The Ninth Amendment: An Underutilized Protection for Reproductive Choice.

Concern about individual rights and the desire to protect them has been part of our nation since its founding, and continues to be so today. The Ninth Amendment was created to assuage the Framers' concerns that enumerating some rights in the Bill of Rights would leave unenumerated rights unrecognized and unprotected, affirming that those rights are not disparaged or denied by their lack of textual support. The Ninth Amendment has appeared infrequently in our jurisprudence, and Courts initially construed it rather narrowly. But starting in the 1960s, the Ninth Amendment emerged as a powerful tool not just for recognizing unanticipated rights, but for protecting or expanding even enumerated rights. The right to privacy--encompassing the right to contraception and abortion--the right to preserve the integrity of your family, the right to vote, the right to own a firearm as an individual--all these rights have been asserted under and found to be supported by the Ninth Amendment. In its Dobbs v. Jackson Women's Health decision overturning Roe, the Supreme Court found that there is no right to abortion because it is not in the Constitution. But the potential of the Ninth Amendment is such that reproductive choice need not be mentioned in the Constitution to be protected. Reproductive choice may rightfully be considered as part of a right to privacy, an unenumerated right that nevertheless has abundant precedent behind it. The Ninth Amendment, and its counterparts found in many state constitutions, has the power to protect not just reproductive choice, but all of our fundamental rights.

Without Due Process of Law: The Dobbs Decision and Its Cataclysmic Impact on the Substantive Due Process and Privacy Rights of Ohio Women.

Since the overturning of prior abortion precedents in Dobbs v. Jackson Women's Health Organization, there has been a question on the minds of many women in this country: how will this decision affect me and my rights? As we have seen in the aftermath of Dobbs, many states have pushed for stringent anti-abortion measures seeking to undermine the foundation on which women's reproductive freedom had been grounded on for decades. This includes right here in Ohio, where Republican lawmakers have advocated on numerous occasions for implementing laws seeking to limit abortion rights, including a 6-week abortion ban advocated for and passed by the Ohio Republican legislature and signed into law by Ohio Governor Mike DeWine. Despite this particular ban being successfully challenged and stayed, significant problems persist regarding due process rights for women in Ohio, particularly in the aftermath of Justice Thomas's concurrence in Dobbs advising the Court to revisit prior precedents, such as Griswold v. Connecticut providing for the right to contraception. If the Court were to revisit and strike down Griswold, it would further undermine privacy and due process rights that have been granted to women across this country, including here in Ohio, for decades. Justice Thomas's concurrence, while merely dicta, encapsulates a Court that has become increasingly hostile to treasured fundamental rights for women, a hostility mirrored in numerous Republican legislatures, including right here in Ohio.

Privacy Barriers in Health Monitoring: Scoping Review.

BACKGROUND: Health monitoring technologies help patients and older adults live better and stay longer in their own homes. However, there are many factors influencing their adoption of these technologies. Privacy is one of them. OBJECTIVE: The aim of this study was to provide an overview of the privacy barriers in health monitoring from current research, analyze the factors that influence patients to adopt assisted living technologies, provide a social psychological explanation, and propose suggestions for mitigating these barriers in future research. METHODS: A scoping review was conducted, and web-based literature databases were searched for published studies to explore the available research on privacy barriers in a health monitoring environment. RESULTS: In total, 65 articles met the inclusion criteria and were selected and analyzed. Contradictory findings and results were found in some of the included articles. We analyzed the contradictory findings and provided possible explanations for current barriers, such as demographic differences, information asymmetry, researchers' conceptual confusion, inducible experiment design and its psychological impacts on participants, researchers' confirmation bias, and a lack of distinction among different user roles. We found that few exploratory studies have been conducted so far to collect privacy-related legal norms in a health monitoring environment. Four research questions related to privacy barriers were raised, and an attempt was made to provide answers. CONCLUSIONS: This review highlights the problems of some research, summarizes patients' privacy concerns and legal concerns from the studies conducted, and lists the factors that should be considered when gathering and analyzing people's privacy attitudes.

Evaluating bias and noise induced by the U.S. Census Bureau's privacy protection methods.

The U.S. Census Bureau faces a difficult trade-off between the accuracy of Census statistics and the protection of individual information. We conduct an independent evaluation of bias and noise induced by the Bureau's two main disclosure avoidance systems: the TopDown algorithm used for the 2020 Census and the swapping algorithm implemented for the three previous Censuses. Our evaluation leverages the Noisy Measurement File (NMF) as well as two independent runs of the TopDown algorithm applied to the 2010 decennial Census. We find that the NMF contains too much noise to be directly useful without measurement error modeling, especially for Hispanic and multiracial populations. TopDown's postprocessing reduces the NMF noise and produces data whose accuracy is similar to that of swapping. While the estimated errors for both TopDown and swapping algorithms are generally no greater than other sources of Census error, they can be relatively substantial for geographies with small total populations.

