Objective The network theory of psychopathology proposes that dense symptom networks foster persistent symptoms. Studies testing this hypothesis in late-life depression (LLD) are lacking. This study examined whether, and how, cross-sectional networks of episodic and persistent/recurrent depressive symptoms in older adults differ. Method Data of adults aged 60 + were drawn from the Survey of Health, Ageing and Retirement in Europe (SHARE). Depressive symptoms were assessed using the EURO-D scale. Participants were classified as episodic or persistent/recurrent based on their EURO-D score at wave 5 (2013) and wave 6 (2015) (EURO-D ≥4). For each group, separate cross-sectional symptom networks at wave 5 were estimated as Ising models and corrected for selection on the sum-score (Berkson's bias). The permutation-based Network Comparison Test was used to compare global strength and network structure. Results Of 8519 participants, 3746 (44.0%) participants showed episodic depressive symptoms, while 4773 (56.0%) showed persistent/recurrent depressive symptoms. Neither global network strength nor network structure differed statistically significantly between groups (p = .17 and p = .60, respectively). In both networks, lack of interest, depressive mood, and suicidality showed highest strength and expected influence. Findings were consistent across sensitivity analyses. Conclusion Our results showed no difference in global strength and network structure between episodic and persistent/recurrent depressive symptoms in older adults, complementing mixed evidence from younger and middle-aged adults. Causal symptom interactions may play a smaller role in the persistence/recurrence of depressive symptoms in later life. Future studies should examine longitudinal networks, subtypes of LLD, and consider external factors.
Objective This study leveraged interpretable machine learning (ML) to map heterogeneous trajectories of depressive symptoms in Chinese older adults with chronic diseases, aiming to develop an interpretable, prediction-oriented framework for personalized mental health interventions. Methods We analyzed four-wave longitudinal data from 5492 participants in the China Health and Retirement Longitudinal Study. Following trajectory identification, 10 ML algorithms were compared. A 50-iteration bootstrap Recursive Feature Elimination (RFE) distilled 10 core predictors from 39 baseline features. Models were evaluated using an 80:20 stratified split, with MICE imputation strictly preventing data leakage. Model interpretability was extracted via SHapley Additive exPlanations (SHAP). Results Three distinct trajectories emerged: Consistently Low, Chronically High, and Rapidly Escalating Risk. The Elastic Net model demonstrated optimal discriminative power (ROC-AUC = 0.710, PR-AUC = 0.468) and a Brier score of 0.337. SHAP analysis indicated that extremely low life satisfaction, severe instrumental functional limitations, and poor self-rated health were strongly associated with higher predicted probabilities of high-risk trajectories, whereas high household income robustly protected the low-risk group. We translated these insights into an interactive web-based risk calculator. Conclusion This study identified critical depressive trajectory classes and established an interpretable predictive model. By translating complex analytics into an interpretable predictive framework, this approach provides a foundation for individualized risk profiling and highlights distinct patterns of risk that may inform future targeted mental health interventions for older adults with chronic conditions.
Background Late-life depression (LLD) is associated with increased risk of cognitive decline and dementia, yet clinically relevant neuroimaging markers of short-term cognitive decline remain uncertain. Methods We conducted a two-stage study. In the Shanghai Action to Prevent the Elderly from Dementia (SHAPE) cohort, baseline MRI was compared among 40 LLD participants with stable cognition (LLDcs), 38 LLD participants with cognitive decline over two years (LLDcd), and 47 healthy controls. Measures included peak width of skeletonized mean diffusivity (PSMD), global and tract-specific difference in distribution function based on mean diffusivity (DDFMD), grey-matter measures, and regional diffusion tensor image analysis along the perivascular space (ALPS) indices. Within-group partial correlations between MRI measures and cognitive performance were also examined. Candidate markers were then evaluated in the Sydney Memory and Ageing Study (MAS) LLD sample (21 LLDcs, 16 LLDcd) using SHAPE-trained single-marker Firth logistic models applied without refitting. Results In SHAPE, LLDcd showed greater white-matter microstructural burden than LLDcs and controls, including higher PSMD, lower global and tract-specific DDFMD, alongside smaller left nucleus accumbens (L_NAcc) volume. Within LLDcd, poorer white-matter integrity was associated with worse orientation and other cognitive domains. In MAS, global DDFMD and L_NAcc volume were the two markers whose discrimination of LLDcd survived correction for multiple comparisons. Conclusions White-matter microstructural burden and smaller L_NAcc volume may help characterize LLD patients at higher near-term risk of cognitive decline. These findings warrant evaluation in larger longitudinal LLD cohorts.
