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PubMed2026

Factors associated with successful integration of pharmacists into residential aged care teams: A qualitative study.

BACKGROUND: Australia's Aged Care Onsite Pharmacist program aims to support quality use of medicines in residential aged care homes. This is a novel role introduced into existing teams in a complex environment. Factors associated with successful integration since implementation are currently unknown. AIM: This study aims to explore the perspectives of pharmacists and other stakeholders within aged care homes regarding successful integration of the novel aged care pharmacist service into healthcare teams. METHODS: A qualitative approach, using interpretive descriptive methodology, was used to explore perspectives. Semi-structured focus groups and interviews with pharmacists, nursing and care staff, allied health professionals, general practitioners, residents, and family members were undertaken. Data were collected via Zoom™, audio- and video-recorded, and transcribed verbatim. Two researchers undertook inductive thematic analysis to identify key themes. RESULTS: 30 participants across focus groups, focus-group interviews, interviews, and member-checking processes contributed. An overarching theme of proactivity and showing a genuine interest in others underpinned three key themes. Theme 1: Pharmacists needed to be seen, through physical presence and availability, as well as developing a distinct identity. Theme 2: Pharmacists needed to build trust, through collaboration in real time and demonstrating value. Theme 3: Pharmacists needed to develop an understanding of the aged care home environment, including social and contextual norms, as well as procedures, routines and roles. DISCUSSION: This research complements existing understandings of interprofessional collaboration and teamwork amongst healthcare professionals. Themes were interlinked; we used a sensitising framework, social cognitive theory, to present and explain the findings and interactions that can support pharmacist integration into existing teams. Aged care services should structure onboarding to prioritise early visibility, clarify roles and organisational needs, and foster in-person collaboration. Pharmacists should demonstrate proactivity and an authentic interest in all staff, residents and families.

Humans↗
PubMed2026

Playing with Fire, Losing the Drive: Bidirectional Links Between Problematic Smartphone Use and Grit Dimensions.

This study examined bidirectional longitudinal associations between grit dimensions (consistency of interest [CI] and perseverance of effort [PE]) and problematic smartphone use (PSU) and tested cognitive flexibility as a mediating mechanism. A sample of 1,641 Chinese university students (55.2 percent female; Mage = 20.1 years) completed measures at two time points 6 months apart. A four-variable cross-lagged panel model revealed that CI and PSU negatively predicted each other over time, whereas PSU unidirectionally predicted decreased PE. Cognitive flexibility partially mediated the PSU-to-PE pathway (indirect effect = -0.004, 95 percent bootstrap CI [-0.010, -0.0001]). Competing models analysis confirmed this directionality: the forward mediation (PSU → cognitive flexibility → PE) was significant, whereas the reverse was not. These findings demonstrate that grit dimensions exhibit distinct longitudinal patterns with PSU and identify cognitive flexibility as a cognitive mechanism through which PSU specifically undermines effort persistence. Implications for dimensional approaches to grit and targeted interventions are discussed.

Humans↗
PubMed2026

Power as equal ability, knowledge and resistance: Systematic review of experiences of adults with noncommunicable diseases.

PURPOSE: To analyse subjective experiences of power of adults with noncommunicable diseases in relationships with healthcare practitioners as well as underlying facilitators and barriers of these experiences. METHODS: Systematic review (4 databases) of experiences using reflexive thematic analysis underpinned by critical realist approach. The analysis was conducted with an abductive reasoning using previous theories on social power as well as retroduction. RESULTS: Based on 24 studies, we formed three themes, which depict experiences of power as 1) the position, equal ability and freedom to make one's own choices and (re)negotiate within shared dialogue, 2) the ability to use knowledge to claim one's rights, 3) resistance. Facilitators were connected to acknowledgement as an equally valuable individual, positive healthcare practitioner attitudes and actions towards patient activity and views, safety in the relationship as well as to sufficient, clear and varied information. Main barriers were experiences of dehumanisation, negative healthcare practitioner attitudes and actions, perceived or assumed practitioner domination in interactions, lack of or incomprehensible knowledge and testimonial smothering. CONCLUSION: Results suggest that adults with noncommunicable diseases may experience power primarily as a positive power: being acknowledged as having legitimate position to make decisions and being in possession of varied knowledge through which they can gain agency to protect and claim their rights, by resisting, if necessary. Healthcare practitioners are in key position to support these experiences through positive transforming actions, while knowledge asymmetries, persistent inequality and paternalistic structures continue to hinder it.

Humans↗
PubMed2026

Bioprospecting microbial genomes to expand the biocatalytic toolbox of rubber oxygenases.

