The growing prominence of artificial intelligence (AI) in mobile health (mHealth) has given rise to a distinct subset of apps that provide users with diagnostic information using their inputted health status and symptom information-AI-powered symptom checker apps (AISympCheck). While these apps may potentially increase access to health care, they raise consequential ethical and legal questions. This paper will highlight notable concerns with AI usage in the health care system, further entrenchment of preexisting biases in the health care system and issues with professional accountability. To provide an in-depth analysis of the issues of bias and complications of professional obligations and liability, we focus on 2 mHealth apps as examples-Babylon and Ada. We selected these 2 apps as they were both widely distributed during the COVID-19 pandemic and make prominent claims about their use of AI for the purpose of assessing user symptoms. First, bias entrenchment often originates from the data used to train AI systems, causing the AI to replicate these inequalities through a \"garbage in, garbage out\" phenomenon. Users of these apps are also unlikely to be demographically representative of the larger population, leading to distorted results. Second, professional accountability poses a substantial challenge given the vast diversity and lack of regulation surrounding the reliability of AISympCheck apps. It is unclear whether these apps should be subject to safety reviews, who is responsible for app-mediated misdiagnosis, and whether these apps ought to be recommended by physicians. With the rapidly increasing number of apps, there remains little guidance available for health professionals. Professional bodies and advocacy organizations have a particularly important role to play in addressing these ethical and legal gaps. Implementing technical safeguards within these apps could mitigate bias, AIs could be trained with primarily neutral data, and apps could be subject to a system of regulation to allow users to make informed decisions. In our view, it is critical that these legal concerns are considered throughout the design and implementation of these potentially disruptive technologies. Entrenched bias and professional responsibility, while operating in different ways, are ultimately exacerbated by the unregulated nature of mHealth.

Th is study offers empirical insights into investor behavior and its correlation with various behavioral biases in the context of investment decisions in the Pakistan Stock Exchange (PSX). Data was collected through a structured questionnaire from 261 individual investors in Pakistan. The study employs hierarchical regression analysis to test the hypothesis. It considers several behavioral biases, and statistically, anchoring and adjustment, overconfidence, and herding show a significant impact. The study uses financial literacy to examine its moderating effects on these biases, and the result suggests that it significantly influences behavioral biases related to investment decisions. The results underscore the unique investment behaviors in emerging markets, contrasting with established norms in well-developed financial markets. These findings can inform policymakers and stock market authorities about investor decision-making in emerging economies.

Women currently represent approximately 70% of the global healthcare workforce, 60.9% of the global dental workforce, 77.6% of the US healthcare workforce, and 36.7% of the US dental workforce. The American Dental Association states that the number of practicing women dentists in the United States has increased by 2.25 times since 2001, with a projected trajectory to level off by 2040. Despite having a major impact on the healthcare sector globally, women earn 24% less than men and only serve in 25% of senior leadership positions. In the US dental schools, only 14% of faculty serve in administrative roles, and as of April 2022, 28.6% of the US dental school deans were women, indicating gender underrepresentation in the highest roles of academic leadership. This corresponds to the data on gender parity still not being the norm in many societies and workplaces and can be attributed to public policies, stereotypical perceptions, and individual factors. Five key factors have been identified to be crucial for women\'s entry or advancement in global health leadership: a) public policy, b) community, c) institutional, d) interpersonal, and e) individual. Individual self-improvement and institutional practices may be used to overcome these barriers to women\'s leadership in healthcare and shift the power dynamics toward reinforcing gender equality. These transformative changes are measured through women\'s collective capacities and skills, relationship dynamics, community perceptions, and environmental practices. This article recognizes the present obstacles to women in healthcare leadership and proposes strategies to achieve gender equality both through individual and institutional practices.

In the dynamic field of medical artificial intelligence (AI), cardiology stands out as a key area for its technological advancements and clinical application. In this review we explore the complex issue of data bias, specifically addressing those encountered during the development and implementation of AI tools in cardiology. We dissect the origins and effects of these biases, which challenge their reliability and widespread applicability in health care. Using a case study, we highlight the complexities involved in addressing these biases from a clinical viewpoint. The goal of this review is to equip researchers and clinicians with the practical knowledge needed to identify, understand, and mitigate these biases, advocating for the creation of AI solutions that are not just technologically sound, but also fair and effective for all patients.

