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PubMed2026

Use of wearable technologies for physical activity promotion in older adults: A systematic review.

This systematic review, conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251055299), examined the use of wearable technologies for promoting physical activity (PA) in adults aged 60 years and older. Searches across five databases (PubMed, Scopus, Web of Science, CINAHL, Cochrane) identified 2438 records, of which only six randomized controlled trials published between 2021 and 2025 met inclusion criteria, with sample sizes ranging from 36 to 551 participants and mean ages between 65 and 79 years. Given the small number of included studies, findings should be interpreted as preliminary. The studies ranged from the standalone use of commercial trackers (Fitbit, Polar, ActiGraph) to multicomponent interventions combining wearables with physiotherapist feedback, telephone counseling, web-based platforms, or interactive cognitive-motor training. Wearables used alone, as in the REACT trial, produced small or non-significant PA effects. In contrast, interventions integrating devices with personalized feedback, professional support, or digital platforms, such as PROMOTE and TASMANIA, were associated with more consistent improvements in PA, physical function, and cognitive outcomes. Multicomponent programs, such as PEER and ICMT, reported broader benefits, including cognition, balance, and reductions in sedentary behavior, though these findings derive from individual trials and require replication. Risk of bias, assessed with the Cochrane Risk of Bias tool version 2 (RoB 2.0), was rated as "some concerns" for five studies and low for only one, mainly due to gaps in randomization reporting, missing data, and lack of preregistration. Tentatively, and based on a very limited evidence base, wearables may have greater impact when embedded within broader behavioral systems, incorporating feedback, coaching, or interactive components, rather than when used in isolation as passive monitoring tools. Adherence and psychosocial outcomes appeared related to comfort and perceived usefulness among older adults, though larger and more robust trials are needed to confirm these patterns.

Humans↗

PubMed2026

Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review.

AIM: To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making. METHODS: An umbrella review of literature reviews. DATA SOURCES: Four major databases were searched for reviews published between 2019 and 2024. RESULTS: Sixteen literature reviews reported on 965 nursing artificial intelligence primary studies. The studies focused on technology development and emerging performance evaluations, whilst real-world testing or implementation in nursing clinical settings was rare. Rigorous comparative analyses were lacking. While artificial intelligence demonstrates promise in decision-making, challenges such as a lack of controlled studies, algorithmic bias, limited reproducibility and insufficient clinical trials hinder its practical impact. Ethical concerns, transparency and patient data privacy issues pose barriers to AI integration in nursing practice. Ethical and legal guidelines for patient privacy are needed and should be taught along with AI literacy training for nurses. CONCLUSIONS: Artificial intelligence has the potential to enhance clinical nursing decision-making, although evidence is limited by too few examples of nurse participation during development. Underutilisation in administrative nursing functions hinders implementation. Nurses should assume a central role in the design and development of AI applications to ensure that these technologies address the realities of nursing practice. With such improvements, artificial intelligence can transform nursing practice, improve nurses' clinical decision-making and ultimately enhance consumer healthcare outcomes. PATIENT OR PUBLIC INVOLVEMENT: No Patient or Public Involvement. REPORTING METHOD: While there is no reporting checklist for umbrella reviews, the PRISMA guide for systematic reviews was followed.

Artificial Intelligence↗

PubMed2026

Efficacy, acceptability, and related outcomes of pharmacological interventions for acute bipolar mania: a systematic review and dose-related network meta-analysis across different age groups.

