Search Results (356)

Background: Population ageing and the gradual implementation of delayed retirement policies have drawn increasing attention to the lives of older adults after retirement age. Although previous studies have examined the relationship between retirement and health outcomes, limited evidence is available on whether continued workforce participation after retirement age affects healthcare utilization. Methods: Using nationally representative data from the 2018 China Health and Retirement Longitudinal Study (CHARLS), we employ negative binomial regression as the baseline model and use an instrumental variable two-stage least squares (IV-2SLS) to address endogeneity. We further conduct heterogeneity and mechanism analyses. Results: The findings reveal that workforce participation after retirement age significantly reduces healthcare utilization: post-retirement workers have 42.1% fewer outpatient visits and 49.2% fewer inpatient admissions than their fully retired counterparts. Mechanism analyses indicate that the negative effect operates primarily through tighter time constraints that crowd out care-seeking time and income fluctuations that alter health investment behaviors. Heterogeneity analyses further show that the reduction in outpatient utilization is more pronounced among males and highly educated individuals, whereas the reduction in inpatient utilization is stronger for females and those with good self-rated health. Conclusions: Workforce participation after retirement age may hinder healthcare utilization among older adults. These findings reveal an unintended consequence of delayed retirement policies and call for flexible, targeted arrangements to balance labor participation and healthcare access for older workers. Full article

This paper addresses non-steady-state scenarios in the human–robot collaborative disassembly process of retired power batteries, including component aging, ambiguous instructions, and sensor drift. In such scenarios, the robot exhibits execution robustness problems. This paper proposes a Planning Domain Definition Language (PDDL) generation framework that integrates long-term and short-term memory. The framework combines large language models with knowledge graphs as a long-term memory module for symbolic task decomposition and domain semantic rule generalization, while using meta-heuristic optimization algorithms as a short-term memory module to adapt and optimize action parameters based on real-time sensor feedback. Through this closed-loop mechanism that combines long-term memory guidance with short-term memory adaptation, the system addresses the limitation of traditional PDDL, which, when facing open, time-varying, and heterogeneous industrial disassembly scenarios, has symbolic action models that have difficulty capturing the uncertainty and unpredictable disturbances in real physical systems, limiting its practicality in complex non-steady-state scenarios. Furthermore, the system establishes a feedback mechanism from short-term memory to long-term memory, enhancing disassembly capabilities in non-steady-state environments by transforming scenario information into supplementary understanding. The research validates this method on a real disassembly platform. Compared with baselines of traditional PDDL, a planning method using only large language models (LLMs), and heuristic algorithms, this method achieved an 88.0% task success rate (significantly superior to the 38.0% of traditional PDDL). Full article

Background: Cardiometabolic multimorbidity (CMM) has emerged as a significant global health challenge. The triglyceride-glucose (TyG) index and a body shape index (ABSI), which are markers of insulin resistance and central obesity, respectively, have each been associated with CMM, but their combined utility remains unclear. This study analyzed the association of cumulative and single-point TyG-ABSI with CMM. Methods: This study included 5334 participants from the China Health and Retirement Longitudinal Study (CHARLS), covering the period from 2011 to 2020. Cumulative TyG-ABSI was derived from data collected in 2011 and 2015. Incident CMM was defined as having at least two of the following: heart disease, stroke, and diabetes. Cox regression models were used to estimate hazard ratios, and restricted cubic splines (RCS) were employed to examine nonlinear associations. Time-dependent receiver operating characteristic (ROC) curves were constructed to compare predictive performance. Subgroup and sensitivity analyses were also performed. Results: Over 9 years of follow-up, 424 participants (7.95%) developed CMM. Those in the highest TyG-ABSI quartile had a 2.46-fold higher risk than those in the lowest quartile. The association varied by sex: cumulative TyG-ABSI showed a nonlinear relationship with a threshold effect in females, whereas in males, only cumulative TyG-ABSI (not the single-point measure) was significant. Cumulative TyG-ABSI demonstrated better 5-year predictive performance than single-point measures. Conclusions: Cumulative TyG-ABSI independently predicts CMM risk across sexes, whereas single-point TyG-ABSI is only predictive in females. Quantifying long-term metabolic burden using cumulative TyG-ABSI offers a practical, noninvasive tool for chronic risk stratification in aging populations. Routine assessment of cumulative TyG-ABSI in clinical and community settings could facilitate early identification of high-risk individuals, enabling targeted preventive interventions to reduce the growing burden of CMM. Full article

