The overarching aim was to explore women registered nurses' perceptions of gender discrimination in the workplace. A descriptive cross-sectional exploratory survey within a sequential explanatory mixed methods study. Between September and December 2023, data were collected from 173 registered nurses who self-identified as women. The survey captured demographic data, attitudes to gender discrimination in society using the 'Contemporary Gender Discrimination Attitude Scale' and perceptions of workplace gender discrimination in nursing across four dimensions, assessed using the 'Perception of Workplace Gender Discrimination for Women Nurses Scale' (PWGD-WN). Descriptive statistics presented as means and standard deviations were used to describe and interpret data. Regression analysis and chi-square tests were employed to examine associations between key variables. The mean score on the Contemporary Gender Discrimination Attitude Scale was 4.56 (on a 6-point scale), indicating that on average respondents agreed that gender discrimination remains an issue in society. The PWGD-WN scale mean scores for the dimensions of gender discrimination (5-point scale) from lowest to highest were: 'Gender bias from other women' (Mean: 3.13, SD: 1.147), 'Interpersonal discrimination' (Mean: 3.30, SD: 1.135), 'Glass escalator' (Mean: 3.77, SD: 0.946) and 'Primary carer' (Mean: 3.86, SD: 0.796); higher scores indicated agreement with items. 'Primary carer' was the strongest predictor of attitude, followed by the 'Glass escalator'. Highest qualification obtained was highlighted as a key predictor of nurses' perceptions of workplace discrimination. The results of this study highlight that women in nursing perceive that systemic and multidimensional discrimination exists in the workplace. The results can be utilised to understand how discrimination manifests in the workplace for women in a woman-dominated profession. This research provides the first quantitative measure of perceived workplace gender discrimination for Australian women registered nurses. We have adhered to relevant EQUATOR guidelines-STROBE. This study did not include patient or public involvement in its design, conduct or reporting.

Letters of recommendation (LORs) are a key component of the residency selection process, particularly as objective metrics become less available. Previous studies across specialties have identified implicit gender and racial biases in narrative LORs (NLOR), potentially influencing perceptions of applicants. This study assessed whether such biases are present in NLORs for Neurology residency applicants. We conducted a retrospective analysis of NLORs written for all American (US) medical school graduates applying to a single academic Neurology residency program during the 2021-2022 application cycle. Letters were analyzed using Linguistic Inquiry and Word Count (LIWC) software to evaluate structural, cognitive, and emotional language features. Custom dictionaries assessed applicant-related language (e.g., ability, doubt-raising, and gendered terms). Multivariable analyses were performed to examine variations in language use by applicant gender (man vs woman) and race (majority vs underrepresented in medicine [URiM]) across predefined linguistic categories. Analyses were further stratified by letter-writer gender, academic rank, and geographic region. A total of 431 NLORs were analyzed; 239 (55.8%) were written for female applicants and 72 (16.7%) for URiM applicants. In primary analysis, no significant differences were seen in LORs based on applicant race or gender. Letters for male applicants written by professors showed more gendered language compared with those for female applicants (0.32, IQR: 0.27-0.37 vs 0.15, IQR: 0.13-0.18, p = 0.002). Secondary subgroup and regional analyses did not reveal any significant findings. In this linguistic analysis of Neurology NLORs, we did not identify broad or systematic bias in letters written by adult neurologists for Neurology applicants. Our findings suggest that the continued use of NLORs for Neurology residency applicants is appropriate. Larger, multi-institutional studies are warranted to validate these findings and clarify the potential biasing effect of gendered language in LORs.

"I had no safe space." Painful childhood experiences in the lives of men who are suicidal: A qualitative thematic analysis.

