SEARCH · Search PubMed

Results for “Dental Prosthesis, Implant-Supported”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,037 records · Page 22Linked to original sources

PubMed2026

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

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

Robotic Surgical Procedures↗

PubMed2026

ARR1 and ARR12 negatively regulate arsenic stress tolerance by controlling flavonoid metabolism in Arabidopsis.

ARR1/12-mediated cytokinin signaling negatively regulates the accumulation of glycosylated flavonoids, thereby increasing plant susceptibility to As(III) stress. Cytokinins negatively regulate arsenic stress tolerance in plants through cytokinin-signaling type-B Arabidopsis response regulators (B-ARRs), specifically ARR1 and ARR12. However, the mechanism by which cytokinin signaling regulates plant metabolite dynamics, particularly antioxidant flavonoids, in response to arsenic toxicity remains largely unknown. Here, we hypothesized that ARR1/12-mediated cytokinin signaling modulates flavonoid metabolism to regulate arsenite [As(III)] tolerance. By comparing the global metabolic changes in roots of the arr1 12 double mutant (rD) and wild-type (WT) plants, we found that As(III) stress globally reduced metabolite abundance in WT roots. Importantly, the rD mutant accumulated significantly more flavonoids, most in glycosylated forms, than WT under As(III) exposure, which was supported by the specific upregulation of UDP-glycosyltransferase genes involved in flavonoid glycosylation. Accordingly, exogenous application of the glycosylated quercitrin-enhanced As(III) tolerance in WT roots, strengthening that the increase of glycosylated flavonoids in rD roots was beneficial for plant survival under As(III) exposure. Our data collectively strongly support that the increased glycosylation of flavonoids in the rD mutant improves their antioxidant functionality, thereby enhancing the As(III) stress tolerance. This study provides a new insight into the negative role of cytokinin signaling in repressing glycosylated flavonoid accumulation, causing increased susceptibility of plants to As(III) stress. Manipulation of cytokinin signaling or flavonoid glycosylation is, therefore, a promising approach for heavy metal stress mitigation in crops.

Arabidopsis↗

PubMed2026

Understanding psychosocial adjustment in military-to-civilian transition: A latent profile analysis of ex-serving Australian Defence Force members.

Military-to-civilian transition is a critical life stage that can expose veterans to elevated risks of psychological distress, social difficulties, and reduced wellbeing. Although psychosocial factors are central to successful reintegration, little is known about distinct patterns of needs among ex-serving Australian Defence Force (ADF) members. This study used latent profile analysis (LPA) to identify psychosocial needs profiles across five domains of the Military-Civilian Adjustment and Reintegration Measure (M-CARM) in a sample of 725 ex-serving ADF members. The optimal three-class solution identified: a Low Adjustment Need (LAN) group (20.7%) reporting minimal reintegration challenges; a Cultural Adjustment Need (CAN) group (42.9%) characterized by cultural adaptation difficulties, particularly beliefs about civilians and regimentation; and a Cultural and Psychological Need (CPN) group (36.4%) showing broader challenges across beliefs about civilians, purpose and connection, regimentation, and resentment and regret. The CAN group was more likely to be male, have lower educational attainment, and have no combat deployment history. The CPN group was similarly male dominated with lower education, and was additionally characterized by Navy service, unemployment or not being in the labor force, and medical discharge. Compared with the LAN group, both CAN and CPN groups reported higher levels of depression, anxiety, posttraumatic stress, and nightmare distress, as well as poorer quality of life and greater functional impairment. These findings highlight persistent reintegration challenges among veterans and support the need for stratified support models, ranging from psychoeducation to intensive multidisciplinary care, to better address diverse psychosocial needs of ex-serving ADF members.

Australian defense force↗

PubMed2026

Teacher- Versus Video-Delivered Classroom Activity Breaks and Student Physical Activity: The PAAC-3 Trial.

