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PubMed2026

Interventions to improve school attendance: a systematic review and meta-analysis of evidence from randomised controlled trials.

BACKGROUND: Poor school attendance adversely affects youth behaviour and health trajectories. We reviewed and synthesised the evidence from randomised controlled trials (RCTs) on interventions to improve school attendance. METHODS: This systematic review and meta-analysis updates the Education Endowment Foundation (EEF) 2022 review on attendance interventions. We synthesised RCT data to inform recommendations. We searched ERIC (via EBSCOhost), PsycINFO, Web of Science and Google Scholar for publications 1 January 2020-16 October 2024 to identify attendance interventions delivered to students, parents/guardians or school staff. We also extracted and analysed RCTs identified in the EEF review. Two reviewers independently extracted data from published articles and assessed risk of bias and certainty of evidence (Grading of Recommendations Assessment, Development and Evaluation, GRADE assessment). We synthesised and meta-analysed data per our protocol (PROSPERO: CRD42024610037). RESULTS: We screened 9366 titles and abstracts and included 61 articles (2000-2024): 43 articles published 2020-2024 plus 18 articles from the previous review (2000-2020), reporting 57 trials of 54 interventions. Pooled mean difference and 95% CIs for days of school attended was 0.63 (-0.34 to 1.61), I2=64.0%, low certainty, for mentoring interventions and 0.43 (0.10 to 0.76), I2=91.9%, moderate certainty, for parental engagement interventions. Other intervention areas including targeted approaches, behavioural programmes and social-emotional interventions had smaller, heterogeneous evidence bases. Risk of bias was moderate-to-low in most trials. CONCLUSION: A large range of interventions exist to address the diverse causes of school absence. Parental engagement demonstrated a small positive effect on attendance, particularly among younger age groups. Most trials were from the USA; implementation and evaluation in other countries will inform effectiveness.

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PubMed2026

Eating Experiences During Cancer Treatment in Adolescents and Young Adults: A Systematic Literature Review and Meta-Synthesis.

Adolescents and young adults (AYAs) aged 15-39 with cancer face distinct challenges during treatment, with eating consistently emerging as one of the most distressing and underrecognized concerns. At a critical life stage, AYAs must navigate illness-related consequences that profoundly affect well-being. Eating reflects these broader challenges and is identified as a key issue requiring health care attention. To address this, we synthesized evidence on AYAs' eating experiences and well-being during mealtime-related activities to inform health care practice. Qualitative and mixed-method studies were identified through searches across CINAHL, Embase, PubMed, Scopus, and Web of Science for studies published up to May 2025, supplemented by snowball searches. Of 3214 records, 74 full-text articles were reviewed, and 18 met the inclusion criteria. These represented 302 AYAs, 73 relatives, and 88 health care professionals. Studies were analyzed using Joanna Briggs Institute review methods and GRADE-CERQual to support clinical interpretability. The meta-synthesis identified one core theme: "Eating as an embodied struggle and act of agency," with three subthemes: (a) living through physical and sensory disruption, (b) carrying the weight of new emotions and shifting relations, and (c) finding ways through gaps in support. Eating emerged as a disrupted, emotionally charged, yet agentic act requiring sensitive, individualized approaches. Thirteen evidence-informed recommendations were developed to guide clinical application. These emphasize early nutritional screening, dietetic support, flexible meal options, respectful family involvement, and psychosocially attuned care. Future research should codevelop and evaluate tailored interventions that address AYAs' embodied, emotional, and social needs to improve eating-related quality of life during cancer treatment.

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PubMed2026

Artificial Intelligence for Diagnosing Meibomian Gland Dysfunction: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies.