AI generated text-to-image tools are rapidly entering educational settings, yet little is known about how their visual biases intersect with goals of equity, inclusion, and critical AI literacy. This systematic literature review maps and analyzes empirical studies that examine bias and representation in educational uses of AI generated text-to-image. Following PRISMA guidelines, we identified 31 peer reviewed studies published between 2023 and 2025 across K-12, higher education, and professional learning contexts. We used a six part analytic framework (gender; race, ethnicity, and socioeconomic status; culture and religion; age; body and (dis)ability; and content) to code how studies conceptualized and investigated bias. Across the corpus, biased representation was pervasive: images frequently centered white, male, Western, thin, and non disabled figures, while diversity related to age, body, and ability was largely overlooked. Most studies relied on image audits and qualitative methods, with few experimental or intervention based designs. This review is the first to synthesize how educational research conceptualizes, measures, and responds to bias in text-to-image tools’ outputs. The findings reveal significant blind spots and highlight directions for research, design, and policy aimed at aligning generative AI with educational inclusion and critical AI literacy. • First systematic review of AI text-to-image use in education (31 studies). • Shows how educators and students use AI images in diverse educational contexts. • Identifies recurring gender, racial, cultural, age, body and (dis)ability biases in AI images. • Reveals tensions between visually appealing images and factual or ethical accuracy. • Argues for moving from prompt engineering toward critical, technomoral AI literacy.

Healthcare providers often rely on the following sort of concerning reasoning when encountering patients with difficult-to-explain symptoms: in the absence of evidence for a physical cause, the symptoms are presumed to be psychological in origin. In this paper, we take up this concern in the context of chronic pain, with particular attention to how such reasoning disproportionately affects women and how it interacts with the many levels of gender bias in medicine. We first examine the unwarranted inference from diagnostic uncertainty to psychogenic diagnosis and explore how identity prejudice and diagnostic uncertainty interact in clinical practice. We then consider additional contributors to diagnostic uncertainty concerning women's pain: gendered research gaps and male-centered diagnostic paradigms. After outlining the harms associated with psychogenic diagnoses, we consider the objection that such diagnoses might be pragmatically justified. We end by calling for a more nuanced approach to diagnosing and treating chronic pain.​​.

Tarsus length as a simple and robust candidate for early sex determination in partridges across contrasting growing contexts: a case study in Rock partridge (Alectoris graeca Meisner, 1804).

ABSTRACT Background and Context Integrating computational thinking (CT) into K-12 education is hindered by insufficient teacher training, gender biases in STEM, and challenges in evaluating professional development (PD) programs due to limited assessment tools. Most research overlooks affective and contextual variables, focusing only on CT skills. Objective The study aims to understand the factors that enable an effective integration of CT teaching practices and gender affirmative actions, after teachers participate in a PD program. Method We used a sequential explanatory mixed methods design to examine a nationwide PD program for middle and high school teachers in a middle-income country. Pretest-posttest surveys (n = 3790) and classroom observations (n = 383) assessed teachers’ CT knowledge, technological self-efficacy, practices, and gender bias, while three focus groups involving 17 teachers explored the mechanisms influencing these outcomes. Findings The PD program significantly improved teachers’ content knowledge in CT, technological self-efficacy, and reduced gender bias in STEM. However, classroom observations revealed incomplete implementation of CT practices and gender equity strategies. Qualitative findings suggest key mechanisms shaping teacher implementation practices: teachers’ cognitive shifts toward recognizing CT’s relevance across disciplinary domains and school subjects; perceived capacity in managing technological tools and technological complexity; the importance of institutional support; and, reflective processes triggered by observing increased engagement among female students. Implications Teachers’ cognitive shifts, self-efficacy, and institutional support are pivotal for effective CT integration into school practices. Our findings underscore the necessity of PD programs to address these aspects, fostering the intentional application of CT practices and gender equity strategies.

Gender biases in healthcare approaches lead to inequities in patient health outcomes, historically affecting women and gender minorities the most. In medicine, the concept of gender medicine explicitly addresses these disparities. Although Miers introduced the term gender-sensitive care in nursing two decades ago, there is still no consensus on how to define this phenomenon within the nursing discipline. To conduct an operational concept analysis of gender-sensitive nursing. A systematic literature review was performed using Walker and Avant's concept analysis method. This approach allowed for the identification of antecedents, defining attributes, empirical referents and consequences, as well as the proposal of model cases to illustrate the findings. A total of 34 articles were analysed. Three antecedents were identified: healthcare system accessibility, organizational commitment to equity and education from a gender perspective. Four defining attributes emerged: gender-aware nurses, legitimization of care, implementation of a gender-sensitive approach in nursing management and leadership, and the integration of gender assessment in the nursing process. Three key consequences were also identified: patient empowerment, harm prevention and minimization, and improvement in the quality and effectiveness of nursing care. Additionally, various instruments and strategies were found to operationalize the empirical referents of the concept. Model cases were proposed to exemplify the synthesized evidence. Far from being an abstract concept, gender-sensitive nursing is a measurable and actionable phenomenon that can be promoted in clinical practice through various empirical indicators. Gender-sensitive nursing legitimizes individual experiences shaped by gender identity and fosters structural improvements that empower patients. Gender-sensitive nursing is a measurable and actionable phenomenon that can be promoted in clinical practice through various empirical indicators.

