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Satisfaction with clinical practice environments among early-career health professionals in South Africa: Findings from the WiSDOM cohort study.

BACKGROUND: The work or practice environments of health professionals play a central role in their retention in the healthcare system and their ability to provide quality patient care. The aim of the study was to examine and compare the satisfaction of early-career health professionals in the WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) study with their clinical practice environments (CPEs) in South Africa, and the factors influencing their satisfaction. METHODS: WiSDOM, a prospective longitudinal cohort study, consists of eight health professions: clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists, and physiotherapists. Every year we collect information on the cohort's involvement in direct patient care, their perceived workload, availability of medicines and equipment for patients in their care, and their satisfaction with the clinical practice environment (CPE).We used Stata&#xae;19 for analysis. We used panel linear regression to investigate factors associated with the cohort's satisfaction with their clinical practice environments from 2018 to 2024, and logistic regression to evaluate the association between CPE and intention to leave in 2024. RESULTS: In 2024, the mean age of the cohort was 30.9 (&#xb1; 2.0), the majority were female (74.4%) and working in urban areas (92.7%). In 2024, 59.7% of the overall cohort reported a heavy workload compared to 69.2% in 2018. Over the follow-up period, reported problems with the availability of medicines or equipment were worse in the public sector and in rural areas, compared to the private sector and urban areas respectively.The cohort's satisfaction score with the CPE was 6.7 out of 10 in 2018 and 6.9 in 2024. The predictors of CPE were year of follow-up, health profession, employment sector, and geographic location. Nurses (&#x3b2;=-1.2; 95% CI -1.7, -0.7; p&#x2009;<&#x2009;0.001), and pharmacists (&#x3b2;=-0.7; 95% CI -1.1, -0.4; p&#x2009;<&#x2009;0.001) scored their CPE significantly lower compared to the other professional groups. Health professionals in the public sector (&#x3b2;=-1.1; 95% CI -1.3, -0.9; p&#x2009;<&#x2009;0.001) and in rural areas (&#x3b2;=-0.6; 95% CI -0.9, -0.3; p&#x2009;<&#x2009;0.001) were less satisfied with their CPE compared to those in the private sector and urban areas respectively. Dissatisfaction with the CPE was significantly associated with intention to leave the workplace and the profession. CONCLUSION: The study findings underscore the need for positive clinical practice environments for early-career health professionals in South Africa both as a health workforce and patient safety imperative.

South Africa

Psychometric Evaluation of the Breast Inflammatory Symptom Severity Index Versions 2 and 3 Among Lactating Women.

OBJECTIVE: To evaluate the psychometric properties of Versions 2 and 3 of the Breast Inflammatory Symptom Severity Index (BISSI). DESIGN: Secondary data analysis of clinical trial data. SETTING: Private physiotherapy practices, a public tertiary hospital, and a community in Melbourne, Australia. PARTICIPANTS: Women more than 7 days after birth with inflammatory conditions of the lactating breast (N = 43). METHODS: We performed confirmatory factor analysis of the BISSI Version 2 to examine item loading, which informed development of the BISSI Version 3 (V3). We assessed convergent validity by comparing total BISSI V3 scores with human milk sodium to potassium ratio (Na+:K+) at Trial Days 1, 3, and 10 using Bland-Altman plots. We compared item-level scores for size of affected area with objective receiver operating characteristic curve analysis to assess discriminant validity for symptom severity and Cronbach's alpha for internal reliability. RESULTS: After confirmatory factor analysis, we removed two items, resulting in a six-item BISSI V3. All retained items demonstrated comparable loading on the overall scale. Limits of agreement for total BISSI V3 scores and item-level scores for size of affected area were acceptable at all time points, with more than 90% of observations falling within 2 standard deviations of the mean difference, supporting convergent validity. Discriminant validity of the BISSI V3 was supported. We found high internal reliability at both time points CONCLUSION: Our findings provide evidence for the validity and reliability of the BISSI V3 and support its continued development and for clinical use of the BISSI V3 and human milk Na+:K+ analysis to enhance management of inflammatory conditions of the lactating breast.

breastfeeding

Health bill beneath the plastic feast: A phthalate contamination alert from takeout food containers.

