Stress and Health最新文献

This study assessed posttraumatic stress (PTSD) symptom changes among active-duty and military veterans before and after participating in a non-exposure-based trauma-informed aquatic therapy treatment. Participants engaged in up to eight treatment sessions over 8-10 weeks. Each individual treatment session was practitioner-led, lasted approximately 50-min, and performed at a private treatment facility. This single-arm retrospective trial enroled 111 participants during calendar year 2023 for treatment. All participants had a prior medical diagnosis of PTSD as verified by medical/military records or a physician letter. The primary study outcome was changes in PTSD symptoms at baseline (pre-treatment) and after up to 8 treatment sessions using the PTSD Checklist Military Version (PCL-M). A total of 86/111 enroled participants (77.5%) completed at least four sessions of treatment for post-testing. PCL-M scores averaged 56.2 (16.2) among all enrollees at baseline and 39.3 (12.9) for those completing 4+ sessions of treatment. The mean PCL-M change for the 86 participants with 4+ sessions was 14.4 (14.2) points, p < 0.001. Sixty-four percent of the latter showed a PCL-M score change ≥ 10 points and 36% showed a change ≥ 20 points. The results of this retrospective trial provide preliminary support for trauma-informed aquatic therapy as a potential non-exposure-based treatment for reducing PTSD symptoms among military populations.

Frailty is characterised by a loss of function across several domains but is not an inevitable aspect of ageing and can be reversed with intervention. Determining those who are more likely to become frail before physical deficits become manifest will allow earlier intervention. One promising indicator of the potential for frailty is allostatic load, a physiological status associated with prolonged stress that is, characterised by multisystem dysfunction. Previous research has sought to understand the links between allostatic load and frailty, but has not yet explored whether allostatic load may be a predictive factor at younger ages and-if so-at what age it may be predictive. The present study sets out establish whether allostatic load can be used as a predictive indicator of frailty. Using the English Longitudinal Survey on Ageing (ELSA) data with an anticipated sample of 1500 people between 50 and 89 years old, time series analysis will determine if, and at what age, allostatic load may be predictive of pre-frailty and frailty. The findings of these analyses may be supportive of early identification of frailty by establishing an age at which a diagnostic test for allostatic load may prove a critical indicator for future frailty.

U.S. Air Force remotely piloted aircraft (USAF RPA) personnel face diverse stressors negatively affecting psychological health and military readiness. Prior research in diverse populations supports predictable impact of the COVID-19 pandemic on occupational stressors, burnout, and more distal outcomes. Extending earlier studies linking broad variables (e.g., COVID-19 threat → work stress → burnout), the current study tests and refines an expanded mediation model based on multiple distinct pandemic concerns, occupational stressors, and burnout facets as antecedents of psychological distress mid-pandemic in RPA personnel (N = 496). Differential representation of demands, resources, and rewards evident across distinct occupational stressors in light of job demands/resources theory guided specification of mediated pathways. SEM analysis yielded moderate fit. Following removal of non-significant paths and addition of two interpretable direct paths, fit was improved, yielding seven dominant pandemic concern → occupational stressor → burnout → psychological distress pathways. In support of domain specification, five 'hub' variables (pandemic-driven change, personal stressors, workload, leader communication, and exhaustion) emerged as key intervention targets in mitigating distress in the USAF RPA community and similar populations during future pandemic-related crises.

The U.S. Army Special Forces Assessment and Selection course (SFAS) is an extremely stressful, physically and mentally challenging 19-20 days long selection procedure. Only 30%-40% of soldiers who volunteer for it complete it. The purpose of SFAS is to identify soldiers who can complete 1-2 years of physically and mentally challenging training for the Special Forces and be successful Special Forces soldiers thereafter. This study examined association of pre-course self-reported mood state and sleep quality and quantity with subsequent success or failure at SFAS. Data from 780 male soldiers collected in 2015-2017 were analysed. Prior to SFAS, the Profile of Mood States (POMS), Dimension of Anger Reactivity (DAR), Duke University Social Support Questionnaire (Duke-SSQ), General Anxiety Disorder and Depression inventories (GAD-7), and Pittsburgh Sleep Quality Index (PSQI) were administered. Group differences among these variables and their ability to predict selection versus non-selection were assessed. There were significant differences in pre-SFAS mood and sleep in selected versus non-selected volunteers. Selected candidates reported more positive mood (POMS vigour, friendliness), less negative mood (POMS depression, anger, fatigue, confusion), less anger (DAR), and less social support (Duke-SSQ). Selected candidates reported longer and higher quality sleep (PSQI) than non-selected soldiers. These differences were not sufficient to serve as an accurate predictive model based on logistic regression, as the best-fit model accounted for 4.9% of the variance. In conclusion, there were differences in pre-course mood state and sleep between those who succeeded or failed a stressful course that selects individuals for elite military training and service, but they were not of sufficient strength to predict individual success of failure.