Objectives Loneliness is a major concern in later life, yet disparities between heterosexual and LGBTQ+ older adults remain insufficiently understood. This study examined how families of origin and families of choice relate to loneliness among adults aged 50 +, and whether these associations differ by sexual orientation. Design Data were collected via online surveys in Israel and compared two groups: LGBTQ+ and heterosexual adults aged 50 +. Participants The analytic sample included 948 participants. Measurements Loneliness was assessed using the brief UCLA Loneliness Scale. Participants identified close members of their family of origin and family of choice, and rated relationship commitment\stability and negativity. Hiererchical regression analyses examined the predictors of loneliness and the interactions of social relationships with sexual orientation group. Results LGBTQ+ participants reported fewer traditional family ties (e.g., children, partners) but more siblings and friends in their close networks. Overall, having a partner, a close sibling, and reporting higher commitment and stability in both family types were associated with lower loneliness, whereas greater negativity in family of choice relationships was associated with higher loneliness. Interaction analyses showed that the protective effects of partnership and high commitment\stability within families of choice were stronger for LGBTQ+ aging adults. Conclusions The findings highlight the central role of chosen family, particularly committed, stable partnerships, in buffering loneliness among LGBTQ+ older adults. Practice and policy in relation to later life should recognize diverse kinship structures and address inequities that shape relational resources in later life, especially among LGBTQ+ aging adults.
OBJECTIVES:This study explored whether distinct Alzheimer's disease (AD) structural atrophy subtypes exhibit divergent functional profiles. DESIGN:A cross-sectional multimodal neuroimaging and electrophysiological study. SETTING:Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China. PARTICIPANTS:A total of 116 patients with AD and 74 cognitively unimpaired controls underwent structural MRI. Patients with AD were stratified into three MRI-derived atrophy-pattern groups corresponding to hippocampal-sparing (HpSp-MRI), typical (tAD-MRI), and limbic-predominant (LP-MRI) subtypes. MEASUREMENTS:Resting-state functional MRI was used to assess intra- and internetwork functional connectivity, and EEG was used to evaluate spectral power and microstate dynamics. RESULTS:The HpSp-MRI subtype showed lower intranetwork connectivity than both the LP-MRI and tAD-MRI subtypes in the visual, somatomotor, and dorsal attention networks. The LP-MRI and tAD-MRI subtypes differed in ventral attention network connectivity. Moreover, the LP-MRI subtype exhibited stronger internetwork connectivity in specific network pairs compared with the other subtypes. EEG analysis suggested a possible difference in the microstate 3-to-1 transition between the LP-MRI and tAD-MRI groups. CONCLUSIONS:MRI-derived atrophy-pattern subtypes showed different resting-state functional connectivity profiles, providing a potential basis for personalized brain network-targeted interventions in AD.
BACKGROUND:Domain-level ADL and IADL independence across MMSE score ranges has been less well described in Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). This study described the observed proportions of basic ADL and IADL independence across MMSE score ranges in these three neurodegenerative dementias. METHODS:In a cohort of 650 patients (524 AD, 90 DLB, 36 FTD), cognitive function was assessed with the Mini-Mental State Examination (MMSE), and daily function was evaluated using the Physical Self-Maintenance Scale and the Lawton IADL scale. Patients were grouped into MMSE score ranges. For each diagnosis and MMSE score range, we calculated the observed proportion of participants rated as independent in each ADL/IADL domain and Wilson score 95% confidence intervals. Because the FTD sample was small (n = 36), with only 1-11 participants in individual five-point MMSE score ranges, and several MMSE-specific subgroup counts were sparse, the analyses were descriptive. RESULTS:Observed independence proportions varied across ADL/IADL domains, MMSE score ranges, and diagnostic groups. In AD and DLB, shopping, food preparation, and medication management had low observed independence proportions even in higher MMSE ranges. In the MMSE 21-30 stratum, selected absolute numerical contrasts between DLB and AD ranged from 7.2 percentage points for feeding to 18.4 percentage points for bathing. Estimates for FTD, which were based on only 1-11 participants per five-point MMSE score range, and for DLB in the MMSE 0-10 stratum were based on small denominators and were therefore imprecise. CONCLUSIONS:This study provides descriptive estimates of domain-level ADL and IADL independence across MMSE score strata in AD, DLB, and FTD. The results may contribute to domain-specific assessment and support planning for people living at home with MCI or dementia. These findings should be regarded as hypothesis-generating for future studies.