BACKGROUND: Classroom activity breaks may increase moderate-to-vigorous physical activity (MVPA); however, few studies have compared teacher and video-delivered approaches under real-world conditions. METHODS: In this cluster randomized trial, 11 elementary schools were assigned to teacher-delivered (PAAC-T; 5 schools, 192 students) or video-delivered (PAAC-V; 6 schools, 276 students) classroom activity breaks across one academic year. Teachers were trained to deliver two 10-min breaks daily. Intervention delivery was tracked via a web-based platform, and classroom MVPA was assessed using accelerometers at baseline and follow-up. RESULTS: Implementation fidelity was low and highly variable, but comparable between PAAC-T (42.3 ± 57.1 activity breaks/teacher/year) and PAAC-V (39.2 ± 33.9; p = 0.96), with teachers delivering ∼50% of the intended daily activity. Classroom MVPA increased significantly in both groups (PAAC-T: 9.8 ± 15.9; PAAC-V: 9.1 ± 15.3 min/day; p < 0.001), with no intervention arm-by-time interaction (p = 0.43). IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY: Classroom physical activity breaks may increase student MVPA, but effectiveness in elementary schools appears to depend on implementation fidelity, administrative support, and equitable system-level infrastructure. CONCLUSIONS: Modest increases in classroom MVPA were observed across both delivery formats, although low and variable implementation fidelity limited conclusions regarding effectiveness and highlighted the need for stronger implementation supports. TRIAL REGISTRATION: NCT03493139.

Humans↗

PubMed2026

Effect of a digitally augmented general health promotion intervention on abstinence from health-risk behaviors among emergency department discharge patients: A randomized controlled trial.

BACKGROUND: Noncommunicable diseases (NCDs) are the leading global cause of death and are driven by modifiable behaviors, such as tobacco use, harmful alcohol consumption, unhealthy diet, and physical inactivity. Recognizing that emergency department (ED) visits represent a unique opportunity to promote behavior change, this trial evaluated a digitally augmented, theory based general health promotion approach, combining a brief telephone-based intervention with mobile instant messaging support, to help discharged ED patients abstain from health risk behaviors. METHODS AND FINDINGS: This assessor-blinded randomized controlled trial was conducted in a major public hospital ED in Hong Kong. Adults (18-65 years) triaged as semi-urgent or non-urgent and with ≥1 health-risk behavior and smartphone access were randomized to receive a digitally augmented, theory‑based general health‑promotion intervention consisting of a brief telephone‑based AWARD‑model intervention (Ask, Warn, Advise, Refer, and Do-it-again) followed by weekly WhatsApp or WeChat messages for 6 months, or to a control group receiving brief telephone advice only. The primary outcome was self-report abstinence from ≥1 health-risk behavior at 6 months; secondary outcomes included the proportion of participants who achieved self-reported abstinence from ≥1 health-risk behavior at 12 months and reduction in the number of behaviors at 6 and 12 months. Of the 2,134 screened patients, 572 were enrolled (286 per group). At 6 months, 30.1% of the intervention participants versus 19.9% of the controls achieved self-reported abstinence (RR = 1.51; 95% CI, 1.13-2.02; P = 0.006). The intervention also significantly increased the likelihood of fewer risky behaviors at 6 (RR = 1.54; P = 0.01) and 12 (RR = 1.48; P = 0.02) months. Physical inactivity showed the greatest improvement at 6 months (31.7% versus 16.2%; P < 0.001). The effects attenuated after cessation of booster messaging. Limitations include reliance on self-reported outcomes, the single-center study design, and loss to follow-up, which may have affected the generalizability of the results. CONCLUSIONS: A digitally augmented, theory-based general health promotion strategy delivered at ED discharge through brief telephone intervention and mobile instant messaging support demonstrated short-term benefits in promoting self-reported abstinence and reducing health-risk behaviors at 6 months. However, the absence of a sustained effect at 12 months suggests that extended support or maintenance strategies may be required to maintain these improvements over time. Multicenter trials with longer follow-up are warranted to evaluate long-term effectiveness. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (Registration No: NCT06077565).

Humans↗

PubMed2026

Perinatal depression, maternal thyroid status and fetus/infant health and development: A systematic review.

BACKGROUND: Thyroid hormones are known to influence both maternal depression and child developmental outcomes, while maternal depression independently affects child outcomes. The potential interaction between thyroid dysfunction and depression in shaping child development remains insufficiently explored. The present study addresses such interplay. METHODS: Following PRISMA 2020 and JBI guidelines, three databases were searched through December 2025 for primary studies on maternal thyroid status, perinatal depression, and child development. Risk of bias (RoB) was assessed using validated tools. Due to clinical and methodological heterogeneity, data were synthesized narratively following SWiM guidelines. RESULTS: Eleven studies were included. Beyond independent risks for preterm birth and behavioral problems, limited evidence supports a synergistic model, while most studies likely reflect the simple co-occurrence of risks. Maternal thyroid peroxidase antibodies (TPO-Ab) were associated with child externalizing problems exclusively in the presence of clinical depression. High depressive symptoms also attenuated the cognitive benefits of prenatal iodine supplementation. Thyroid status appears to function as a risk moderator rather than a mediator. However, 50% of observational studies presented high RoB, primarily due to participant attrition. CONCLUSION: Findings are still scarce to support a synergistic risk model where specific maternal thyroid parameters (i.e. thyroid autoimmunity and iodine status) may moderate the impact of depressive symptoms on child development. Despite the high RoB in half of the studies, results highlight the need for integrated screening protocols. Simultaneously assessing mental health and thyroid status may optimize risk stratification for high-risk mother-infant dyads.