Supported Privacy: An Essential Principle for End-of-Life Care for Children and Families in the PICU.

Caring for children and their families at the end-of-life is an essential but challenging aspect of care in the PICU. During and following a child's death, families often report a simultaneous need for protected privacy and ongoing supportive presence from staff. Balancing these seemingly paradoxical needs can be difficult for PICU staff and can often lead to the family feeling intruded upon or abandoned during their end-of-life experience. In this "Pediatric Critical Care Medicine Perspectives" piece, we reframe provision of privacy at the end-of-life in the PICU and describe an essential principle that aims to help the interprofessional PICU team simultaneously meet these two opposing family needs: "Supported Privacy." In addition, we offer concrete recommendations to actualize "Supported Privacy" in the PICU, focusing on environmental considerations, practical needs, and emotional responses. By incorporating the principles of "Supported Privacy" into end-of-life care practices, clinicians can support the delivery of high-quality care that meets the needs of children and families navigating the challenges and supports of end-of-life in the PICU.

Digital abuse among dating partners: perspectives and experiences of adolescents from two Brazilian capitals.

The conceptions, values, and experiences of students from public and private high schools in two Brazilian state capitals, Vitória-ES and Campo Grande-MS, were analyzed regarding digital control and monitoring between intimate partners and the unauthorized exposure of intimate material on the Internet. Data from eight focus groups with 77 adolescents were submitted to thematic analysis, complemented by a questionnaire answered by a sample of 530 students. Most students affirmed that they do not tolerate the control/monitoring and unauthorized exposure of intimate materials but recognized that such activity is routine. They point out jealousy, insecurity, and "curiosity" as their main reasons. They detail the various dynamics of unauthorized exposure of intimate material and see it as a severe invasion of privacy and a breach of trust between partners. Their accounts suggest that such practices are gender violence. They also reveal that each platform has its cultural appropriation and that platforms used by the family, such as Facebook, cause more significant damage to the victim's reputation.

COMMENTARY: Protecting healthcare privacy: Analysis of data protection developments in India.

Patient privacy is essential and so is ensuring confidentiality in the doctor-patient relationship. However, today's reality is that patient information is increasingly accessible to third parties outside this relationship. This article discusses India's data protection framework and assesses data protection developments in India including the Digital Personal Data Protection Act, 2023.

Between Technological Utopia and Dystopia: Online Expression of Compulsory Use of Surveillance Technology.

This study investigated people's ethical concerns of surveillance technology. By adopting the spectrum of technological utopian and dystopian narratives, how people perceive a society constructed through the compulsory use of surveillance technology was explored. This study empirically examined the anonymous online expression of attitudes toward the society-wide, compulsory adoption of a contact tracing app that affected almost every aspect of all people's everyday lives at a societal level. By applying the structural topic modeling approach to analyze comments on four Hong Kong anonymous discussion forums, topics concerning the technological utopian, dystopian, and pragmatic views on the surveillance app were discovered. The findings showed that people with a technological utopian view on this app believed that the implementation of compulsory app use can facilitate social good and maintain social order. In contrast, individuals who had a technological dystopian view expressed privacy concerns and distrust of this surveillance technology. Techno-pragmatists took a balanced approach and evaluated its implementation practically.

Ethical considerations and concerns in the implementation of AI in pharmacy practice: a cross-sectional study.

BACKGROUND: Integrating artificial intelligence (AI) into healthcare has raised significant ethical concerns. In pharmacy practice, AI offers promising advances but also poses ethical challenges. METHODS: A cross-sectional study was conducted in countries from the Middle East and North Africa (MENA) region on 501 pharmacy professionals. A 12-item online questionnaire assessed ethical concerns related to the adoption of AI in pharmacy practice. Demographic factors associated with ethical concerns were analyzed via SPSS v.27 software using appropriate statistical tests. RESULTS: Participants expressed concerns about patient data privacy (58.9%), cybersecurity threats (58.9%), potential job displacement (62.9%), and lack of legal regulation (67.0%). Tech-savviness and basic AI understanding were correlated with higher concern scores (p < 0.001). Ethical implications include the need for informed consent, beneficence, justice, and transparency in the use of AI. CONCLUSION: The findings emphasize the importance of ethical guidelines, education, and patient autonomy in adopting AI. Collaboration, data privacy, and equitable access are crucial to the responsible use of AI in pharmacy practice.

Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress Detection.

Smartwatch health sensor data are increasingly utilized in smart health applications and patient monitoring, including stress detection. However, such medical data often comprise sensitive personal information and are resource-intensive to acquire for research purposes. In response to this challenge, we introduce the privacy-aware synthetization of multi-sensor smartwatch health readings related to moments of stress, employing Generative Adversarial Networks (GANs) and Differential Privacy (DP) safeguards. Our method not only protects patient information but also enhances data availability for research. To ensure its usefulness, we test synthetic data from multiple GANs and employ different data enhancement strategies on an actual stress detection task. Our GAN-based augmentation methods demonstrate significant improvements in model performance, with private DP training scenarios observing an 11.90-15.48% increase in F1-score, while non-private training scenarios still see a 0.45% boost. These results underline the potential of differentially private synthetic data in optimizing utility-privacy trade-offs, especially with the limited availability of real training samples. Through rigorous quality assessments, we confirm the integrity and plausibility of our synthetic data, which, however, are significantly impacted when increasing privacy requirements.

A strategy to balance location privacy and positioning accuracy.

In privacy protection methods based on location services, constructing anonymous areas using location information shared by collaborative users is the main method. However, this collaborative process not only increases the risk of mobile users' location privacy being leaked, but also reduces positioning accuracy. In response to this problem, we propose a balancing strategy, which transforms the problem of protecting mobile users' location privacy and improving positioning accuracy into a balance issue between location privacy and positioning accuracy. The cooperation of mobile users with different collaborating users is then modeled as an objective optimization problem, and location privacy and positioning accuracy are evaluated separately to make different selection strategies. Finally, an optimization function is constructed to select the optimal selection strategies. Experimental results show that our proposed strategy can effectively achieve the balance between location privacy and positioning accuracy.

Navigating privacy and security in telemedicine for primary care.

OBJECTIVE: To examine patient and provider perspectives on privacy and security considerations in telemedicine during the COVID-19 pandemic. STUDY DESIGN: Qualitative study with patients and providers from primary care practices in 3 National Patient-Centered Clinical Research Network sites in New York, New York; North Carolina; and Florida. METHODS: Semistructured interviews were conducted, audio recorded, transcribed verbatim, and coded using an inductive process. Data related to privacy and information security were analyzed. RESULTS: Sixty-five patients and 21 providers participated. Patients and providers faced technology-related security concerns as well as difficulties ensuring privacy in the transformed shared space of telemedicine. Patients expressed increased comfort doing telemedicine from home but often did not like their providers to offer virtual visits from outside an office setting. Providers initially struggled to find secure and Health Insurance Portability and Accountability Act-compliant platforms and devices to host the software. Whereas some patients preferred familiar platforms such as FaceTime, others recognized potential security concerns. Audio-only encounters sometimes raised patient concerns that they would not be able to confirm the identity of the provider. CONCLUSIONS: Telemedicine led to novel concerns about privacy because patients and providers were often at home or in public spaces, and they shared concerns about software and hardware security. In addition to technological safeguards, our study emphasizes the critical role of physical infrastructure in ensuring privacy and security. As telemedicine continues to evolve, it is important to address and mitigate concerns around privacy and security to ensure high-quality and safe delivery of care to patients in remote settings.

When Parents Request Nondisclosure: Rights of Adolescents to Access Their Health Information and Implications of the 21st Century Cures Act Final Rule.

AbstractDespite broad ethical consensus supporting developmentally appropriate disclosure of health information to older children and adolescents, cases in which parents and caregivers request nondisclosure continue to pose moral dilemmas for clinicians. State laws vary considerably regarding adolescents' rights to autonomy, privacy, and confidentiality, with many states not specifically addressing adolescents' right to their own healthcare information. The requirements of the 21st Century Cures Act have raised important ethical concerns for pediatricians and adolescent healthcare professionals regarding the protection of adolescent privacy and confidentiality, given requirements that chart notes and results be made readily available to patients via electronic portals. Less addressed have been the implications of the act for adolescents' access to their health information, since many healthcare systems' electronic portals are available to patients beginning at age 12, sometimes requiring that the patients themselves authorize their parents' access to the same information. In this article, we present a challenging case of protracted disagreement about an adolescent's right to honest information regarding his devastating prognosis. We then review the legal framework governing adolescents' rights to their own healthcare information, the limitations of ethics consultation to resolve such disputes, and the potential for the Cures Act's impact on electronic medical record systems to provide one form of resolution. We conclude that although parents in cases like the one presented here have the legal right to consent to medical treatment on their children's behalf, they do not have a corresponding right to direct the withholding of medical information from the patient.

