Does what doctors wear really matter? The DRESS prospective study on patient trust.

Urgent Need for Artificial Intelligence Readiness: Insights From a Multicenter Cross-Sectional Study on Medical Undergraduates and Radiology Trainees in Central and Western China.

This article examines systematic breaches of medical confidentiality in Argentina's reproductive healthcare system, where healthcare providers often report patients experiencing obstetric emergencies to law enforcement agencies. Drawing on judicial records, interviews with healthcare professionals, and analysis of medical curricula, the study shows how structural weaknesses, regulatory ambiguities, and biases in medical education undermine professional confidentiality, turning hospitals into patients' entry points to the criminal justice system rather than spaces of care. Despite strong constitutional protections and Supreme Court rulings affirming patients' rights to confidentiality, significant gaps persist between legal standards and practice. Situating Argentina within broader Latin American patterns, the article argues that clearer institutional guidelines, improved professional training, and consistent judicial interpretation are needed to align medical practice with human rights standards and rebuild patient trust.

Overactive bladder (OAB) is a prevalent condition associated with impaired quality of life, yet many patients do not pursue treatment or minimally invasive therapies (MIT). Physician-patient concordance has been proposed as a factor influencing trust, although its role in OAB care is not well defined. We evaluated the association between physician gender concordance and patient trust, and examined the relationship of trust with health literacy, medical mistrust, and treatment preferences for OAB among broad U.S. consumers. In this survey-based study, Black and White women were randomized to view 1 of 4 standardized videos describing OAB treatments, differing only by physician race and gender. Trust was dichotomized from a 4-point Likert scale. Participants reported treatment preferences and completed the eHealth Literacy Scale (eHEALS) and Group-Based Medical Mistrust Scale (GBMMS). Associations were assessed using chi-square tests and multivariable logistic regressions. Among 1,027 participants, physician gender concordance was not associated with trust (p>0.05). Trust was strongly associated with both OAB diagnosis (p=.001) and selection of MIT (p<.001). Higher eHealth literacy independently increased the odds of trust (OR 1.06, p<.001), whereas greater medical mistrust reduced the odds (OR 0.94, p<.001). Income was also independently associated with trust. Race was not an independent predictor, although Black participants reported significantly higher medical mistrust. Greater patient trust increased likelihood of having an OAB diagnosis and selection of MIT. Health literacy and medical mistrust demonstrated stronger associations with trust than physician gender concordance, highlighting potential areas for improving patient engagement in OAB care.

CORR Insights®: Are LGBTQ+ Allyship Symbols Associated With Patient Trust in the Orthopaedic Surgeon? A Dual Cohort Survey.

To assess patient trust in AI-generated medication information, examine associated behavioral safety risks, and evaluate patient expectations regarding the role of clinical pharmacists in preventing medication-related harm. A cross-sectional survey was conducted among adult patients attending outpatient clinics and community pharmacies in Abha, Saudi Arabia. Data were collected across 3 sites (King Khalid University Hospital outpatient department and 2 affiliated community pharmacies) over a 10-week period (December 2025-January 2026), after ethical approval (KKU-147-2025-31). A structured questionnaire assessed demographic characteristics, AI use patterns, trust in AI-generated medication information, verification behaviors, and perceptions of pharmacist involvement. Psychometric evaluation demonstrated good internal consistency of the trust in AI scale. Data were analyzed using descriptive statistics, nonparametric tests, exploratory factor analysis, and ordinal logistic regression. Among 167 participants, trust in AI-generated medication information varied significantly across demographic groups and AI platforms, with higher trust reported for large language model-based tools. Participants without health care backgrounds demonstrated higher trust than health care professionals. Increasing trust was associated with higher behavioral risk, including acting on AI-generated medication advice without verification (P=0.002). Factor analysis identified distinct cognitive trust and behavioral engagement dimensions. Strong support was observed for pharmacist involvement in verifying AI-generated medication information. Patient trust in AI-generated medication information is closely linked to behaviors that may increase medication-related safety risks. Clinical pharmacists play a critical role as a safety barrier, underscoring the need to integrate pharmacist-led verification into AI-informed medication counseling to enhance patient safety.