Background/Objectives: While the health effects of economic fluctuations are well-documented, the role of policy-related uncertainty remains underexplored. The objective of this study is to examine the association between economic policy uncertainty (EPU) and mortality. Furthermore, we investigate whether changes in lifestyle behaviors are associated with EPU and may help shed light on the relationship between EPU and health outcomes. Methods: We utilize a mixed data sampling (MIDAS) framework to analyze US state-level data from 2009 to 2020. The model controls for unemployment, income, demographic characteristics, as well as state and year fixed effects. This approach enables the incorporation of high-frequency uncertainty measures to capture dynamic mortality responses. Results: The results indicate a statistically significant inverse association between EPU and total mortality. The association is negative across both genders, with a stronger effect observed among males. Across age cohorts, the retirement-age group exhibits the highest sensitivity. In terms of cause-specific mortality, EPU is positively associated with mortality from respiratory diseases and suicide, while it is negatively associated with mortality from homicide, accidents, and pneumonia and influenza. In addition, EPU is significantly associated with a lower prevalence of current drinking and smoking, a higher likelihood of being in a healthy weight range, improved self-reported health, and reduced time spent traveling. Conclusions: The findings suggest heterogeneous associations between EPU and mortality outcomes across demographic groups and causes of death, highlighting the complex and multifaceted nature of the relationship between policy-related uncertainty and population health rather than a uniform response across health outcomes. Full article

Background: Clinical artificial intelligence (AI) is rapidly moving from retrospective model development into prospective evaluation, implementation, and routine care. Existing reviews have addressed specific aspects of this transition, including monitoring, drift, implementation, governance, and human–AI interaction; however, these bodies of work remain methodologically and conceptually fragmented across different review traditions. Methods: We conducted a scoping review of review-level and review-oriented literature. We searched MEDLINE, Embase, Scopus, and Web of Science Core Collection from database inception to 28 February 2026. We charted review characteristics and conducted an inductive thematic synthesis of extracted review-level findings, while distinguishing operational, deployment-proximal, methodological, and conceptual/governance-oriented evidence. Results: We included 25 review-level publications spanning systematic, scoping, methodological, narrative, and governance-oriented reviews. Three major themes emerged. First, clinically important risks were consistently framed as socio-technical rather than purely algorithmic: trustworthiness depended not only on technical performance, but also on fairness, transparency, workflow fit, human oversight, and organisational readiness. Second, the included review literature consistently recommended post-deployment monitoring but showed limited operational maturity; monitoring methods, action thresholds, fairness surveillance, and corrective responses were weakly standardised, and mature evidence from activated systems in routine care remained sparse. Third, trustworthy implementation was increasingly framed as a lifecycle governance challenge extending beyond procurement and initial validation to include local validation, subgroup auditing, drift detection, controlled updating, incident response, and, where necessary, rollback or retirement. Discussion: The review literature suggests a persistent normative–operational gap, meaning that recommendations about what trustworthy clinical AI should require have advanced faster than evidence on how monitoring, updating, and governance are implemented in routine care. The strongest unresolved challenge is therefore not principal generation alone, but the translation of monitoring and governance expectations into actionable operational systems. Conclusions: Post-development trustworthiness in clinical AI should be understood as a lifecycle property, not a one-time technical achievement. Future work should prioritise stronger operational evidence, clearer reporting of deployment-proximal and post-deployment evaluation, methodological standardisation of monitoring metrics and thresholds, implementation research on feasible governance models, and evaluation frameworks for assessing post-deployment safety, fairness, accountability, and sustainability. Full article