PURPOSE: To identify, appraise, and synthesize the performance of artificial intelligence-based meibography reading as compared with human graders in diagnosing meibomian gland dysfunction. METHODS: We followed Cochrane methodology and reporting guidelines for diagnostic test accuracy reviews. To assess potential risk of bias and applicability, we used a modified Quality Assessment of Diagnostic Accuracy Studies-2 checklist. We applied bivariate logistic models to estimate summary sensitivity and specificity when appropriate and used the GRADE framework to rate the certainty of the evidence. RESULTS: We identified 14 eligible studies involving 5511 predominantly middle-aged participants (average age: 27-55 years) who were primarily female (≥54.5%). A total of 18,926 meibography images were obtained through noncontact infrared (11 studies) or in vivo confocal microscopy (three studies). Two studies reported external validation of deep learning models, 12 reported internally validated models, and one reported both. All but one study had high risk of bias in at least one domain; 12 studies raised high or intermediate concern about applicability. Based on three external evaluations, the summary sensitivity and specificity for diagnosing meibomian gland dysfunction from normal glands were 97.5% (95% confidence interval: 77.5%-99.8%) and 85.5% (95% confidence interval: 47.3%-97.5%). Sources of heterogeneity in internally validated models included study population, case mix, and others. The overall evidence was very low to low certainty because of imprecision, high risk of bias, and concerns about applicability. CONCLUSIONS: Artificial intelligence-based meibography grading appears less accurate than human graders. Future studies should adopt rigorous designs, including a more diverse participant pool (or image set), and external validation.

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PubMed2026

How AI-supported intelligent systems support infection prevention and control training in healthcare: A systematic review of educational functions and outcomes.

AIMS: Artificial intelligence (AI)-supported intelligent systems have been increasingly incorporated into infection prevention and control (IPC) education and training, primarily to support the monitoring of observable behaviors and the provision of feedback. However, existing evidence has focused largely on short-term compliance outcomes, with limited synthesis of the educational role of AI-supported intelligent systems in supporting sustained IPC competence. This systematic review examined how AI-supported intelligent systems have been designed and used to support IPC education and training, with a focus on system characteristics, educational functions, and reported outcomes. DESIGN: A systematic literature search was conducted across the PubMed/MEDLINE, Embase, Cochrane, and CINAHL databases. DATA SOURCES: A total of 18 studies met the inclusion criteria. Findings were qualitatively synthesized according to system design characteristics, educational functions, and outcome domains. REVIEW METHODS: Methodological quality was appraised using the Mixed Methods Appraisal Tool. RESULTS: Most AI-supported intelligent systems focused on hand hygiene and relied on fully automated monitoring systems to capture behaviors and provide performance feedback. Educational functions were predominantly limited to performance assessment, automated feedback, and reminders. Outcomes were mainly measured using compliance or performance metrics, whereas sustained behavioral change and decision quality were rarely assessed. CONCLUSIONS: AI-supported intelligent systems have been used primarily to reinforce short-term IPC performance and compliance. However, their current applications for supporting sustained competence over time remain limited. The findings of this review suggest that AI-supported intelligent systems may serve as maintenance-oriented educational support by extending learning beyond initial instruction through repeated practice and feedback. Future research should prioritize outcome measures that capture the durability of performance and decision-making processes to better align AI-supported intelligent systems used in IPC education and training with the educational demands of clinical practice.

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PubMed2026

Perspectives of participating neurologists and study nurses - Mixed-methods process evaluation of a web-based program for relapse management in multiple sclerosis (POWER@M2).

BACKGROUND: Relapsing-remitting multiple sclerosis is a chronic inflammatory disease of the central nervous system and the leading cause of disability in young adults. In Germany, 90% of relapses are treated with high-dose intravenous glucocorticoids, despite limited evidence for long-term benefit and international preference for oral administration. Time constraints often hinder informed decision-making. The multicentre Randomized Controlled Trial (RCT) POWER@MS2 (N = 160, 2020-2023), conducted at 18 German MS-centres, aimed to promote self-determined relapse management through a complex intervention (dialogue-based decision aid, nurse-led webinar, online-chat). OBJECTIVE: While RCTs demonstrate effectiveness, process evaluations are essential to understand implementation, mechanisms of impact and contextual factors. This study explored healthcare professionals' experiences and attitudes toward implementing relapse self-management and self-medication in clinical practice. METHODS: A mixed-methods process evaluation followed the UK Medical Research Council- framework. Quantitative data were collected via validated questionnaires at up to three time points and analysed descriptively. Interview guides were developed based on these results. Qualitative data from neurologist and study nurse interviews were thematically analysed. Results were triangulated using a joint display. RESULTS: Data were collected from 55 neurologists and 17 study nurses (quantitative) and from 7 neurologists and 4 nurses (qualitative) (2020-2024). Most neurologists opposed routine steroid use, reserving it for severe relapses. Some voiced concerns about self-management, but informed patients were generally viewed as capable of safe self-medication. Study nurses gave mixed feedback on the intervention, citing overload and improved guidance. CONCLUSION: Clinicians showed openness toward implementing the intervention. Enhancing accessibility and addressing specific concerns may support broader adoption.