The rapid growth of takeout food consumption in China has raised concerns regarding exposure to phthalic acid esters (PAEs) from food packaging. This study investigated the presence, source, contribution, and health risk of PAEs in commonly used takeout containers. Widespread contamination was observed, with total PAE concentrations ranging from below the limit of detection to 222,000 ng/g. Diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), and bis(2-ethylhexyl) phthalate (DEHP) were identified as the predominant compounds, accounting for 7.50 %, 14.7 %, and 18.7 % of the total concentration, respectively. These PAEs may originated from additives during manufacturing and potential contamination of raw materials. Human exposure assessment showed that daily exposure doses of DIBP, DBP, and DEHP via container ranged from 0.00 to 2340 ng/(kg&#xb7;day) among frequent takeout consumers, contributing substantially to overall PAE body burdens. To further assess exposure and associated risks, a nationwide online questionnaire survey was conducted across China. Based on this national-scale behavioral dataset, the health risks among Chinese residents were evaluated. Although the modeled non-carcinogenic risks of DIBP, DBP, and DEHP remained within acceptable limits, the simulation suggested that approximately 70 % of participants may experience potential exceedance of the carcinogenic risk threshold for DEHP. The frequency of takeout food consumption was identified as the most important factor affecting PAE exposure. These findings underscore the importance of limiting takeout frequency and reducing reliance on plastic containers to mitigate health risks. This study provides scientific evidence to support the development of safer packaging materials and informs public health strategies.

Phthalic Acids

A Duty to Act.

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healthcare

Views and Experiences of People With Dementia, Informal Caregivers and Professionals on Eating and Drinking Difficulties: A Qualitative Systematic Review.

AIM: This study aims to explore the views and experiences of people with dementia, informal caregivers and professionals regarding eating and drinking difficulties. DESIGN: A qualitative systematic review was conducted. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines were used to conduct this systematic review. The quality of the included studies was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research, and the data were thematically synthesised using Thomas and Harden's three-stage method. DATA SOURCES: Six electronic databases (PubMed, EMBASE, Cochrane Library, Web of Science, CINAHL and PsycINFO) were searched from their respective inception dates to August 2025 to identify relevant studies. RESULTS: Thematic analysis of the 16 included studies identified four key themes: (1) Physiological and psychological changes in people with dementia and caregivers; (2) factors influencing eating and drinking in people with dementia; (3) needs and recommendations for people with dementia, informal caregivers and professionals; (4) selection of eating methods for end-stage people with dementia. CONCLUSIONS: Eating and drinking difficulties affect the well-being of both patients and caregivers. A good dining environment improves mealtime pleasure but demands caregivers' time and energy. All parties emphasised the importance of effective communication. In end-stage dementia, professional assistance is crucial for enteral nutrition decisions. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Collaboration among patients, caregivers and professionals is vital for creating tailored nutritional plans and improving mealtime environments, thereby enhancing nutritional intake. In advanced dementia, providers must provide balanced information on comfort feeding versus enteral nutrition to aid decision-making. IMPACT: What problems were addressed in this study? This study addressed the lack of a consolidated, tri-perspective understanding of eating and drinking difficulties in dementia care settings. What are the main findings? Four key themes were identified: physiological and psychological changes, influencing factors, stakeholder needs and end-of-life decision-making. Where and on whom will the research have an impact? This will impact care practices for people with dementia and inform the training and support of informal caregivers and healthcare professionals.

Humans

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

How do women with a history of childhood sexual abuse experience the preconception and perinatal period? A qualitative systematic review.

CONTEXT: Child sexual abuse (CSA) is a public health issue that predominantly affects women and has both short- and long-term consequences. The perinatal period can represent a challenge, but also an opportunity to identify a history of CSA and to provide sensitive care that may help prevent the intergenerational transmission of trauma. AIM: To describe and understand the experiences and coping strategies of women who are survivors of child sexual abuse and are transitioning to motherhood. METHOD: We conducted a systematic review of qualitative studies according to a protocol registered in PROSPERO, following methodological standards and reporting the results according to the ENTREQ guideline. A search was conducted on five databases up to July 2025. Two authors independently selected the articles and assessed their methodological quality. Data were analysed using thematic synthesis and the confidence in the findings was evaluated according to GRADE-CERQual. RESULTS: We included 21 qualitative studies that resulted in six themes. The findings reveal how women who experienced child sexual abuse and are transitioning to motherhood may experience this stage with ambivalence-ranging from revictimisation to identity reconstruction-where perinatal care emerges as a potential healing vehicle throughout this process. CONCLUSIONS: The perinatal period becomes a window of opportunity to heal deep wounds, with perinatal care playing a key role. The findings support trauma-informed perinatal care, underpinned by reflective practice and a holistic approach. Further work is needed to improve the identification of child sexual abuse, enhance professional training and review current practices to ensure sensitive care.

Humans

Meta-analysis of growth and inactivation kinetics of Legionella.