Background: Depression has become a prevalent and serious public health problem worldwide, attracting widespread attention from governments and international organizations and being included in key health policy issues. There is a close interaction between depression and economic factors such as household savings, a link particularly pronounced in Asian countries. However, evidence of a two-way association is limited. This study aims to explore the two-way relationship between depression and savings among middle-aged and older adults. Methods: Data were collected from 6746 respondents in the China Health and Retirement Longitudinal Study (CHARLS) in 2013, 2015, and 2018. A cross-lagged panel model was used to test the two-way relationship between depression and savings. Results: The results showed a significant cross-time effect of depression on savings (T0 → T1: β = −0.052; T1 → T2: β = −0.077), suggesting that higher levels of depression in the early stages are associated with lower levels of savings later. Moreover, savings had a stronger negative predictive effect on depression (T0 → T1: β = −0.463; T1 → T2: β = −0.510), indicating that higher levels of savings in the early stages are associated with lower levels of depression later. Furthermore, the grouping test showed that the two-way negative effect remained stable in both male and female groups (p ≤ 0.001). Conclusions: This study reveals the dynamic two-way influence between depression and savings, providing a basis for policy formulation that synergistically promotes residents’ mental health and household financial stability. Full article

Objective: This study aimed to assess whether older American adults with multimorbidity are at higher risk of becoming edentate over time. Methods: We used data from three waves of the Health and Retirement Study (HRS), a longitudinal survey of older American adults aged 50 years and over. Data on multimorbidity was from 2012, while data on complete tooth loss was from 2018. Multimorbidity included five common and serious conditions, namely diabetes, heart conditions, lung diseases, cancer, and stroke. Socioeconomic factor was indicated by total wealth in 2006; behaviour was indicated by smoking in 2012. We used Structural Equation Modelling (SEM) to assess the relationship between multimorbidity in 2012 and complete tooth loss in 2018. Participants with complete tooth loss in 2012 were excluded from the analysis. Results: Among 6286 participants with complete data across all three waves, each additional chronic condition in 2012 was associated with 1.30 times higher odds of edentulism in 2018 (95% CI: 1.12, 1.52). In the SEM, multimorbidity in 2012 was positively associated with being edentate in 2018 (estimate: 0.01, 95% CI 0.01, 0.02); smoking and wealth were also significantly associated with edentulism. Wealth and smoking were also associated with multimorbidity. Conclusions: Older adults with multimorbidity appear to have a higher probability for becoming edentate. The findings highlight the need for oral health promotion activities for those with multimorbidity. Full article

Background: Population ageing increases reliance on family caregivers (FCGs) for very old adults (80+). While caregiving is often studied as a source of burden, its impact on caregivers’ daily life and occupational balance remains underexplored. This study aimed to explore how caregiving responsibilities shape the daily lives, occupational balance, and support needs of FCGs, using the Stress Process Model (SPM) and the concept of Occupational Balance (OB). Methods: A qualitative study was conducted in the PACA region (France) within the SCOPE project. Seventeen semi-structured interviews were analysed using thematic content analysis, with independent double coding by two researchers. Results: Six themes were identified: caregiving role and identity, consequences, occupational patterns, needs, proposed actions, and barriers and facilitators. Caregiving generated both primary stressors (physical and emotional demands) and secondary stressors (role conflicts, financial strain, and social isolation). It also led to occupational imbalance, characterized by reduced leisure, diminished self-care, and reorganization of daily routines. Working FCGs reported greater role strain and time constraints, whereas retired FCGs emphasized informational needs and adaptation strategies. Across both groups, caregivers’ needs were rarely formally assessed. Conclusions: These findings highlight that caregiving for very old adults profoundly reshapes caregivers’ daily lives through both stress-related mechanisms and disruptions in occupational balance. They underscore the need for tailored, context-sensitive support strategies, including systematic needs assessment and more structured, individualized coordination approaches such as case management. Full article

As Taiwan faces rapid population aging and increasing longevity, individuals are expected to assume greater responsibility for their own financial security in later life. Future Time Perspective (FTP) is a well-established cognitive-motivational construct associated with long-term planning, while curiosity has been linked to adaptive functioning and sustained cognitive engagement across the lifespan. However, its role in shaping perceived timing of financial preparation remains underexplored. This study examined the associations among FTP, joyous exploration (JE), and perceived timing for financial preparation, and tested whether curiosity mediates this relationship. Cross-sectional data from 435 adults in Taiwan (aged 31–89 years) were analyzed. Participants completed validated measures of FTP, JE, and perceived timing for initiating financial preparation. OLS regression and mediation analyses were conducted, controlling for age, sex, education, and health. FTP was positively associated with JE. JE predicted earlier perceived financial preparation timing. Although the direct effect of FTP indicated endorsement of later preparation ages when controlling for JE, a significant negative indirect effect demonstrated that higher FTP was linked to earlier preparation ages through increased JE, reflecting inconsistent mediation. JE may represent a modifiable psychological pathway for promoting earlier and more proactive financial preparation in super-aging societies such as Taiwan. Full article