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PubMed2026

Comparative phylogenomics and transcriptional regulatory networks of AQPs, HSPs, and LEA proteins in salt-stressed Portulaca oleracea.

Soil salinization severely threatens global food security, necessitating systematic investigations of halophytes like Portulaca oleracea to decode the molecular mechanisms of environmental resilience. Utilizing an integrated framework of deep learning-based genome annotation (58,817 predicted genes; 96.5% BUSCO completeness), multi-tissue RNA-Seq, phylogenomics, and gene regulatory network (GRN) inference, the synergistic orchestration of 78 aquaporins (AQPs), 525 heat shock proteins (HSPs), and 119 late embryogenesis abundant (LEA) proteins was elucidated. The active transcriptome, encompassing 39,065 expressed loci, revealed a systemic growth-defense trade-off. Tissues displayed distinct adaptive mechanisms: leaves modulated intracellular water balance via specialized AQPs, whereas adult roots maintained proteostasis through robust HSP20/HSP70 induction. Phylogenomic clustering across 154 species demonstrated that salinity tolerance constitutes an evolutionary mosaic, identifying 81 halophyte-exclusive orthogroups and 1129 species-specific clusters. Comparative topology across six independent GRNs (4.2M-5.3 M edges) unmasked a highly modular transcriptional reprogramming strategy governed by a core apparatus of 22 stress-exclusive regulators, with functional enrichment heavily prioritizing protein dimerization and chromatin remodeling. Theoretically, the distinct convergence of Trihelix transcription factors with guard cell differentiation pathways offers a candidate transcriptomic framework to explain the plant's characteristic C4-CAM photosynthetic plasticity under severe osmotic pressure. Practically, these evolutionary blueprints and specific master switches transcend single-gene transgenic limitations. Utilizing these root-sustained and stress-inducible targets under localized promoters provides a naturally optimized, network-level precision engineering roadmap to transfer robust, compartmentalized halotolerance to sensitive glycophytic crops.

Gene Regulatory Networks↗

PubMed2026

Mixed Methods Research on Family Caregiving for Stroke Survivors: A Methodological Systematic Review.

AIM: To examine how mixed methods research has been applied in studies of family caregiving for stroke survivors, focusing on key methodological components (rationale, design types, integration strategies, and use of joint displays). DESIGN: Methodological systematic review. METHODS: A systematic search of five databases yielded 17 studies. The extraction focused on mixed methods features (rationale, design, integration, joint displays), and quality was appraised using the Mixed Methods Appraisal Tool. DATA SOURCES: PubMed, CINAHL, Scopus, Web of Science, and PsycINFO were searched for relevant studies published from 2010 to 2025. RESULTS: The included studies addressed topics such as caregiver burden, coping, resilience, and intervention outcomes. Convergent and explanatory sequential designs predominated. Complementarity was the most frequent rationale for mixing methods. Integration occurred mainly through merging, with fewer instances of connecting or building. Three studies included joint displays to integrate the results. CONCLUSION: Mixed methods research is increasingly applied in family caregiving. To advance the field, researchers should strengthen integration during analysis and results and improve transparency in reporting key design features. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Strengthening methodological rigour in mixed methods studies on stroke caregiving will improve the evidence base for nursing practice. Intentional and meaningful integration of qualitative and quantitative evidence can better inform effective interventions and support programs, ultimately enhancing care for stroke survivors and their families. IMPACT: This review evaluates how mixed methods research is applied in family caregiving studies. It identifies significant methodological gaps, including unclear reporting of design and limited use of advanced integration techniques. The recommendations provide practical guidance for researchers to improve reporting and integration, yielding richer evidence to inform interventions and policies that support family caregivers. REPORTING METHOD: The review followed the PRISMA 2021 guidelines for transparent reporting of systematic reviews. PATIENT OR PUBLIC CONTRIBUTION: No patient or public involvement.