Female↗

PubMed2026

Cytonuclear conflict and reticulate evolution in the Morelloid clade (Solanum, Solanaceae): Insights from genome skimming and network Phylogenomics.

The Morelloid clade (black nightshades) is one of the most strongly supported clades within the megadiverse Solanum genus. It comprises 76 globally distributed, non-spiny herbaceous and suffrutescent species. While often erroneously considered poisonous weeds, several species are economically important as orphan crops. The clade is closely related to tomato and potato but, due to a lack of focused breeding efforts, remains a putative reservoir of genetic diversity for crop improvement. Despite this potential, we lack fundamental knowledge on the evolution of the Morelloid clade. The group includes polyploid species with unknown parental origins-likely reflecting reticulate processes such as hybridization, introgression, and associated backcrossing events. Prior analyses have been unable to disentangle these processes, leaving the mechanisms underlying reticulate evolution in the Morelloid clade poorly understood. Here, we use genome skimming to produce a well-supported maximum likelihood plastid phylogeny from complete circularized plastomes and a coalescent-based species tree from combined Angiosperms353 and conserved ortholog set nuclear markers. Our dataset, composed of previously published data and deep genome skimming from herbarium samples, spans 26 Morelloid species. To investigate phylogenetic discordance, we used a nuclear phylogenetic network, multispecies coalescent simulations, a fused rooted nuclear chloroplast tree, and quantification of nuclear gene tree concordance. We show that incongruence between nuclear and plastid trees is pervasive and cannot be explained by incomplete lineage sorting alone. Instead, our results demonstrate that events consistent with repeated chloroplast capture have shaped the reticulate evolutionary history of the clade, especially among African polyploid and Pan-American diploid lineages.

Phylogeny↗

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

From premature adrenarche to adult metabolic risk and hyperandrogenism: a systematic review and meta-analysis.

CONTEXT: Idiopathic premature adrenarche (IPA) has been associated with a higher risk of metabolic and reproductive dysfunction, but long-term/adult outcomes remain incompletely known. OBJECTIVE: To assess the relationship between IPA and metabolic syndrome, as well as polycystic ovarian syndrome, in premenarcheal adolescent and adult women. METHODS: We conducted a systematic review and meta-analysis of observational studies reporting outcomes in females with IPA after menarche. Databases were searched through February 2025. Primary outcomes included body mass index (BMI), insulin resistance markers, and clinical and biochemical markers of hyperandrogenism. Data were pooled using random-effects models. The GRADE approach was applied to assess the certainty of evidence. RESULTS: A total of 21 studies comprising 635 females with IPA and 307 age-matched controls were included. Compared to controls, IPA individuals showed significantly higher BMI (mean difference: 1.4; CI: 1.0-1.9), fasting insulin, and homeostasis model assessment of insulin resistance, indicating persistent insulin resistance. Markers of hyperandrogenism, including Ferriman-Gallwey score, dehydroepiandrosterone sulfate, and Free androgenic index, were also elevated. Secondary analyses revealed higher triglycerides, lower high-density lipoprotein, increased leptin, and greater carotid intima-media thickness, supporting an early pattern of cardiometabolic risk. GRADE assessment rated most outcomes as low certainty. CONCLUSION: Women with a history of IPA are at increased risk of long-term insulin resistance and hyperandrogenism, with early signs of adverse cardiometabolic profiles. These findings support the need for long-term monitoring in this population.

Humans↗

PubMed2026

Smartphone Apps for Preventing Adolescent Health Problems Among Health Care Professionals: Systematic Search and Quality Assessment.