A set of rubber oxygenases was discovered through phylogenetic analysis and AI-based structural modeling of complexes of the putative enzymes with a substrate mimicking cis-1,4-polyisoprene. Sixteen candidate proteins were selected from thermophilic microorganisms, all sequence-related to the Latex clearing protein from Streptomyces sp. K30 (LcpK30). Sequence truncation and solubility tags were then evaluated to enhance protein expression, with the SUMO tag proving to be the most effective. Including LcpK30, nine heme-containing oxygenases were successfully expressed in E. coli NEB 10-beta cells, purified (35-157 mg L-1 yield) and characterized. Steady-state kinetics revealed significant rubber latex-degrading properties for six of them, with the truncated SUMO-fused LcpK30 (SUMO-LcpK30T) showing activity in agreement with literature. Notably, the catalytic efficiencies of all the expressed homologs lay within one order of magnitude and the oxygenase from Thermomonospora echinospora was found to be particularly promising in terms of activity, especially at high latex concentrations (more than 1% w/v). The analysis of reaction mixtures by both HPLC and HPLC-MS confirmed the oxidation of cis-1,4-polyisoprene to form the expected isoprenoid oligomers (n = 2-12), whose distribution was consistent with the usual endo-type cleavage pattern in all but one case. This bioprospecting effort afforded a platform of new rubber-degrading enzymes with diverse efficiencies and product profiles, capable of adapting to targeted applications.

Oxygenases↗
PubMed2026

Assessment of Methodological Bias in Studies Reporting Racial Differences in Retinopathy of Prematurity in the United States.

PURPOSE: To assess methodological biases in studies reporting racial and ethnic differences in retinopathy of prematurity (ROP). METHODS: Systematic review of peer-reviewed studies published between 2014 and 2024 that reported on ROP outcome measures by race, ethnicity, or social determinants of health (SDOH). Three reviewers independently assessed each observation for selection and collider bias using definitions derived from perinatal epidemiology literature. Findings were also compared using a structured comparative synthesis between studies with and without identified methodological bias. RESULTS: A structured PubMed search identified 78 articles; 13 met inclusion criteria, with one study contributing two distinct analytical approaches, yielding 14 total observations. Survivorship bias was identified in 6 of 14 observations (42.9%), primarily due to the exclusion of infants who died prior to ROP screening. Potential collider bias was most common, found in 9 of 14 observations (64.3%), and was introduced through adjustment or stratification by gestational age and/or birthweight. Three studies did not exhibit either assessed biases. Among studies with identified bias, 8 of 10 observations reported lower ROP risk among Black versus White infants, whereas 3 of 4 observations without identified bias reported higher ROP risk or incidence among Black infants. CONCLUSION: Methodological biases in ROP studies investigating race or ethnicity are prevalent. Adjustment for gestational age or birthweight may introduce spurious race-ROP associations and contribute to paradoxical findings. Further exploration of the impact of SDOH on disease outcomes may reduce the misattribution of race as a biological risk factor and improve the interpretation of ROP disparities.

Collider bias↗
PubMed2026

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand for timely expert interpretation continues to outpace capacity, creating diagnostic delays and inter-observer variability that impact patient care. Recent research has suggested computer vision artificial intelligence (AI) models can generate accurate preliminary comprehensive TTE reports, however, prospective evaluation is needed to determine whether AI-assisted TTE interpretation can improve clinician efficiency while preserving diagnostic accuracy. METHODS: AI ECHO INSIGHT is a prospective randomized blinded clinical trial conducted at Kaiser Permanente Northern California that will evaluate 1200 historical TTE studies (1000 consecutive unselected studies plus 200 with moderate or greater valvular disease) interpreted using three workflows: (1) AI-generated preliminary report finalized by a blinded cardiologist (AI-assisted); (2) cardiologist-generated preliminary report finalized by a blinded cardiologist (cardiologist-assisted); and (3) sonographer-generated preliminary report finalized by a blinded cardiologist (sonographer-assisted). The primary outcome is the rate of substantial change between preliminary and final reports, comparing the AI-assisted workflow to the pooled cardiologist-assisted and sonographer-assisted workflows. Secondary outcomes include cardiologist interpretation time for report finalization, superiority testing for diagnostic accuracy, and reporting consistency. CONCLUSION: AI ECHO INSIGHT is a prospective randomized blinded clinical trial evaluating the clinical impact of AI-assisted TTE interpretation on diagnostic accuracy, cardiologist efficiency, and reporting consistency in real-world echocardiography workflows. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT07229300.

Humans↗
PubMed2026

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures↗
PubMed2026

Exploring Implementation of Cantonese Radio Broadcasting as a Mental Health Promotion Initiative for Linguistically Isolated Immigrants.

