Age and ageing最新文献

Background: Family caregivers of persons with dementia experience a substantial caregiver burden. Digital psychological interventions represent a promising approach to mitigating this burden.

Objectives: This study aims to examine the impact of digital psychological interventions on the caregiver burden of dementia caregivers and investigates potential effect-modifying factors and assesses their effects on depression, self-efficacy and quality of life.

Methods: This study systematically searched six databases for randomized controlled trials or non-randomized studies of interventions and included studies from database inception to 18 May 2025. Meta-analysis was performed using Review Manager 5.4, and subgroup analysis explored the effects of different intervention duration, formats and technological platforms.

Results: A total of 16 studies involving 750 family caregivers were included. Meta-analysis showed digital psychological interventions significantly reduced caregiver burden [Standardized mean difference (SMD) = -0.21, 95% CI: -0.35 to -0.07; P = .003] and improved self-efficacy (SMD = 0.38, 95% CI: 0.15 to 0.61, P = .001) and quality of life (SMD = 0.59, 95% CI: 0.27 to 0.91, P < .001). But digital psychological interventions have no statistically significant in alleviating depressive symptoms (P = .06). Subgroup analyses revealed that interventions lasting ≤2 months, whether delivered in group or individual formats and implemented via web-based or mobile application platforms, had statistically significant effects on caregiver burden.

Conclusion: Digital psychological interventions effectively alleviate caregiver burden and enhance their self-efficacy and quality of life. Future studies should prioritize short-term interventions and develop integrated approaches combining individual and group formats.

Background: While demographic and socioeconomic factors such as female sex and socioeconomic disadvantage are well-established risk factors for pain onset, previous studies examining long-term pain trajectories give mixed results and often overlook how pain fluctuates. This study identified demographic and socioeconomic risk factors for pain progression, remission and recurrence using multistate models to capture the dynamic nature of long-term pain.

Methods: Data were drawn from 9369 adults aged 50-98 from the English Longitudinal Study of Ageing (study years: 2002/03-2021/23). The baseline wave for each participant was their first wave of pain (moderate-severe or mild pain). Pain severity at subsequent waves was categorised into three states: (i) moderate-severe; (ii) mild; or (iii) none. We used multistate models to examine associations of demographic and socioeconomic factors with pain improvement (state 1-2), worsening (state 2-1), remission (state 1-3) and recurrence (state 3-1).

Results: Findings particularly highlighted sex and socioeconomic disparities: compared with males, females were less likely to experience pain improvement (hazard ratio [HR] = 0.84, 95% confidence interval = 0.74-0.96) or remission (HR = 0.72, 0.64-0.80), and more likely to experience recurrence (HR = 1.45, 1.25-1.68). More education was associated with pain improvement (HR = 1.43, 1.16-1.76) and remission (HR = 1.30, 1.07-1.58), and lower risk of worsening (HR = 0.52, 0.42-0.64) and recurrence (HR = 0.67, 0.52-0.85); similar patterns were observed for wealth, with greater wealth associated with more favourable pain trajectories.

Conclusion: Pain fluctuates over time, following socially patterned trajectories, with women and socioeconomically disadvantaged individuals more likely to experience persistent or recurring pain. These findings highlight the importance of risk-stratified approaches, including proactive monitoring and management.

Background: Assessment of physical function, a key outcome in geriatric research, relies on either patient-reported or performance-based assessments. While several patient-reported instruments have been successfully linked to the standardised Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function scale, commonly used performance-based tools, such as the Short Physical Performance Battery (SPPB), remain uncalibrated to this scale. This lack of standardisation limits interpretability, comparability, and integration of physical function data across instruments, studies, and clinical settings.

Objective: To link SPPB scores to the PROMIS Physical Function T-score metric in older adults.

Methods: This analysis is part of the Standardizing-PF project, a prospectively designed cross-sectional study examining the possibility of mapping patient-reported and performance-based assessments onto a common scale. In the present study, 556 older adults (mean age 74 years) from different clinical and community-based settings subsequently completed a generic 20-item PROMIS Physical Function short form (PROMIS-PF20a) and the SPPB. Assumptions of item response theory modelling were investigated. We estimated a unidimensional item response theory-based linking model and derived cross-walks to convert SPPB scores into standardised PROMIS PF T-scores.

Results: SPPB and PROMIS-PF20a were highly correlated (latent correlation = 0.89); assumptions of item response theory modelling were fulfilled. After linking, agreement between observed and linked T-scores was stable across several subsamples.