BackgroundThe use of generative artificial intelligence (AI) by pharmaceutical companies and other organizations for preparing patient-facing documents reporting results of clinical research is becoming more common. This raises concerns about whether the accuracy and quality of these documents could be affected, as well as the potential impact on patient perceptions and trust. Accurate and trustworthy information is critical to health care decision-making. Little is known about patient perceptions of AI-generated content.ObjectiveThis study aimed to better understand patient experience and familiarity with AI, their resulting confidence in the abilities of AI, and their trust in the use of AI by research organizations to generate clinical research documents.MethodsAn online survey was conducted using an online health care panel of patients in Europe and the United States to assess familiarity with AI, trust in organizations reporting on research, and trust in the use of AI to prepare clinical research documents. The survey also asked directly about the importance of human involvement and of transparency in disclosing AI use.ResultsA total of 1010 respondents completed the online survey. About half of respondents were from the United States and half from Europe. Survey results showed that 63.6% (642/1010) of respondents had used AI before with 74.9% (756/1010) reporting being “Somewhat” or “Very” familiar with AI. AI use was influenced by country, gender, education level, race/ethnicity, and clinical trial experience. Higher familiarity with AI was observed among younger participants. Respondents were generally confident in the capabilities of AI, as more than half believed AI use would reduce grammar and data errors. Trust in clinical trial documents generally increased with greater human oversight, as trust was lowest for documents created by AI with no human involvement (12.3% “A lot” of trust, 124/1010) and highest for documents created by humans without AI (39.1% “A lot” of trust, 395/1010). 95.0% (959/1010) of respondents considered human involvement in clinical trial document review as “Very important” or “Somewhat important.” The majority (62.4%, 630/1010) of respondents felt it was “Very important” for pharmaceutical companies and academic institutions to be transparent about their use of AI in public-facing documents. Transparency was considered more important among respondents in the United States and the United Kingdom compared to those in the European Union.ConclusionsThe survey results reveal high familiarity with, and confidence in the capabilities of, AI. Despite this confidence, respondents emphasized the need for human involvement in the creation of clinical trial documents and the importance of disclosing AI usage, underscoring the critical role of human oversight in maintaining patient trust. Transparent integration of AI with deliberate human involvement remains essential to ensure trust in patient-facing documents.

Quality assessment of persian epilepsy mobile applications: A systematic review using uMARS and DISCERN.

The COVID-19 pandemic was a global public health crisis that demanded a "whole-of-society" response. In many countries, coordinating efforts across public and private health care sectors proved challenging. Yet South Korea maintained one of the world's lowest excess mortality rates despite having a predominantly privatized health care system, with 90.3% of hospital beds privately owned. This outcome was enabled in part by the government's strategy of disproportionately mobilizing and repurposing public hospitals as dedicated COVID-19 treatment facilities. These hospitals, historically few in number, chronically under-resourced, and marginalized as safety nets for vulnerable populations, became the backbone of Korea's health care system response. This qualitative study examines how this process unfolded and its consequences for public hospitals and marginalized populations they serve, drawing on in-depth interviews with public hospital staff and community activists, complemented by publicly available government reports and administrative data. Our findings reveal that the repurposing of public hospitals was carried out through a highly centralized, top-down process with minimal coordination, inadequate legal safeguards, and no institutional protection. This approach generated short-term gains but ultimately led to reduced patient trust, financial instability, and a staffing exodus that compromised the long-term capacity of the public health sector.

