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PubMed2026

The effectiveness of digital health interventions for type 2 diabetes in underserved populations: A systematic review and meta-analysis.

This systematic review and meta-analysis of 12 randomized controlled trials (1835 participants) evaluated whether digital health interventions (DHIs) improve glycemic control among underserved adults with type 2 diabetes (T2D), including racial/ethnic minority, low-income, Medicaid-insured, rural, and low-health-literacy populations. Searches of PubMed, Embase, and the Cochrane Central Register of Controlled Trials from inception to December 20, 2025 identified eligible parallel-group randomized controlled trials reporting change in hemoglobin A1c (HbA1c). Two reviewers independently screened studies, extracted data, and assessed risk of bias using the revised Cochrane Risk of Bias 2 tool. Random-effects meta-analysis showed that DHIs produced a modest but statistically significant HbA1c reduction versus control (mean difference, -0.37 %age points; 95% CI, -0.44 to -0.30; P < .0001; equivalent to -4.0 mmol/mol). Heterogeneity was moderate-to-substantial (I² = 69.9%). Subgroup analyses suggested directionally similar effects by population group and intervention modality, but interpretation was limited by study-level data and the small number of trials. Funnel-plot inspection and Egger's test (P = .31) did not suggest major small-study effects, although power was limited. Overall certainty for HbA1c was moderate. DHIs may support more equitable diabetes care when implemented with cultural tailoring, language access, digital-literacy support, and technology-access safeguards.

Humans↗

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

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

The influence of organizational culture on medication safety practices and associated risk factors in the community setting: A systematic review.

BACKGROUND: Increasing attention has been given to the role of organizational culture in influencing medication safety practices across healthcare settings. The lack of widely accepted standardized instrumentation makes operational measurement of organizational culture and medication safety challenging. The purpose of this systematic review was to examine the impact of organizational culture on medication safety within community healthcare settings. METHODS: MEDLINE, CINAHL, Scopus, and Nursing & Allied Health were searched in August 2025 using keywords, subject terms, field codes, and Boolean operators to identify papers relevant to the review question; bibliographies of included studies were also reviewed. Screening and full-text review were completed independently by two reviewers with a third to adjudicate conflicts. The Critical Appraisal Skills Programme was used for quality assessment. The PRISMA statement guided the development and implementation of the review. RESULTS: Thirteen articles were included representing various community settings. Most studies reported on untoward medication events, but few measured systematically collected safety data before and after an intervention. Organizational culture was seldom defined or operationalized. Most studies were methodologically sound, but the overall level of evidence was weak to moderate. CONCLUSION: Organizational culture influences medication safety through aspects such as communication channels, teamwork, training, and an environment that allows error and near-miss reporting. Few studies explicitly evaluate the causal impact of culture interventions on measurable medication safety outcomes in community healthcare settings. Further research should incorporate standardized measurement tools and intervention-based, pre-post designs to better understand how organizational culture influences medication safety in community healthcare settings.

Organizational Culture↗

PubMed2026

Orofacial Cleft Disparities in American Indian and Alaska Native Populations: A Systematic Review and Meta-Analysis.

ObjectiveTo evaluate the prevalence, access to care, and health outcomes of orofacial clefts (OFCs) among American Indian and Alaska Native (AI/AN) populations through a systematic review and meta-analysis.DesignSystematic review and meta-analysis performed in accordance with PRISMA 2020 guidelines and registered with PROSPERO (CRD420251035364).SettingUS-based population registries, hospital databases, and institutional or community-level retrospective studies involving AI/AN populations.Patients and ParticipantsAI/AN individuals with OFCs compared with non-Hispanic White patients.InterventionsPrimary cleft lip and palate repair, secondary cleft-related procedures, and multidisciplinary cleft care.Main Outcome Measure(s)Prevalence of OFCs, timing of cleft surgery, discharge disposition, access to specialists, and qualitative determinants of disparities.ResultsEighteen studies including more than 1985 AI/AN patients were identified. Meta-analysis of 5 studies estimated a pooled OFC prevalence of 15 per 10 000 live births (95% confidence interval: 5-49), with substantial heterogeneity (I2 = 99.8%). Individual studies reported significantly higher OFC prevalence in AI/AN populations compared to non-Hispanic Whites (odds ratio range: 1.44-2.68). Geographic maldistribution of craniofacial-trained surgeons, increased odds of nonhome discharge, and delayed cleft palate repair were consistently observed barriers. Qualitative analyses highlighted structural inequities, perceived racism, and lack of culturally responsive care as major contributors to disparities.ConclusionsAI/AN populations face a disproportionately high burden of OFCs alongside structural barriers to timely, culturally competent care. Addressing these disparities requires community-engaged, multidisciplinary interventions that improve geographic access and integrate culturally responsive approaches to care.