BACKGROUND: Acute bipolar mania carries negative social and economic consequences. We investigated the comparative efficacy/response/acceptability of pharmacological interventions for acute bipolar mania, considering dose effects across different age groups. METHODS: We conducted a network meta-analysis (NMA) to search for randomized controlled trials (RCTs) comparing pharmacological interventions with one another or placebo in acute bipolar mania patients, indexed in PubMed/MEDLINE, Embase, Web of Science, and Scopus (from inception through 2025.12.24). Co-primary outcomes were change in manic symptoms/response/and acceptability. Tolerability/remission and rate of adverse events were secondary outcomes. Confidence-In-Network-Meta-Analysis was likewise appraised. RESULTS: 113 RCTs, encompassing 49 distinct treatment combinations, included 20,666 participants. Sensitivity analysis retaining only low-risk-of-bias studies and excluding outliers for possible effect modifiers indicated that risperidone 3 mg/day(SMD = -7.57;95%C.I. = -8.25;-5.85); tamoxifen 160 mg/day(SMD = -1.73;95%C.I. = -2.32;-1.13); rivastigmine 3 mg/day(SMD = -1.13;95%C.I. = -1.06;-0.58); haloperidol 30 mg/day(SMD = -0.96;95%C.I. = -1.25;-0.75); valproate 750 mg/day(SMD = -0.76;95%C.I. = -1.48;-0.58); tamoxifen 40 mg/day(SMD = -0.75;95%C.I. = -1.41;-0.59); celecoxib 400 mg/day(SMD = -0.74;95%C.I. = -1.20;-0.38); paliperidone extended-release 12 mg/day(SMD = -0.62; 95%C.I. = -0.91;-0.32); olanzapine 15 mg/day(SMD = -0.59;95%C.I. = -0.60;-0.38); olanzapine 20 mg/day(SMD = -0.52;95%C.I. = -0.66;-0.38); risperidone 4 mg/day(SMD = -0.53;95%C.I. = -0.76;-0.29); allopurinol 600 mg/day(SMD = -0.54;95%C.I. = -0.67;-0.22); cariprazine 12 mg/day(SMD = -0.49;95%C.I. = -0.66;-0.33); risperidone 4.2 mg/day(SMD = -0.46;95%C.I. = -0.75;-0.17); lithium 1500 mg/day(SMD = -0.42;95%C.I. = -0.57;-0.28); ziprasidone 160 mg/day(SMD = -0.49;95%C.I. = -0.68;-0.31); asenapine 20 mg/day(SMD = -0.38;95%C.I. = -0.53;-0.22); haloperidol 8 mg/day(SMD = -0.34;95%C.I. = -0.63;-0.05); aripiprazole 15 mg/day(SMD = -0.33;95%C.I. = -0.61;-0.06) outperformed placebo. Ziprasidone 160 mg/day, celecoxib 200 mg/day, asenapine 20 mg/day, and asenapine 10 mg/day proved more efficacious than placebo in children. No statistically significant differences were reported between treatments and placebo for response/remission/acceptability/tolerability, and manic/hypomanic switch. A meta-regression of efficacy effect sizes against the adapted AMSTAR-Plus content scores showed that larger SMDs were associated with lower AMSTAR scores, indicating lower study quality, warranting further caution for such large efficacy estimates. CONCLUSIONS: Our findings are consistent with previous NMAs and current guidelines, expanding the current knowledge base while concurrently appraising different drugs, doses, and age groups.

Humans↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

Virtual, Augmented, and Mixed Reality Technologies in Neurosurgical Training: Enhancing Skills and Surgical Outcomes: A Systematic Review.

OBJECTIVE: To systematically review the role of virtual reality (VR), augmented reality (AR), and mixed reality (MR) in neurosurgical education and training. DESIGN: Systematic review conducted in accordance with the PRISMA guidelines. SETTING: A comprehensive search was performed across PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar for English-language studies published between 1 January 2020 and 30 April 2026. PARTICIPANTS: Studies involving neurosurgeons, fellows, residents, and medical students (maximum sample size: n = 48) were included. RESULTS: Of 7,204 initially identified studies, 25 met the inclusion criteria. VR was primarily used for surgical simulation (100% of VR studies) and anatomical education (62.5%). AR demonstrated broader applications, including preoperative planning (40%) and intraoperative support (30%). MR was evenly distributed across simulation, planning, and intraoperative support (40% each). The most frequently improved outcomes were training effectiveness (52%) and technical proficiency (44%). Methodological quality scores, assessed using the Modified Medical Education Research Study Quality Instrument (MMERSQI), ranged from 39.5 to 84.5, indicating varied rigor. CONCLUSION: VR, AR, and MR technologies show potential to enhance surgical precision, technical skills, and educational outcomes in neurosurgical training. However, standardization of methodologies and cost-effective solutions remain essential. Future research should focus on long-term clinical impact and integration of AI-driven training models.