BACKGROUND:Vascular depression (VaD) is a subtype of late-life depression (LLD) associated with cerebrovascular disease, cognitive impairment, and poor response to standard antidepressants. Despite its clinical relevance and association with increased risk of dementia, no specific treatment guidelines currently exist. OBJECTIVES:To systematically review randomised controlled trials (RCTs) on the clinical efficacy of pharmacological and non-pharmacological interventions for VaD in older adults. METHODS:A systematic search of MEDLINE, EMBASE, Web of Science and ClinicalTrials.gov registry identified 7994 records, of which 8 RCTs met inclusion criteria. Studies included participants with late-life VaD. Interventions comprised pharmacological treatments (augmentation with tandospirone and nimodipine) and neuromodulation techniques (rTMS and tDCS). Outcomes included treatment response and remission, change in depressive symptoms, and other clinical outcomes. RESULTS:Augmentation with tandospirone was associated with faster early symptom improvement in three of four trials. Nimodipine improved remission at 2 months and reduced recurrence in one of two trials. Neuromodulation interventions showed promising antidepressant effects and cognitive benefits (based on two trials). Treatments were generally well tolerated. However, study heterogeneity, small sample sizes, and short follow-up durations limited comparability and precluded meta-analysis. The overall certainty of evidence was low to very low. CONCLUSIONS:Evidence on treatment for VaD remains limited, highlighting the need for large, well-designed RCTs and integrated approaches combining vascular risk management with targeted therapies.
BACKGROUND:Understanding the temporal order of clinical symptoms is critical for improving disease progression assessment in biomarker-defined Alzheimer's disease (AD). However, the sequential emergence of cognitive, neuropsychiatric, and functional manifestations remains incompletely characterized. The purpose of this study is to characterize the population-level sequence in which Alzheimer's disease symptoms appear, to help understand how the disease is progressing. METHODS:We analyzed 932 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including 546 amyloid-positive individuals across the AD continuum and 386 amyloid-negative individuals in the comparison group. Longitudinal cumulative incidence was analyzed to estimate the temporal emergence of major clinical symptoms. Any symptom onset was defined using a > 50% cumulative incidence threshold. Cross-sectional relationships between the sequence of clinical symptoms and Mini-Mental State Examination (MMSE) scores were analyzed using locally estimated scatterplot smoothing (LOESS). The concordance between the clinical symptom sequence and PET-derived Braak staging was assessed using weighted kappa statistics. RESULTS:A reproducible temporal ordering of clinical symptoms was observed across longitudinal and cross-sectional analyses. Memory impairment emerged earliest, affecting 63.75% of participants at baseline, followed by behavioral and affective symptoms. At intermediate stages, executive dysfunction and instrumental activities of daily living (IADL) impairment affected 52.44% and 54.85% of participants, respectively. Language and visuospatial impairments appeared later, affecting 51.25% and 51.54% of participants, respectively, followed by psychotic symptoms and severe functional decline in basic activities of daily living (BADL), which suggests the disease has reached its late stage. The order in which different symptom groups appear-from memory to executive function and instrumental abilities, then language and visuospatial skills, and finally psychotic symptoms and basic abilities-shows moderate consistency respectively with CDR staging (κ = 0.596, 95%CI: 0.524-0.668), and the PET-derived Braak staging (κ = 0.517, 95%CI: 0.436-0.598). CONCLUSION:Clinical symptoms in AD tend to emerge in a temporal sequence. This finding may help to better characterize disease progression clinically, serving as a symptom-staging framework for symptomatic AD and providing interpretable turning points for clinical assessment and individualized management.