BACKGROUND: Health care professionals must consider multiple dimensions of prevention when consulting with adolescents. Identifying risky behaviors early in adolescence is crucial for reducing both morbidity and mortality. General practitioners are increasingly eager to incorporate digital tools for prevention into their consultations with adolescents; however, the relevance and clinical validity of these digital tools are not always established or well-known. Consequently, primary care professionals require guidance and support in selecting relevant mobile health (mHealth) tools. OBJECTIVE: The aim of this study is to identify relevant and useful digital apps to help primary care professionals detect at-risk adolescents across all recommended areas of prevention: orthopedics, mental health, substance abuse, risk behaviors, sexual health, vaccinations, social relationships, and nutrition. METHODS: A systematic review of smartphone apps, with an analysis of content quality, was carried out by 4 researchers using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. The App Store and Google Play Store platforms were surveyed. The inclusion criteria were as follows: free of charge, date of last update, availability in French or English, relevance of the preventive approach to adolescents, and scientific validation. Four health care professionals assessed the apps: 2 selected the apps relevant to health care professionals, then 3 analyzed these apps using the French version of the Mobile App Rating Scale (MARS-F). Intraclass correlation coefficient, model (2,1) (2-way random effects, absolute agreement, single measures); standard error of measurement; and mean absolute error were also calculated. RESULTS: A total of 976 apps were identified, 49 of which had disappeared from the platforms prior to analysis. Nine apps were retained. Seven (0.72%) were included after evaluation using the MARS-F: 2 on mental health and 5 on sexual health (including 3 on contraception only). The mean MARS-F interrater score ranged from 2.5/5 to 3.8/5. The global MARS-F score demonstrated a pooled SD of 0.60 and an intraclass correlation coefficient (2,1) of 0.0003, resulting in a calculated standard error of measurement of 0.60. The average discrepancy between raters was a mean absolute error of 0.53. CONCLUSIONS: No similar studies have been identified in the literature that specifically focus on mobile apps designed to support health care professionals in delivering preventive care to adolescents. Of the 8 areas of prevention identified as relevant for adolescents, only 3 are addressed by the apps validated through our methodology (5 focus on sexual health). Consequently, current apps are insufficient to support health care professionals in their overall preventive work with adolescents. Such a review should be conducted systematically prior to the development of any new tool to prevent duplication and channel creative efforts toward truly innovative digital solutions. Furthermore, a thorough analysis of relevant, recommended websites is essential, as these resources complement the use of mobile apps designed for health care professionals.

Humans↗

PubMed2026

Journey Mapping of the Patient Experience from Diagnosis to End of Life in Lung Cancer: A Qualitative Meta-Synthesis.

OBJECTIVES: This study aimed to systematically synthesize the lived experiences and journey narratives of lung cancer patients across disease stages, and identify key tasks and pain points during the disease course through patient journey mapping, providing evidence for comprehensive disease management throughout the patient journey. METHODS: Ten databases, including PubMed, Embase, Web of Science, Scopus, PsycINFO, CINAHL, Cochrane Library, CNKI, Wanfang, and SinoMed, were systematically searched, with a search period from database inception to August 15, 2025. The JBI Critical Appraisal Tool for qualitative studies was used to evaluate the quality of studies, and the results were integrated using a meta-aggregative approach. RESULTS: Thirteen studies were included. Based on the patient journey mapping, the lung cancer patient journey comprises four potential stages: evaluation and diagnosis, initial treatment, maintenance therapy, and end-of-life. A total of 30 themes emerged within three dimensions: tasks, emotions, and pain points. Each dimension of each stage consists of 2-3 themes. CONCLUSION: The journey of lung cancer patients is protracted and complex, characterized by stage-specific needs and challenges. Future management strategies should be tailored to these distinct phases, providing precision supportive care to optimize treatment outcomes and enhance patients' quality of life. IMPLICATIONS FOR NURSING PRACTICE: This Patient Journey Map integrates routine clinical pathways with patients' lived experiences across each stage, revealing stage-specific challenges and providing targets for tailored nursing interventions. The framework promotes multidisciplinary, digitally enabled supportive care and indicates the importance of including patients' social circles to enhance patient-centered outcomes.

Humans↗

PubMed2026

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans↗

PubMed2026

Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans↗

PubMed2025

Social Responsiveness as a Mediator in Adapted Cognitive Behavioral Therapy for Autistic Youth with Maladaptive and Interfering Anxiety.