Patients and Stakeholders' Perspectives Regarding the Privacy, Security, and Confidentiality of Data Collected via Mobile Health Apps in Saudi Arabia: Protocol for a Mixed Method Study.

BACKGROUND: There is data paucity regarding users' awareness of privacy concerns and the resulting impact on the acceptance of mobile health (mHealth) apps, especially in the Saudi context. Such information is pertinent in addressing users' needs in the Kingdom of Saudi Arabia (KSA). OBJECTIVE: This article presents a study protocol for a mixed method study to assess the perspectives of patients and stakeholders regarding the privacy, security, and confidentiality of data collected via mHealth apps in the KSA and the factors affecting the adoption of mHealth apps. METHODS: A mixed method study design will be used. In the quantitative phase, patients and end users of mHealth apps will be randomly recruited from various provinces in Saudi Arabia with a high population of mHealth users. The research instrument will be developed based on the emerging themes and findings from the interview conducted among stakeholders, app developers, health care professionals, and users of mHealth apps (n=25). The survey will focus on (1) how to improve patients' awareness of data security, privacy, and confidentiality; (2) feedback on the current mHealth apps in terms of data security, privacy, and confidentiality; and (3) the features that might improve data security, privacy, and confidentiality of mHealth apps. Meanwhile, specific sections of the questionnaire will focus on patients' awareness, privacy concerns, confidentiality concerns, security concerns, perceived usefulness, perceived ease of use, and behavioral intention. Qualitative data will be analyzed thematically using NVivo version 12. Descriptive statistics, regression analysis, and structural equation modeling will be performed using SPSS and partial least squares structural equation modeling. RESULTS: The ethical approval for this research has been obtained from the Biomedical and Scientific Research Ethics Committee, University of Warwick, and the Medical Research and Ethics Committee Ministry of Health in the KSA. The qualitative phase is ongoing and 15 participants have been interviewed. The interviews for the remaining 10 participants will be completed by November 25, 2023. Preliminary thematic analysis is still ongoing. Meanwhile, the quantitative phase will commence by December 10, 2023, with 150 participants providing signed and informed consent to participate in the study. CONCLUSIONS: The mixed methods study will elucidate the antecedents of patients' awareness and concerns regarding the privacy, security, and confidentiality of data collected via mHealth apps in the KSA. Furthermore, pertinent findings on the perspectives of stakeholders and health care professionals toward the aforementioned issues will be gleaned. The results will assist policy makers in developing strategies to improve Saudi users'/patients' adoption of mHealth apps and addressing the concerns raised to benefit significantly from these advanced health care modalities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54933.

Integrating blockchain and ZK-ROLLUP for efficient healthcare data privacy protection system via IPFS.

With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput.

Ethical guidance for conducting health research with online communities: A scoping review of existing guidance.

Online research methods have grown in popularity due in part to the globalised and far-reaching nature of the internet but also linked to the Covid-19 pandemic whereby restrictions to travel and face to face contact necessitated a shift in methods of research recruitment and data collection. Ethical guidance exists to support researchers in conducting online research, however this is lacking within health fields. This scoping review aims to synthesise formal ethical guidance for applying online methods within health research as well as provide examples of where guidance has been used. A systematic search of literature was conducted, restricted to English language records between 2013 and 2022. Eligibility focused on whether the records were providing ethical guidance or recommendations, were situated or relevant to health disciplines, and involved the use or discussion of online research methods. Following exclusion of ineligible records and duplicate removal, three organisational ethical guidance and 24 research papers were charted and thematically analysed. Four key themes were identified within the guidance documents, 1) consent, 2) confidentiality and privacy, 3) protecting participants from harm and 4) protecting researchers from harm with the research papers describing additional context and understanding around these issues. The review identified that there are currently no specific guidelines aimed at health researchers, with the most cited guidance coming from broader methodological perspectives and disciplines or auxiliary fields. All guidance discussed each of the four key themes within the wider context of sensitive topics and vulnerable populations, areas and issues which are often prominent within health research thus highlighting the need for unifying guidance specific for health researchers. Further research should aim to understand better how online health studies apply ethical principles, to support in informing gaps across both research and guidance.

Using Wearable Digital Devices to Screen Children for Mental Health Conditions: Ethical Promises and Challenges.

