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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

Implementation outcomes of a dementia-focused intervention for family care partners and clinicians in home hospice care.

OBJECTIVES: End-of-life care for persons living with dementia in home hospice relies heavily on coordination between family care partners (FCPs) and clinicians (e.g., hospice social workers and nurses). FCPs and clinicians have reported support and knowledge gaps in end-of-life dementia care. Interventions are needed to improve FCPs' support and clinicians' educational gaps. METHODS: A pilot randomized controlled trial was designed to examine implementation outcomes for a dementia-focused end-of-life intervention for FCPs (n = 37) and clinicians (n = 15). Data on survey completion and acceptability were collected at baseline, during 4 follow-up visits, and at the conclusion of the study. RESULTS: Twenty-eight (75%) caregivers completed the post-study survey, and 10 (27%) reported using the structured worksheet. Thirteen (87%) clinicians completed the post-training survey, 8 (53%) completed the post-study survey, and 8 (100%) used the worksheet. Clinicians (n = 8) were satisfied or highly satisfied with the instructional videos, and half (50%) used the information frequently with patients. Both groups reported the worksheet helpful, easy to use, and satisfactory, though clinicians rated helpfulness slightly higher (mean = 3.88 vs. 3.70 for FCPs). Clinicians liked the worksheet's structured guidance and the enhanced collaboration. SIGNIFICANCE OF RESULTS: This study provides preliminary evidence for implementation outcomes of a dementia-focused end-of-life intervention in home hospice. Findings suggest the intervention can be implemented in a hospice setting, with moderate worksheet uptake and perceived value among FCPs and clinicians.

Humans↗

PubMed2026

Beyond risk factors: A capacity framework for cancer survivorship research.

Cancer survivorship research has identified numerous biological, behavioral, psychosocial, health care, and structural factors that influence recovery. However, these factors are typically studied as separate determinants rather than interacting influences. This commentary proposes available survivorship capacity as a unifying framework that explains how these diverse determinants collectively shape recovery and survivorship outcomes. Concepts from geroscience, health care delivery, rehabilitation, occupational therapy, and human factors science were synthesized to develop a conceptual framework of available survivorship capacity. The framework conceptualizes recovery as a function of the capacity remaining after competing health care and life demands draw upon survivors' finite physical, cognitive, emotional, social, financial, temporal, and health care resources. It generates testable propositions for measurement, intervention research, health care delivery, and implementation science while positioning available survivorship capacity as a common mechanism linking diverse determinants of recovery and identifying actionable targets for intervention. Available capacity offers a unifying conceptual framework for understanding heterogeneity in survivorship outcomes and intervention effectiveness while generating a research agenda for future survivorship science. Measuring and strengthening survivors' available capacity, while reducing unnecessary demands, may improve engagement in care, health behaviors, and long-term recovery.

Humans↗

PubMed2026

Implementing a novel digital health platform for self-management of postmenopausal osteoporosis: A qualitative study of user experiences, perspectives and implementation outcomes.

BACKGROUND: Osteoporosis self-management requires scalable support, and digital health platforms may meet this need. This study aimed to characterise the experiences and perspectives of postmenopausal women who participated in a 12-month randomised controlled trial (RCT) of a digital voice assistant (DVA) delivered osteoporosis self-management intervention, and to assess key implementation outcomes. METHODS: This was a qualitative analysis of interviews with postmenopausal women from the intervention arm (DVA group) of the RCT. The DVA program broadcast education videos, medication reminders, home-based exercise, nutrition advice and monthly quizzes through a DVA device. Semi-structured interviews were recorded, transcribed and managed in NVivo through reflexive thematic analysis, guided by the Practical Planning for Implementation and Scale-Up and Proctor's implementation outcome taxonomy frameworks. Evidence weighting summarised participant coverage and code density. RESULTS: Twenty-two of 25 (88%) DVA group participants completed semi-structured interviews. Thematic analysis identified seven themes mapped to Proctor's implementation outcomes. Evidence weighting indicated strong support for the intervention's appropriateness and acceptability, moderate support for its adoption, fidelity, feasibility and sustainability, and limited support for costs. Participants valued clear audiovisual guidance, conversation-based interactions with natural language, and flexible home-based access to self-management. CONCLUSION: Digital health platforms for osteoporosis self-management appear feasible, acceptable and sustainable among postmenopausal women. Findings indicate that these platforms are approaching readiness for evaluation in implementation-focused settings, contingent on streamlined content, reliable delivery modalities, accessible user support, clear privacy regulations and pragmatic pricing models.