Virtual Reality↗

PubMed2026

A homogeneous immunoassay based on AlphaLICA technology for detecting florfenicol residues in animal-derived foods.

Florfenicol (FF), a broad-spectrum amide antibiotic widely used in livestock, poultry, and aquaculture, poses potential threats to food safety and public health due to its residual accumulation. In this study, a novel homogeneous immunoassay based on Amplified Luminescent Proximity Homogeneous Assay (AlphaLICA) technology was developed for the first time for rapid screening of FF residues in milk and egg matrices. By covalently immobilizing the FF-BSA conjugate and goat anti-mouse IgG onto luminescent and photosensitive microspheres, respectively, the method achieved wash-free, homogeneous quantitative detection through a competitive immunoreaction. Under optimized conditions, the assay exhibited a linear range of 0.2-16.2 ng mL-1, with a limit of detection of 9.7 pg mL-1 and a limit of quantification of 183 pg mL-1. The intra- and inter-batch coefficients of variation ranged from 3.08% to 5.70% and 2.44% to 7.09%, respectively. Spike recovery rates in milk and egg matrices ranged from 93.18% to 107.17% (RSD ≤ 5.57%). Cross-reactivity with 11 other common antibiotics, including chloramphenicol and thiamphenicol, was below 0.1%, demonstrating excellent specificity. Comparative analysis with a commercial ELISA kit showed high consistency (r2 = 0.9332, p < 0.001). With high sensitivity, strong specificity, simple operation, and a detection time of only 10 min, this method provides a reliable technical platform for high-throughput, rapid monitoring of FF residues in milk and egg matrices.

Journal Article↗

PubMed2026

Current Concepts and Emerging Technologies in Aesthetic Outcome Assessment of Breast Reconstruction.

Aesthetic outcomes are a crucial determinant of the overall success of breast reconstruction. Recently, aesthetic assessment has evolved from relying mainly on subjective impressions to incorporating more quantitative methods. This systematic review summarizes current concepts and emerging technologies in aesthetic outcome assessment after breast reconstruction. A comprehensive search of studies evaluating aesthetic outcomes following implant-based, autologous or hybrid breast reconstruction was performed between 2000 and 2025. Assessments were classified as subjective or objective. Extracted variables included assessment characteristics, aesthetic outcome domains, and patient-centered outcomes. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Levels of evidence were classified according to the Oxford Centre for Evidence-Based Medicine. A total of 51 studies involving 7711 participants from 16 countries were included. Subjective tools were most frequently employed, led by the BREAST-Q (35/51, 69%), followed by expert- or panel-based evaluations (17/51, 33%) and the visual analog scale (2/51, 4%). Objective methods were applied in 19 studies and included 3-dimensional surface imaging (8/51, 16%), BCCT.core (7/51, 14%), eye tracking (3/51, 6%), and artificial intelligence-based analyses (3/51, 6%). Although subjective tools captured satisfaction with breast appearance, objective tools quantified morphological parameters and positional landmarks. BREAST-Q remains the cornerstone of outcome evaluation after breast reconstruction, providing patient-centered perspectives, including, but not limited to, aesthetic perception. A progressive shift toward multimodal evaluation was noticed, as no single modality comprehensively addressed all aesthetic domains. Future research should focus on integrating subjective and objective assessment methods within a unified framework. Level of Evidence: 3 (Therapeutic) For image description, please refer to the figure legend and surrounding text.

Humans↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

How Following Medical Artificial Intelligence Advice Can Mitigate Malpractice Liability: Cross-National Insights from a Randomized Trial.