In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization. Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, who tend to unintentionally under-report, and in some cases over-report, child symptomology. Digital phenotype screening tools (DPSTs), currently being developed in research settings, may help overcome reporting bias by providing objective measures of physiology and behavior to supplement child mental health screening. Prior to their implementation in pediatric practice, however, the ethical dimensions of DPSTs should be explored. Herein, we consider some promises and challenges of DPSTs under three broad categories: accuracy and bias, privacy, and accessibility and implementation. We find that DPSTs have demonstrated accuracy, may eliminate concerns regarding under- and over-reporting, and may be more accessible than gold-standard surveys. However, we also find that if DPSTs are not responsibly developed and deployed, they may be biased, raise privacy concerns, and be cost-prohibitive. To counteract these potential shortcomings, we identify ways to support the responsible and ethical development of DPSTs for clinical practice to improve mental health screening in children.

Patients' Perspectives on the Data Confidentiality, Privacy, and Security of mHealth Apps: Systematic Review.

BACKGROUND: Mobile health (mHealth) apps have the potential to enhance health care service delivery. However, concerns regarding patients' confidentiality, privacy, and security consistently affect the adoption of mHealth apps. Despite this, no review has comprehensively summarized the findings of studies on this subject matter. OBJECTIVE: This systematic review aims to investigate patients' perspectives and awareness of the confidentiality, privacy, and security of the data collected through mHealth apps. METHODS: Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a comprehensive literature search was conducted in 3 electronic databases: PubMed, Ovid, and ScienceDirect. All the retrieved articles were screened according to specific inclusion criteria to select relevant articles published between 2014 and 2022. RESULTS: A total of 33 articles exploring mHealth patients' perspectives and awareness of data privacy, security, and confidentiality issues and the associated factors were included in this systematic review. Thematic analyses of the retrieved data led to the synthesis of 4 themes: concerns about data privacy, confidentiality, and security; awareness; facilitators and enablers; and associated factors. Patients showed discordant and concordant perspectives regarding data privacy, security, and confidentiality, as well as suggesting approaches to improve the use of mHealth apps (facilitators), such as protection of personal data, ensuring that health status or medical conditions are not mentioned, brief training or education on data security, and assuring data confidentiality and privacy. Similarly, awareness of the subject matter differed across the studies, suggesting the need to improve patients' awareness of data security and privacy. Older patients, those with a history of experiencing data breaches, and those belonging to the higher-income class were more likely to raise concerns about the data security and privacy of mHealth apps. These concerns were not frequent among patients with higher satisfaction levels and those who perceived the data type to be less sensitive. CONCLUSIONS: Patients expressed diverse views on mHealth apps' privacy, security, and confidentiality, with some of the issues raised affecting technology use. These findings may assist mHealth app developers and other stakeholders in improving patients' awareness and adjusting current privacy and security features in mHealth apps to enhance their adoption and use. TRIAL REGISTRATION: PROSPERO CRD42023456658; https://tinyurl.com/ytnjtmca.

Protecting Privacy of Pregnant and LGBTQ+ Research Participants.

This Viewpoint summarizes existing federal regulations aimed at protecting research data, describes the challenges of enforcing these regulations, and discusses how evolving privacy technologies could be used to reduce health disparities and advance health equity among pregnant and LGBTQ+ research participants.

Sparsified federated learning with differential privacy for intrusion detection in VANETs based on Fisher Information Matrix.

With the continuous development of vehicular ad hoc networks (VANET) security, using federated learning (FL) to deploy intrusion detection models in VANET has attracted considerable attention. Compared to conventional centralized learning, FL retains local training private data, thus protecting privacy. However, sensitive information about the training data can still be inferred from the shared model parameters in FL. Differential privacy (DP) is sophisticated technique to mitigate such attacks. A key challenge of implementing DP in FL is that non-selectively adding DP noise can adversely affect model accuracy, while having many perturbed parameters also increases privacy budget consumption and communication costs for detection models. To address this challenge, we propose FFIDS, a FL algorithm integrating model parameter pruning with differential privacy. It employs a parameter pruning technique based on the Fisher Information Matrix to reduce the privacy budget consumption per iteration while ensuring no accuracy loss. Specifically, FFIDS evaluates parameter importance and prunes unimportant parameters to generate compact sub-models, while recording the positions of parameters in each sub-model. This not only reduces model size to lower communication costs, but also maintains accuracy stability. DP noise is then added to the sub-models. By not perturbing unimportant parameters, more budget can be reserved to retain important parameters for more iterations. Finally, the server can promptly recover the sub-models using the parameter position information and complete aggregation. Extensive experiments on two public datasets and two F2MD simulation datasets have validated the utility and superior performance of the FFIDS algorithm.