Applied psychology. Health and well-being最新文献

Cardiac vagal tone has been associated with mental and physical health and presents opportunities for preventive and therapeutic applications in mental health and cardiovascular medicine. Vagally-mediated heart rate variability (vmHRV), a marker of cardiac vagal tone, has been associated with multiple factors related to well-being. Recent research further suggests that stress regulation, social connection, and lifestyle jointly contribute to improved well-being. In a large-scale study (n = 2252), we measured depressive symptoms, work stress, social support, and physical activity (T1) and then investigated whether these factors were prospectively associated with resting vmHRV measured at the 10-year follow-up assessment (T2). We also investigated whether these factors and their changes from T1 to T2 were associated with resting vmHRV at T2. Results showed that more physical activity was associated with higher resting vmHRV at T2. However, resting vmHRV was not associated with other factors at T2 and in longitudinal analyses. Latent profile analysis revealed that individuals maintaining moderate physical activity over these years showed higher resting vmHRV. This large population-based longitudinal study conducted in Belgium provides important evidence supporting the link between cardiac vagal tone and physical activity but does not support an association with depressive symptoms, work stress, and social support.

Stressful events can adversely affect individuals' well-being and mental health, increasing the likelihood of developing symptoms and psychopathological disorders. This study aimed to assess the effectiveness of three brief individual intervention programs—positive cognitive–behavioral, mindfulness, and brief systemic—for reducing emotional distress and enhancing well-being in individuals exposed to a stressful event within the past 3 months. Participants (N = 147) were randomly assigned to one of the three intervention programs or a waiting-list control group. Symptoms of post-traumatic stress and depression, post-traumatic growth (PTG), and life satisfaction were assessed at three points: before the intervention, 1 month after the intervention, and at the 6-month follow-up. Analyses revealed significant improvements across all four variables at post-intervention, with moderate to large effect sizes, and no significant differences between the programs. These findings support the effectiveness of brief intervention programs in reducing emotional distress and enhancing well-being. The contributions and limitations of these brief interventions for individuals exposed to significant life events are discussed.

Under the dual influences of aging and digitization, it is of great significance to reveal the key factors that affect the life satisfaction of older adults in a digital society. This study investigates the determinants of life satisfaction by analyzing survey data from 1,102 older adults in China. Four machine learning algorithms (Regularized Logistic Regression, Random Forest, XGBoost, and Support Vector Machine) were systematically evaluated to identify the most effective predictive model. The XGBoost model demonstrated superior performance. An Interpretable Machine Learning (IML) framework (XGBoost-SHAP-PDP) was then employed to move beyond prediction and explain how these factors operate. The results showed that the feature importance analysis included economic situation, digital competence, digital self-efficacy, and use intensity as the main predictors. The SHAP analysis revealed a significant asymmetry: only digital competence is positively rewarding, while use intensity functions primarily as a one-way penalty for low use, offering no significant positive impact. Furthermore, the PDP analysis identified a non-linear zero-to-activation dynamic, showing that the benefits of digital competence do not appear until a specific proficiency threshold is attained. These findings provide quantitative refinements to digital divide theory, demonstrating that the quality of digital engagement, not the quantity, is the key determinant of life satisfaction. It is necessary to shift from promoting basic access toward intensive training programs designed to help older adults cross this functional competence threshold.

For effective management of extreme rainstorm disasters, a timely understanding of the public emotional perception of risk is crucial to enhancing governmental risk communication and emergency response strategies. Therefore, this study develops a sentiment analysis framework that combines a rainstorm-specific sentiment lexicon with a deep learning model. By utilizing large-scale social media data, the framework further achieves dynamic monitoring and early warning of the public emotional perception of risk during extreme rainstorm events. Specifically, this paper employed text mining techniques to analyze the emotional features of 51,222 Weibo posts related to rainstorm disasters, thereby constructing a specialized sentiment lexicon. The lexicon was then integrated into a TextCNN model to create a knowledge-enhanced hybrid sentiment analysis model. Compared with baseline models including GPT-4o, LLaMA-3, and RoBERTa, this hybrid method achieved optimal performance across all evaluation metrics, with accuracy and F1-score improvements of 10.9% and 9.9%, respectively. Moreover, an empirical analysis of the 2023 Zhuozhou extreme rainstorm disaster validated the framework's efficacy. Findings reveal that our method can effectively monitor the public emotional perception of risk and provide early warning of risk anomalies during severe rainstorms by using the emotion index, which yields valuable insights for governmental bodies to accurately understand public risk perception and the dynamic evolution of disaster scenarios.

Positive exercise experiences are associated with greater health benefits. However, no large-scale synthesis has been conducted to clarify how music influences the affective responses to acute exercise. This study systematically examined the effects of music on affective responses to acute exercise. The Web of Science, PubMed, Cochrane CENTRAL, and ProQuest databases were systematically searched. A total of 507 effect sizes extracted from 59 studies were included in the multilevel meta-analysis. The results demonstrated that music had a positive effect on affective valence (g = 0.403, 95% CI [0.317, 0.489]) and arousal (g = 0.391, 95% CI [0.252, 0.530]) in response to acute exercise. Moderation analyses revealed that exercise intensity, music tempo, and motivational quality moderated the effects of music on both valence and arousal, while exercise habits moderated the effect on valence. Sex, exercise type, selection, and delivery mode were not significant moderators. This study highlights the important role of music in optimizing exercise experience, which may create favorable conditions for long-term exercise engagement and enhance health benefits.