Conclusions: The SPPB can be meaningfully linked to the PROMIS PF T-score metric, enabling standardised interpretation, comparison, and aggregation of performance-based and self-reported physical function in older adults. We provide a user-friendly score cross-walk table to facilitate application in clinical practise and standardisation in geriatric research.

This study presents the preliminary validation of the WHO Ageism Towards Older Persons Scale (WHO-A-TOPS), a new measure designed to comprehensively assess ageism, whilst capturing its three dimensions (e.g. stereotypes, prejudices, and discrimination based on age). The study evaluated the structural validity, measurement invariance, internal consistency, and construct validity of the WHO-A-TOPS. Data were collected from four countries: Czech Republic, Germany, Israel, and the United Kingdom, with a total sample of 1778 participants aged 20-90 years. Through an iterative process, a 10-item one-factor model was identified, demonstrating acceptable partial scalar measurement invariance across the four countries and invariance across different age groups. Hence, indicating that the new measure can capture a common construct across the four investigated countries and the three age groups. The final 10-item scale captures all three dimensions of ageism: stereotypes, prejudices, and discrimination. The new tool represents an exceptional attempt to develop a measure of high psychometric properties following current state-of-the-art guidelines. The tool can be used across different countries and age groups. The study discusses the implications of these findings for ageism research and practise, highlighting the importance of cross-country validation and the complexities of measuring ageism's multifaceted nature.

Background: To examine associations between accelerometer-derived active weekend warrior (WW) pattern [most moderate to vigorous-intensity physical activity (MVPA) achieved over 1-2 days] vs. MVPA spread more evenly with risks of incident probable sarcopenia, sarcopenia and falls.

Methods and findings: This prospective cohort study comprises three substudies (probable sarcopenia, confirmed sarcopenia and falls). Objective physical activity data were collected from Axivity AX3 wrist-worn triaxial accelerometers on their dominant wrist for 7 consecutive days. Three MVPA patterns were compared: active WW (≥150 min/week and ≥50% of total MVPA over 1-2 days), active regular (≥150 min/week but not meeting active WW), and inactive (<150 min/week). Over 7.8 years median follow-up, there were 1785 (8.4%) incident (probable) sarcopenia, 1855 (8.7%) incident sarcopenia and 4166 (4.9%) incident falls. Compared to inactive participants, the effect sizes for active WW pattern at the guideline-based threshold with ≥50% of total MVPA over 1-2 days were: probable sarcopenia {hazard ratio [HR], 0.79 [95% confidence interval (CI), 0.70-0.89], P = 1.5 × 10-4}, sarcopenia [HR, 0.74 (95% CI, 0.63-0.87), P = 6.6 × 10-4], falls [HR, 0.79 (95% CI, 0.72-0.85), P = 7.4 × 10-8] and recurrent falls [HR, 0.82 (95% CI, 0.75-0.90), P = 9.1 × 10-5]. The active WW pattern was associated with a 24%-32% reduction in the risk of (probable) sarcopenia, while active regular pattern was associated with a 12%-23% reduction in the risk. Regardless of the thresholds defining the active WW group, both activity patterns (active regular and active WW) showed a lower risk of falls.

Conclusions: Weekly physical activity concentrated in 1-2 days had a similarly low risk of sarcopenia and falls as a regular active pattern. Even resistance training 1-2 days per week can serve as an effective public-health strategy for preventing sarcopenia and falls.

Background: Mobility, defined as movement in all its forms, is a hallmark of healthy ageing. As wearable technologies become increasingly integrated into population health surveillance and ageing research, the absence of standardised terminology, measurement protocols and reporting practices presents a major barrier to progress. This consensus exercise aimed to establish minimum standards for measuring mobility with wearable technology in ageing populations and set priorities for future research in the field.

Methods: A two-day, in-person consensus meeting was convened with 24 international experts in ageing, mobility and digital health. Using a modified nominal group technique facilitated by a trained moderator, participants engaged in structured small-group brainstorming, followed by iterative large-group discussions. Consensus was achieved through anonymised digital voting on proposed measures, principles and priorities.

Findings: Consensus (≥80% agreement) was reached on 20 core device-derived mobility measures and 30 guiding principles for the optimal use of wearable technology in older populations. Experts also identified and ranked 16 priority areas for future research, with the top five including: (i) longitudinal studies and data collection, (ii) digital biomarkers and health outcomes, (iii) contextual data capture, (iv) algorithm development and validation and (v) integration with healthcare systems.

Interpretations: These consensus-based standards provide a foundational framework for the consistent and transparent use of wearable devices in ageing research and practice. They can inform the development of regulations and guidelines, support harmonisation across studies and chart a path for future research to enhance the utility and impact of wearable technologies in ageing populations.