Humans↗

PubMed2025

Feasibility, Acceptability, and Preliminary Effectiveness of Family Navigation for Low-income Ethnoracially Diverse Preschoolers with Developmental Concern.

OBJECTIVE: To assess for feasibility, acceptability, and preliminary effectiveness of an ethnoracially-matched family navigation intervention aimed at reducing barriers to developmental evaluations for preschoolers with developmental concern attending Head Start. METHODS: Fifty-eight parents of Head Start preschoolers who were identified as at risk for developmental delay were assigned using stratified block random sampling to the family navigation intervention (n = 28) and 30 controls (usual care). Key outcomes included the percentage of children who completed the planned intervention visits, satisfaction with the intervention, and the proportion of children guided by family navigators who completed developmental evaluations. RESULTS: Of the 28 families, 21 parents completed the family navigation intervention visits. The intervention sample was diverse, including 57% Black, 24% White, and 19% Latino(a) parents. Ninety percent of Head Start educators (n = 18) and 100% of healthcare providers (n = 6) were satisfied with the intervention. Parents qualitatively reported that they valued the advocacy support from the family navigators and navigators (n = 7) valued their role in "giving back." Sixty-six percent of the intervention group were seen by a healthcare provider to discuss developmental concerns showing preliminary effectiveness for completion of healthcare evaluations. However, there was no significant difference between those in the intervention and control group completing Head Start recommended evaluations, and over half of all participants were not referred for educational evaluations. CONCLUSION: Results support the feasibility, acceptability, and preliminary effectiveness of an ethnoracially matched family navigation intervention to reduce barriers to developmental healthcare evaluations for preschoolers at risk for developmental delays. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03499405; Date of Registration: April 9, 2018.

Humans↗

PubMed2026

New Horizons in the Development of Treatments for Substance Use Disorders.

Substance use disorders (SUDs) are a major public health problem in the United States and cause substantial morbidity and mortality. There are meaningful gaps in the available SUD treatment options, and the development of new therapies is urgently needed. While medications with U.S. Food and Drug Administration approval are available for alcohol, nicotine, and opioid use disorders, there are no approved pharmacotherapies for cannabis, cocaine, or methamphetamine use disorders. Behavioral treatments for SUDs have significant limitations in effectiveness and accessibility, and there is a need for the development of both new behavioral treatment options and new models of treatment delivery. The next generation of treatments for SUDs will likely come from a diverse set of interventions, including new drug classes, new technologies, and new methods of delivery.

Humans↗

PubMed2026

Interhospital transfer and outcomes after robotic emergency general surgery: a national analysis.