Quantitative risk assessments intended to inform evidence-based water management plans and public health targets for Legionella in engineered water systems are constrained by fragmented and heterogeneous growth and inactivation kinetics. We conducted a meta-analysis of 25 growth and 39 thermal- and chemical-inactivation studies, fitting microbial persistence models to harmonize parameters. Nonlinear models outperformed first-order formulations, indicating that lag phases and resistant or protected subpopulations are central to Legionella persistence. Random forest analysis identified environmental and methodological drivers of variability based on 226 growth rates and reduction times for thermal (209) and chemical (135) inactivation. Growth was primarily governed by temperature, nutrient availability, and compatible Legionella-host pairings; thermal inactivation by quantification method, temperature, and turbidity; and chemical inactivation by inoculum size, disinfectant type, concentration, and host-associations. Accordingly, temperature-dependent growth parameters and exposure metrics for heat, free-chlorine, and monochloramine, expressed as TT (Temperature&#xd7;time) and CT (Concentration&#xd7;time), were derived as condition-specific inputs for predictive models. Growth optima around 37-40 &#xb0;C, together with lag-time estimates, indicate that hot-water temperature setbacks and energy-saving practices may favor Legionella proliferation under repeated or prolonged lukewarm exposure. Culture- and viability-based TT differences highlight the need to consider viable&#x2011;but-non-culturable persistence in monitoring programs. CT comparisons suggest monochloramine may be advantageous because of its lower apparent sensitivity to host-associated protection. Although limited by restricted experimental conditions, the findings show that predictive models should account for microbial ecology, water matrix effects, and quantification endpoints. Future kinetic studies should prioritize realistic multi-host systems, strain pre-adaptation, complementary viability measurements, and standardized protocols and reporting to ensure reproducibility and enable robust system-level predictive modeling.

Legionella

"Orphaned bereavement": Toward a public health model for bereavement.

Bereavement is increasingly recognized as a public health concern, yet support systems in many welfare states continue to allocate support according to the circumstances of death rather than the functional needs of bereaved families. Existing bereavement frameworks have substantially advanced understanding of social recognition and public legitimacy but provide more limited guidance for understanding how institutional responsibility for bereaved families is organized. using Israel as a bereavement-saturated case, this study introduces the concept of orphaned bereavement to describe bereavement in which no institution holds clearly defined and continuing responsibility for identifying needs, coordinating support, and ensuring continuity of care. Drawing on 25 semi-structured interviews with five bereaved family members and 20 professionals, analyzed using reflexive thematic analysis, the analysis generated three interrelated themes: institutionalized invisibility and unequal recognition; reorganizing life in the absence of institutional support; and pathways toward a needs-based model of bereavement support. The findings extend existing theories of disenfranchized grief and grievability by introducing institutional responsibility as a complementary lens for understanding bereavement inequality and support a needs-based public health approach in which support is organized according to families' evolving functional needs rather than the circumstances of death.

Journal Article

Artificial intelligence in genitourinary oncology: publication trends and systematic review.

OBJECTIVE: To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current state of artificial intelligence (AI) use in genitourinary (GU) oncology, as AI has emerged as a transformative tool in healthcare with potential applications in diagnostics, treatment planning, and prognostication. METHODS: We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE; Ovid), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) Ultimate for studies related to AI and GU oncology, excluding non-English papers, non-human studies, review articles, and articles using AI solely for manuscript writing. Publication trends were analysed from 2013 to 2023 and categorized by study design and cancer type. RCTs were evaluated through systematic review using Covidence (Veritas Health Innovation Ltd, Melbourne, Victoria, Australia) for screening and data extraction. Two reviewers independently assessed all studies, with risk of bias (RoB) evaluated using the Cochrane RoB 2.0 tool. RESULTS: Of 2409 articles identified, 1220 met inclusion criteria. These included 962 retrospective articles, 175 prospective studies, 79 studies with combined retrospective/prospective methods, and four RCTs. Studies most commonly addressed prostate (n&#x2009;=&#x2009;923), renal (n&#x2009;=&#x2009;274), and urothelial (n&#x2009;=&#x2009;194) cancers. Publications grew from 14 in 2013 to 362 in 2023, with substantial acceleration in 2019. Four RCTs were identified - one in urothelial cancer and three in prostate cancer. Two RCTs evaluated AI-based diagnostics, demonstrating improved performance over conventional methods; the remaining two RCTs evaluated AI in prognostication and treatment planning, showing improved gains in imaging interpretation and operational efficiency. RoB varied across studies, primarily related to randomisation and deviations from intended interventions. CONCLUSIONS: Artificial intelligence research in GU oncology has grown, although high-level evidence from RCTs remains limited. Existing trials underscore AI's promise in diagnostics, prognostication, and treatment planning, and the rapidly evolving nature of this field warrants continued prospective investigation.

Humans

Investing in Canada's nursing workforce: a comprehensive review to inform policy innovations and directions.