Digital-first public health efforts often miss linguistically isolated immigrant communities because of structural barriers and stigma. Ethnic legacy media can reach these groups, but keeping programs funded and operational over the long term is frequently difficult. This Practice Note examines a Cantonese-language radio health program in "Los Angeles County" that ran 128 live broadcasts across a full 12-year Chinese zodiac cycle. Instead of a top-down clinical model, the show endured by acting as an informal community navigation hub. We examine two recurring administrative frictions: anonymous off-air calls about urgent economic needs (e.g., hotel job referrals) and on-air audience corrections of mispronounced medical terms. We argue these interactions should be seen not as disruptions but as measurable indicators of structural trust that sustain programs. We offer practical guidance for recruiting undergraduates to expand reach via ethnic print newspapers, using peer-recovery milestones to amplify impact. The note concludes with a pragmatic blueprint for health educators to manage professional boundaries, preserve commercial-clinical separation, and uphold cultural safety in isolated communities.

Chinese American health↗
PubMed2025

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

Humans↗
PubMed2026

Implementation outcomes of a dementia-focused intervention for family care partners and clinicians in home hospice care.

OBJECTIVES: End-of-life care for persons living with dementia in home hospice relies heavily on coordination between family care partners (FCPs) and clinicians (e.g., hospice social workers and nurses). FCPs and clinicians have reported support and knowledge gaps in end-of-life dementia care. Interventions are needed to improve FCPs' support and clinicians' educational gaps. METHODS: A pilot randomized controlled trial was designed to examine implementation outcomes for a dementia-focused end-of-life intervention for FCPs (n = 37) and clinicians (n = 15). Data on survey completion and acceptability were collected at baseline, during 4 follow-up visits, and at the conclusion of the study. RESULTS: Twenty-eight (75%) caregivers completed the post-study survey, and 10 (27%) reported using the structured worksheet. Thirteen (87%) clinicians completed the post-training survey, 8 (53%) completed the post-study survey, and 8 (100%) used the worksheet. Clinicians (n = 8) were satisfied or highly satisfied with the instructional videos, and half (50%) used the information frequently with patients. Both groups reported the worksheet helpful, easy to use, and satisfactory, though clinicians rated helpfulness slightly higher (mean = 3.88 vs. 3.70 for FCPs). Clinicians liked the worksheet's structured guidance and the enhanced collaboration. SIGNIFICANCE OF RESULTS: This study provides preliminary evidence for implementation outcomes of a dementia-focused end-of-life intervention in home hospice. Findings suggest the intervention can be implemented in a hospice setting, with moderate worksheet uptake and perceived value among FCPs and clinicians.

Humans↗
PubMed2026

Physical Appearance Anxiety and Eating Disorders Symptomatology: A Systematic Review and Meta-Analysis.

The present study aimed to assess the link between physical appearance anxiety (PAA) and eating disorder (ED) symptomatology by a meta-analysis of existing literature. Eligible studies were searched across six electronic databases up until November 20, 2025. Pooled effect sizes (r) were calculated using random-effects models. Potential variables that influence effect heterogeneity were analyzed by univariable and multivariable meta-regressions. Influence analyses and a three-parameter selection model (3PSM) were used to assess robustness of the results and publication bias. Twenty-seven effect sizes from 21 studies (N = 5261) were obtained. The results indicated a strong association (i.e., r = 0.559) between the two variables under consideration, which was notably stronger (i) among females compared to males; and (ii) for overall eating disorder symptoms rather than bulimic symptoms. The results of this study advocate for further investigation into the effectiveness of addressing anxiety responses related to personal body traits, particularly among females, within the context of preventing and treating eating disorders.

Humans↗
PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗
PubMed2026

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

Humans↗
PubMed2026

The role of media in reducing and reinforcing stigma: A randomized controlled trial investigating the impact of positive and negative representations of visible difference.

OBJECTIVES: Individuals with visible differences often experience appearance-related stigma and discrimination, reinforced by negative media portrayals. In contrast, positive portrayals may challenge stereotypes and promote acceptance. This study examined whether exposure to positive, negative or neutral images of visible difference influences appearance-related stigma, body appreciation and broad conceptualizations of beauty. It was hypothesized that positive images would decrease stigma and increase body appreciation and broad conceptualizations of beauty, whereas negative images would increase stigma and reduce broad conceptualizations of beauty. DESIGN: An online randomized controlled experiment using a mixed repeated-measures design compared three conditions (positive, negative, neutral) across pre- and post-exposure. METHODS: A sample of 103 adults viewed 10 images of individuals with visible differences presented in one of three conditions: positive (positive captions), negative (villains with visible differences and negative captions) or neutral (without captions). Participants completed pre- and post-measures of appearance-related stigma, body appreciation and broad conceptualizations of beauty. Repeated-measures ANOVAs examined within- and between-group changes. RESULTS: Appearance-related stigma significantly increased in the negative condition, while remaining unchanged in the positive and neutral groups. Body appreciation significantly increased from pre- to post- across all conditions. No significant effects emerged for broad conceptualizations of beauty. CONCLUSIONS: Negative portrayals of visible difference may reinforce stigma, highlighting the need to discourage such depictions in media. While positive exposure did not significantly reduce stigma, viewing images of visible difference increased observers' body appreciation, indicating potential downward social comparison. Future research should explore strategies to strengthen stigma reduction and broaden conceptualizations of beauty.