The outcomes of patients transferred to receiving centers who subsequently undergo robotic EGS remain uncharacterized at a national level. We aimed to quantify the association between transfer and outcomes among adults undergoing robotic EGS. We performed a retrospective cohort study of the Nationwide Readmissions Database (2016-2019) including adult nonelective admissions undergoing robotic EGS. Interhospital transfer versus direct admission was the exposure. Survey-weighted logistic regression estimated adjusted odds ratios (aOR) for clinical outcomes; generalized linear models with gamma family and log link estimated adjusted mean ratios (aMR) for length of stay (LOS) and cost. Average marginal effects provided adjusted risks/means and absolute differences. Among 26,869 unweighted robotic EGS admissions, representing an estimated 46,517 admissions nationally, 246 unweighted admissions were interhospital transfers, representing an estimated 444 transfers (1.0%) nationally. Transfers were older, more comorbid, and more severely ill and were treated predominantly at large, teaching hospitals. After adjustment, transfer was associated with a higher risk of postprocedural complications (8.0% vs. 3.5%; aRR 2.26, 95% CI 1.25-3.27), non-home discharge (31.2% vs. 18.9%; aRR 1.65, 95% CI 1.38-1.92), longer LOS (11.49 vs. 5.53 days; AMR 2.08, 95% CI 1.78-2.42), and higher cost ($43,340 vs. $21,821; AMR 1.99, 95% CI 1.68-2.35). The association with postprocedural complications was attenuated after additional adjustment for APR-DRG Severity of Illness, whereas associations with non-home discharge, LOS, and cost persisted. Among patients undergoing robotic EGS, interhospital transfer is independently associated with higher complication burden and greater resource use. Transferred patients represent a small but distinctly high-risk subgroup whose worse outcomes may reflect drivers that extend beyond the choice of surgical approach.

Humans↗

PubMed2026

A bimodal large language model reduces misalignment in patient education: A double-blinded randomized trial.

BACKGROUND: Effective patient education requires accurate communication aligned with patients' emotional and semantical needs. Text-based large language models (LLMs) lack access to non-verbal cues, which may contribute to misaligned responses. METHODS: We evaluated emotional and semantic misalignment in a text-based LLM using 64,200 utterances from 16,583 patient education cases across six departments and three centers. Dolphin was developed integrating text and audio cues and evaluated through emotion recognition, semantic consistency assessment, branch-level ablations, and a double-blinded randomized trial against a matched text-based LLM comparator (Chinese Clinical Trial Registry: (ChiCTR2500095933). FINDINGS: The text-based LLM showed emotional misalignment in 36.7% of responses and semantic misalignment in 28.3% of cases, with higher misalignment under greater burden. Dolphin outperformed the text-based LLM in emotion recognition accuracy (0.886 vs. 0.713) and semantic consistency (84.9% vs. 82.1%; both adjusted p < 0.001). Ablations supported contribution of audio branches. Dolphin received higher expert ratings than the text-based LLM and human educators (all p < 0.001). In 555 patients, Dolphin was associated with greater patient satisfaction (98.6% vs. 93.8%), suggestion acceptance (76.1% vs. 58.9%; p < 0.001), proactive disclosure (44.6% vs. 26.5%; p < 0.001), and fewer 7-day unplanned recontact (12.9% vs. 22.9%; p = 0.002). No unsafe recommendations or safety events were identified. CONCLUSIONS: Compared with text-based LLM, Dolphin improved emotional-semantic alignment and patient-education outcomes, supporting bimodal alignment as a strategy for reducing misalignment-driven communication failures. FUNDING: National Natural Science Foundation of China, State Key Laboratory Special Fund, and Chinese Academy of Medical Sciences Innovation Fund.

Humans↗

PubMed2026

Disparities in guideline-adherent cardiovascular preventive care for people with diabetes: A systematic review and meta-analysis.

BACKGROUND: Clinical practice guidelines offer guidance on delaying the progression of cardiovascular disease in people living with diabetes. We sought to determine whether guideline-recommended cardiovascular preventive care for people living with diabetes differs according to sociodemographic indicators, globally. METHODS: We conducted a systematic review of studies that compared the sociodemographic characteristics of people diagnosed with type 1 or 2 diabetes who received cardiovascular preventive care as recommended by guidelines to those who did not. Sociodemographic predictors were defined by PROGRESS+ (an equity framework). We searched MEDLINE, EMBASE, and APA PsychInfo from 2010 to January 21, 2026. Studies were screened independently by two people. One person assessed the risk of bias and extracted data, and another verified. We pooled results using a random-effects model and assessed the certainty of evidence using GRADE. RESULTS: Twenty-five studies were included. Meta-analyses showed female, Black, and Hispanic individuals had slightly lower odds of receiving guideline-recommended prescriptions for lipid-lowering medication compared to Male, and White individuals, respectively (OR:0.89, 95%CI:0.79,1.00, moderate certainty; OR:0.78, 95%CI:0.74,0.81, high certainty; OR:0.86, 95%CI:0.59,1.26, low certainty). Individuals aged 18-45 years had moderately lower odds (OR:0.33, 95%CI:0.19,0.57, moderate certainty), no observed association for Asian individuals. Asian individuals had moderately lower odds of antihypertensive medication prescription (OR:0.42, 95%CI:0.38,0.46, high certainty). Evidence suggests likely no association between HbA1c testing and sex/gender or between sex/gender and lipid panel testing. CONCLUSIONS: Some disparities in guideline-recommended cardiovascular preventive care among people living with diabetes were found. These results are consistent with previous reviews and highlight the need to ensure guidelines consider equity and with improved dissemination.