BACKGROUND: Health systems worldwide face persistent health workers challenges including nursing shortages, workforce strain, and inequities. In Canada, these challenges have prompted renewed national and provincial reforms to strengthen recruitment, retention, leadership, and sustainability. This paper compares nursing workforce policy directions across Canada, and international jurisdictions to inform policy and planning. METHODS: A cross-country comparative analysis of policies building on a comprehensive national funded review that included an umbrella review of 69 systematic reviews, a comparative policy review of nursing workforce strategies in five jurisdictions, and validation through national horizon-scanning and policy dialogues (n >100). Evidence was analyzed across system, organizational, and individual levels. RESULTS: At the system level, international jurisdictions demonstrate comprehensive, legislated approaches integrating data, governance, and multi-year funding have advanced key nursing strategies. In Canada, the advances show the importance of strategies to have national and provincial/territorial alignment emphasizing leadership, flexibility, and inclusion as key levers. Organizational and individual-level reforms such as mentorship, leadership development, and wellness initiatives are expanding but remain variably evaluated. Experts identified national workforce data strategies and policy integration with embedded evaluation as key enablers to inform scalability and sustainability of implemented strategies. CONCLUSIONS: Canada's nursing workforce reforms are advancing toward coordinated, equity-driven, and evidence-informed strategies. Continued investment in evaluation, leadership, and national integrated data systems along with integrating nursing workforce planning within broader intersectoral planning will consolidate these gains and position Canada as an international leader in sustainable nursing workforce policy.

Canada

Implementation factors shaping British Columbia's drug decriminalization pilot: A systematic review with narrative synthesis.

BACKGROUND: In January 2023, British Columbia (BC) became the first Canadian province to implement a legally sanctioned drug decriminalization policy, removing criminal penalties for adults possessing 2.5 g or less of opioids, cocaine, methamphetamine, and MDMA. Introduced as a three-year pilot, it aimed to reframe substance use as a public health issue, reduce stigma, and improve health and social service engagement. Criminal penalties were reintroduced for drug possession in most public spaces in May 2024, and the pilot ended in January 2026. Its termination has been interpreted as policy failure; this review aimed to examine how the pilot was implemented in practice and to identify factors that shaped its operationalization and early implementation-relevant outcomes. METHODS: We conducted a systematic review with narrative synthesis of peer-reviewed literature examining implementation-relevant aspects of BC's decriminalization pilot. Six databases were searched (January-February 2026) for studies published May 31, 2022-February 1, 2026. The protocol was registered in PROSPERO (CRD420251271694). RESULTS: Twenty-seven studies were included. Four cross-cutting implementation barriers were identified: pilot design features, public and cross-sector communication gaps, limited frontline training, and insufficient funding and infrastructure. Design features included the 2.5 g possession threshold, misalignment with real-world drug use patterns; the three-year timeframe, which constrained system-level effects; and the May 2024 amendment, which introduced additional instability. The pilot was implemented without commensurate investment in harm reduction, treatment, or housing infrastructure, within already constrained systems. CONCLUSION: BC's decriminalization pilot suggests the effects of legal reform are shaped by implementation context. Early outcomes may reflect design features, institutional readiness, and system capacity rather than legal change alone; longer-term impacts remain uncertain. Future reforms should align legal change with coordinated implementation, operational guidance, public communication, and adequate service infrastructure.

British Columbia

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques

From fear to empowerment: the&#xa0;impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans

A risk-need-responsivity (RNR)-informed systematic review of needs during the pretrial period.

OBJECTIVE: Pretrial risk assessments are becoming increasingly popular in the United States. Despite the importance of assessing and intervening around "needs" in the risk-need-responsivity model, few pretrial risk assessments include comprehensive assessment of needs. We aim to provide a systematic review of the prevalence of and predictive utility of needs within the pretrial population. HYPOTHESES: There were no hypotheses given the nature of the study. METHOD: We conducted searches for articles in the EBSCO, ProQuest, and Google Scholar databases using key words related to 11 needs domains: antisocial personality, procriminal attitudes, procriminal associates, substance use, family/marital relationships, school/work, prosocial recreational activities, self-esteem, housing, mental health, and physical health. We identified 215 articles that reported on the prevalence of needs or explored their predictive associations with pretrial misconduct outcomes in adult populations. RESULTS: Overall, we find few comprehensive investigations of needs in the pretrial domain, apart from substance use. Variation in methodology and operationalization contributes to wide variability in prevalence estimates. We found only 15 articles that examined predictive associations between pretrial needs and outcomes, which were limited to investigations of behavioral health, employment, and housing needs. Substance use and housing needs emerged as the only consistent predictors of pretrial misconduct. CONCLUSIONS: Researchers should more directly assess the prevalence and predictive utility of needs within the pretrial period to bolster the evidence base for including these factors in pretrial risk assessments. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Humans