Humans↗

PubMed2026

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

Digital health interventions for diabetes management in the eastern mediterranean region: A systematic review of types and effectiveness.

AIM: The aim of this study was to systematically review and evaluate the types and effectiveness of digital health interventions used for diabetes management in the Eastern Mediterranean Region (EMRO). METHODS: This systematic review, conducted according to PRISMA guidelines, searched PubMed, Web of Science, and Scopus up to May 2025 to identify studies on digital interventions for diabetes management in EMRO countries. Methodological quality of the included studies was evaluated using the EPHPP tool, and findings were categorized by intervention type, outcome measures, and intervention effectiveness. RESULTS: A total of 46 studies were included, mainly from Iran and Saudi Arabia. Phone calls and SMS were the most common digital tools. Digital interventions significantly improved HbA1c, fasting blood sugar, and several behavioral outcomes such as physical activity, medication adherence, and self-efficacy, while effects on psychological outcomes were mixed. CONCLUSION: Digital health interventions, especially phone calls and SMS, effectively improve glycemic control and self-care behaviors, though their impact on psychological outcomes remains inconsistent.

Humans↗

PubMed2025

A Systematic Review of Help-Seeking Barriers for Racial-Ethnic Minority Caregivers Accessing Autism Diagnostic and Intervention Services.

Caregivers play an essential role in early help-seeking and intervention for children with Autism Spectrum Disorder (ASD). Caregivers, therefore, provide a crucial role in helping to address the racial and ethnic disparity identified in accessing ASD intervention and diagnostic services (Bejarano-Martín et al., Journal of Autism and Developmental Disorders 50(9), 3380-3394, 2020). Unfortunately, racial-ethnic minority caregivers of children with autism (CCA) are less likely to contact a physician or healthcare professionals about their concerns and more likely to delay their contact to have their child evaluated (Zeleke et al., Journal of Autism and Developmental Disorders 49(10), 4320-4331, 2019). However, little evidence exists to explain why such a gap exists in the help-seeking behaviors between White and racial-ethnic minority CCA. To address this knowledge gap, we conducted a systematic literature review to identify articles that have studied barriers in help-seeking for racial-ethnic minority CCA. A broad literature search across four databases was conducted (i.e., PubMed, PsycINFO, Education Resources Information Center, and Child Development and Adolescent Studies). The coding team identified 17 articles on help-seeking barriers for racial-ethnic minority CCA. A thematic analysis was used to narratively synthesize the help-seeking barriers identified across these 17 studies. Four themes emerged from our findings: logistical barriers, provider competence, ASD literacy, and cultural stigma. We also provided clinical recommendations for healthcare providers working with families with racial-ethnic minority CCA.

Humans↗

PubMed2026

Leading with Innovation: Maternal Health Transformation in New York City Health + Hospitals.

New York City's (NYC) maternal health crisis drew close attention in the late 2010s, driven by alarming data: Approximately 30 women died annually during childbirth in NYC, Black non-Hispanic women were 12 times more likely to die than white women, and more than 3,000 women experienced life-threatening birth complications each year. In response, NYC committed $12.8 million in July 2018 to reduce maternal mortality and eliminate racial disparities.NYC Health + Hospitals (H+H)-the nation's largest public health system, serving 1.1 million patients annually with roughly 15,000 births per year-became the primary vehicle for this initiative. With 80 percent of the system's deliveries covered by Medicaid and a patient population that is 51.2 percent Hispanic and 27.1 percent Black, H+H is uniquely positioned to lead the fight against maternal health inequity.Three flagship programs anchor H+H's response to the city's maternal mortality rate. The OB Simulation Program, launched in 2012 and expanded in 2018, was the first in the nation to use mannequins of color to train thousands of providers in obstetric emergencies. The Maternal Home Program, piloted at H+H's Kings County Hospital in 2019 and scaled system-wide by 2021, has served more than 10,341 patients, generating more than 33,000 referrals for social, behavioral health, and community resources. The Cardio-Obstetrics Program located at Kings County Hospital targets cardiovascular disease-the leading cause of maternal death among Black women-through screening, education, and community outreach. These programs are a health equity imperative, made more urgent by impending federal Medicaid cuts resulting from the H.R.1 One Big Beautiful Bill Act (passed on July 4, 2025).

