高齢者のメンタルヘルス支援に関する新研究(Swansea study offers practical insights to support mental health in older adults)

ad

2025-09-04 スウォンジー大学

Web要約 の発言:
スウォンジー大学の研究は、英国バイオバンクの8,000名超(平均65歳)のデータを解析し、高齢者のメンタルヘルスに影響する要因を明らかにした。最も重要なのは「意味志向行動」で、幸福感を高め心理的苦痛を減らすとともに、社会的つながりやレジリエンスを強化する役割を持つことが分かった。また、心拍変動(HRV)はストレス適応力の指標として幸福感と関連し、生涯にわたる困難経験は心理的苦痛を増大させる強い要因とされた。さらに幸福と苦痛は単一の連続体ではなく、非線形的かつ複雑な関係を持ち、HRVや困難経験の影響も段階的に異なるパターンを示した。本研究は、症状の軽減だけでなく「意味ある活動」「社会的つながり」「身体的適応力」を育む支援が高齢者の心の健康維持に不可欠であることを示している。

<関連情報>

高齢者の不健康と健康の経路、予測因子、逆説:英国バイオバンク研究からの知見 Pathways, predictors and paradoxes of illbeing and wellbeing in older adults: Insights from a UK Biobank study

Tom C. Gordon,Andrew H. Kemp,Darren J. Edwards
PLOS Mental
Health  Published: September 3, 2025
DOI:https://doi.org/10.1371/journal.pmen.0000336

高齢者のメンタルヘルス支援に関する新研究(Swansea study offers practical insights to support mental health in older adults)

Abstract

This study presents the first UK Biobank analysis to concurrently model subjective wellbeing and illbeing within a unified biopsychosocial framework, offering a novel, data-rich perspective on psychological functioning in later life. While wellbeing and illbeing are often studied in isolation, there is growing recognition that their determinants may differ in kind and form. We address this gap by examining how biological, psychological, and social factors dynamically shape both outcomes in a large community-dwelling sample. Drawing on data from 8,047 participants (mean age = 64.8 years; 46.7% male; 90.7% White British), we constructed a theory-informed partial least squares structural equation model (PLS-SEM) linking heart rate variability (HRV), meaning-oriented behaviour (MOB), resilience, social connectedness, and lifetime adversity to wellbeing and illbeing. Model robustness was supported through 10,000-sample bootstrapping and split-half replication. Network centrality analysis (NCA) was used to identify key drivers, and Bayesian regression was applied to test non-linear functional forms for each path, validated using a held-out test dataset. MOB emerged as the strongest direct predictor of both increased wellbeing and reduced illbeing. HRV influenced wellbeing indirectly via psychosocial mediators. Adversity had the largest total effect on illbeing but no direct effect on wellbeing. Together, predictors accounted for ~52% of variance in both outcomes. Bayesian models revealed exponential, cubic, and logarithmic forms, indicating that conditions optimising wellbeing are not merely the inverse of those reducing illbeing. These findings offer a detailed mapping of non-linear biopsychosocial pathways in older adults and challenge the assumption that wellbeing and illbeing lie on a single continuum. The study provides a robust empirical foundation for developing process-based, context-sensitive mental health interventions. Longitudinal and more demographically diverse studies are now needed to test causal directions and broader generalisability.

医療・健康
ad
ad
Follow
ad
タイトルとURLをコピーしました