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PubMed2026

Comparative safety of lipid-lowering drugs alone or in combination: insights from a systematic review and network meta-analysis.

BACKGROUND AND AIMS: Although the safety profile of lipid-lowering therapies (LLTs) is known, there are no comprehensive comparative assessments. We aimed to compare the risk of muscle-related events, diabetes, liver dysfunction, and cognitive disorders among LLTs through a network meta-analysis. METHODS AND RESULTS: Databases were searched from inception to May 2025. Eligible studies included adult patients, using statins, ezetimibe, PCSK9 monoclonal antibodies (PCSK9mAbs), inclisiran, bempedoic acid, or their combinations as intervention, reporting the information about any of the selected adverse events, a total sample size of ≥200 subjects, and had ≥1 month of intervention. Pooled estimates were assessed by fixed effects model within a frequentist setting. Pooled relative risks (RR) and their 95% confidence interval were estimated. A total of 303,397 subjects from 153 RCTs were included. Bempedoic acid ranked the lowest risk of myalgia (vs PCSK9mAbs, RR 0.80 [0.69, 0.93]). PCSK9mAbs were associated with lower incidence of creatine kinase (CK) elevation, diabetes, and liver dysfunction comparing to statins (statins vs PCSK9mAbs, RR 1.44 [1.14, 1.81], RR 1.13 [1.05, 1.22], and RR 1.38 [1.17, 1.62], respectively). In terms of muscle-related events and cognitive disorders, no significant risk differences were found among treatments and their combinations. CONCLUSIONS: PCSK9mAbs appear to have a more favourable safety profile regarding the risk of CK elevation, diabetes, and liver dysfunction. Bempedoic acid seem to be a better choice for subjects with high risk of myalgia. This information can be valuable when selecting therapy for specific patient subgroups at higher risk of certain adverse events.

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PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

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PubMed2026

Development, feasibility, acceptability, and preliminary impact of NutriSOS®: A behavioral mobile app to promote sustainable diets.

The primary objective of this study was to describe the development of the NutriSOS® app and to evaluate its feasibility and acceptability for its use in the NutriSOS® Randomized Controlled Trial (RCT) to promote sustainable diets. A secondary objective was to explore preliminary changes in dietary and physical activity behaviors and environmental impact following app use. The NutriSOS® app integrates personalized dietary advice, educational content, self-monitoring, and social interaction features. A single-arm, pre-post pilot study was conducted in 37 young Mexican adults over four weeks. Feasibility, acceptability, quality, and usability were assessed using online surveys, alongside exploratory changes in dietary and physical activity behaviors, environmental indicators, and their association with perceived behavioral determinants. Feasibility and acceptability were high overall, with favorable responses reaching up to 100% in key components such as the nutritional guide and learning modules, and above 90% for messaging, registration, and design. Greater variability was observed in some sections, particularly the 24-h recall (41-86%). Reductions in red and processed meat and ultra-processed food consumption were observed (from 3 to 1 times/week, p < 0.01), with ∼60% decreases in their related environmental footprints (p < 0.01) and favorable self-reported behavioral determinants (p < 0.0001). Physical activity type and intensity changed (p < 0.05). These findings support NutriSOS® as a feasible and acceptable tool, while highlighting areas for refinement, particularly those related to the time and effort required for data entry, prior to its implementation in the NutriSOS® RCT, in which its effectiveness will be formally evaluated.

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PubMed2026

Development and Crossover Evaluation of an Artificial Intelligence-Assisted System for Solid Pancreatic Lesion Detection and Pancreatic Parenchyma Recognition in Endoscopic Ultrasonography (With Video).