Humans↗

PubMed2026

Effects of Family-Based Intervention for Childhood Obesity on Parental and Offspring Outcomes: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Childhood obesity is a global public health issue with strong familial and intergenerational transmission. However, existing syntheses often overlook the active role of parents and fail to assess outcomes beyond the child. This systematic review and meta-analysis specifically investigate the effects of family-based interventions, which position parents as active co-agents of change, on health outcomes for both children with obesity and their parents. METHODS: A systematic review and meta-analysis were conducted. Six databases were searched for randomized controlled trials (RCTs) targeting children with obesity and at least one family member. Primary outcomes were children's BMI z-score and parental BMI; secondary outcomes included other adiposity measures and dietary behaviors. Outcomes for both children and parents were synthesized. Subgroup analyses were conducted based on intervention characteristics. Risk of bias was assessed using RoB 2, and evidence certainty was evaluated using GRADE. RESULTS: Twenty RCTs with 1740 participants were included in the meta-analysis. The interventions demonstrated a significant reduction in children's BMI z-score. Additional benefits were observed for long-term BMI z-score and percentage of total body fat. The most effective interventions commonly integrate health education, behavioral strategies, and motivational support. Subgroup analyses indicated that interventions positioning parents as active co-participants, rather than mere supporters, yielded larger effects. However, no significant effects were found on parental BMI. CONCLUSION: This study demonstrates that family-based interventions can confer significant benefits for children with obesity. Their success hinges on strategically framing parents as active co-agents and integrating motivational strategies.

Humans↗

PubMed2026

Self-healing materials for food packaging: Design principles, activation mechanisms and implications for food safety.

Self-healing materials (SHMs), originally developed to restore mechanical integrity, have recently attracted growing interest in food packaging. By autonomously repairing physical damage, SHMs help preserve packaging integrity, barrier performance, food safety, and shelf-life during storage and transportation. This review summarizes recent advances in the design principles, activation mechanisms, material systems and food packaging applications of SHMs. Key healing strategies, including microencapsulation, dynamic covalent bond exchange, reversible non-covalent interactions and responsiveness to external stimuli such as temperature, pH, and humidity, are discussed. Representative material systems, including biopolymer-based films, hydrogels, nanocomposites, and stimuli-responsive polymers are evaluated with respect to their relevance to packaging animal-derived foods, fruits, and vegetables. Performance evaluation methods, sustainability implications, and food-contact safety concerns are addressed. Despite promising healing efficiency and mechanical resilience, challenges remain regarding production cost, food-grade safety, migration risks, trigger compatibility and stability under fluctuating environmental conditions. Future research should focus on scalable manufacturing, standardized evaluation protocols, repeated damage-healing safety assessment, regulatory compliance, and integration with intelligent packaging technologies.

Food Packaging↗

PubMed2026

Criteria for Safe Hospital Discharge in Bronchiolitis: A Systematic Review.

Bronchiolitis is the leading cause of hospital presentation and admission for infants in Australasia. We aimed to synthesise current evidence on the effect of discharge criteria for infants (aged < 12 months) who are presenting to or are admitted to hospital with bronchiolitis, to inform a binational guideline recommendation update. Systematic searches were conducted on MEDLINE, EMBASE, PubMed, Cochrane Library and CINAHL (last search 19 February 2025) for non-randomised studies evaluating hospital discharge criteria in bronchiolitis. The primary outcomes were length of stay (LOS) and readmission rates. The risk of bias (ROBINS-I) and certainty of the evidence (GRADE) were appraised, and findings were narratively synthesised. GRADE evidence-to-decision methodology, expert consensus voting and interest-holder consultation were used to finalise the recommendation update. Two retrospective observational studies were included (N = 2697) (low to very low quality), reporting on unique discharge criteria. In both studies, use of the discharge criteria was associated with a significant reduction in LOS relative to alternative protocols. There was no significant difference in readmission rates observed in either study. There was low to very low certainty evidence across outcomes due to risk of bias, indirectness and imprecision. The review findings informed a recommendation update for safe discharge criteria in the 2025 Australasian Bronchiolitis Guideline update. Updated, prescriptive discharge criteria and flow chart were developed, covering clinical stability, oxygen saturation/support, feeding difficulties, caregiver confidence and education on deterioration, social factors and follow-up. The revised criteria provide clinicians with increased certainty in decision-making in bronchiolitis, albeit with further research needed.