BACKGROUND AND OBJECTIVES:With Delphi panels in aging research proliferating, we conducted a scoping review to: (1) aggregate key practice recommendations; (2) document their use in aging research; and (3) use findings to recommend practices and their reporting for aging researchers in the form of a Delphi Quality Criteria Rating Form for Aging (DQ4A). RESEARCH DESIGN AND METHODS:We conducted a scoping review of Delphi studies focused on aging published in peer-reviewed journals using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Searches were run in May 2025 in relevant databases. Titles, abstracts, and full-texts screening yielding a sample of 102 articles. Data were extracted and synthesized to feature study characteristics and Delphi methodological practices. Results informed creation of the DQ4A. RESULTS:Adherence to methodological recommendations varied, highlighting the need for streamlined guidance. Common practices included specification of panelist selection criteria (95%), provision of the final product (93%), and substantiation of Delphi method use (78%). Least represented practices included targeting number of panelists based on anticipated attrition (11%), use of double blinding (14%), and panelist review of original and modified products (18%). Using the DQ4A, we demonstrate that 24% of all studies had average quality, 33% had higher-than-average quality, and 43% had lower-than-average quality. DISCUSSION AND IMPLICATIONS:Findings highlight methodological gaps, indicating recommendations to improve the Delphi method in gerontology and geriatrics. Investigators can use the DQ4A to improve conduct and reporting of Delphi studies while ensuring that resultant products reflect diverse stakeholder needs.
BACKGROUND:Verbal fluency is a core marker for early cognitive decline in older adults. This study aimed to compare the relative efficacy of different digital cognitive training (DCT) regimens on verbal fluency in older adults, and identify the optimal intervention and moderators. METHODS:A search was conducted across PubMed, Web of Science, PsycINFO and IEEE Xplore from January 2015 to November 2025, and included randomized controlled trials (RCTs) of DCT for verbal fluency in adults aged ≥ 65 years. We conducted pairwise meta-analysis and frequentist network meta-analysis (NMA), with Bayesian model validation, subgroup analysis and meta-regression. Risk of bias was assessed with RoB 2.0, and evidence quality with GRADE. FINDINGS:20 RCTs with 1358 participants were included. Compared with passive control, computerized cognitive training (CCT) combined with social/language activities had the optimal efficacy (SMD=0.47, 95%CI [0.02, 0.93], SUCRA=0.84), with greater benefits in older adults with cognitive impairment and lower education level. Furthermore, optimal therapeutic gains were observed following an initial acclimation period (i.e., >20 h of intervention duration). CONCLUSIONS:CCT combined with social/language activities is the most effective DCT regimen to improve verbal fluency in older adults, especially for those with cognitive impairment and lower education level.The research protocol has been pre-registered on the Open Science Framework (OSF)( Registration DOI: 10.17605/OSF.IO/UGR7Y).This work was supported by the National Natural Science Foundation (NNSF) of China under Grant Nos. 32371132.
The growing use of large language model-supported companion robots in later-life care warrants closer scrutiny beyond conversational performance alone. While the original cross-cultural study offers valuable qualitative insights from the United Kingdom and Japan, its findings also expose unresolved questions regarding cross-cultural generalisability, sustained relational value, and the ethical implications of embedding generative AI in companionship technologies. Meaningful support for loneliness in older adults cannot be inferred from dialogue fluency alone, because loneliness is a multidimensional condition shaped by social context, identity, and care environment. This commentary therefore argues for a more context-sensitive and longitudinal research agenda that prioritises adaptive memory, culturally attuned interaction design, and human oversight within hybrid care models. By reframing companion robots as supportive tools rather than substitutes for human relationships, the discussion advances a critical perspective on how relational AI should be developed, evaluated, and governed in psychogeriatric care.
Nigeria's rapidly expanding older adult population, mirroring a global demographic shift, is driving a surge in dementia cases. Currently 4.9% of Nigerian older adults have dementia and this figure is set to increase. Fragmented care delivery, weak institutional infrastructure, and pervasive social stigma severely hinder effective diagnosis, treatment, and structural support. This paper proposes a Modern Service Framework for Dementia Care in Nigeria; a proactive, evidence-based national strategy designed to overhaul Nigerian healthcare delivery through six critical, intersecting pillars. The proposed framework establishes a coordinated intervention pathway by: (1). Creating integrated, communicative health systems, (2). Promoting healthy ageing and life-course prevention, (3). Driving diagnostic innovation and primary-care screening, (4). Raising targeted community, traditional, and religious awareness, (5). Scaling workforce capacity alongside sustainable funding mechanisms, and (6). Fostering cross-sectoral partnerships to safeguard vulnerable individuals. Rapid, formal adoption of this comprehensive framework is vital to mitigate the immense economic and caregiving burdens placed on families and the broader healthcare system, ultimately ensuring that every Nigerian living with dementia receives equitable, dignified, and rights-based support.