Humans↗
PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗
PubMed2026

Comparison of summative assessments between simulated electronic health records versus traditional paper-based patient cases: A non-inferiority randomized controlled trial.

INTRODUCTION: Electronic health records are fundamental to contemporary pharmacy practice, yet evidence supporting their use in pharmacy education is lacking. This single-center, non-inferiority randomized controlled trial with blinded outcome assessment evaluated whether delivering patient cases via a simulated academic EHR (aEHR) was non-inferior to a traditional paper-based format in student exam performance. METHODS: 53 third-year PharmD students at the University of British Columbia were randomized 1:1 to complete a mock summative examination using either the aEHR or paper-based case delivery, stratified by self-reported EHR comfort level. The primary outcome was mean written exam score (%). Non-inferiority was pre-specified at a margin of 14%. Adjusted linear regression was used for the primary analysis, with a multiple imputation sensitivity analysis. Student perceptions were explored through post-exam focus groups analyzed using inductive thematic analysis. RESULTS: 42 students (21 per group) completed the exam and were included in the primary analysis. Mean scores were 66% (SD 11) in the aEHR group and 68% (SD 10) in the paper group. The adjusted mean difference (paper minus aEHR) was -2.2% (95% CI -9.2% to +4.8%), satisfying non-inferiority but not superiority. Sensitivity analysis (n = 53) yielded consistent results (-2.3%; 95% CI -7.1% to +4.1%). Focus groups revealed initial student anxiety with the aEHR but recognized its alignment with clinical practice. DISCUSSION: These findings support the feasibility of integrating simulated EHRs into summative pharmacy assessments without compromising performance. CONCLUSION: Simulated EHRs are a non-inferior assessment medium compared with paper-based formats and represent a viable step toward technology-driven pharmacy practice environments.

Humans↗
PubMed2024

Promoters and Barriers of Vaccine Hesitancy.

This systematic review explores the psychological antecedents of Vaccine Hesitancy, a significant determinant of vaccination behavior. Following PRISMA guidelines, an extensive search was conducted starting from 1673 papers and resulting in 48 publications from various databases. The review identifies psychological factors, specifically cognitive, personality, experiential, and social factors contributing to hesitancy. Cognitive factors include health literacy, conspiracy beliefs, trust, and perceived risk. Personality traits such as extraversion, openness, and psychological capital impact hesitancy, while psychopathy increases it. Personal experiences, like perceived stress and racial discrimination, indirectly affect hesitancy. Social factors, including social relationships and norms, play a significant role in reducing hesitancy. Tailored interventions addressing these factors can enhance vaccine acceptance.

Humans↗
PubMed2026

Reported exposure to news portrayals about mental health problems and their impact: Findings from the 2025 National Survey of Stigma and Discrimination.

OBJECTIVE: Media portrayals of people with mental illness have the power to mitigate or perpetuate stigma related to mental health. This study aimed to investigate reported real-world exposure to news media portrayals about people with mental health problems in the past 12 months and the impact of these. METHODS: Data were from a nationally representative survey of 6032 Australians exploring attitudes towards people with mental health problems. Participants were asked about their exposure to positive news stories about a person with a mental health problem, as well as negative portrayals, in which someone was harmed by a person with a mental health problem. Further questions covered the sources (traditional or social media) and impact of these exposures. RESULTS: Regression models were used to explore sociodemographic predictors of impact. Most participants reported exposure to negative news portrayals (68.4%, 95% confidence interval = [66.9, 69.8]), while fewer reported exposure to positive news stories (33.7%, 95% confidence interval = [32.3, 35.2]). Most people exposed to the negative news stories reported a negative impact (69.0%, 95% confidence interval = [67.2, 70.7]), and most exposed to positive news stories reported a positive impact (80.2%, 95% confidence interval = [77.6, 82.5]). Age and gender were associated with reported impact but not lived experience of mental illness. CONCLUSIONS: Exposure to negative news stories about mental health problems was prevalent. Given their impact on news audiences broadly, negative news stories need to be accurate and responsible to mitigate negative impacts. A renewed focus on generating and promoting positive and stigma-challenging news stories is needed to increase subsequent positive impacts.

Humans↗