Humans↗

PubMed2026

Tele-Oncology in the Post-Pandemic Era: Clinical Integration, Access Disparities and Medico-Legal Accountability.

PURPOSE OF THE REVIEW: Tele-health has evolved from a marginal tool confined to rural populations and selected follow-up programs into a structurally integrated component of modern cancer care. Prior to COVID-19, its adoption was constrained by regulatory fragmentation, non-uniform reimbursement, and licensure barriers. This narrative review evaluates the evolutionary integration of tele-health in oncology post-COVID-19, examines digital disparities across patient populations, and addresses the medico-legal implications of this integration, with the objective of providing a comprehensive and clinically actionable framework for the governance of virtual oncology care. RECENT FINDINGS: The pandemic acted as a global catalyst, driving telehealth to over 50% of oncology outpatient encounters in some settings, before stabilising post-pandemic at approximately 10-20% of consultations within hybrid care models. Evidence supports meaningful clinical benefits - improved access to specialist services, reduced travel burden, and sustained continuity of care - with outcomes comparable to in-person care in postoperative follow-up, symptom monitoring, and survivorship. However, persistent disparities in device availability, connectivity, and digital literacy disproportionately affect older, rural, and socioeconomically disadvantaged patients, raising the risk that geographic inequalities are replaced by technological ones. From a medico-legal standpoint, the remote modality does not modify the applicable standard of care, yet restricted physical examination and reliance on patient-reported data introduce risks of diagnostic delay and incomplete clinical assessment, with direct implications for professional liability, data protection under HIPAA and GDPR, cross-border licensure, and multi-party accountability across physicians, institutions, and technology providers. Tele-oncology has become a permanent structural feature of modern cancer care, offering demonstrable benefits in access, continuity, and patient satisfaction. Yet its integration has been uneven, its governance remains fragmented, and its medico-legal landscape is still evolving. Realising the full potential of virtual oncology care - equitably and safely - requires coherent regulatory frameworks, sustained investment in digital infrastructure, and explicit attention to the populations at greatest risk of being left behind.

Humans↗

PubMed2026

From fear to empowerment: the 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↗

PubMed2025

Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.

Cognitive-behavioral treatments (CBTs) for adolescents with ADHD demonstrate promise of long-term effects on outcome. However, their implementation in routine care community clinics faces barriers that impact quantity, efficiency, and quality of delivery, as well as client outcomes. This study is a randomized controlled trial designed to evaluate the impact of an AI-assisted service delivery model on therapist implementation of Supporting Teens' Autonomy Daily (STAND), a CBT blended with Motivational Interviewing (MI) for adolescents with ADHD. Adolescents with ADHD (N = 51), who were clients at three community mental health agencies, received treatment from 23 therapists. There was randomization of adolescents and therapists to AI-assisted or standard implementation supports. In addition to standard supports (i.e., training, standard facilitation resources, technical assistance, case supervision), AI-assisted support package included digitized facilitation resources housed in a clinical dashboard (Care4), feedback on content fidelity, and AI-generated feedback on MI implementation quality. The AI-assisted group was associated with more efficient treatment delivery and lower number of appointments attended by the adolescent. There was also a significant decrement in MI quality over time in the AI-assisted group compared to the standard support group. Feedback in focus groups indicated that therapists perceived a task-oriented mindset to be associated with receipt of the AI-assisted support package, leading therapists to prioritize efficiency over relational aspects of therapy. Following the results of this trial, a future, larger RCT should examine the impact of the AI-assisted implementation model on mental health outcomes and cost savings to organizations, third party payers, and clients. Trial registration number: NCT05135065; https://www.clinicaltrials.gov ; Registered September 2021.