BACKGROUND AND STUDY AIMS: Pancreatobiliary endoscopic ultrasonography (EUS) is technically demanding, and supervised training opportunities are limited. We developed an artificial intelligence (AI) overlay system for detecting solid pancreatic lesions (SPL) and recognizing pancreatic parenchyma (PP) and evaluated its effect on reader performance. PATIENTS AND METHODS: Across six centers, two deep learning-based models were trained using expert-annotated EUS frames. We then conducted a randomized, two-sequence, two-period crossover reader study in which eight endosonographers (five novices and three experts) interpreted image sets with and without AI assistance. The primary endpoint was superiority of sensitivity for SPL detection among novices; key secondary endpoints included specificity and PP recognition. RESULTS: From 118 patients, 120 SPL-positive/negative image sets and 160 PP-positive/negative image sets were constructed. Among novices, AI assistance improved SPL detection sensitivity (88.7% vs. 76.8%, p < 0.001) and accuracy (86.4% vs. 78.7%), while specificity met the predefined noninferiority criterion (84.2% vs. 80.5%, p < 0.001). For PP recognition, sensitivity increased numerically (86.3% vs. 83.3%) but did not meet the predefined superiority criterion (p = 0.095); specificity met the noninferiority criterion (87.8% vs. 81.0%), and accuracy increased from 82.1% to 87.0%. Among experts, sensitivity was maintained for both tasks, whereas specificity increased with AI assistance. CONCLUSIONS: AI assistance improved SPL detection among novice endosonographers. For PP recognition, sensitivity increased without reaching statistical superiority, whereas specificity met the predefined noninferiority criterion. These findings support a potential adjunctive role for AI in EUS interpretation.

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PubMed2026

Diagnostic communication in functional neurological disorder: A systematic review and meta-analysis of patient acceptance and clinical outcomes.

OBJECTIVES: Diagnostic disclosure is a key therapeutic moment in Functional Neurological Disorder (FND). This systematic review aimed to evaluate quantitative evidence on diagnostic acceptance, understanding, satisfaction, symptom outcomes, and healthcare utilisation following diagnostic disclosure in FND, and to conduct a meta-analysis of diagnostic acceptance. METHODS: Systematic searches of PubMed, Scopus, PsycINFO, and Web of Science identified quantitative studies in adults with FND. Screening followed predefined inclusion criteria. Data were extracted using a structured template and risk of bias was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis of proportions was conducted using the Freeman-Tukey transformation. RESULTS: Fifteen studies were included, four of which contributed to the meta-analysis (n = 481). Reported diagnostic acceptance rates ranged from 38.7% to 90%, although the timing and method of assessment varied across studies. Pooled acceptance was 0.68 (95% CI 0.44-0.88), with substantial heterogeneity. Structured or reinforced communication was frequently associated with improved understanding and satisfaction, although its superiority for diagnostic acceptance was not established. In some studies, diagnostic acceptance was associated with more favourable clinical outcomes, although findings were inconsistent. Some studies reported reductions in healthcare utilisation or costs following satisfactory diagnostic explanation, whereas others found no sustained overall reduction. CONCLUSIONS: Diagnostic communication in FND is associated with differences in acceptance, understanding, and downstream clinical and healthcare outcomes. Approximately two-thirds of patients were reported as accepting the diagnosis following disclosure, although the timing and method of assessment varied substantially across studies. Empathic and evidence-informed communication may enhance understanding and engagement, although its effects on healthcare use and recovery remain uncertain. PRACTICE IMPLICATIONS: Diagnostic disclosure should be delivered clearly, empathically, and with reinforcement over time. Written information, reputable educational resources, and opportunities for follow-up clarification may support patient understanding and engagement, although stronger comparative evidence is needed.

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PubMed2026

The musculoskeletal pain literacy questionnaire (MSK-PLq) - Part 1: Development of a preliminary version through a systematic review and Delphi consensus.

OBJECTIVE: Chronic musculoskeletal (MSK) pain is a leading cause of disability worldwide, and self-management is a first-line approach recommended by international clinical guidelines. Access to evidence-based information that enhances health literacy may support patients' engagement in their self-management and treatment decision-making, potentially reducing disease burden and pain. However, no tool currently exists to assess health literacy specifically in MSK pain. This study aimed to develop and describe the preliminary version of a knowledge-based questionnaire to evaluate MSK pain literacy, the Musculoskeletal Pain-Literacy questionnaire (MSK-PLq). METHODS: A systematic literature review identified existing health literacy instruments and generated a preliminary list of domains. A two-round Delphi study with 22 panellists (19 experts and three people living with chronic MSK pain), followed by consensus meetings, was used to refine domains and items (≥70% agreement). Readability was assessed using the Flesch Reading Ease (FRE) score and three stakeholders were consulted to review the questionnaire for comprehensibility, clarity, and face validity. RESULTS: Six domains were retained (Understand, Access, Appraise, Apply, Digital, Beliefs), comprising 20 items in the preliminary version of MSK-PLq. Readability was acceptable (mean FRE 74, indicating fairly easy reading), and subject feedback supported the questionnaire's clarity and face validity. CONCLUSIONS: The preliminary version of the MSK-PLq is proposed as the first knowledge-based tool to assess functional, interactive, and critical aspects of MSK pain literacy. It may have applications in clinical practice, research, education, and digital health, by informing tailored patient education and supporting self-management strategies, although further psychometric validation is required.