Disparities in pain care are well-documented such that women and people of color have their pain undertreated and underestimated compared to men and White people. One of the contributors of the undertreatment of pain for people of color and women may be the inaccurate assessment of pain. Understanding the pain assessment process is an important step in evaluating the magnitude of and intervening on pain disparities in care. In the current work, we focus on documenting intersectional race and gender biases in pain assessment and present the results of a novel intervention for reducing these biases. Across 3 studies (N = 532) and a mini meta-analysis using real videotaped people in pain as stimuli, we demonstrate that observers disproportionately underestimated women of color\'s pain compared to all other groups (men of color, White women, and White men). In study 3 (N = 232), we show that a novel intervention focused on behavioral skill building (ie, practice and immediate feedback) significantly reduced observers\' pain assessment biases toward marginalized groups compared to all other types of trainings (raising awareness of societal biases, raising awareness of self-biases, and a control condition). While it is an open question as to how long this type of intervention lasts, behavioral skills building around assessing marginalized people\'s pain more accurately is a promising training tool for health care professionals. PERSPECTIVE: This article demonstrates the underestimation of pain among people of color and women. We also found support that a novel intervention reduced observers\' pain assessment biases toward marginalized groups. This could be used in medical education or clinical care to reduce intersectional pain care disparities.

UNASSIGNED: All individuals and groups have blind spots that can create problems if unaddressed. The goal of this study was to examine blind spots in medical education from international perspectives.
UNASSIGNED: From December 2022 to March 2023, we distributed an electronic survey through international networks of medical students, postgraduate trainees, and medical educators. Respondents named blind spots affecting their medical education system and then rated nine blind spot domains from a study of U.S. medical education along five-point Likert-type scales (1 = much less attention needed; 5 = much more attention needed). We tested for differences between blind spot ratings by respondent groups. We also analyzed the blind spots that respondents identified to determine those not previously described and performed content analysis on open-ended responses about blind spot domains.
UNASSIGNED: There were 356 respondents from 88 countries, including 127 (44%) educators, 80 (28%) medical students, and 33 (11%) postgraduate trainees. At least 80% of respondents rated each blind spot domain as needing \'more\' or \'much more\' attention; the highest was 88% for \'Patient perspectives and voices that are not heard, valued, or understood.\' In analyses by gender, role in medical education, World Bank country income level, and region, a mean difference of 0.5 was seen in only five of the possible 279 statistical comparisons. Of 885 blind spots documented, new blind spot areas related to issues that crossed national boundaries (e.g. international standards) and the sufficiency of resources to support medical education. Comments about the nine blind spot domains illustrated that cultural, health system, and governmental elements influenced how blind spots are manifested across different settings.
UNASSIGNED: There may be general agreement throughout the world about blind spots in medical education that deserve more attention. This could establish a basis for coordinated international effort to allocate resources and tailor interventions that advance medical education.

UNASSIGNED: Scientists studying intergroup biases are often concerned with lessening discrimination (unequal treatment of one social group versus another), but many interventions for reducing such biased behavior have weak or limited evidence. In this review article, we argue one productive avenue for reducing discrimination comes from adapting interventions in a separate field-judgment and decision-making-that has historically studied \"debiasing\": the ways people can lessen the unwanted influence of irrelevant information on decision-making. While debiasing research shares several commonalities with research on reducing intergroup discrimination, many debiasing interventions have relied on methods that differ from those deployed in the intergroup bias literature. We review several instances where debiasing principles have been successfully applied toward reducing intergroup biases in behavior and introduce other debiasing techniques that may be well-suited for future efforts in lessening discrimination.