Humans↗

PubMed2026

Patient and hospital factors associated with disparities in acute stroke treatment in community and academic hospitals.

BACKGROUND: Systemic barriers may affect identification, emergency transportation (EMS), and care coordination for people with stroke. We assessed patient- and hospital-level factors for associations with pre-hospital and emergency department care. We compared trends for patients presenting to an academic medical center (AMC) versus community hospitals (CHs). METHODS: We conducted a retrospective cohort study at an AMC (Tufts Medical Center) with 542 patients aged ≥18 years hospitalized with acute ischemic stroke or transient ischemic attack between 1/1/2018-12/31/2020 who presented directly to AMC or presented to AMC as a transfer from initial contact CHs. Primary outcomes were EMS use, stroke code activation, door-to-CT time, and door-to-needle time. RESULTS: AMC patients identifying as non-Hispanic Asian (odds ratio (OR) = 0.25; 95% confidence interval (CI) = 0.13-0.47) and Hispanic (OR = 0.19; 95% CI = 0.05-0.72) and CH non-Hispanic Black/African-American patients (OR = 0.17; 95% CI = 0.05-0.62) were less likely to use EMS compared to non-Hispanic white patients. Patients with non-English primary language were less likely to use EMS (OR = 0.38; 95% CI = 0.23-0.63) compared to English-speaking patients in both hospital settings. CH Hispanic patients were less likely to have stroke code activation (OR = 0.24; 95% CI = 0.05-0.86) compared to non-Hispanic white patients. CH patients were less likely to have stroke code activation (OR = 0.12; 95% CI = 0.07-0.19), had 31% shorter door-to-CT time (95% CI = 15-43% shorter), and had 29% longer door-to-needle time (95% CI = 5-58% longer). CONCLUSION: Patient-level factors and hospital setting were associated with differences in acute care suggesting opportunities for community outreach on EMS use, interventions to alleviate language barriers, and a need to address systemic biases.

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PubMed2026

Impact of Physical Environment of Pediatric Inpatient Wards on Children: A Systematic Literature Review.

ObjectiveThe study aimed to examine empirical studies published between 2003 and 2025 to identify elements of physical environments influencing health outcomes and experiences of children and families.BackgroundIn the past 40 years, research has shown that the physical environment influences the health and well-being of patients in the healthcare environment. However, similar research in the context of "pediatric inpatient wards" remains underexplored.MethodsPubMed, Embase, Scopus, and Web of Science were used to identify relevant articles. All extracted articles underwent a three-step screening process using PRISMA. A total of 30 eligible articles were used for the analysis. The protocol is registered at PROSPERO (CRD42023408997).ResultsKey findings reveal positive and negative impacts of identified elements. Positive-effect elements include play spaces, space for parents, natural light, connections with nature, and so on, which promote comfort, healing, and emotional resilience. Conversely, negative-effect elements, such as noise, artificial lighting, uncomfortable temperature, and so on, contribute to stress and disrupted sleep. Mixed effects were observed for elements like art and television, which underscore the complexity of designing environments that address the diverse needs of different age groups and genders.ConclusionsThe review findings highlight significant knowledge gaps. The study also tries to bridge existing gaps between research and practice by systematically identifying environmental elements, offering actionable insights to architects, designers, healthcare providers, and policymakers. Future research must adopt rigorous, culturally inclusive approaches to advance the field of pediatric healthcare design and ensure equitable care across diverse sociocultural contexts.

Humans↗

PubMed2026

Antibiotic Self-Medication and Public Awareness During the 2023 Gaza War: A Cross-Sectional Investigation.