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PubMed2026

Post-intervention effectiveness of a computerized personalized cognitive stimulation program adapted according to cognitive reserve in older adults without cognitive impairment in Primary Care: A randomized clinical trial.

BACKGROUND: Cognitive reserve may influence responsiveness to cognitive interventions, yet it is rarely used to tailor computerized stimulation. OBJECTIVE: To evaluate the effectiveness of a computerized cognitive stimulation program personalized according to cognitive reserve on cognition, reserve-related activities, and digital competence in community-dwelling older adults without cognitive impairment in Primary Care. METHODS: In this randomized clinical trial, 102 adults aged ≥65 years with normal cognitive performance were recruited from three primary care centers in Zaragoza, Spain, and stratified by cognitive reserve level before random allocation to intervention or control. The intervention comprised digital literacy sessions followed by 8 weeks of home-based computerized cognitive stimulation tailored to participants' cognitive reserve profiles and life history. Controls received a single group-based health education session focused on maintaining everyday cognitive activity. Outcomes were assessed at baseline and post-intervention using global cognition (MEC-35), the Cognitive Reserve Questionnaire, the Mobile Device Proficiency Questionnaire-16, and domain-specific neuropsychological tests. A total of 100 participants completed the final evaluation and were included in complete-case analyses. RESULTS: Compared with controls, the intervention group showed greater adjusted post-intervention improvements in global cognition (MEC-35 between-group difference: 1.8 points) and several cognitive measures, including temporal orientation, calculation, attention, praxis, verbal fluency, processing speed, executive functions, and verbal learning. CRQ scores and digital competence also improved, with small-to-large effect sizes. CONCLUSIONS: A computerized cognitive stimulation program adapted according to cognitive reserve appears feasible in Primary Care and may improve cognition, engagement in reserve-related activities, and digital competence in older adults without cognitive impairment.

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PubMed2026

Age at menopause and subjective cognitive symptoms predict digital cognitive outcomes at the gynecological Well-Woman visit.

INTRODUCTION: Women are at increased risk for Alzheimer's Disease (AD). Growing evidence suggests that the menopausal transition may represent a vulnerable window for development of AD-related pathology. Yet, women are diagnosed with AD later than men. Conducting routine cognitive screenings and integrating information about both cognitive symptoms and age at menopause may help address sex-based disparities in detection and prevention. This study investigated whether subjective cognitive symptoms, in combination with age at menopause, were associated with performance on a digital cognitive task in postmenopausal women. METHODS: 183 postmenopausal women (mean age = 63.8, range = 45-85) were recruited after their Well-Woman visit. Participants completed the Screener for Cognitive Problems in Everyday Life (SCoPE) to assess subjective cognitive symptoms, followed by a sensitive measure of objective cognition: the Linus Health Digital Clock and Recall (DCR™). Information was also collected on age at menopause. We examined associations of subjective cognitive symptoms and age at menopause with digital cognitive performance, adjusting for age, education and depression. Model fit was evaluated using adjusted R2, AIC, and BIC. RESULTS: 48.1% of women reported one or more cognitive symptoms on the SCoPE. On objective testing, 73.2% scored in the normal range, 20.8% in the borderline range, and 6.0% in the impaired range. SCoPE total score was negatively associated with objective cognitive performance in adjusted models (B = -.12, p = .03). Age at menopause showed a significant quadratic association with cognitive performance (B = -0.006, p<.001). SCoPE total was not associated with DCR subtests, while age at menopause predicted both Delayed Recall and Clock Drawing. CONCLUSION: Subjective cognitive symptoms and age at menopause were associated with lower performance on a sensitive, objective cognitive test. Findings support routine cognitive screening and suggest that subjective cognitive symptoms as well as age at menopause are associated with cognitive function.