Background: Frailty is a fluctuating health state that may worsen or improve over time and is linked to adverse outcomes, including musculoskeletal disorders such as arthritis. However, evidence on whether frailty changes predict arthritis onset remains limited. This study examined the relationship between changes in frailty status and incident arthritis among Chinese adults aged 45 years and older. Methods: We performed a longitudinal cohort analysis using data from the China Health and Retirement Longitudinal Study (CHARLS). Frailty was quantified with a 30-item Frailty Index (FI) and categorized as robust, pre-frail, or frail. Frailty transitions were defined by changes in FI-based categories across survey waves. Incident arthritis was identified as self-reported physician-diagnosed arthritis during follow-up. Associations between frailty transitions and arthritis onset were evaluated using Cox regression, reporting hazard ratios (HRs) and 95% confidence intervals (CIs). Models were adjusted for demographic characteristics, health behaviors, and biochemical indicators, and sensitivity analyses were conducted to verify result stability. Results: Among 4982 participants (mean age 58.97 years; 45.58% female). Relative to robust individuals, baseline pre-frailty (HR 1.67, 95% CI 1.41–1.97) and frailty (HR 2.76, 95% CI 1.97–3.85) were associated with higher arthritis risk. Participants whose frailty status worsened from robust to pre-frail or frail also showed higher arthritis risk (HR 1.68, 95% CI 1.34–2.10). In contrast, transitions from frail to pre-frail or robust were associated with lower risk (HR 0.44, 95% CI 0.21–0.92). Higher cumulative frailty burden and greater frailty progression were also associated with increased arthritis risk. Conclusions: Frailty transitions are strongly associated with incident self-reported physician-diagnosed arthritis. Monitoring frailty trajectories may improve arthritis risk stratification and support prevention strategies. Full article

Retirement wealth is a core indicator of financial security, autonomy, and inequality in later life. This paper examines how cohort, institutional context, and social class interact to shape retirement wealth, focusing on Generation X. Gen X occupies a critical but understudied position in the life course between peak earning years and full retirement; they also came of age during a major restructuring of the U.S. economy that shifted financial risk from institutions to individuals. I compare Gen X retirement wealth to that of adjacent cohorts, evaluating how different asset and debt types contribute to cohort differences in retirement readiness. I also examine intra-cohort inequality by wealth class. Findings suggest that retirement wealth inequality is especially severe among those nearing and exiting the labor force. The analyses highlight how long-term economic security is socially structured and historically contingent—making retirement wealth a powerful lens for understanding inequality across time and class. Full article

Background/Objectives: The COVID-19 pandemic substantially affected both the provision and demand for health services. There are few studies that analyzed factors associated with unmet healthcare needs during the COVID-19 pandemic relative to regular pre-pandemic period, mainly in high-income countries. This study examines the change in the likelihood of reporting unmet healthcare needs as well as individual demographic, socioeconomic, health-related, and geographical characteristics associated with unmet healthcare needs during the COVID-19 pandemic and during the pre-pandemic period in Serbia. Methods: We utilized data from the Survey on Income and Living Conditions in the Republic of Serbia for 2019 and 2021. Multivariable logistic regression analysis was conducted on the pooled sample comprising 21,422 respondents aged 16 years and older from both survey years. Results: Overall, respondents had 1.6 times higher odds of reporting unmet healthcare needs during the COVID-19 pandemic compared with the pre-pandemic period. In the pooled multivariable analysis, older adults (OR = 2.32), individuals reporting poor or very poor self-rated health (OR = 2.16), and those with chronic diseases (OR = 1.46) were more likely to report unmet healthcare needs. In contrast, individuals with higher levels of education (ORs = 0.72 for high school, 0.65 for college, and 0.51 for master’s degree), retired individuals (OR = 0.70), inactive persons (OR = 0.76), and students/pupils (OR = 0.22) had significantly lower odds of unmet needs, compared to their counterparts. Relative to the poorest income quintile, individuals in all higher income quintiles were less likely to report unmet healthcare needs, with the lowest odds observed in the 5th quintile (OR = 0.49). Residents of thinly populated areas had higher odds compared to those in densely populated areas (OR = 1.19). Conclusions: Identified associations with unmet healthcare needs should be used to develop targeted strategies for strengthening healthcare access, particularly in the context of future crises. Full article