BACKGROUND: Antimicrobial resistance is driven by inappropriate antibiotic use, particularly self-medication. The 2023 Gaza War disrupted healthcare services, increasing resistant infections and reliance on self-treatment practices. OBJECTIVES: To determine the prevalence of antibiotic self-medication and assess public awareness during the 2023 Gaza War. METHODS: A cross-sectional survey was conducted between May and October 2025 among adults residing in the Gaza Strip during the 2023 Gaza War. A multistage non-probability recruitment strategy, organized across predefined governorate and residential-setting strata, was used to recruit 422 participants from primary healthcare centers, community pharmacies, and displacement shelters. The questionnaire demonstrated good internal consistency (Cronbach's α = 0.857). Ethical approval was obtained from the relevant institutional review board, and informed consent was secured from all participants. RESULTS: The overall KAP score was moderate (67.46%), with attitudes scoring highest (74.62%), followed by knowledge (66.23%) and practices (61.52%). Reported antibiotic self-medication increased from 60.4% before the war to 80.6% during the war (p < 0.001), with significant changes in reasons for self-medication and antibiotic procurement sources. The mean antimicrobial-resistance perception score was 82.19 ± 11.10%, and knowledge was strongly correlated with the total KAP score (r = 0.836, p < 0.001). CONCLUSIONS: Reported antibiotic self-medication was markedly higher during the 2023 Gaza War despite moderate public awareness, highlighting the urgent need for education, antibiotic stewardship, and improved healthcare accessibility.

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PubMed2025

Impacts of Climate Change and Related Weather Events on the Health and Wellbeing of Culturally and Linguistically Diverse Communities: A Systematic Review.

BACKGROUND: Vulnerable populations such as culturally and linguistically diverse communities (CALD), ethnic minorities and racial groups face a disproportionate burden of climate change-related health impacts due to a combination of socio-cultural and economic factors, geographic vulnerabilities and health disparities. This review synthesised the existing evidence on the health and wellbeing impacts of climate change and related weather events among CALD communities. METHODS: A narrative synthesis approach was utilised to conduct a systematic review. Three electronic databases (PubMed, Scopus and Web of Science) were searched, identifying 25 studies for appraisal and synthesis. Studies published in the English language from January 2010 to March 2024 were included in the review. RESULTS: The reviewed studies, mostly carried out in the USA, employed varied study designs, and focused on diverse CALD groups such as migrants, farmworkers and racial and ethnic minorities. The included studies addressed broader and specific climate change-related events, ranging from heat-related impacts and hurricanes to occupational heat exposure. CALD communities were found to be more vulnerable to climate change-related negative physical and mental health issues, further exacerbated by poor living conditions, limited access to healthcare, and cultural and language barriers. CONCLUSION: Future efforts by governments, healthcare agencies, employers and research institutions should prioritise multilingual risk communication strategies, providing culturally appropriate health education and healthcare access, housing improvements and the investigation of long-term health impacts of climate change and coping mechanisms adopted among CALD populations.

Climate Change↗

PubMed2025

Predictive Validity of Violence Screening Tools in Emergency and Psychiatric Services: A Systematic Review.

Violence against healthcare staff, including a threat or an act of violence toward people during their work, poses a physical and psychological risk to workers internationally. Screening is an important strategy in preventing violence against healthcare professionals. The aim of this systematic review was to synthesize evidence on the predictive validity of risk assessment tools used to screen for violence and aggression risk toward healthcare workers in emergency and psychiatric departments (PD). Primary studies that examined the predictive validity of risk assessment tools for workplace violence were identified via a systematic search of Medline, PsycINFO, Embase, and the Cochrane databases. There were 62 eligible studies, ten of which had a lower risk of bias (RoB). Those studies with high RoB were primarily due to a failure to present calibration measures as part of the analysis. All included studies adopted a longitudinal design and were conducted in PDs. The ten highest-quality studies reported on eight different instruments, four of which showed acceptable to outstanding predictive performance. The Dynamic Appraisal of Situational Aggression and the Brøset Violence Checklist showed the best predictive performance; they were also validated in emergency departments and are best suited for short-term risk prediction. We recommend that the selection of a risk assessment tool should consider the following: (a) the target population, (b) the violence operationalization, and (c) the purpose of the monitoring. We note that the use of a screening tool should be a part of a multicomponent strategy to ensure staff safety.

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