Though subgroup performance reporting helps ensure the safety of artificial intelligence (AI) products, the extent of this reporting remains unclear. This scoping review identifies studies validating commercially available AI-based products and reports the trends in performance reporting across sex, age, and race/ethnicity demographic subgroups. Peer-reviewed validation studies of commercially available products published after 2010 were collected from the Health AI Register and PubMed on 29 November 2024. Study trends in the reporting of sex, age, and race/ethnicity were mapped with regression analysis. We apply the Wilson confidence interval equation to estimate which tuberculosis detection studies are underpowered for subgroup meta-analysis. Three hundred ninety-two of 545 studies validating 252 products reported subgroup demographic data for any of the three groups. Only 77 of these presented subgroup performance results. Skeletal (20/88) and lung (30/139) studies, and those utilizing chest (24/79) or bone (19/63) radiographs, most often presented subgroup performance data. We found no evidence that more recent studies (OR: 1.039 [95% CI: 0.959-1.127]) or company sponsorship (OR: 1.010 [95% CI: 0.492-1.920]) led to increased subgroup reporting. We show that 14/21 tuberculosis datasets may be underpowered for post-hoc subgroup meta-analysis. This scoping review quantifies how fragmented the commercial validation landscape is, showing that reporting for both the demographics and per-subgroup performance is inadequate for estimating subgroup bias. This systemic problem requires effort from all stakeholders, from researchers to regulatory agencies, encouraging thorough reporting and commercial product validation to support physician and patient trust in medical AI products. Question The number of studies validating the performance of each commercially available radiology AI product for minority subgroup bias is unclear. Findings The currently available commercial AI validation studies often neglect to describe demographic subgroup data, and fewer provide performance results per subgroup, prohibiting algorithmic bias meta-analysis. Clinical relevance Physician and patient trust in the medical AI already used clinically must be built on peer-reviewed literature and meta-analysis. The current literature is insufficient for determining the safety and performance of these products for demographic minorities.

The rapid growth of online healthcare in China is accompanied by challenges in physician-patient relationships and patient compliance. Drawing on the pathway model in physician-patient communication (PPC) and language expectancy theory (LET), we conceptualized a framework to explore the impact of online patient-centered communication (OPCC) on patient compliance, with positive expectancy violation (PEV) and patient trust as mediators and eHealth literacy as a moderator. Through a two-wave longitudinal survey in China (Wave 1: N = 1000; Wave 2: N = 498), we found that the direct relationship between OPCC and patient compliance was not significant. However, there was a significant serial mediation effect of OPCC on patient compliance through PEV and patient trust. Additionally, we tested the moderating effect of eHealth literacy. This study contributes to the theoretical extension of OPCC and offers practical implications for enhancing PEV, improving patient trust, and increasing online medical compliance in the Chinese context.

To develop a research model to investigate the impact of hospital service quality (HSQ) on patient satisfaction (PS), trust (PT), and loyalty (PL) among elderly patients with chronic conditions in government and private medical facilities in Chhattisgarh, India. This quantitative study employed the survey approach. The study used Matlab and the structured model analysis approach to evaluate the data. AMOS and SPSS Statistics were used for reliability analysis and descriptive statistics. The measurement model was utilized to evaluate reliability and validity, and the structural model was employed to examine the proposed relationship. HSQ positively influences PT and PL in both government and private hospital settings. However, PS's positive effect on PL was found to be significant only in private hospitals. The results emphasize that service quality and trust are vital for promoting enduring patient loyalty in both hospital contexts, but suggest that the relationship dynamic with patient satisfaction differs between government and private healthcare settings. This highlights the need for tailored strategies for improving patient relationships in each sector. The findings from Study 1 and Study 2 reveal distinct patterns in the associations between Hospital Quality of Service, Patient Trust, Patient Satisfaction, and Patient Loyalty. In both studies, HSQ consistently demonstrated a significant impact on PT and PL, underscoring the critical role of service quality in fostering trust and loyalty among patients.

