Hasil untuk "Men"

M. Litwin, Hung-Jui Tan

A. Bill-Axelson, L. Holmberg, H. Garmo et al.

BACKGROUND Radical prostatectomy reduces mortality among men with localized prostate cancer; however, important questions regarding long-term benefit remain. METHODS Between 1989 and 1999, we randomly assigned 695 men with early prostate cancer to watchful waiting or radical prostatectomy and followed them through the end of 2012. The primary end points in the Scandinavian Prostate Cancer Group Study Number 4 (SPCG-4) were death from any cause, death from prostate cancer, and the risk of metastases. Secondary end points included the initiation of androgen-deprivation therapy. RESULTS During 23.2 years of follow-up, 200 of 347 men in the surgery group and 247 of the 348 men in the watchful-waiting group died. Of the deaths, 63 in the surgery group and 99 in the watchful-waiting group were due to prostate cancer; the relative risk was 0.56 (95% confidence interval [CI], 0.41 to 0.77; P=0.001), and the absolute difference was 11.0 percentage points (95% CI, 4.5 to 17.5). The number needed to treat to prevent one death was 8. One man died after surgery in the radical-prostatectomy group. Androgen-deprivation therapy was used in fewer patients who underwent prostatectomy (a difference of 25.0 percentage points; 95% CI, 17.7 to 32.3). The benefit of surgery with respect to death from prostate cancer was largest in men younger than 65 years of age (relative risk, 0.45) and in those with intermediate-risk prostate cancer (relative risk, 0.38). However, radical prostatectomy was associated with a reduced risk of metastases among older men (relative risk, 0.68; P=0.04). CONCLUSIONS Extended follow-up confirmed a substantial reduction in mortality after radical prostatectomy; the number needed to treat to prevent one death continued to decrease when the treatment was modified according to age at diagnosis and tumor risk. A large proportion of long-term survivors in the watchful-waiting group have not required any palliative treatment. (Funded by the Swedish Cancer Society and others.).

M. Mielke, P. Vemuri, W. Rocca

With the aging of the population, the burden of Alzheimer’s disease (AD) is rapidly expanding. More than 5 million people in the US alone are affected with AD and this number is expected to triple by 2050. While men may have a higher risk of mild cognitive impairment (MCI), an intermediate stage between normal aging and dementia, women are disproportionally affected with AD. One explanation is that men may die of competing causes of death earlier in life, so that only the most resilient men may survive to older ages. However, many other factors should also be considered to explain the sex differences. In this review, we discuss the differences observed in men versus women in the incidence and prevalence of MCI and AD, in the structure and function of the brain, and in the sex-specific and gender-specific risk and protective factors for AD. In medical research, sex refers to biological differences such as chromosomal differences (eg, XX versus XY chromosomes), gonadal differences, or hormonal differences. In contrast, gender refers to psychosocial and cultural differences between men and women (eg, access to education and occupation). Both factors play an important role in the development and progression of diseases, including AD. Understanding both sex- and gender-specific risk and protective factors for AD is critical for developing individualized interventions for the prevention and treatment of AD.

Patricia G. Tjaden, N. Thoennes

S. Berry, D. S. Coffey, P. Walsh et al.

C. Hales, D. Barker, P. Clark et al.

Tom Bidewell, Artemis Deligianni, Tuğrulcan Elmas et al.

The influence of gender on online political communication remains contested, with existing scholarship providing mixed evidence as to whether gender shapes political messaging in digital environments. However, this debate has largely centred on mainstream platforms such as X (formerly Twitter), leaving the dynamics of alt-tech social media underexamined. This paper addresses this gap by analysing gendered patterns of political communication on Truth Social, a hyper-partisan platform that functions as a hub for the most committed followers of the American far right, a community closely associated with hegemonic masculine norms. To address this gap, we present the first large-scale analysis of political elite communication on Truth Social, using a novel dataset of 107k posts from 129 U.S. political figures. We examine the extent to which gender influences rhetorical style, topic framing, and audience engagement. We find that many gendered communication patterns documented on mainstream platforms persist on Truth Social. In particular, women political elites tend to express more joy and less anger than men and receive significantly higher levels of audience engagement. At the same time, more nuanced differences emerge. Although men and women political elites discuss largely similar conservative themes, they differ in how these issues are framed and in the rhetorical strategies employed. Notably, posts associated with women political elites contain higher levels of fear-based rhetoric, potentially suggesting selective adaptation in communicative style to navigate gender norms on the platform. These findings suggest that on Truth Social, an alt-tech platform with distinct ideological characteristics, mainstream gendered constraints persist, but are expressed through platform-specific communicative patterns shaped by its partisan orientation and sociotechnical environment.