The rise in mental health conditions and stress has attracted global attention. Non-pharmacological and traditional approaches like meditative practices are showing promising results. Therefore, the aim of the study was to evaluate the effect of Heartfulness meditation on stress biomarkers, burnout, and well-being. A double-arm prospective randomized controlled study was carried out on 100 participants aged between 18 and 24 years, experiencing moderate to high perceived stress as assessed by the Perceived Stress Scale (PSS-10). These participants were randomized into a study group (meditation) and control group (sham meditation). An intervention of Heartfulness meditation was carried out daily for 12 weeks. Psychometric analysis was carried out to study burnout (exhaustion, cynicism and professional efficacy) and well-being using the standard validated questionnaires- Maslach Burnout Inventory (MBI) and WHO-Well-being Index (WHO-WBI). Biochemical analysis was also carried out to study psychological stress (serum cortisol), and oxidative stress (serum nitrate/nitrite and serum malondialdehyde (MDA) at baseline and post-intervention. Statistical analysis was carried out using the IBM SPSS software version 26.0. p values < 0.05 were considered statistically significant. A significant increase in serum nitrate/nitrite levels, professional efficacy, and well-being, and a significant decrease in measures such as exhaustion, cynicism, and cortisol levels were observed in the study group than the control group post-intervention. A significant negative correlation was also observed between serum MDA and well-being, whereas a positive correlation was observed between MDA and cortisol. The findings from this research suggest the role of Heartfulness meditation in reducing stress and burnout along with improving the well-being of an individual. Therefore, Heartfulness meditation can be used as a potential tool to improve mental health and well-being. However, future studies with a larger number of samples are needed to strengthen our findings. Trial Registration: Clinical Trial Registry of India: CTRI/2023/10/058,423 (https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=ODIyOTA=&Enc=&userName=CTRI/2023/10/058423).

Online self-guided interventions appear efficacious for alleviating some mental health concerns. However, among persons who are offered online interventions, only a fraction access them (i.e., achieve uptake). Machine learning methods may be useful to predict who will achieve uptake, which could inform improvements to interventions and their methods of delivery. We used secondary data from participants given access to a self-guided online stress intervention during the COVID-19 pandemic in a randomised trial (N = 301, among whom 158 achieved uptake). This study built and evaluated several models for predicting uptake. Putative predictors included demographic characteristics, mental health service utilization and interest, and mental health symptoms assessed before participants were provided access to the intervention. The best-performing model, a linear support vector machine model, had 70% accuracy and 0.70 area under the receiver operating characteristics curve in a held-out dataset, though these metrics were not significantly better than competitor models. Model inspection revealed that participants who reported interest in mental health treatment and lesbian, gay, bisexual, and other sexual minority participants were more likely to achieve uptake. Additionally, male participants were less likely to achieve uptake. The best-performing machine learning model achieved an acceptable level of performance in predicting uptake. Self-reported treatment interest was especially predictive of uptake. Future research should attempt to understand gender and sexual orientation differences in self-guided online mental health intervention uptake. Additionally, research should evaluate the utility of machine learning to inform targeted motivational enhancement of those less likely to achieve uptake.

To systematically evaluate the intervention effect of repetitive transcranial magnetic stimulation (rTMS) combined with pharmacological interventions on sleep quality and depressive symptoms in patients with depression, identify optimal stimulation parameters, and explore potential clinical applications to facilitate individualised therapeutic strategies. Databases including Pubmed, Web of Science, Cochrane Library, Embase, CNKI, Wanfang Medical Database, and VIP database were searched up to 31 December 2024, for randomized controlled trials (RCTs) assessing rTMS combined with pharmacological intervention for sleep disorders and depressive symptoms in patients with depression. Data analysis was performed using Stata software. 17 RCTs involving 1667 patients were included. Meta-analysis revealed that rTMS significantly improved sleep quality (SMD = -0.57, 95% CI: -1.02 to -0.12, P < 0.05) and reduced depressive symptoms (SMD = -0.73, 95% CI: -1.37 to -0.10, P < 0.05). Subgroup analyses showed that the optimal parameters for improving sleep quality were high-frequency rTMS targeting the left dorsolateral prefrontal cortex, high stimulation intensity, low total pulse count (< 1200 pulses), session duration ≤ 20 min daily, for 5-8 weeks. For depressive symptoms, a daily treatment duration of 21-30 min was more effective under similar parameter conditions. rTMS effectively improves sleep quality and alleviates depressive symptoms in patients with depression, showing a dose-dependent effect with stimulation parameters. However, in patients with a prolonged disease course or greater symptom severity, particularly those with vascular and other neurological comorbidities, rTMS alone may be insufficient. Integrating additional therapeutic strategies or tailoring personalised treatment protocols may be necessary to optimise clinical outcomes. Future research should further explore the synergistic potential of rTMS combined with orexin receptor antagonists (ORAs), offering a novel, multimodal approach for managing depression with comorbid insomnia.