Artificial intelligence (AI) increasingly influences clinical decision-making, yet its recommendations may diverge from standard care. Although malpractice concerns are thought to discourage physicians from following AI advice, experimental evidence from the United States suggests the opposite: lay jurors are more likely to hold physicians liable when they reject AI recommendations. Whether this pattern extends to systems in which court-appointed experts, not lay jurors, determine liability remains unknown. Methods: To examine how physicians and laypeople in expert-based and lay-juror legal systems evaluate physicians' acceptance or rejection of AI recommendations, particularly when those recommendations deviate from standard care, we designed a randomized vignette study: a 2 × 2 factorial design varying the AI recommendation (standard vs. nonstandard care) and a fictional physician's decision (accept vs. reject). The study was conducted online in 2023 among nationally representative samples of U.S. and German adults and from 2023 to 2024 among German physicians. In total, 387 German physicians, 2291 U.S. adults, and 2283 German adults participated; those not completing the survey or failing attention checks were excluded per preregistered criteria. Participants were randomly assigned to 1 of 4 vignettes, varying the AI recommendation (standard vs. nonstandard care) and physician's decision (accept vs. reject). The reasonableness of the fictional physician's decision was measured, rated by participants on a Likert scale. Results: Analysis, following preregistered exclusion criteria, included 248 German physicians, 1202 U.S. adults, and 1358 German adults. Physicians accepting standard-care AI recommendations were rated more reasonable than those rejecting them (U.S. laypeople: t = 5.36; 95% CI, 0.45-0.97; P < 0.001; German physicians: t = 2.47; 95% CI, 0.14-1.30; P = 0.02; German laypeople: t = 4.14; 95% CI, 0.27-0.76; P < 0.001). Ratings of physicians accepting versus rejecting AI nonstandard-care recommendations were statistically equivalent. Equivalence was tested at an α-value of 0.05 using a two 1-sided tests procedure, reported with 90% CIs per standard convention (U.S. laypeople: t = -4.90; 90% CI, -0.1 to 0.36; P < 0.001; German physicians: t = -1.76; 90% CI, -0.12 to 0.67; P = 0.04; German laypeople: t = 5.35; 90% CI, -0.35 to 0.06; P < 0.001). Conclusion: Across the United States and Germany, samples representative of lay jurors and court-appointed experts viewed accepting standard-care AI advice as more reasonable, whereas accepting or rejecting nonstandard-care AI advice was judged similarly. Contrary to predictions, malpractice liability regimes do not necessarily pose a barrier to AI use in precision medicine.

Artificial Intelligence↗

PubMed2026

Technology choice, glycemic control and patient-reported outcome measures in adults with type 1 diabetes: A randomized crossover trial comparing a smart insulin pen with an automated insulin delivery system (EBIACE-1).

AIMS: To compare glycemic outcomes and patient-reported outcome measures (PROMs) between smart insulin pens (SIP) and an automated insulin delivery (AID) system in adults with type 1 diabetes (T1D), and to identify individuals able to maintain near-optimal glycemic control using SIP. METHODS: EBIACE-1 was a randomized, open-label, crossover trial including 31 adults with T1D. Participants received SIP (InPen™) and AID (MiniMed™ 780G) for 6 months each. Co-primary outcomes were time in range (TIR 70-180 mg/dL) and HbA1c. Treatment effects were assessed using longitudinal models in intention-to-treat (ITT) and per-protocol (PP) analyses. Predictors of near-optimal glycemic control with SIP were evaluated using multivariable logistic regression. RESULTS: AID improved glycemic control versus SIP, with higher TIR (81 % vs 66 %; +15 %, 95 % CI 10-19; P < 0.001) and lower HbA1c (6.9 % [52 mmol/mol] vs 7.3 % [56 mmol/mol]; -0.4 %, 95 % CI - 0.6 to - 0.3; P < 0.001). Near-optimal glycemic control with SIP was achieved by 12 of 26 participants (46 %). In exploratory analyses, higher baseline diabetes-related life interference was associated with a lower probability of achieving this outcome. CONCLUSIONS: AID provides superior glycemic control, although nearly half of participants achieved near-optimal control with SIP, supporting a personalized approach to technology selection.