Artificial intelligence (AI) is increasingly utilized in surgical care for decision support, operative planning, intraoperative guidance, and autonomous functions. While these systems can enhance efficiency and clinical performance, they also introduce risks related to technology, human factors, legal issues, and ethics. Current regulatory and legal frameworks are not fully equipped to address the challenges of AI-assisted surgery. This SAGES white paper synthesizes current regulatory, legal, ethical, and clinical considerations relevant to the deployment of AI systems in surgery. We review market safety regulation, data privacy law, informed consent, malpractice and liability principles, and propose a conceptual framework for understanding risk in surgical AI implementation. Risks associated with surgical AI can be understood through a tripartite framework: risks inherent to the AI system, risks introduced by the clinician-user, and risks arising from institutional deployment. These risks may manifest clinically as diagnostic error, treatment error, compromised informed consent, erosion of patient trust, threats to therapeutic autonomy, and privacy violations. Although surgeons remain the ultimate clinical decision-makers, liability may also extend to developers for defective design or failure to warn, and to institutions for negligent implementation or oversight. The safe integration of AI into surgery requires more than technical performance alone. Robust governance, ongoing performance surveillance, incident response pathways, clinician credentialing, and specialty-society engagement are needed to reduce harm and clarify accountability.

BackgroundMedical real-world data (RWD) are often siloed across organizations, making them inaccessible for research. Unlocking these data could advance clinical research and patient care. The pan-European Data Nexus platform (DNP) links RWD, facilitating its use, for example by artificial intelligence (AI) tools, to support the generation of real-world evidence. In Europe, particularly Germany, the secondary use of health data is governed by stringent regulatory requirements, including informed consent.ObjectiveThis study evaluated the informed broad consent form for the RWD (Data Nexus) platform, predicated on the principles of the Medical Informatics Initiative in Germany, and contextualized its implications for future data governance and regulatory use of RWD.MethodsThe broad consent form was developed for the DNP and cross-sectionally distributed to consecutive rheumatology outpatients during routine follow-up at a tertiary center. Analyses included rates of agreement to the predefined broad consent items. A zero-inflated model (using R) was used to predict response rates.ResultsFrom July 2023 to May 2024, 74.9% (292/390) of the patients signed the broad consent form and consented to DNP data donation. Median age was 56 (IQR 43.0-65.0) years, 72.5% (211/291) were female, and median disease duration was 12 (IQR 4.0-22.0) years. Diagnoses included rheumatoid arthritis (96/291, 33.3%), psoriatic arthritis (30/291, 10.3%), spondyloarthritis (15/291, 5.2%), systemic lupus erythematosus (90/291, 30.9%), systemic sclerosis (14/291, 4.8%), and other conditions (16/291, 5.5%). Patients also answered 8 yes/no broad consent items, with an average of “yes” and “no” responses of 7.5 (SD 1.5) and 0.2 (SD 0.5), respectively. Missing responses averaged 0.4 (SD 1.4). Of all participants, 78.4% (228/291) agreed to all broad consent items. Approval rates for individual items exceeded 86%, indicating strong patient acceptance of secondary use of RWD under a structured governance framework, possibly reflecting trust, perceived benefit, low perceived risk, and governance confidence. Importantly, patients agreed to new techniques such as AI-based analysis of their donated RWD and, despite the social and ethical sensitivity, data distribution to third parties, including commercial industry. Consent rates were also high for the use of valuable omics and genomics data from biomaterial donations. Women showed higher consent rates, whereas educational attainment was not an indicator of response behavior.ConclusionsThis is the first study assessing the willingness of patients with inflammatory rheumatic diseases to grant broad consent for secondary data use in an innovative RWD platform, implementing a modern framework in routine care and considering detailed patient preferences. Patients demonstrated high willingness to grant broad consent, providing key real-world evidence on patients’ actual consent behavior for implementing RWD platform integration—such as the European Health Data Space. The DNP supports scalable, General Data Protection Regulation–compliant data sharing, enabling real-world and AI-driven research while preserving patient trust.