Numerous adaptations to interventions have been included in cognitive behavioral therapy (CBT) for autistic youth. This study examines the degree to which CBT adapted to the social needs of autistic youth confers significant benefit by promoting social responsiveness. A secondary analysis was conducted on a multisite randomized clinical trial (Wood et al. in JAMA Psychiatry 77:474-483, 2020) comparing adapted CBT with standard-of-practice CBT and treatment-as-usual (TA). Autistic youth (N = 167; aged 7-13) with maladaptive and interfering anxiety participated. The adapted CBT (BIACA) uses a modular format, with an emphasis on supplementing common CBT practice elements (reframing and graded exposure) with social skill supports. The primary outcome measure was the Pediatric Anxiety Rating Scale. Social responsiveness was assessed with the Social Responsiveness Scale, Second Edition. Participants' general mental health was assessed as a secondary outcome using the Brief Problem Checklist. Mediation was tested using the SPSS PROCESS macro. Analyses suggested that the effect of adapted CBT on anxiety was mediated by its effects on social responsiveness, with a statistically significant indirect effect. Youth randomly assigned to adapted CBT exhibited better overall mental health at posttreatment compared to those randomized to the other conditions, and this effect was also mediated by improved social responsiveness. CBT adapted to address some of the social needs of autistic youth may enhance mental health outcomes by supporting social responsiveness, perhaps increasing the ease and effectiveness with which some youth can navigate potentially stressful situations such as entering and participating in group activities.

Humans↗

PubMed2026

An introductory practical guide to secondary data analysis in pediatric urology.

INTRODUCTION: Secondary data analysis (SDA) has become an increasingly important approach in pediatric urology, enabling the study of long-term outcomes, care variation, and disparities in populations with chronic or congenital urologic conditions. With the growing availability of large datasets, a structured approach to designing and conducting SDA studies is increasingly relevant. OBJECTIVES: To provide an introductory, practical guide to SDA in pediatric urology by (1) summarizing commonly used data sources with representative studies, (2) outlining a stepwise approach to designing and executing SDA studies, and (3) highlighting key methodological considerations, limitations, and opportunities for future work. STUDY DESIGN: Narrative review of existing literature and commonly used datasets relevant to pediatric urology, including administrative claims, hospital encounter databases, clinical registries, electronic health record networks, and population-based surveys. RESULTS: Data sources differ in scope, clinical granularity, longitudinal follow-up, and representativeness, and each is suited to specific research questions. We present a practical workflow for SDA, including dataset selection, cohort definition, and analytic planning. Linkage across datasets can provide a more comprehensive view of care patterns and outcomes, although feasibility is influenced by legal, technical, and data-quality constraints. DISCUSSION: SDA enables population-level analyses and the study of rare conditions that are challenging to evaluate through single-center or prospective designs. However, careful cohort definition, feasibility assessment, and awareness of data limitations are essential to ensure validity and interpretability. CONCLUSION: SDA provides a scalable, cost-efficient framework for generating meaningful evidence in pediatric urology. Continued efforts to harmonize data elements, improve linkage infrastructure, and support cross-institution collaboration will enhance the quality and impact of future research. This article provides a practical framework and examples to support the design and execution of SDA studies.

Humans↗

PubMed2026

Haemodialysis Nurses' Self-Reported Cultural Competence and Responsiveness: A Cross-Sectional Survey.

BACKGROUND: People receiving in-centre haemodialysis have distinct cultural care needs and preferences, and nurses are expected to respond to these. However, haemodialysis nurses' cultural competence and responsiveness are unknown. OBJECTIVES: To examine nurses' cultural competence and responsiveness when caring for people with diverse cultural characteristics. DESIGN: An online cross-sectional survey. PARTICIPANTS: Haemodialysis nurses from Australia and New Zealand (n = 123), recruited through the Renal Society of Australasia and professional networks. MEASUREMENTS: The 25-item Cultural Competence Assessment instrument measured cultural awareness and sensitivity, and culturally responsive behaviours. Demographic characteristics were also collected. RESULTS: Of 123 complete responses, overall cultural competence was high (M = 5.09, SD = 0.76), particularly awareness and sensitivity (M = 5.76, SD = 0.53), with significantly higher scores among those who had completed cultural awareness training (p = 0.009). In contrast, culturally responsive behaviours were moderate (M = 4.53, SD = 1.23), highlighting the gap between cultural competence and responsiveness. The lowest scoring areas were documentation of patients' cultural needs (M = 3.88, SD = 2.02) and access to cultural learning resources (M = 3.02, SD = 1.75), indicating limited supports. Qualitative findings reflected practices of culture care preservation and accommodation, with themes of cultural awareness and language differences highlighting barriers related to language and resources. CONCLUSIONS: High cultural competence does not necessarily translate into culturally responsive behaviour. Organisational supports, including guidance for documenting cultural needs, cultural assessment tools and accessible learning resources, may help strengthen culturally responsive haemodialysis care.