BACKGROUND: Family reconstitution and data from online genealogies, such as FamiLinx, are two potential sources for investigating mortality dynamics for the period before official lifetables became available. In this paper, we use two of them, the family reconstitution of Imhof and the FamiLinx dataset based on geni.com, to estimate dynamics in life expectancy and discuss the sex-specific differential mortality in the German Empire.
METHODS: Sex-specific lifetables are estimated for the territory of the German Empire from the individual data of the family reconstitution and the online genealogies. On the basis of these lifetables, we estimate the conditional life expectancy and derive the corresponding sex-specific differential mortality. Findings are compared with the official lifetable of the German Empire in 1871-1910. The contribution of each age group to the differential mortality is determined using the stepwise-replacement algorithm.
RESULTS: The family reconstitution overestimates conditional life expectancy less than FamiLinx after 1871, when official lifetables are available in the German Empire. However, both sources fail to capture the sex-specific mortality differentials of the official lifetables at the end of the nineteenth century and show a higher life expectancy for males instead of females. The bias in sex-specific mortality rates is particularly pronounced in the age groups 15 to 45.
CONCLUSIONS: Finally, we discuss possible explanations for the biased findings. Notability bias, the patriarchal approach to family trees, and maternal mortality are important mechanisms in the FamiLinx dataset. Censoring due to mobility serves as a potential reason for the bias in the family reconstitution.
UNASSIGNED: HINTERGRUND: Familienrekonstitutionen und Familienstammbäume genealogischer Online-Plattformen sind 2 mögliche Datenquellen für die Untersuchung der Sterblichkeit in einer Zeit, als noch keine amtlichen Sterbetafeln verfügbar waren. Der vorliegende Artikel diskutiert anhand zweier Beispiele, der Familienrekonstitution aus Imhof und dem auf geni.com beruhenden Datensatz FamiLinx, die geschätzten Verläufe der Lebenserwartung im Deutschen Reich mit einem Fokus auf die geschlechtsspezifische differenzielle Mortalität.
METHODS: Mithilfe der Individualdaten aus der Familienrekonstitution und aus den Online-Genealogien werden die geschlechtsspezifischen Sterbetafeln geschätzt. Aus ihnen wird die bedingte Lebenserwartung ermittelt und die entsprechende geschlechtsspezifische differenzielle Mortalität abgeleitet und mit den amtlichen Sterbetafeln für die Jahre 1871–1910 abgeglichen. Der Beitrag der einzelnen Altersklassen zur differenziellen Sterblichkeit wird mit dem Stepwise Replacement Algorithm bestimmt.
UNASSIGNED: Die Ergebnisse der Familienrekonstitution überschätzen die Lebenserwartung nach 1871 weniger stark als die FamiLinx-Schätzungen. Die geringere Sterblichkeit der Frauen in der amtlichen Statistik wird von beiden Quellen nicht abgebildet. Im Gegensatz zur amtlichen Statistik ist die geschätzte Lebenserwartung der Männer höher als die der Frauen. Diese verzerrte geschlechtsspezifische Abbildung der Mortalitätsraten geht insbesondere auf die Altersklassen von 15 bis 45 Jahren zurück.
CONCLUSIONS: Der Notability Bias, der patriarchische Ansatz in der Erstellung von Familienstammbäumen und die Müttersterblichkeit sind mögliche Ursachen für diese Beobachtungen in FamiLinx. In der Familienrekonstitution ist die mit der Mobilität einhergehende Zensierung ein Erklärungsansatz.

This article explores the persistent and deeply troubling issue of conflict-related sexual violence (CRSV) throughout history and in contemporary conflicts. It examines the roots of wartime sexual violence in wartime, the evolving international legal framework for the protection of civilians, and the emergence of concerns about the protection of women and girls from such violence. The article delves into controversial aspects, including competing theories to explain CRSV, the challenges in obtaining accurate data on its prevalence, and the often-overlooked issue of CRSV against men and boys. It also addresses the cultural and societal factors that perpetuate CRSV and the long-lasting consequences on survivors. The article concludes by underscoring the importance of comprehensive care for survivors and the need to tackle the deep-seated causes of this violence, including gender inequality.

UNASSIGNED: To examine the immediate effects of a comprehensive pain course on medical students\' pre-existing perceptions and attitudes toward pain patients and opioid management.
UNASSIGNED: First-year medical students at a major academic medical center enrolled in a required pre-clerkship pain course in June 2020 and completed pre- and post-course online surveys with Likert-scale questions about their attitudes toward pain management and opioid-related issues. Additionally, the surveys included a free-text question where the students listed the first five words that came to mind when hearing the word \"opioids\". These words were categorized as \"professional\" or \"lay\" words and further as having \"positive\", \"negative\", or \"neutral\" connotations. Data analyses included descriptive statistics, as well as non-parametric and parametric tests.
UNASSIGNED: Fifty-four of the 119 students responded to pretest and posttest surveys and were included in paired analyses. There was a significant difference between the number of professional words used before (M=1.21, SD=0.97) and after the course (M=2.40 SD=1.33); t(52)=-6.39, P<0.001. Students also used more lay-positive words after the course (M=0.81, SD=0.63) than they used pre-course (M=0.23, SD=0.43); t(51)=-5.98, P<0.001. Students\' post-course responses to several key Likert-scale questions showed significant shifts toward more positive attitudes about caring for patients with pain. For example, students acknowledged greater comfort in providing opioids for chronic pain (P<0.001) where appropriate, and enhanced interest in handling complex pain cases (P<0.001).
UNASSIGNED: Results showed that a comprehensive, multi-disciplinary pain course could greatly enhance first-year medical students\' attitudes toward pain management, chronic pain patients, and the complex issues surrounding opioids.