Cancer has become a major global public health threat, and individuals diagnosed with cancer and their family caregivers often seek to understand their illness experiences. Religious, spiritual, and sociocultural beliefs play a central role in shaping illness interpretations and care-seeking behaviors. However, in Ethiopia, limited attention has been paid to how these frameworks influence cancer experiences. This study explored religious narratives and interpretations of illness etiology among individuals diagnosed with cancer and their family caregivers and examined their influence on illness experiences and health-seeking practices. An interpretive phenomenological approach was employed using semi-structured, in-depth interviews with 41 participants, including individuals with cancer, family caregivers, and religious leaders. Data were transcribed, translated, and thematically analyzed to examine the processes of meaning-making. The findings showed that participants commonly conceptualized addiction as spiritually mediated rather than merely biologically determined. Illness was frequently interpreted as having a divine or supernatural origin, including punishment, a test of faith, God’s will, or spiritual affliction. These interpretations were dynamic and shaped by religious teachings, sociocultural contexts and personal reflections. Religious frameworks influence emotional responses, coping strategies, and health-seeking behaviors, providing comfort and resilience while shaping treatment decisions. They functioned not only as explanatory frameworks for illness but also as practical resources that structured participants’ responses to and negotiations with uncertainty, suffering, and responsibility. Religious meaning-making plays a central role in illness interpretations and overall experiences in cancer trajectories. Recognizing and engaging with these spiritual frameworks may enhance culturally responsive and patient-centered cancer care. Integrating spiritual sensitivity into clinical practice and collaborating with religious leaders may improve communication, trust, and psychosocial support for patients and their families.

There is still a lack of research to analyze the development trajectory of the level of self-advocacy and related factors in patients with adjuvant chemotherapy after breast cancer. The present study aims to analyze the development trajectory of self-advocacy and its predictors in patients with adjuvant chemotherapy after breast cancer. A total of 242 breast cancer patients admitted to our hospital from January 2024 to December 2024 were collected. A total of 200 patients participated in 4 follow-up surveys before chemotherapy (T1), early chemotherapy (T2), mid-chemotherapy (T3), and late chemotherapy (T4), with a valid questionnaire recovery rate of 82.64%. Latent class growth analysis was used to analyze the development trajectory of self-advocacy in patients with postoperative adjuvant chemotherapy for breast cancer, and the influencing factors’ development trajectory of self-advocacy level was analyzed by binary logistic regression. The self-advocacy scores of breast cancer patients with adjuvant chemotherapy after surgery at T1 to T4 were (56.49 ± 13.89), (56.69 ± 14.50), (57.15 ± 16.89), and (56.59 ± 19.96) points, respectively. The scores of self-advocacy at the 4 time points were positively correlated (P < .05), which met the premise of model fitting. The development trajectory of self-advocacy of patients with adjuvant chemotherapy after breast cancer surgery was plotted, and the patients were divided into high self-advocacy group (n = 85) and low self-advocacy group (n = 115) according to the development trajectory. Multivariate logistic regression analysis showed that breast-conserving surgery, education, Consumer Experiences of Stigma Questionnaire score, and Nurse Patient Trust Scale score were the influencing factors of the development trajectory of self-advocacy in patients with adjuvant chemotherapy after breast cancer surgery (P < .05). Breast-conserving surgery, education, Consumer Experiences of Stigma Questionnaire score, and Nurse Patient Trust Scale score were the influencing factors of the development trajectory of self-advocacy in patients with adjuvant chemotherapy after breast cancer surgery.

Patients' and physicians' biased behaviours during pre-anaesthesia consultation: The BiPAC prospective survey study.