Kimi Team, Tongtong Bai, Yifan Bai et al.

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that two modalities enhance each other. This includes a series of techniques such as joint text-vision pre-training, zero-vision SFT, and joint text-vision reinforcement learning. Building on this multimodal foundation, K2.5 introduces Agent Swarm, a self-directed parallel agent orchestration framework that dynamically decomposes complex tasks into heterogeneous sub-problems and executes them concurrently. Extensive evaluations show that Kimi K2.5 achieves state-of-the-art results across various domains including coding, vision, reasoning, and agentic tasks. Agent Swarm also reduces latency by up to $4.5\times$ over single-agent baselines. We release the post-trained Kimi K2.5 model checkpoint to facilitate future research and real-world applications of agentic intelligence.

Ana Maria Jaramillo, Mariana Macedo, Marcos Oliveira et al.

The participation of women in academia has increased in the last few decades across many fields (e.g., Computer Science, History, Medicine). However, this increase in the participation of women has not been the same at all career stages. Here, we study how gender participation within different fields is related to gender representation in top-ranking positions in productivity (number of papers), research impact (number of citations), and co-authorship networks (degree of connectivity). We analyzed over 80 million papers published from 1975 to 2020 in 19 academic fields. Our findings reveal that women remain a minority in all 19 fields, with physics, geology, and mathematics having the lowest percentage of papers authored by women at 14% and psychology having the largest percentage at 39%. Women are significantly underrepresented in top-ranking positions (top 10% or higher) across all fields and metrics (productivity, citations, and degree), indicating that it remains challenging for early researchers (especially women) to reach top-ranking positions, as our results reveal the rankings to be rigid over time. Finally, we show that in most fields, women and men with comparable productivity levels and career age tend to attain different levels of citations, where women tend to benefit more from co-authorships, while men tend to benefit more from productivity, especially in pSTEMs. Our findings highlight that while the participation of women has risen in some fields, they remain under-represented in top-ranking positions. Greater gender participation at entry levels often helps representation, but stronger interventions are still needed to achieve long-lasting careers for women and their participation in top-ranking positions.

Maria Teleki, Xiangjue Dong, Haoran Liu et al.

Masculine defaults are widely recognized as a significant type of gender bias, but they are often unseen as they are under-researched. Masculine defaults involve three key parts: (i) the cultural context, (ii) the masculine characteristics or behaviors, and (iii) the reward for, or simply acceptance of, those masculine characteristics or behaviors. In this work, we study discourse-based masculine defaults, and propose a twofold framework for (i) the large-scale discovery and analysis of gendered discourse words in spoken content via our Gendered Discourse Correlation Framework (GDCF); and (ii) the measurement of the gender bias associated with these gendered discourse words in LLMs via our Discourse Word-Embedding Association Test (D-WEAT). We focus our study on podcasts, a popular and growing form of social media, analyzing 15,117 podcast episodes. We analyze correlations between gender and discourse words -- discovered via LDA and BERTopic -- to automatically form gendered discourse word lists. We then study the prevalence of these gendered discourse words in domain-specific contexts, and find that gendered discourse-based masculine defaults exist in the domains of business, technology/politics, and video games. Next, we study the representation of these gendered discourse words from a state-of-the-art LLM embedding model from OpenAI, and find that the masculine discourse words have a more stable and robust representation than the feminine discourse words, which may result in better system performance on downstream tasks for men. Hence, men are rewarded for their discourse patterns with better system performance by one of the state-of-the-art language models -- and this embedding disparity is a representational harm and a masculine default.