BACKGROUND:Subcortical vascular mild cognitive impairment (svMCI) is an early stage of cognitive decline, frequently accompanied by emotional disturbances like depressive symptoms. While previous studies have explored cognitive and emotional symptoms in svMCI, research on the associated brain functional changes remains limited. Dynamic functional magnetic resonance imaging (fMRI) provides a novel approach to examining temporal variability in brain activity, offering insights into dynamic neural function changes. This study aims to investigate alterations in dynamic fMRI metrics in svMCI patients and analyze their relationships with cognitive function and depressive symptom. METHODS:This study enrolled 116 patients with svMCI (60 with depressive symptoms (svMCI+D) and 56 without depressive symptoms (svMCI-D)) and 36 healthy controls (HC). All participants underwent resting-state functional magnetic resonance imaging (fMRI). Dynamic amplitude of low-frequency fluctuations (dALFF), dynamic fractional ALFF (dfALFF), and dynamic regional homogeneity (dReHo) were calculated as key indices. Group differences were tested using one-way analysis of covariance (ANCOVA) with age and gender as covariates, followed by post hoc two-sample t-tests for pairwise comparisons. Partial correlation analyses examined associations between dynamic metrics and cognitive performance (MMSE and MoCA) as well as affective symptoms (HAMD and HAMA). Mediation analyses were then conducted to further probe potential pathways linking altered brain dynamics to clinical measures. RESULTS:Compared with HC, both the svMCI + D and svMCI-D showed significantly reduced dALFF in several regions, including the left lingual gyrus, left superior temporal gyrus, left cuneus, and right paracentral lobule. In addition, the svMCI + D group exhibited increased dALFF in the right hippocampus. The svMCI-D group showed lower dALFF in the left gyrus rectus and left cuneus. For dReHo, the svMCI + D group demonstrated higher values in the right cingulate gyrus and adjacent cortex, along with lower values in the left thalamus and left inferior frontal gyrus. These altered dynamic measures were positively correlated with depressive severity and negatively correlated with cognitive performance. CONCLUSIONS:The study showed that patients with svMCI, especially those with depressive symptoms, exhibited significant alterations in dynamic fMRI metrics across multiple brain regions. These changes were associated with cognitive performance and depressive symptom severity. Dynamic measures, including dALFF and dReHo, provide neurobiological markers to better characterize cognitive and emotional disturbances in svMCI.
OBJECTIVES:Individuals with very late-onset schizophrenia-like psychosis (VLOSLP) experience a persistent mortality gap compared to the general population, yet no validated prognostic tools tailored to this growing population exist. We aimed to develop and validate a 3-year all-cause mortality prediction model (VALOR-m) for individuals with VLOSLP. DESIGN:We developed VALOR-m with LASSO-penalised Cox regression. To evaluate temporal drift and geographic generalisability, we employed a two-stage approach: 1)temporal validation stratified by two time periods (period 1: 2002-2013; period 2: 2014-2024), and 2)temporal recalibration with internal-external cross-validation (IECV) stratified by seven catchment areas in period 2. Discrimination was assessed by time-dependent AUC and Harrell's c-statistic; calibration by calibration slope and observed-to-expected ratio (O/E ratio). PARTICIPANTS:Using a population-based electronic health record cohort from Hong Kong (2002-2024), we identified 33,594 older adults (aged≥60 years) with VLOSLP. RESULTS:Of 33,594 individuals included (16,262[48·4%] male; mean age of onset 76·4 years), 11,272 (33·6%) died within 3 years. VALOR-m retained 11 predictors and demonstrated good discrimination (pooled time-dependent AUC:0·772 95%CI[0·765-0·779]; Harrell's c-statistic 0·734 95%CI[0·728-0·741]) and satisfactory calibration (calibration slope 0·885 95%CI[0·859-0·911]; O/E ratio 0·972 95%CI[0·908-1·041]) in IECV. CONCLUSIONS:VALOR-m provides the first validated individualised mortality risk estimates for individuals with VLOSLP, applicable to real-world clinical practice using routinely collected data. VALOR-m achieved comparable discrimination to conventional comorbidity indices with fewer predictors, suggesting that it better captures the unique mortality profile of VLOSLP, and supporting its use to guide antipsychotic treatment decisions, personalised healthcare management in this understudied yet growing population.