Adult↗

PubMed2026

Intentions to use different modalities of long-acting HIV PrEP among men who have sex with men and transgender and gender diverse persons in the Netherlands.

Insight into intentions to use long-acting HIV pre-exposure prophylaxis (PrEP) is essential for successful implementation. We assessed intention to use three hypothetical long-acting PrEP modalities (oral, intramuscular and subdermal) among HIV-negative men who have sex with men (MSM) and transgender and gender diverse persons in Amsterdam, recruited through the Amsterdam Cohort Studies (ACS-participants) and social media (survey-participants). Intention was measured per modality using a 7-point Likert scale. We modeled the probability of high intention to use long-acting PrEP using relative risk regression. Of 1258 participants [1231 (97.9%) MSM; 557 ACS and 701 survey; median age 40 years (IQR 32-50)], 76% had ever used oral short-acting PrEP. Intention to use was highest for monthly oral long-acting PrEP [ACS: median 4.5 (IQR 2-6), 38% high intention; survey: median 7 (IQR 6-7), 81% high intention], followed by 2-monthly intramuscular PrEP [ACS: median 3 (IQR 2-5), 19% high intention; survey: median 5 (IQR 3-7), 47% high intention], and implants [ACS: median 2 (IQR 1-4), 9% high intention; survey: median 4 (IQR 2-7), 37% high intention]. PrEP-experienced participants had higher intention to use oral long-acting PrEP and injectables than PrEP-naïve participants. Offering multiple PrEP modalities may improve the acceptability of HIV prevention strategies and increase PrEP uptake and retention in PrEP care.

Humans↗

PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗

PubMed2026

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of ≥1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans↗

PubMed2026

Driven toward care, avoiding the end: A systematic review and meta-analysis of the relationship between death anxiety and healthcare utilisation.

Both overuse and underuse of the healthcare system have been recognised as significant problems. Relatedly, growing research has recognised the key role of death anxiety in driving various health-relevant behaviours. However, the relationship between death anxiety and healthcare utilisation has not yet been systematically explored. The current systematic review and meta-analysis addressed this gap. In total, 987 papers were screened for inclusion, of which 63 were included in the final review (Ntotal = 21,271). This included 33 quantitative studies, 27 qualitative studies and 3 mixed-methods designs. In total, 17 studies contained sufficient data to be meta-analysed. Overall, the included studies highlighted a significant relationship between death anxiety and healthcare utilisation; in particular, positive associations with desire for life-prolonging treatments and contact with hospitals and medical professionals. By contrast, a negative association was found with other aspects of healthcare utilisation, including hospice use and end-of-life communication. The sample type emerged as a significant moderator, suggesting that the relationship between death anxiety and healthcare usage was strongest in non-medical samples. The current findings suggest that death anxiety plays a key role in utilisation of the healthcare system. The fear of death may need to be targeted in psychological interventions, in order to ensure maximal effectiveness of health services, and improve outcomes for healthcare users.

Humans↗

PubMed2026

Evaluating the Efficacy of Electronic Screening, Brief Intervention, and Referral to Treatment (e-SBIRT) for Gambling: An Online Pilot Randomised Trial.

OBJECTIVES: To investigate the efficacy of electronic screening, brief intervention, and referral to treatment (e-SBIRT) at improving gambling outcomes and increasing help-seeking. METHODS: We conducted a two-arm, randomised online pilot trial (n = 83) comparing an e-SBIRT intervention with an active control over 12 weeks. The brief intervention was informed by motivational interviewing and incorporated personalised normative feedback, information provision, and relapse-prevention components. Eligible participants were aged 18 or older, resided in the UK and had scores indicating at least moderate severity gambling. RESULTS: Participants (54 [65.1%] male; mean [SD] age = 40.58 [12.75] years, mean [SD] PGSI = 7.16 [5.58]) in the e-SBIRT and control conditions showed improvements in gambling harms (p = 0.033) and perceived ability to control gambling (p = 0.029). No significant effects of condition assignment or condition x time interactions were observed. However, exploratory analyses of individual model coefficients suggested greater improvement in perceived ability to control gambling among participants receiving e-SBIRT at 12 weeks (p = 0.043). Exploratory analyses also suggested higher rates of help-seeking at 12-week follow-up among participants receiving e-SBIRT. CONCLUSION: Overall, e-SBIRT did not demonstrate clear advantages over assessment and information provision alone. Further research should prioritise refining intervention components and evaluating SBIRT approaches in settings that better reflect its opportunistic delivery model.