Hartmut Häntze, Myrthe Buser, Alessa Hering et al.

Overlap-based metrics such as the Dice Similarity Coefficient (DSC) penalize segmentation errors more heavily in smaller structures. As organ size differs by sex, this implies that a segmentation error of equal magnitude may result in lower DSCs in women due to their smaller average organ volumes compared to men. While previous work has examined sex-based differences in models or datasets, no study has yet investigated the potential bias introduced by the DSC itself. This study quantifies sex-based differences of the DSC and the normalized DSC in an idealized setting independent of specific models. We applied equally-sized synthetic errors to manual MRI annotations from 50 participants to ensure sex-based comparability. Even minimal errors (e.g., a 1 mm boundary shift) produced systematic DSC differences between sexes. For small structures, average DSC differences were around 0.03; for medium-sized structures around 0.01. Only large structures (i.e., lungs and liver) were mostly unaffected, with sex-based DSC differences close to zero. These findings underline that fairness studies using the DSC as an evaluation metric should not expect identical scores between men and women, as the metric itself introduces bias. A segmentation model may perform equally well across sexes in terms of error magnitude, even if observed DSC values suggest otherwise. Importantly, our work raises awareness of a previously underexplored source of sex-based differences in segmentation performance. One that arises not from model behavior, but from the metric itself. Recognizing this factor is essential for more accurate and fair evaluations in medical image analysis.

Marije H. Sluiskes, Eva A. S. Koster, Jelle J. Goeman et al.

Abstract Background Vulnerable subgroups of the population, such as care home residents, often face elevated mortality risks during crises like pandemics or wars. To correctly model and interpret the excess mortality of vulnerable groups during crises, a distinction must be made between the pre-existing heightened mortality of the vulnerable group, the general population’s excess mortality during the crisis, and the crisis-specific excess mortality unique to the vulnerable group. Methods We introduce the concept of “excess excess” mortality, which captures the extra excess mortality experienced by vulnerable groups during crises, beyond what can be explained by their excess mortality due to being vulnerable and general population excess mortality. Using individual-level data from Statistics Netherlands, we model the excess excess mortality of Dutch care home residents aged 70 and older during the Covid-19 pandemic. We extend standard relative survival methods by incorporating multiple excess mortality components and use an additive hazards model to accommodate periods of negative excess hazard. Results The findings confirm the severe impact of the Covid-19 pandemic on care home residents. In general, men and older age groups experienced higher excess excess mortality, both in absolute and relative terms. Conclusions Our approach offers a new perspective on how to model and interpret excess mortality in vulnerable groups during a crisis and provides a methodological foundation for investigating excess excess mortality in other contexts.

Mi Zhou, Vibhanshu Abhishek, Timothy Derdenger et al.

This study analyzed images generated by three popular generative artificial intelligence (AI) tools - Midjourney, Stable Diffusion, and DALLE 2 - representing various occupations to investigate potential bias in AI generators. Our analysis revealed two overarching areas of concern in these AI generators, including (1) systematic gender and racial biases, and (2) subtle biases in facial expressions and appearances. Firstly, we found that all three AI generators exhibited bias against women and African Americans. Moreover, we found that the evident gender and racial biases uncovered in our analysis were even more pronounced than the status quo when compared to labor force statistics or Google images, intensifying the harmful biases we are actively striving to rectify in our society. Secondly, our study uncovered more nuanced prejudices in the portrayal of emotions and appearances. For example, women were depicted as younger with more smiles and happiness, while men were depicted as older with more neutral expressions and anger, posing a risk that generative AI models may unintentionally depict women as more submissive and less competent than men. Such nuanced biases, by their less overt nature, might be more problematic as they can permeate perceptions unconsciously and may be more difficult to rectify. Although the extent of bias varied depending on the model, the direction of bias remained consistent in both commercial and open-source AI generators. As these tools become commonplace, our study highlights the urgency to identify and mitigate various biases in generative AI, reinforcing the commitment to ensuring that AI technologies benefit all of humanity for a more inclusive future.

