering to diverse technical expertise, its external accessibility enables personnel outside the hospital to use the platform. Overall, the GEN-RWD Sandbox emerges as a comprehensive solution for healthcare distributed analytics, maintaining a delicate equilibrium between accessibility, scalability, and security.

Security Analysis for Smart Healthcare Systems.

The healthcare industry went through reformation by integrating the Internet of Medical Things (IoMT) to enable data harnessing by transmission mediums from different devices, about patients to healthcare staff devices, for further analysis through cloud-based servers for proper diagnosis of patients, yielding efficient and accurate results. However, IoMT technology is accompanied by a set of drawbacks in terms of security risks and vulnerabilities, such as violating and exposing patients' sensitive and confidential data. Further, the network traffic data is prone to interception attacks caused by a wireless type of communication and alteration of data, which could cause unwanted outcomes. The advocated scheme provides insight into a robust Intrusion Detection System (IDS) for IoMT networks. It leverages a honeypot to divert attackers away from critical systems, reducing the attack surface. Additionally, the IDS employs an ensemble method combining Logistic Regression and K-Nearest Neighbor algorithms. This approach harnesses the strengths of both algorithms to improve attack detection accuracy and robustness. This work analyzes the impact, performance, accuracy, and precision outcomes of the used model on two IoMT-related datasets which contain multiple attack types such as Man-In-The-Middle (MITM), Data Injection, and Distributed Denial of Services (DDOS). The yielded results showed that the proposed ensemble method was effective in detecting intrusion attempts and classifying them as attacks or normal network traffic, with a high accuracy of 92.5% for the first dataset and 99.54% for the second dataset and a precision of 96.74% for the first dataset and 99.228% for the second dataset.

Are Rights-Based Services Important? An Adolescent PrEP Demonstration Project in Brazil.

In this study, we systematically examined the importance of human rights standards and principles for rights-based pre-exposure prophylaxis (PrEP) provision for marginalized adolescents. Nested within a demonstration study of PrEP provision to adolescent men who have sex with men, travestis, and transgender women, we carried out interviews in São Paulo, Brazil with 25 adolescents, eight health providers, and six workers involved in community-based demand creation. Analysis focused on participants' narratives about aspects of human rights within service delivery, including the availability, accessibility, acceptability, and quality of services; informed decision-making; nondiscrimination; and privacy and confidentiality. Clients and service providers highlighted the importance of availing a range of services beyond PrEP and described how community outreach and social media helped promote accessibility. Acceptability centered around clients feeling heard and respected. Health workers appreciated having time to build trusting relationships with clients to ensure quality of care and support informed decision-making. Nondiscrimination was valued by all, including using clients' chosen pronouns. Privacy and confidentiality were primary concerns for clients who were not "out" about their sexuality or PrEP use; to mitigate this, health workers sought to accommodate clients' preferred channels of communication. Rights-based PrEP services can help promote engagement and retention in PrEP services, particularly for marginalized populations.

End-to-end pseudonymization of fine-tuned clinical BERT models : Privacy preservation with maintained data utility.

Many state-of-the-art results in natural language processing (NLP) rely on large pre-trained language models (PLMs). These models consist of large amounts of parameters that are tuned using vast amounts of training data. These factors cause the models to memorize parts of their training data, making them vulnerable to various privacy attacks. This is cause for concern, especially when these models are applied in the clinical domain, where data are very sensitive. Training data pseudonymization is a privacy-preserving technique that aims to mitigate these problems. This technique automatically identifies and replaces sensitive entities with realistic but non-sensitive surrogates. Pseudonymization has yielded promising results in previous studies. However, no previous study has applied pseudonymization to both the pre-training data of PLMs and the fine-tuning data used to solve clinical NLP tasks. This study evaluates the effects on the predictive performance of end-to-end pseudonymization of Swedish clinical BERT models fine-tuned for five clinical NLP tasks. A large number of statistical tests are performed, revealing minimal harm to performance when using pseudonymized fine-tuning data. The results also find no deterioration from end-to-end pseudonymization of pre-training and fine-tuning data. These results demonstrate that pseudonymizing training data to reduce privacy risks can be done without harming data utility for training PLMs.