Previous studies have demonstrated that mindfulness-enhanced exercise training (MEET) exerts positive effects on mental health of college students. This research aims to compare the similarities and differences in efficacy, trajectories of effects, and the underly mechanism between two distinct types of MEET, which integrates mindfulness practices with tai chi (MTC) or resistance training (MR). A total of 149 undergraduate students were randomly assigned to either the MTC or MR group. Participants attended 26 weekly sessions. Mindfulness, anxiety, and well-being were assessed at baseline, post-intervention, and 4-month follow-up, with 25 weekly measurements tracking temporal changes. Mixed analysis of variance (ANOVA) was used to evaluate intervention effects, while Hierarchical Linear Modeling (HLM) and Dynamic Structural Equation Modeling (DSEM) were used to analyze longitudinal trajectories and dynamic relationships. Mixed ANOVAs revealed that both interventions improved mindfulness and well-being and reduced anxiety, with benefits sustained at follow-up. HLM indicated linear improvement trajectories, reflecting cumulative gains. Interaction analyses revealed that MTC produced faster initial mindfulness improvements, whereas MR yielded stronger well-being gains in later phases. DSEM identified a bidirectional relationship: mindfulness reduced anxiety and enhanced well-being, while these changes reinforced mindfulness. These findings suggest that MEET enhances mental health in students regardless of exercise modality, supporting mindfulness as a flexible component of wellness programs.

This study maps 1941 Web of Science articles (2000–May 2025) to clarify how mindfulness research relates to psychological well-being and priorities under Sustainable Development Goal 3. Using network and temporal analyses, we identify 11 thematic clusters spanning clinical care, workplace motivation and self-determination, cognitive-neuroscience mechanisms, measurement/psychometrics, family and developmental settings, trauma recovery, and cardiometabolic health. Publication activity has increased substantially, and the thematic center of gravity has shifted from symptom reduction toward resilience-oriented and technology-enabled applications. Emerging fronts include self-compassion and related strengths, interoception and mind–body practices, and digital delivery (telehealth/mobile health). Persistent gaps involve under-representation of non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) populations, limited attention to eudaimonic outcomes, incomplete specification of mechanisms, and sparse long-term or implementation evidence. By integrating two previously parallel literatures, the review offers a concise field map that highlights established anchors and actionable frontiers. The results inform the design, targeting, and evaluation of mindfulness programs that advance population mental health and flourishing.

Severe mental disorders (SMDs), such as schizophrenia, bipolar disorder, and personality disorders, present significant challenges for stress and anxiety management due to cognitive vulnerabilities. Self-regulated learning (SRL) models offer a structured framework for analyzing self-management strategies, yet their application in mental health contexts remains underexplored. This study applies Pintrich's (2000) SRL model to examine how individuals with SMDs manage stress and anxiety, identifying strengths and gaps across the forethought, monitoring, control, and reaction/reflection phases. A qualitative approach was employed, analyzing focus group discussions with 28 adults diagnosed with SMDs. Thematic analysis, conducted using NVivo, combined inductive coding and theory-driven interpretation based on the SRL framework. Results show that the forethought phase was most frequently represented, emphasizing participants' cognitive preparation and anticipation of stressors. The control phase followed, highlighting behavioral and contextual coping strategies such as relaxation, problem-solving, and support-seeking. However, the monitoring and reaction/reflection phases were less developed, with limited focus on real-time awareness and evaluation. These findings point to the need for tailored interventions and highlight theoretical adaptations required to extend SRL to clinical contexts. We discuss how integrating SRL with recovery-oriented frameworks could support more adaptive, person-centered strategies for managing stress and anxiety in SMDs.

This systematic review aimed to consolidate evidence regarding the effect of skin diseases (SD) on body image (BI) and to examine the sociodemographic, clinical, and psychosocial correlates of BI in individuals with SD. A comprehensive search was conducted in December 2024 across nine databases, including MEDLINE, Web of Knowledge, PsycINFO, EBSCO, BVSALUD, Scopus, PubMed, Google Scholar, and LILACS. Twenty-five case–control and cross-sectional studies met the inclusion criteria. The findings revealed greater body dissatisfaction in individuals with SD compared to control groups. Age was not associated with BI, and results on gender differences were mixed—some studies found greater dissatisfaction among women, while others showed no significant differences. Associations between BI and clinical features such as disease severity, duration, and disability were inconclusive due to limited data. However, BI showed strong correlations with quality of life, depression, anxiety, self-esteem, and aspects of intimate and social relationships. Overall, the evidence suggests that individuals with SD experience negative changes across multiple dimensions of body experience, which are associated with poorer psychosocial health outcomes. Positive body image may serve as a valuable target for interventions aimed at enhancing well-being among individuals with chronic skin conditions, highlighting the psychosomatic significance of BI and the need for integrated psychological and medical approaches.

The Lifestyles of Health and Sustainability (LOHAS) paradigm is increasingly cited as a bridge between personal well-being, environmental sustainability, and ethical consumption. To chart its scholarly evolution, we conducted a bibliometric analysis in accordance with PRISMA, covering 743 Web of Science articles published from 1993 to 2024. VOSviewer network maps of keyword co-occurrences, co-citations, and country collaborations revealed five dominant research clusters: (1) sustainability and consumer behavior, (2) physical activity and chronic disease prevention, (3) lifestyle, mental health, and well-being, (4) measurement and intervention design, and (5) environment, public policy, and social sustainability. Annual output has climbed from one paper in 1993 to 110 papers in 2024, and centrality analyses place ‘sustainability,’ ‘health,’ and ‘physical activity’ at the core of the field. Although recent studies increasingly probe psychological mechanisms—such as behavior change, social support, and mindfulness—these remain less developed than environmental or consumption themes. We conclude that LOHAS scholarship now sits at an interdisciplinary inflection point and recommend deeper engagement with Behavioral Theory, broader international collaboration, and rigorous mixed-method designs that track the dual benefits of human health and planetary sustainability.