The OET Autism Framework represents a social justice response to the diagnostic disparities of misdiagnosis, underdiagnosis, and late diagnosis experienced by adolescent and adult autistic females. The theoretical intersection of optimal distinctiveness and empowerment theories and trauma-informed care incorporates lived experience narratives to produce an intersectional, antioppressive, and strengths-based approach to holistic therapeutic assessment to inform treatment choice. The author proposes core principles that are aligned with the theoretical underpinnings of the OET Autism Framework to guide practitioners in its clinical application to foster collaborative goal setting, treatment planning, and treatment choice with this population. Seminal and present-day autism scholarship is revisited to expose the impact of gender assumptions and biases that have perpetuated harm and informed treatment choice for adolescent and adult autistic females. Accentuating the ethical responsibilities of the social work profession, the author proposes future recommendations to invite critical analysis from autism scholars to explore the efficacy of the framework and clinical assessment tool identification.

This paper introduces the Semantic Propagation Graph Neural Network (SProp GNN), a machine learning emotion prediction (EP) architecture that relies exclusively on syntactic structures and word-level emotional cues to predict emotions in text. By semantically blinding the model to information about specific words, it is robust to social biases such as political or gender bias that have been plaguing previous machine learning-based EP systems. The SProp GNN shows performance superior to lexicon-based alternatives such as VADER (Valence Aware Dictionary and Sentiment Reasoner) and Emotlas on two different prediction tasks, and across two languages. Additionally, it approaches the accuracy of transformer-based models - with an average of 5.7% difference in accuracy scores on discrete English benchmarks, and from 0.075 to 0.145 correlation difference on English and Polish dimensional emotion prediction datasets - while significantly reducing bias in emotion prediction tasks. By offering improved explainability and reducing bias, the SProp GNN bridges the methodological gap between interpretable lexicon approaches and powerful, yet often opaque, deep learning models, offering a robust tool for fair and effective emotion prediction in understanding human behavior through text.

Feminism is culturally salient for adolescent girls and may be psychologically protective. Despite adolescence being a key period of identity development, little is known about how adolescent girls perceive and orient toward feminism. Using a diverse sample of 586 adolescent girls from across the US (32% Black, 28% white, 11% Latina, 5% Asian American, 21% multiracial), a mixed methods analysis was conducted to explore (1) girls' rates of feminist orientation, (2) their beliefs about feminism, and (3) the psychosocial factors related to a feminist orientation. Nearly half of girls considered themselves to be feminists and qualitative responses revealed considerable diversity and nuance in girls' beliefs about feminism, including varied praises and criticisms. Quantitative analysis showed feminist orientation to be correlated with more frequent experiences with gender discrimination, as well as indices of gender identity, including gender identity centrality and self-perceived similarity to boys (though not similarity to girls). These findings provide important insights into the ways a feminist identity can support adolescent girls' well-being.

Global mental health disparities among transgender women and transfeminine people living with HIV: a systematic review and meta-analysis of 63 studies.

ABSTRACT After the Islamic revolution, women in Iran were banned from entering soccer stadiums. However, despite this prohibition, many Iranian women are passionate about soccer and are attempting to establish a fandom subculture to combat gender discrimination. This study aims to explore the life stories of these women in Isfahan, Iran, using narrative analysis and Clandinin and Connelly’s narrative model. The research will demonstrate how Iranian women experience a unique form of soccer fandom despite being barred from entering the stadium.