Humans↗

PubMed2026

Unacknowledged Burdens and Clinical Assets of BIPOC Genetic Counseling Students: Qualitative Evidence to Inform Supervision.

As the genetic counseling profession works to diversify its predominantly white workforce, understanding the experiences of Black, Indigenous, and People of Color (BIPOC) students is central to equity efforts. While BIPOC students bring invaluable cultural and linguistic diversity that improves patient care, they often navigate clinical training environments that lack diversity and psychological safety. This article draws on data from a longitudinal constructivist qualitative study to examine how racial and ethnic concordance (or lack thereof) with patients and clinical supervisors influenced the clinical training, professional development, and well-being of BIPOC genetic counseling students. Semi-structured interviews were conducted with 25 BIPOC genetic counseling students in the United States and Canada. Interviews were recorded using Zoom.us, transcribed using Rev.com, and analyzed in NVivo using reflexive thematic analysis. The analysis led to the construction of three themes: (1)Shared identity with patients is a clinical advantage: Participants leveraged their cultural and linguistic intuition to establish trust and rapport with patients; (2) Identity navigation involves cognitive and emotional labor: Participants shouldered an unacknowledged burden in managing stereotype threat, overcoming feelings of exclusion, and educating supervisors; and (3) Racial/ethnic identity shapes supervisory dynamics: Participants described BIPOC supervisors as providing identity-affirming support, while some white supervisors avoided discussions about identity or committed microaggressions. These results suggest that BIPOC genetic counseling students have clinical assets rooted in biculturalism, yet carry a burden that often goes unacknowledged of managing power imbalances and pressure to assimilate in predominantly white clinical supervision spaces. To promote equitable training, programs should implement supervisor training on culturally responsive identity broaching, establish independent, transparent mechanisms for students to report biases they encounter in clinic, and expand mentorship networks to provide additional support.

Humans↗

PubMed2026

Psychological distress and incident cardiovascular disease independent of life's essential 8: a prospective cohort study.

BACKGROUND: Although psychological stress has emerged as an important determinant of cardiovascular disease (CVD) risk, it remains excluded from the recently updated cardiovascular health (CVH) metrics, known as Life's Essential 8 (LE8). This study aimed to examine the association between psychological distress and the incidence of CVD, independent of Life's Essential 8 metrics, in a large Korean adult population. METHODS: This study included 6,410 participants from the Korean Genome and Epidemiology Study Ansan-Ansung cohort, who had no history of CVD and had complete baseline data on psychological distress and Life's Essential 8 cardiovascular health (LE8 CVH) metrics. Psychological distress was assessed using the Psychosocial Wellbeing Index Short Form (PWI-SF). CVD events were identified based on participants' self-reports of physician-diagnosed conditions: myocardial infarction, stroke, coronary artery disease, and congestive heart failure. Cox proportional hazards models were used to examine the association between PWI-SF scores and incident CVD, adjusting for age, sex, residential area, educational attainment, household income, and LE8 CVH metrics. RESULTS: During a median follow-up of 13.8 years, 500 new cases of CVD were identified. Higher PWI-SF scores were independently associated with an increased risk of CVD after adjusting for LE8 CVH metrics and other potential confounders (hazard ratio: 1.321; 95% confidence interval: 1.067-1.636; p = 0.011). CONCLUSION: These findings suggest that higher levels of psychological distress are independently associated with an increased risk of CVD, even after accounting for established LE8 CVH metrics. Incorporating psychological distress into future CVH assessments may enhance risk stratification and prevention strategies.

Humans↗

PubMed2026

Sociodemographic and clinical characteristics associated with nocturnal enuresis among children in a tertiary care center in Cairo, Egypt: A cross-sectional study.