To investigate the factors affecting the utilization of retired Thoroughbred racehorses in equestrian disciplines, Bayesian linear mixed models were separately fitted using rank, round time, and obstacle faults from show-jumping competitions restricted to retired Thoroughbred racehorses as dependent variables, with the interaction between horse sex and the interval from race retirement to competition (as a proxy for transition training to show-jumping) as a fixed effect. When the interval was short (≤1 year), the estimated marginal mean of rank was statistically significantly lower in stallions (0.26) than in mares (0.41) and geldings (0.39). However, ranking improved with longer intervals in all sexes, with the greatest improvement observed in stallions, and the significant sex-related differences disappeared at the 3-year interval, suggesting an effect of transition training on ranking. Round time improved significantly with longer intervals in all sexes, consistent with the ranking pattern; significant improvement in obstacle faults was observed only in stallions and geldings. The explanatory power of the models, including major random effects, rider, horse ability, sire and affiliation after retirement, was moderate (conditional R²: 0.40–0.65), whereas that of the fixed effects was small (marginal R²: 0.02–0.07), indicating the multifactorial nature of success in competition. Full article

Retirement marks a pivotal transition not only for individuals but also for their families. Existing research has examined relational aspects of retirement but primarily focuses on how family members influence the retiree’s well-being rather than on the impact of this transition on other family members and the broader family system. To address this imbalance, the present review synthesizes evidence drawing upon Family Life Course Theory and Family Systems Theory. Using a well-established five-stage framework, we conducted extensive database searches and refined our guiding research question. Of the 4034 studies identified, 61 were selected for detailed analysis. Data extraction and thematic coding, supported by MAXQDA 24 software, revealed eight interconnected themes: marital quality and conflict; dyadic adjustments between partners; financial impacts and concerns; time use and leisure; redistribution of domestic roles; health outcomes; emotional and psychological effects on the family unit; and intergenerational dynamics. Across these domains, gender consistently emerged as a central, asymmetrical determinant of adaptation. Ultimately, this review demonstrates that retirement constitutes a relational turning point within families and calls for future research to adopt inclusive, longitudinal designs, and for practitioners and policymakers to develop family-centred interventions that recognize the systemic impact of retirement. Full article

Reliable state estimation is critical for the safe operation of second-life battery systems but is severely hindered by significant parameter heterogeneity arising from diverse historical aging conditions. Traditional static models struggle to adapt to such variability, while online identification methods are prone to divergence under dynamic loads. To overcome these challenges, this paper proposes a Dual-Anchor Adaptive Fusion Framework for robust State of Charge (SOC) estimation and State of Health (SOH) soft-sensing. Specifically, to establish a reliable physical baseline, an automated Dynamic Relaxation Interval Selection (DRIS) strategy is introduced. By minimizing the fitting Root Mean Square Error (RMSE), DRIS systematically extracts high-fidelity parameters to construct two “anchor models” that rigorously define the boundaries of the aging space. Subsequently, a residual-driven Bayesian fusion mechanism is developed to seamlessly interpolate between these anchors based on real-time voltage feedback, enabling the model to adapt to uncalibrated target batteries. Concurrently, a novel “SOH Soft-Sensing” capability is unlocked by interpreting the adaptive fusion weights as real-time health indicators. Experimental results demonstrate that the proposed framework achieves robust SOC estimation with an RMSE of 0.42%, significantly outperforming the standard Adaptive Extended Kalman Filter (A-EKF, RMSE 1.53%), which exhibits parameter drift under dynamic loading. Moreover, the a posteriori voltage tracking residual is compressed to ~0.085 mV, effectively approaching the hardware’s ADC quantization limit. Furthermore, SOH is inferred with a relative error of 0.84% without additional capacity tests. This work establishes a robust methodological foundation for calibration-free state estimation in heterogeneous retired battery packs. Full article