22q11 deletion syndrome (22q11DS) is the most common microdeletion in humans, leading to a wide range of variable clinical manifestations that can affect any part of the body. Most individuals with 22q11DS are diagnosed during childhood and the responsibility of care falls on their primary caregivers, usually their parents, who need to balance the needs of all family members including themselves. This affects parental wellbeing. This study investigates the perspective of healthcare professionals (HCPs), in Europe and Canada, on the parents' struggle with time invested in caring for their children, factors contributing, the impact of this responsibility and some strategies on how to support the families. This interview study was part of a larger research initiative aimed at improving the psychosocial well-being of individuals with 22q11DS and their families. The qualitative component concentrated on gathering insights from HCPs involved in patient care. We conducted qualitative content analysis after transcribing the semi-structured interviews. The research question focused on time poverty within families caring for a child with 22q11DS from the perspective of HCPs. The 20 HCPs interviewed came from diverse professional backgrounds, but all had clinical experience with children with 22q11DS. Our analysis of the data identified three primary themes, centered on time poverty of families caring for a child with 22q11DS. Centralization of care and insufficient coordination were the main modifiable reasons for the time struggle, affecting the families, especially mothers and families living in rural areas. Strategies proposed to mitigate this issue included improved coordination and decentralization of care, and digitalization. Time poverty for families with a child with 22q11DS may result from fragmented and uncoordinated medical care, and centralized care disconnected from local care. Better communication between different HCPs, local and central, and a robust support system could enhance these families' well-being and assure an equal distribution of care services without gender bias or exclusion of rural underserved populations.

The purpose of this commentary is to highlight the mechanisms through which the contradiction between capital and life manifests itself by analyzing the sustainability of debt and fiscal rules. Debt management instruments are designed to reduce the risks faced by capital in the event of a debt crisis at the expense of exacerbating the crisis of social reproduction, the costs of which fall on families and women. Gender biases in the international debt architecture challenge the sustainability of life, and it is necessary to discuss the changes required.

ABSTRACT How does gender impact the amount of media coverage individual extremists receive? In criminology and terrorism studies, a large body of research has shown that women are viewed differently when it comes to crime and terrorism. Yet, these insights have not led to an examination of the question of gender and the amount of media coverage as it applies to extremism. This article remedies this by presenting and testing an argument regarding the impact of gender on media coverage of extremists using newly collected data of media attention given to individual extremists in the United States from 2001 to 2021. The results show that women extremists are given less media coverage than men, even when controlling for other factors. Media organizations need to ensure that they are providing consistent coverage to all aspects of the issue of extremism and terrorism to ensure the public is well informed about the overall threat.

To develop and evaluate an automatic patient review analyzer that applies advanced Natural Language Processing (NLP) and machine learning methods to improve the efficiency, fairness, and accuracy of healthcare feedback analysis. We designed a multi-component pipeline incorporating sentiment analysis, key theme extraction, clinical Named Entity Recognition (NER), and fairness modules. Bias mitigation was addressed through the integration of three complementary approaches: adversarial debiasing, Hard Debiasing, and Iterative Null-space Projection (INLP). Multiple BERT-based models (DistilBERT, BioBERT, RoBERTa-base, BERT-base-uncased) were trained and evaluated under varying hyperparameters and fairness/adversarial loss configurations. Model performance was assessed using accuracy, F1, recall, precision, AUC, Equalized Odds (EOD), and Word Embedding Association Test (WEAT) metrics. Adversarial loss ([Formula: see text]) consistently decreased model performance across accuracy, F1, precision, and recall. In contrast, Hard Debiasing and INLP improved WEAT scores while preserving or enhancing other metrics, with INLP yielding the best overall performance. Specifically, INLP with fairness loss improved EOD by 14%, gender WEAT scores by 15%, and achieved slight gains for ethnicity and socioeconomic WEAT scores. The best model achieved accuracy of 0.856, F1 score of 0.812, recall of 0.798, and precision of 0.829. The key theme analysis module identified 82% of expert-labeled themes, though 21% of patient comments lacked expert labels for valence or related attributes. Our results demonstrate the trade-offs between fairness and performance in bias mitigation strategies. While adversarial debiasing reduced predictive accuracy, INLP and Hard Debiasing improved fairness without significant degradation in task performance. Gender bias was easier to mitigate than multi-class sensitive attributes such as ethnicity and income. This difference indicates a need for fairness techniques designed for multi-class sensitive attributes. This work presents an NLP pipeline for patient feedback analysis with multiple debiasing strategies. This pipeline improves the fairness and accuracy of insights from unstructured patient reviews and supports inclusive patient-centered care.