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PubMed2026

A framework for delivering real-time, instrument-relative navigation in transoral robotic surgery.

Transoral robotic surgery (TORS) is a minimally invasive, inside-out technique that, compared with traditional open approaches, provides fewer post-operative complications, shorter hospital stays, and improved survival for early-stage head and neck cancer. However, TORS is limited by its steep learning curve and poor visualization of deep tumor margins. This randomized crossover study evaluated a surgical navigation system's potential to enhance accuracy and user experience with real-time, instrument-relative feedback. Seven Teflon beads (d = 2.381 mm) were embedded at the tongue base of a porcine pharynx-and-larynx model. Tongue blade compression and retraction were applied to the model to mimic intraoperative tissue deformation, reproducing the anatomical shifts that occur relative to preoperative imaging. Eight participants used the da Vinci Surgical system to localize the beads by placing pins under two conditions: (a) preoperative computed tomography with no navigation; (b) model-based visual navigation with quantitative instrument-to-target metrics. Surgical accuracy was determined by calculating the target localization error (TLE, pin-to-bead Euclidean distance) and the angular error (AE, pin axis trajectory to bead). Accounting for training level and bead depth, surgical navigation reduced TLE by 5.44 mm (95% CI, 4.02-6.86 mm; p = 2.00e-11) and AE by 8.47 degrees (95% CI, 6.21-10.72 degrees; p = 5.17e-11). Impressions of the system were generally favorable using a 5-point Likert survey and task duration (p = 0.26) or cognitive workload via the NASA-Task Load Index (p = 0.22) were not significantly affected. The navigation system demonstrated translational promise, offering improved target localization accuracy and more consistent performance across experience levels, two critical determinants of surgical quality in TORS.

Robotic Surgical Procedures↗

PubMed2026

Executive function in alcohol use disorder with low psychiatric comorbidity: Comparison with a non-clinical sample and predictive value for treatment outcome.

BACKGROUND: Executive functions (EF) encompass abilities such as planning, decision-making, and inhibitory control, critical for learning, establishing and maintaining behavioral change. The association between alcohol use disorder (AUD) and impairments in EF are well established. However, prior research is dominated by studies on convenience samples including individuals with severe AUD with high levels of psychiatric comorbidity, which limits generalizability. The present study therefore aimed to investigate the degree of impairment and predictive ability of EF, on alcohol consumption, among individuals with moderate AUD with low levels of psychiatric comorbidity. METHODS: Adults with moderate AUD (n = 147) were recruited at three specialized addiction outpatient clinics in Stockholm, to a randomized controlled trial investigating the efficacy of two psychological treatments. Participants underwent neuropsychological testing before treatment. Eight tests from the CANTAB® battery were administered at baseline, assessing mental flexibility, sustained attention, visuospatial working memory, response inhibition, and delay discounting. Assessments of alcohol use and related symptoms were conducted at baseline, the 12- and 26-weeks follow-up. A non-clinical reference sample (n = 72) completed corresponding CANTAB® tests. The two groups were compared regarding EF using descriptive statistics and t-tests, and the predictive value of EF for reduction in alcohol consumption, was investigated using multiple regression models. RESULTS: Individuals with AUD did not perform worse on any of the tests on executive function (CANTAB®) as compared to the non-clinical reference sample. Measures of EF were not significant predictors for reduction in alcohol use for the 12-week, or the 26-week follow-up. CONCLUSIONS: EFs were not impaired and were not a clinically relevant predictor of treatment outcomes in this population with AUD. Future research on EF as a predictor in AUD treatment, needs to corroborate the present findings, and include other populations, e.g., with different socio-economic backgrounds and by including other methodologies for measuring EF.

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PubMed2026

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n = 24) and direct mediator (n = 22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD = 1.49, 95% CI [0.55,2.43], p = 0.002) and skills (SMD = 0.66, 95% CI [0.02,1.31], p = 0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

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