Unraveling Trust Issues Towards Mental Health Professionals Among Bedouin-Arab Minority in Israel.

Trust in mental health professionals and services profoundly impacts health outcomes. However, understanding trust in mental health professionals, especially in ethnic minority contexts, is lacking. To explore this within the Bedouin-Arab minority, a qualitative study conducted semi-structured interviews with 25 Bedouins in southern Israel. Participants were primarily female (60%) married (60%), averaging 34.08 years old. Employing grounded theory, three themes emerged. Firstly, concerns about confidentiality were central, eroding trust due to societal repercussions. Secondly, factors influencing confidentiality concerns and distrust were tied to Bedouin-Arab social structures and cultural values rather than professional attributes. Lastly, the consequences of distrust included reduced help-seeking. This study enriches the understanding of trust in mental health professionals among non-Western ethnic minorities, highlighting how cultural factors shape perceptions of mental health services and distrust. Addressing confidentiality worries demands Bedouin mental health professionals to acknowledge hurdles, build community ties, and demonstrate expertise through personal connections and events.

Using 42 CFR part 2 revisions to integrate substance use disorder treatment information into electronic health records at a safety net health system.

BACKGROUND: Regulations put in place to protect the privacy of individuals receiving substance use disorder (SUD) treatment have resulted in an unintended consequence of siloed SUD treatment and referral information outside of the integrated electronic health record (EHR). Recent revisions to these regulations have opened the door to data integration, which creates opportunities for enhanced patient care and more efficient workflows. We report on the experience of one safety-net hospital system integrating SUD treatment data into the EHR. METHODS: SUD treatment and referral information was integrated from siloed systems into the EHR through the implementation of a referral order, treatment episode definition, and referral and episode-related tools for addiction therapists and other clinicians. Integration was evaluated by monitoring SUD treatment episode characteristics, patient characteristics, referral linkage, and treatment episode retention before and after integration. Satisfaction of end-users with the new tools was evaluated through a survey of addiction therapists. RESULTS: After integration, three more SUD treatment programs were represented in the EHR. This increased the number of patients that could be tracked as initiating SUD treatment by 250%, from 562 before to 1,411 after integration. After integration, overall referral linkage declined (74% vs. 48%) and treatment episode retention at 90-days was higher (45% vs. 74%). Addiction therapists appreciated the efficiency of having all SUD treatment information in the EHR but did not find that the tools provided a large time savings shortly after integration. CONCLUSIONS: Integration of SUD treatment program data into the EHR facilitated both care coordination in patient treatment and quality improvement initiatives for treatment programs. Referral linkage and retention rates were likely modified by a broader capture of patients and changed outcome definition criteria. Greater preparatory workflow analysis may decrease initial end-user burden. Integration of siloed data, made possible given revised regulations, is essential to an efficient hub-and-spoke model of care, which must standardize and coordinate patient care across multiple clinics and departments.

Artificial Intelligence in the Provision of Health Care: An American College of Physicians Policy Position Paper.

Internal medicine physicians are increasingly interacting with systems that implement artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and health care systems are even developing their own AI models, both within and outside of electronic health record (EHR) systems. These technologies have various applications throughout the provision of health care, such as clinical documentation, diagnostic image processing, and clinical decision support. With the growing availability of vast amounts of patient data and unprecedented levels of clinician burnout, the proliferation of these technologies is cautiously welcomed by some physicians. Others think it presents challenges to the patient-physician relationship and the professional integrity of physicians. These dispositions are understandable, given the "black box" nature of some AI models, for which specifications and development methods can be closely guarded or proprietary, along with the relative lagging or absence of appropriate regulatory scrutiny and validation. This American College of Physicians (ACP) position paper describes the College's foundational positions and recommendations regarding the use of AI- and ML-enabled tools and systems in the provision of health care. Many of the College's positions and recommendations, such as those related to patient-centeredness, privacy, and transparency, are founded on principles in the ACP Ethics Manual. They are also derived from considerations for the clinical safety and effectiveness of the tools as well as their potential consequences regarding health disparities. The College calls for more research on the clinical and ethical implications of these technologies and their effects on patient health and well-being.