Asian American women represent a significant portion of the healthcare workforce, but there has been little research on their experiences of workplace bias, such as microaggressions and discrimination. To describe the experiences of Asian American women healthcare workers (HCWs) on the issues of race, gender, and workplace bias within healthcare organizations. Semi-structured qualitative interviews were conducted via video-conferencing from July 2022 to March 2023. Twenty-five participants who self-identified as Asian American women and worked in the Pacific Northwest were interviewed. Participants held a variety of professional roles, such as nursing assistants (CNAs), medical assistants (MAs), nurses (RNs), advanced practice providers (APPs), and physicians. They were employed in various medical and surgical specialties and worked in both clinics and hospitals in urban and rural settings. The types of workplace bias experienced by Asian American women HCWs, their impact on participants, and how participants coped with these experiences were recorded through one-on-one interviews with study authors. These interviews were transcribed and analyzed using an inductive approach to thematic analysis. Participants reported a variety of interpersonal microaggressions and organizational discrimination with impacts on their wellbeing and career trajectories. Microaggressions included underestimation of a participant's role and competence, stereotypes of homogeneity, assumption of foreignness, and hypersexualization. Participants reported developing a variety of coping strategies to deal with microaggressions and organization-level discrimination. Asian American women HCWs commonly reported facing challenges of racism and sexism and experiencing heightened stress from workplace bias. Healthcare organizations need a greater understanding of these challenges to support women HCWs of color and boost retention of healthcare professionals with diverse backgrounds.

ABSTRACT This article explores how conflict intensifies and institutionalises gender bias in radio journalism in Burkina Faso, revealing a self-reinforcing cycle between newsroom practices, gendered power relations, and media representations. Bridging media, gender, and conflict studies, it shows how entrenched societal gender norms and structural inequalities within media organisations are sharpened under conditions of insecurity. The findings demonstrate that journalists’ often unconscious gender biases shape editorial decisions, field assignments, and interactions with affected communities, and are reproduced in broadcast content. Women journalists reported systematic exclusion from “hard news” and conflict reporting due to assumptions of fragility, while simultaneously being assigned emotionally demanding coverage such as trauma and gender-based violence. These contradictions both reflect and reinforce conflict-driven gender expectations associated with hegemonic masculinity and constructions of feminine vulnerability. Methodologically, the study combines focus groups, interviews, and radio content analysis. To organise and interpret the findings, we applied a framework comprising seven areas of analysis to identify domains of gender bias in humanitarian organisations and adapted it here to journalism in conflict settings. This framework elucidates how gender bias emerges across day-to-day practices, fieldwork, organisational processes, professional development, and interactions with affected populations, showing how conflict exacerbates existing inequalities in the media sector.

Chronic fluid overload (FO) can be detected using bioimpedance spectroscopy (BIS) and is associated with higher mortality risk than interdialytic weight gain in patients receiving hemodialysis (HD). This study aimed to explore patients' perspectives and comprehension of FO and dry weight. Qualitative study arm of an exploratory, nonrandomized observational study. Semistructured interviews were conducted in 25 HD patients at Vienna General Hospital. A survey was developed based on the interview data and distributed across 3 HD centers (n = 148). A mixed-methods approach was applied: grounded theory guided qualitative coding, whereas survey data were analyzed descriptively. 11 of 25 interviewed patients had chronic FO > 15% BIS-defined extracellular volume predialysis. Theme 1, "Being aware of fluid restrictions," contained the following subthemes: (1a) "Restrictive fluid intake is the major burden," (1b) "Symptom awareness of FO," (1c) "Misconception of chronic FO," (1d) "Unawareness of BIS," and (1e) "neglected salt restriction." Subthemes 1c and 1d were reinforced by the survey, in which 54.7% fully or partially agreed that chronic FO occurs between HD sessions (misunderstood as interdialytic weight gain). Theme 2, "Dry weight is a feel-good factor," contained subthemes, (2a) "Inconclusive definitions of dry weight," (2b) "Better too high than too low," (2c) "Self-management of dry-weight prescription," and (2d) "Uncertainties in weight documentation." In our survey, 77.9% reported being able to define dry weight; 64.2% fully or partially agreed they currently had the correct dry weight; and 65.0% did not feel overhydrated (chronic FO was prevalent in ∼40%). 64.5% were not interested in participating in an educational event on dry weight and chronic FO. Sample size, gender bias, and the survey was not validated externally. Substantial knowledge gaps existed regarding dry weight and chronic FO, necessitating improved patient engagement strategies into fluid management and further research into the underlying reasons for patients' disinterest.