Artificial intelligence (AI) is rapidly reshaping clinical practice, and has prompted the Health Professions Council of South Africa to publish Booklet 20- its first ethical framework for AIuse in healthcare. This review critically evaluates Booklet 20 through the lens of the South African Medical Association AITask Team, examining its alignment with national legislation, emerging regulatory mechanisms, broader policy commitments and the ethico-social context. Drawing on the Protection of Personal Information Act, the South African Health Products Regulatory Authority's 2025 guidance for AI‑enabled medical devices, the National AIPolicy Framework and the 2024 National Health Research Ethics Council ethics guidelines, the analysis identifies key operational gaps relating to human oversight, disclosure, data sovereignty, equity, accountability and risk categorisation. The article argues that while Booklet 20 establishes an important foundation, its principles require concrete implementation tools, including risk‑tiered safeguards, structured consent templates, meaningful governance co-ordination and context‑appropriate standards for transparency, explainability and bias mitigation. Grounding these enhancements in South Africa's communitarian ethic of ubuntu highlights the need for relational accountability, fairness and community participation to ensure safe and equitable AIintegration. The article concludes with a set of practical recommendations aimed at strengthening ethical governance and supporting patient trust and professional integrity as AIbecomes embedded in clinical workflows.

Repetitive transcranial magnetic stimulation (rTMS) has expanded in Japan since its inclusion under public insurance in 2019. This review examines systemic barriers to equitable adoption, ethical and legal challenges, and proposes Shared Decision Making (SDM) as a clinical and policy framework to ensure patient-centered care. A narrative policy and practice review was conducted, synthesizing evidence from peer-reviewed studies, registry data, government guidance, and professional society statements. Comparative analysis with the United States and Europe was used to contextualize Japan's distinctive financing and governance arrangements. Implementation of rTMS in Japan remains concentrated in tertiary hospitals and metropolitan centers, with limited diffusion to rural areas. Strict eligibility criteria under public insurance restrict access, while private-pay clinics have proliferated with heterogeneous protocols and variable disclosure practices. These structural imbalances generate inequities in access, ethical tensions regarding transparency, and legal concerns about informed consent. Additional barriers include limited public awareness, variability in provider expertise, and constrained outpatient consultation time. International comparisons highlight broader indications and more flexible reimbursement abroad, supported by stronger governance structures. Embedding SDM into both insured and private rTMS practice in Japan is essential to safeguard equity, transparency, and sustainability. A pragmatic SDM framework, incorporating standardized information materials, AI-enabled decision aids, multidisciplinary collaboration, and registry-linked accountability, can transform rTMS adoption into a model of patient-centered governance. Institutionalizing SDM will not only improve treatment concordance and patient trust in Japan but also provide lessons for global mental health policy.

With the increasing pace of globalization and transnational migration, healthcare systems are becoming more culturally diverse. In Taiwan, demographic changes have introduced increasing numbers of patients from diverse cultural backgrounds into clinical care environments, presenting new challenges for nursing practice. Cultural safety has emerged as an important framework for promoting equitable healthcare and improving the quality of patient care. Under this concept, patients' lived experiences and perceptions of care are used as central indicators of healthcare quality, and healthcare professionals are encouraged to reflect critically on the power dynamics and institutional biases within their healthcare interactions. In this article, the practical implications of cultural safety in nursing practice are discussed in the context of four culturally diverse populations in Taiwan: indigenous residents, migrant workers and other expatriates, sexual and gender minorities, and non-Taiwanese spouses and new immigrants. Language barriers, varied levels of health literacy, culturally shaped health beliefs, and limited social support are all factors that may influence patient trust, engagement in care, and adherence to treatment. When healthcare providers lack cultural sensitivity and reflective awareness, communication gaps and subtle forms of exclusion may occur in clinical encounters. Strengthening cross-cultural communication, encouraging patient participation in decision-making, fostering professional self-reflection, and creating institutional environments that support culturally safe practice are essential strategies to improving care. Therefore, cultural safety offers an important framework for developing strategies to enhance patient trust, improve care experiences, and advance health equity in multicultural healthcare settings.