Medical Information Protection in Internet Hospital Apps in China: Scale Development and Content Analysis.

BACKGROUND: Hospital apps are increasingly being adopted in many countries, especially since the start of the COVID-19 pandemic. Web-based hospitals can provide valuable medical services and enhanced accessibility. However, increasing concerns about personal information (PI) and strict legal compliance requirements necessitate privacy assessments for these platforms. Guided by the theory of contextual integrity, this study investigates the regulatory compliance of privacy policies for internet hospital apps in the mainland of China. OBJECTIVE: In this paper, we aim to evaluate the regulatory compliance of privacy policies of internet hospital apps in the mainland of China and offer recommendations for improvement. METHODS: We obtained 59 internet hospital apps on November 7, 2023, and reviewed 52 privacy policies available between November 8 and 23, 2023. We developed a 3-level indicator scale based on the information processing activities, as stipulated in relevant regulations. The scale comprised 7 level-1 indicators, 26 level-2 indicators, and 70 level-3 indicators. RESULTS: The mean compliance score of the 52 assessed apps was 73/100 (SD 22.4%), revealing a varied spectrum of compliance. Sensitive PI protection compliance (mean 73.9%, SD 24.2%) lagged behind general PI protection (mean 90.4%, SD 14.7%), with only 12 apps requiring separate consent for processing sensitive PI (mean 73.9%, SD 24.2%). Although most apps (n=41, 79%) committed to supervising subcontractors, only a quarter (n=13, 25%) required users' explicit consent for subcontracting activities. Concerning PI storage security (mean 71.2%, SD 29.3%) and incident management (mean 71.8%, SD 36.6%), half of the assessed apps (n=27, 52%) committed to bear corresponding legal responsibility, whereas fewer than half (n=24, 46%) specified the security level obtained. Most privacy policies stated the PI retention period (n=40, 77%) and instances of PI deletion or anonymization (n=41, 79%), but fewer (n=20, 38.5%) committed to prompt third-party PI deletion. Most apps delineated various individual rights, but only a fraction addressed the rights to obtain copies (n=22, 42%) or to refuse advertisement based on automated decision-making (n=13, 25%). Significant deficiencies remained in regular compliance audits (mean 11.5%, SD 37.8%), impact assessments (mean 13.5%, SD 15.2%), and PI officer disclosure (mean 48.1%, SD 49.3%). CONCLUSIONS: Our analysis revealed both strengths and significant shortcomings in the compliance of internet hospital apps' privacy policies with relevant regulations. As China continues to implement internet hospital apps, it should ensure the informed consent of users for PI processing activities, enhance compliance levels of relevant privacy policies, and fortify PI protection enforcement across the information processing stages.

Secrets Clutched in a Dead Hand: Rethinking Posthumous Psychotherapist-Patient Privilege in the Light of Reason and Experience with Other Evidentiary Privileges.

Attorney-client privilege was held by the Supreme Court to extend beyond death in 1996, albeit only ratifying centuries of accepted practice in the lower courts and England before them. But with the lawyer's client dead, the natural outcome of such a rule is that privilege--the legal enforcement of secrecy--will persist forever, for only the dead client could ever have waived and thus end it. Perpetuity is not traditionally favored by the law for good reason, and yet a long and broad line of precedent endorses its application to privilege. The recent emergence of a novel species of privilege for psychotherapy, however, affords an opportunity to take a fresh look at the long-tolerated enigma of eternity and the imprudence of thoughtlessly importing it to the newest addition to the family of privileges. Frankly, humanity has always deserved better than legalisms arrogating to the inscrutability of the infinite.