Ayhan Tabur, Feruza Turan Sonmez

Suicide is a major global public health issue and a growing concern in Turkiye, driven by demographic and societal changes. This study aimed to examine suicide trends in Turkiye from 2000 to 2022, focusing on sociodemographic changes, gender differences, and public health implications, particularly in emergency medicine. A retrospective analysis was conducted using data from the Turkish Statistical Institute (TurkStat) and other national databases. Between 1975 and 2022, suicide rates in Turkiye increased by 81%, rising from 2.75/100,000 in 1975 to 4.98/100,000 in 2021. A total of 145,200 suicides were recorded, with most occurring between 2000 and 2022. Men accounted for 71.6% of suicides, with an average rate of 6.12/100,000, compared to 2.35/100,000 for women. The most notable increase in female suicide rates occurred in the last decade, with a 45% rise from 2012 to 2021, peaking at 3.65/100,000 in 2021. In contrast, the male suicide rate peaked at 6.94/100,000 during the same year. The highest suicide rates were observed in the 20–24 age group, with a peak of 7.43/100,000 in 2020. While the overall rate among individuals aged 65 and older was lower (2.9/100,000), a significant increase was noted in recent years, peaking at 4.2/100,000 in 2019. From 2010 to 2021, total suicide rates increased by 35%, with female suicides rising by 45% and male suicides by 27%. These findings highlight the urgent need for targeted public health interventions in Turkiye, particularly for young adults and women. Emergency departments play a pivotal role in identifying at-risk individuals, emphasizing the importance of enhanced screening protocols and mental health assessments. Addressing broader socioeconomic and cultural factors is essential for effective suicide prevention strategies. [Med-Science 2024; 13(4.000): 911-20]

Nazlı Kazanoğlu

Gender equality has long been a central theme of the European social model since the Maastricht Treaty. Using the example of work - life balance policies, this article aims to identify two successive periods and explore the changing policy paradigm with respect to gender equality at the EU. In so doing, the article draws on two conceptual approaches in terms of theoretical basis: (a) Esping-Andersen’s three welfare pillar conceptualisation and (b) genderised and de-genderised distinction. Drawing on a comprehensive literature review and the content analysis of official EU policy texts, the article contends that the EU gender policies have shifted away from serving to change the redistribution of work between men and women, towards improving women’s employment opportunities.

Diego GentilePassaro, Fuhito Kojima, Bobak Pakzad-Hurson

Equal pay laws increasingly require that workers doing "similar" work are paid equal wages within firm. We study such "equal pay for similar work" (EPSW) policies theoretically and test our model's predictions empirically using evidence from a 2009 Chilean EPSW. When EPSW only binds across protected class (e.g., no woman can be paid less than any similar man, and vice versa), firms segregate their workforce by gender. When there are more men than women in a labor market, EPSW increases the gender wage gap. By contrast, EPSW that is not based on protected class can decrease the gender wage gap.

Fabiana Martins Dias de Andrade, Ísis Eloah Machado, Maria Imaculada de Fátima Freitas et al.

This study aimed to describe the characteristics of elderly people abuse notifications by gender and to assess notification patterns according to gender. We analyzed data from the Brazilian Information System for Notificable Diseases (SINAN) in 2017. We carried out a descriptive analysis of victim characteristics, violence, and the probable perpetrator according to gender. Pearson’s χ2 test was used to assess the significance between groups. Then, we verified the main relationships between the studied characteristics and the victim’s gender by simple correspondence analysis (SCA). Thus, 17,311 cases/suspicions of elderly people abuse were notified, corresponding to 7.2% of the total number of violence notifications. Of these victims, 50.4% were white, 42.3% were married, and 17.2% had a disability/disorder; 76.9% occurred at home, 62.8% included physical violence, and 49.5% were cases of repeated violence. Most perpetrators were men (62%), and violence by two or more perpetrators was observed in 62.8% of the cases. SCA evidenced inequalities in older adults’ gender, which proved to be higher among women. Physical violence was the most common among younger and old individuals, whereas neglect/abandonment tended to occur more frequently among the oldest individuals, and was most often committed by daughters. In sum, this study demonstrated evidence of gender-based violence, especially among older adults. Disability proved to be an essential characteristic for neglect/abandonment in older adults. In this context, policies are needed to reduce gender inequalities and implement a care network for older adults who are victims of violence.