BACKGROUND: Nocturnal enuresis (NE) is a significant pediatric health concern that warrants increased attention from healthcare providers, educators, and society. This study aimed to determine the frequency of NE among children attending a tertiary care center in Cairo, Egypt, and to explore their sociodemographic characteristics and associated factors. METHODS: A cross-sectional study was conducted among 1587 children aged 6-16 years attending a tertiary care center in Cairo from December 2022 to February 2024. Data were obtained from parents via a structured questionnaire covering sociodemographic characteristics. Sleep problems were assessed via the Children's Sleep Habits Questionnaire. The multivariate logistic regression analysis was conducted to estimate the odds ratio and identify factors associated with NE. RESULTS: The total prevalence of NE among children attending a tertiary care center was 333 (21%). Our results indicated that being female and being older were associated with a lower likelihood of NE. Low socioeconomic status (OR = 5.559; 95% CI = 1.24-24.88), stressful events (OR = 3.697; 95% CI = 1.73-7.88), a family history of NE (OR = 26.231; 95% CI = 8.617-79.85), and sleep problems (OR = 13.233; 95% CI = 6.082-28.793) were associated with increased odds of NE. Furthermore, consuming caffeinated drinks before sleep, the presence of urinary tract infections, and intestinal infestations were also associated with NE. CONCLUSION: The findings of the present study confirm the multifactorial etiology of NE and identify several associated factors. Integrating these factors into screening and management programs may improve early identification and lead to more effective, tertiary care-specific preventive and therapeutic interventions.

Humans↗

PubMed2026

Regional and statewide hysterectomy-corrected endometrial cancer incidence and five-year relative survival in Texas.

BACKGROUND: Rising endometrial cancer (EC) incidence nationwide, particularly among Hispanic women, and high prevalence of risk factors such as obesity and comorbidities in Texas, motivated us to estimate EC incidence rates (IRs) and survival by age (<50 years/ early-onset, ≥50 years/late-onset), race-ethnicity (Non-Hispanic-White [NHW], -Black [NHB], Hispanic), histology (endometrioid, non-endometrioid), and area-based socioeconomic (SES) factors across Texas Health Service Regions (HSRs). STUDY DESIGN: Between 2000 and 2019, a total of 42,571 women (20-79 years) with EC were reported from Texas within the Surveillance, Epidemiology, and End Results Program. IRs and 5-year relative survival were calculated using SEER*Stat. IRs were corrected for hysterectomy using Behavioral Risk Factor Surveillance System data. RESULTS: Statewide EC IRs rose from 38.5 (2000-2009) to 44.5 (2010-2019), with the highest increase in the Upper-South (42.6 to 53.8). Across HSRs, Upper-South consistently had higher IRs among women < 50 (13.9) and ≥ 50 years (112.7). Among those < 50 years, Hispanics had the highest IRs (12.4), predominantly endometrioid tumors, whereas in women ≥ 50 years, NHB had the highest IRs (119.2) with a large proportion of non-endometrioid tumors. IRs were higher in areas with lower poverty, and higher education, income, and urbanization. Associations with unemployment were mixed. Worse survival outcomes were observed among NHBs, non-endometrioid, advanced-stage, and lower SES. Central Texas had more favorable survival outcomes compared to other HSR. CONCLUSION: EC IRs and survival rates in Texas largely mirror national trends, with regional differences likely reflecting sociodemographic and histologic distributions.

Humans↗

PubMed2026

Loneliness and Personality: Noise- and Bias-Free True Correlations Between Loneliness and the Big Five Personality Domains.

OBJECTIVE: While loneliness is intertwined with many mental and physical health problems, its origins are not yet well understood. We sought to better understand its link to personality in a large national cohort. METHODS: Combining self- and informant ratings in multiple samples, we conducted the largest study to date to examine loneliness' true correlations (rtrues) with the Big Five personality traits, free of single-method biases and transient and random errors. RESULTS: Across three samples (Estonian-speaking, N = 20,893; Russian-speaking, N = 762; English-speaking, N = 599), we found a strong relationship between loneliness and Neuroticism (rtrue = 0.60-0.70). Loneliness also had robust but much weaker associations with Extraversion (rtrue = -0.20 to -0.30), and only weak associations (rtrue = 0.10 to -0.20) with Agreeableness, Conscientiousness, and Openness. Collectively, the Big Five accounted for over 50% of loneliness variance. In a subsample, the associations were only slightly smaller longitudinally over approximately 10 years. CONCLUSION: Overall, feeling lonely is more closely related to Neuroticism than previously understood, and the association endures over time.

Humans↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

Humans↗