Objectives Depressive symptoms are influenced by multiple social factors, but their association with the polysocial risk score (PsRS) remains unclear. This study aimed to examine the association between PsRS and depressive symptoms, including its network structure. Design Population-based cross-sectional study. Setting Jilin Province, China, from June to December 2025. Participants A total of 1740 older adults were included in the analysis. Measurements PsRS was measured using 10 indicators across three domains: socioeconomic status, psychosocial factors, and living environment. Depressive symptoms were assessed using the Patient Health Questionnaire-9. Logistic regression and network analyses were performed. Results The prevalence of depressive symptoms among older adults was 33.85%. The participants with depressive symptoms had higher PsRS (4.49 ± 1.94) than those without (3.82 ± 1.89). Higher PsRS was associated with higher odds of depressive symptoms (OR = 1.21, 95% CI: 1.14–1.28). Compared with the low-PsRS group, the odds of depressive symptoms were higher in the moderate-PsRS and high-PsRS groups (moderate: OR = 1.57, 95% CI: 1.25–1.97; high: OR = 2.38, 95% CI: 1.71–3.32; P for trend < 0.001). Each of the three domains was significantly associated with depressive symptoms. Network analysis identified social isolation, psychosocial factors, and worthlessness as structurally important nodes. Conclusions Higher PsRS was associated with a greater likelihood of depressive symptoms. Social isolation and worthlessness played important roles in linking polysocial adversity to depressive symptoms.
Objectives Agitation is a common and distressing phenomenon across neurocognitive disorders (NCD). It is linked to decreased quality of life of the person with NCD, cognitive and functional decline, increased health-care utilization and institutionalization rates, and substantial burden for family carers and care professionals. Its management is particularly challenging. The objective of this International Psychogeriatric Association’s (IPA) task force was to synthesize recent advances in nomenclature and assessment, epidemiology, progression, etiology, detection, impact, approaches to managing agitation; and to make recommendations to guide IPA’s next 10-year strategy. Methods A multidisciplinary expert workgroup met multiple times virtually and during the 2024 IPA Congress in person to discuss the current scientific and clinical practice landscape for agitation in NCD. The group integrated evidence about validated behavioral measures, biomarkers, digital monitoring, psychosocial and environmental interventions, and pharmacological options. Results Agitation is attributed to disruptions in fronto-limbic circuitry with contributions from neuroimmune dysregulation, neurotransmitter alterations, and mitochondrial dysfunction, and various psychosocial and environmental factors. Psychosocial and environmental strategies can reduce agitation, though magnitude and durability of responses vary. Pharmacological options can have short-term benefits but carry risks that require strict patient selection, counseling, monitoring and medication stewardship. Approved medications based on controlled clinical trials remain limited. Conclusion Care and support in agitation in NCD should involve the implementation of person-centered, rights-based psychosocial and environmental approaches, with time-limited pharmacological adjuncts as second-line. Key evidence gaps include head-to-head and longer-term trials, active safety surveillance, validated agitation measures, and equity-focused implementation across settings and cultures.
BACKGROUND:Bullying is a common issue that undermines older adults' health and well-being yet often goes unnoticed. Despite its impact, assessment tools specifically designed to identify bullying against this population are limited. OBJECTIVES:This study aimed to develop the Bullying Experiences of the Elderly (BEE) scale and evaluate its psychometric properties among older adults. METHODS:The BEE scale was theoretically grounded in Olweus's bullying framework, stereotype embodiment theory, and social-ecological theory. A three-phase cross-sectional design was used, including item generation based on theoretical foundations, refinement through content and face validity review, and evaluation of construct validity in a larger survey sample. A sample of 922 community-dwelling older adults was recruited from commonly frequented or residential locations in Taiwan. Recruitment was conducted through door-to-door visits and face-to-face interactions. Factor analysis was performed for data analysis. RESULTS:The finalized BEE scale includes 18 items and a four-factor structure: ageism-related bullying, sexual bullying, dignity violation, and social bullying. The scale demonstrated strong content validity and good internal consistency, with Cronbach's α coefficients exceeding.80. The indices of confirmatory factor analysis supported the internal measurement structure of the four-factor model, with composite reliability values exceeding.60 and the square roots of the average variance extracted for each factor being greater than the inter-factor correlations. CONCLUSION:The BEE scale is a reliable instrument for assessing bullying experiences among older adults, offering valuable support for improving geriatric care. Its routine application may inform the development of targeted interventions; however, further research is required to validate the scale across different contexts.