Humans↗

PubMed2026

Effectiveness of Caregiver-Mediated Spoken Language Interventions for Children Under Five at Risk of Developmental Language Disorder: A Systematic Review and Meta-Analysis.

BACKGROUND AND AIMS: Caregiver-mediated interventions are commonly used by Speech and Language Therapists to support early language development. Developmental Language Disorder (DLD) is associated with reduced quality of life throughout the lifespan. Understanding factors that predict intervention success is essential for developing appropriate, cost-effective therapy provision for the approximately 12% of preschool children who present with early markers for Developmental Language Disorder (DLD). This systematic review and meta-analysis examined the effectiveness of caregiver-mediated spoken language interventions for under-fives at risk of DLD, and factors influencing intervention effectiveness. METHODS: A systematic review following PRISMA guidelines was conducted. Five electronic databases were searched to identify experimental studies comparing caregiver-mediated spoken language interventions to control conditions in under-fives presenting with risk factors for DLD. Risk factors included prematurity, socioeconomic factors, caregiver language development concerns, and formal or informal language screening or assessment scores. Twenty-six experimental studies with 1407 child participants were included in qualitative synthesis. Meta-analysis was performed on nine Randomised Controlled Trials involving 947 children. RESULTS: Effectiveness was examined for outcomes including child language gains, child wellbeing, inclusion and attainment. Meta-analysis indicated a significant effect of caregiver-mediated spoken language interventions on language outcomes compared to treatment-as-usual, non-language intervention or waitlist control conditions. Non-language outcomes were evaluated via qualitative synthesis. Interventions significantly improved language development trajectories for under-fives presenting with risk factors or early markers for DLD. CONCLUSION AND IMPLICATIONS: This review contributes to the growing evidence base demonstrating that caregiver-mediated interventions can positively impact language development and wellbeing outcomes for children under five at risk of DLD. These findings support the implementation of caregiver-mediated environmental language interventions in clinical practice to maximise accessibility and cost-effectiveness while delivering optimal outcomes for vulnerable populations. WHAT THIS PAPER ADDS: What is already known on this subject Previous research on caregiver-mediated spoken language interventions has highlighted gaps in the evidence regarding the impact of risk factors, demographic characteristics, dosage and intervention components on child language outcomes. Developmental Language Disorder has relatively high population prevalence, estimated at 7%. Prevalence is associated with risk factors including low household socioeconomic status (SES), prematurity and late language emergence. In contrast to its prevalence, there is low public and professional awareness of DLD and a low diagnostic rate. Therefore, a strengthened evidence base and additional insights into the factors affecting success of family-based interventions is important in order to increase the effectiveness of service provision and care planning for this underserved population. Timely and effective intervention with young children presenting with early markers for DLD has the potential to offer lifelong improvement to their wellbeing, inclusion and attainment outcomes. Recent systematic reviews of the effectiveness of caregiver-mediated language interventions had differences in population age range and diagnostic inclusion criteria. What this paper adds to existing knowledge Our review examines the effectiveness of caregiver-mediated early spoken language interventions on child language, attainment and wellbeing, and on caregiver self-efficacy and adherence to language support strategies. Our population was children under five presenting with risk factors for Developmental Language Disorder, in the absence of other neurodevelopmental or genetic conditions such as intellectual disability or autism. This review adds depth and detail to the evidence base supporting the effectiveness of caregiver-mediated spoken language interventions in improving outcomes for this population of young children, and factors that influence their success. What are the potential or actual clinical implications of this work? The high prevalence of Developmental Language Disorder, estimated at around 7% of the population, and the strong association with risk factors including low SES, prematurity and late language emergence, coupled with the low awareness of DLD and low diagnostic rate, mean that a strengthened evidence base and additional insights into the factors affecting success of family-based interventions can increase the effectiveness of service provision and care planning for this population. Timely and effective intervention in this group of young children has the potential to improve wellbeing and attainment outcomes across the lifespan. This review contributes to our understanding of how to implement cost-effective, socially valid and maximally engaging partnership working with families of young children at risk for DLD.

Humans↗

PubMed2026

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

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

Humans↗