Jose Maria Pereira de Godoy, Fernando Reis Neto, Gabriela Leopoldino da Silva et al.

Aortic thrombosis has been studied little in patients with COVID-19 and an association has recently been reported with the vaccine for this disease. The aim of the present study is to report five cases of aortic thrombosis at our institution within a three-month period associated with the COVID-19 vaccine. Five cases of aortic thrombosis were evaluated—three women and two men aged 29, 49, 51, 60, and 79 years. Four thrombi involved the thoracic aortic and one involved the abdominal aorta, with embolisms found in the kidneys, spleen, liver, upper limbs, and lower limbs. Embolectomy was performed on the limbs, and anticoagulant therapy was performed for the abdominal arteries. The patients recovered well and anticoagulant therapy was maintained. Aortic thrombosis is uncommon but was associated with the AstraZeneca vaccine in this case series.

Manuel-Vicente Garnacho-Castaño, Marcos Faundez-Zanuy, Noemi Serra-Payá et al.

This study aimed to assess the reliability and validity of the Polar V800 to measure vertical jump height. Twenty-two physically active healthy men (age: 22.89 +- 4.23 years; body mass: 70.74 +- 8.04 kg; height: 1.74 +- 0.76 m) were recruited for the study. The reliability was evaluated by comparing measurements acquired by the Polar V800 in two identical testing sessions one week apart. Validity was assessed by comparing measurements simultaneously obtained using a force platform (gold standard), high-speed camera and the Polar V800 during squat jump (SJ) and countermovement jump (CMJ) tests. In the test-retest reliability, high intraclass correlation coefficients (ICCs) were observed (mean: 0.90, SJ and CMJ) in the Polar V800. There was no significant systematic bias +- random errors (p > 0.05) between test-retest. Low coefficients of variation (<5%) were detected in both jumps in the Polar V800. In the validity assessment, similar jump height was detected among devices (p > 0.05). There was almost perfect agreement between the Polar V800 compared to a force platform for the SJ and CMJ tests (Mean ICCs = 0.95; no systematic bias +- random errors in SJ mean: -0.38 +- 2.10 cm, p > 0.05). Mean ICC between the Polar V800 versus high-speed camera was 0.91 for the SJ and CMJ tests, however, a significant systematic bias +- random error (0.97 +- 2.60 cm; p = 0.01) was detected in CMJ test. The Polar V800 offers valid, compared to force platform, and reliable information about vertical jump height performance in physically active healthy young men.

Sayma Sultana, Asif Kamal Turzo, Amiangshu Bosu

Context: Contemporary software development organizations lack diversity and the ratios of women in Free and open-source software (FOSS) communities are even lower than the industry average. Although the results of recent studies hint the existence of biases against women, it is unclear to what extent such biases influence the outcomes of various software development tasks. Aim: We aim to identify whether the outcomes of or participation in code reviews (or pull requests) are influenced by the gender of a developer.. Approach: With this goal, this study includes a total 1010 FOSS projects. We developed six regression models for each of the 14 dataset (i.e., 10 Gerrit based and four Github) to identify if code acceptance, review intervals, and code review participation differ based on the gender and gender neutral profile of a developer. Key findings: Our results find significant gender biases during code acceptance among 13 out of the 14 datasets, with seven seven favoring men and the remaining six favoring women. We also found significant differences between men and women in terms of code review intervals, with women encountering longer delays in three cases and the opposite in seven. Our results indicate reviewer selection as one of the most gender biased aspects among most of the projects, with women having significantly lower code review participation among 11 out of the 14 cases. Since most of the review assignments are based on invitations, this result suggests possible affinity biases among the developers. Conclusion: Though gender bias exists among many projects, direction and amplitude of bias varies based on project size, community and culture. Similar bias mitigation strategies may not work across all communities, as characteristics of biases and their underlying causes differ.