The COVID-19 pandemic significantly impacted the psychological well-being of the general population. However, there are limited studies that examine its mental health effects on patients who have experienced traumatic injuries and tracked their recovery over time. This study aimed to: (1) compare the rates and severity of post-traumatic stress disorder (PTSD) and depression between patients who sustained traumatic injuries before the COVID-19 pandemic (pre-pandemic) and those injured during the pandemic (peri-pandemic); and (2) assess whether the degree of pandemic-related stress (e.g., worry about infection, social isolation, loss of home/job) predicted the severity of PTSD or depression symptoms. Participants (N = 198) were recruited from a Level 1 Trauma Centre in Southeastern Wisconsin following admission for a single-incident traumatic injury. Symptoms of PTSD and depression were assessed during hospitalisation and at three additional points within the subsequent 6 months. Self-report measures were used to evaluate PTSD and depression severity among patients injured before (pre-pandemic; n = 126) and during (peri-pandemic; n = 73) the pandemic. Peri-pandemic participants also completed a modified version of the COVID-19 Family Stress Screener to measure pandemic-related stress. Exploratory factor analysis was conducted to identify the dimensions of pandemic-related stress in our sample. The findings indicated that participants injured during the pandemic exhibited higher symptoms of PTSD and depression compared to those injured before the pandemic. Additionally, greater pandemic-related stress correlated with elevated levels of depression and PTSD at baseline. Our results highlight that the broader context in which patients recover from injuries can intensify the negative mental health consequences of traumatic injury. This underscores the need for enhanced access to psychological services for trauma patients, particularly during major societal stressors like a global pandemic.

According to the Dimensional Model of Adversity and Psychopathology (DMAP), childhood trauma (CT) can be categorised into two dimensions: abuse and neglect. While CT is widely recognized as a risk factor for obsessive-compulsive symptoms (OCS), the specific dimension that primarily contributes to this risk remains unclear. This study sought to distinguish the effects of different CT dimensions on the developmental trajectory of OCS. A total of 3535 Chinese college freshmen (Age _Mean = 18.01, Age _SD = 0.77; 65.60% female) participated in a 3-year, 5-waves longitudinal tracking study. A latent growth curve model (LGCM) was constructed to examine the effects of two CT dimensions (abuse and neglect) on the developmental trajectory of OCS. Sex and recent perceived stress were also added to the conditional LGCM. Results showed that the rates of 'moderate to severe' emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect were 3.68%, 3.62%, 5.57%, 10.46%, and 19.54%, respectively. The unconditional LGCM revealed a U-shaped developmental trajectory of OCS. The conditional LGCM revealed that childhood experiences of abuse, rather than neglect, significantly predicted the intercept (β = 0.159, p < 0.001), the linear slope (β = -0.222, p < 0.01), and the quadratic slope (β = 0.195, p < 0.05) of the trajectory of OCS. Specifically, higher abuse levels were associated with higher initial OCS levels and a slower rate in linear downtrend of OCS over time, resulting in a U-shaped trend. Besides, sex did not predict the developmental trajectory of OCS. These findings highlight the association between childhood experiences of abuse, rather than neglect, with the development of OCS and may provide targeted direction and guidance for preventing OCS among Chinese college students.

Heightened reactivity to ambiguous emotional stimuli, such as surprized faces, is a transdiagnostic psychopathology risk factor. Women show elevated amygdala activation to ambiguous emotional stimuli relative to men, which may underlie their significantly higher risk for mood disorders. Moreover, there are sex/gender differences in the effects of stress on both emotion processing and emotion regulation, with greater impact of stress on negative emotionality in females. We predicted that chronic stress would be associated with stronger amygdala activation to surprized faces, and these effects would be amplified in girls/women. We tested the interactions of chronic stress and gender/sex on amygdala activity in a sample of 297 healthy participants (59% girls/women, age range 6-75 years) who provided a saliva sample and who viewed emotional face stimuli while undergoing functional neuroimaging. Saliva samples were assayed for two markers of chronic stress: Epstein-Barr Virus (EBV) expression and diversity of Lactobacilli species. Among girls/women, higher chronic stress was associated with greater amygdala activation to ambiguous emotional images than lower stress exposure, although this effect was not statistically significant. Counter to predictions, the reverse effect was found among boys/men (i.e., higher stress exposure was associated with lower amygdala activation). Results were similar across left and right amygdalae, and across both stress measures. Although our findings are preliminary and should be replicated, they align with findings on gender differences in valence bias, and broadly support the hypothesis that there are gender/sex differences in the effects of chronic stress on neural reactivity to emotional ambiguity, particularly in areas of the brain sensitive to emotion regulation. Possibly, stress does not universally increase negativity, but instead amplifies default emotional biases-which for boys/men, may result in less amygdala reactivity.