Humans↗

PubMed2025

Barriers and Facilitators of Help-Seeking for LGBTQ+ Survivors of Sexual Violence: A Systematic Review.

People who identify as LGBTQ+ (Lesbian, Gay, Bisexual, Transgender, Queer, plus) are known to experience similar or higher levels of sexual violence compared to their heterosexual cisgender counterparts. However, sexual violence research has largely focused on heterosexual female survivors of male perpetrated crime. Thus, the unique support needs and help-seeking patterns of LGBTQ+ survivors are poorly understood. This review addresses this gap by systematically exploring literature on barriers and facilitators to help-seeking for LGBTQ+ survivors of sexual violence. Four databases (PsycINFO, CINAHL, MEDLINE, and Web of Science) were searched to identify relevant material, with 35 articles (30 qualitative, 1 quantitative, and 4 mixed-methods) meeting the inclusion criteria. Data were extracted and analyzed using a narrative synthesis. The topic was investigated almost exclusively cross-sectionally. Barriers included discrimination experiences, myths and stereotypes, feelings of shame and self-blame, and rejection of victim status. Additional barriers were reported by survivors who hold multiple minority identities, in particular LGBTQ+ people of color and sex workers. Facilitators to help-seeking included the intrinsic need to connect with others, social encouragement and empowerment, and positive disclosure experiences. The Power Threat Meaning framework provides insight into these findings by presenting help-seeking behaviors as adaptive responses to increase a sense of safety following a traumatic experience. The analyzed data indicate several implications for the development and improvement services to support LGBTQ+ survivors. They further serve to highlight the need for additional robust research, conducted with an intersectional lens, to explore the needs of sexual and gender minority survivors of sexual violence.

Humans↗

PubMed2026

Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice.

PURPOSE: This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare. FINDINGS: The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology. ORIGINALITY/VALUE: This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

Students, Medical↗

PubMed2026

Determinants of private health insurance uptake and its association with healthcare utilization in Gulf Cooperation Council countries: a systematic review.

All Gulf Cooperation Council (GCC) countries have a multi-payer healthcare system that comprises governmental health coverage (GHC), funded by the government, and private health insurance (PHI), mainly sponsored by employers and purchased by individuals. Both are expected to influence healthcare utilization and contribute to system efficiency and patient well-being. This systematic review explored the determinants of PHI uptake and its association with healthcare service utilization in the presence of GHC in GCC countries. We systematically searched CINAHL, PubMed, Scopus, Web of Science, and Cochrane Library for peer-reviewed studies published between January 2012 and October 2022. Study quality was assessed using the Critical Appraisal Skills Programme (CASP) checklists for both quantitative and qualitative studies, following PRISMA guidelines. Twenty-six studies met the inclusion criteria. Determinants of PHI uptake were mapped to Andersen's Behavioral Model of Health Services Use (BMHSU) and categorized into (1) predisposing factors (sex, age, marital status, and education), (2) enabling factors (employment/income and health system-related factors such as access and perceived service quality), and (3) need factors (health status, including chronic noncommunicable diseases). PHI uptake was positively associated with being male, married, highly educated, employed with a high income, and having chronic diseases. PHI was positively associated with healthcare utilization, particularly routine check-ups, preventive services, and the use of prescribed medicines. In GCC countries, PHI uptake is influenced by sociodemographic and socioeconomic characteristics, health status, and perceived service quality. PHI is also associated with higher healthcare utilization, underlining the need for evidence-informed policies that enhance equity and expand coverage.

Humans↗