Multicomponent Stress Research Articles

Exploring Patient Perspectives on a 12-Week Online, Stress Reduction Intervention in Inflammatory Bowel Disease.

Online stress reduction interventions may be useful adjuncts to standard medical therapies for inflammatory bowel disease (IBD). As part of the evaluation of a 12-week randomized control trial (RCT) of an online multicomponent stress reduction program, our aim for the current study was to use qualitative methods to more deeply explore the patient experience with the online programming. Upon completion of the 12-week RCT, all intervention participants were invited to participate in semistructured interviews. A qualitative descriptive approach was used. Interviews were analyzed through a theoretical thematic analysis process, whereby transcripts were coded, and codes then grouped into larger categories and themes. A total of 56 interviews were analyzed with the emergence of 3 main themes: (1) IBD as a source of stress and uncertainty, (2) understanding the positive impacts of the stress reduction program, and (3) suggested strategies to enhance program desirability. IBD was described as causing uncertainty, significant disruptions to daily activities, and stress, which in turn worsened symptoms. The online program was associated with a perceived reduction in IBD symptom burden, an increased ability to manage daily and disease-associated stressors, and a more positive mindset. Variation in program content and fostering connections with others in the IBD community were identified as potential strategies to enhance future programming. This qualitative companion study highlights the power of the patient voice to deepen our understanding of the impact of IBD, and the potential benefit of an online stress reduction program including suggestions for iterative refinement.

Multicomponent Stress-Strength Model Based on Generalized Progressive Hybrid Censoring Scheme: A Statistical Analysis.

The statistical inference of the reliability and parameters of the stress–strength model has received great attention in the field of reliability analysis. When following the generalized progressive hybrid censoring (GPHC) scheme, it is important to discuss the point estimate and interval estimate of the reliability of the multicomponent stress–strength (MSS) model, in which the stress and the strength variables are derived from different distributions by assuming that stress follows the Chen distribution and that strength follows the Gompertz distribution. In the present study, the Newton–Raphson method was adopted to derive the maximum likelihood estimation (MLE) of the model parameters, and the corresponding asymptotic distribution was adopted to construct the asymptotic confidence interval (ACI). Subsequently, the exact confidence interval (ECI) of the parameters was calculated. A hybrid Markov chain Monte Carlo (MCMC) method was adopted to determine the approximate Bayesian estimation (BE) of the unknown parameters and the high posterior density credible interval (HPDCI). A simulation study with the actual dataset was conducted for the BEs with squared error loss function (SELF) and the MLEs of the model parameters and reliability, comparing the bias and mean squares errors (MSE). In addition, the three interval estimates were compared in terms of the average interval length (AIL) and coverage probability (CP).

Reliability inference for multicomponent stress–strength model from Kumaraswamy-G family of distributions based on progressively first failure censored samples

Reliability inference for multicomponent stress–strength model from Kumaraswamy-G family of distributions based on progressively first failure censored samples

A randomized controlled trial of a multicomponent online stress reduction intervention in inflammatory bowel disease.

Background:Psychological stress negatively impacts inflammatory bowel disease (IBD) outcomes. Patients have prioritized access to online interventions; yet, the data on these have been limited by mixed in-person/online interventions, low adherence, and non-randomized controlled trial (RCT) design.Objectives:We assessed the efficacy of and adherence to a 12-week online multicomponent stress reduction intervention in IBD.Design:This is a RCT.Methods:Adult participants on stable IBD medical therapy with elevated stress levels from four centers were randomized to intervention or control groups. Intervention participants received a 12-week online program including a weekly yoga, breathwork and meditation video (target 2–3 times/week), a weekly cognitive behavioral therapy/positive psychology informed video activity, and weekly 10-min check-ins by a study team member. Control participants received weekly motivational messages by email. All patients received standard of care IBD therapy. The primary outcome was Cohen’s Perceived Stress Scale (PSS). Secondary outcomes evaluated mental health, resilience, health-related quality of life (HRQoL), symptom indices, acceptability, adherence, and inflammatory biomarkers. Analysis of covariance was used to determine between-group differences.Results:Of 150 screened patients, 101 were randomized to the intervention (n = 49) and control (n = 52) groups (mean age: 42.5 ± 14.1 years; M:F 1:3, 48% with ulcerative colitis and 52% with Crohn’s disease). The between-group PSS improved by 22.4% (95% confidence interval, 10.5–34.3, p < 0.001). Significant improvements were seen in mental health, resilience, and HRQoL measures, with a median satisfaction score of 89/100 at the end of the 12 weeks. In the 44/49 patients who completed the intervention, 91% achieved program adherence targets.Conclusion:This 12-week online intervention improved perceived stress, mental health, and HRQoL, but did not impact IBD symptom indices or inflammatory biomarkers. The program was readily adopted and adhered to by participants with high retention rates. After iterative refinement based on participant feedback, future studies will evaluate the impact of a longer/more intense intervention on disease course.Registration:ClinicalTrials.gov Identifier NCT03831750Plain Language Summary An online stress reduction intervention in inflammatory bowel disease patients improves stress, mental health, and quality of life People with inflammatory bowel disease (IBD) have high levels of stress, anxiety, and depression. Although IBD patients have expressed the need for online mental wellness interventions, the existing data to support these interventions in IBD are limited. In this trial, 101 IBD patients had the chance to participate in a 12-week online stress reduction intervention. In those patients randomly selected to participate in the online intervention, each week they received the following: a 20- to 30-min yoga, breathwork, and meditation video that they were asked to do 2–3 times a week, a 10- to 20-min mental wellness activity they were asked to do once during the week, and a 10-min telephone check-in with a study team member. Participants who were not selected to use the online intervention received a weekly motivational message by email. In all, 90 of the 101 participants (89%) completed the study with the mean age of participants being 43 years and the majority being females (75%). Ninety-one percent of participants who completed the intervention met the program target of doing the yoga, breathwork, and meditation video at least 2 times per week. Significant improvements were seen in perceived stress (by 22.4%), depression (by 29.5%), anxiety (by 23.7%), resilience (by 10.6%), and quality of life (by 8.9%). No changes were seen in IBD severity or in blood markers of inflammation. In conclusion, this study demonstrates evidence that a 12-week online stress reduction intervention had low dropout rates, high adherence and beneficial effects on stress, mental health, and quality of life measures. Continued feedback will be sought from study participants and our IBD patient partners to refine the intervention and assess the impact in future studies of patients with active IBD, as well as the impact of a longer/more intense intervention.

INDIVIDUAL AND TYPOLOGICAL FEATURES OF THE RESPONSE OF LABORATORY RATS TO MULTI-COMPONENT STRESS

INDIVIDUAL AND TYPOLOGICAL FEATURES OF THE RESPONSE OF LABORATORY RATS TO MULTI-COMPONENT STRESS

Do coping strategies really affect cardiovascular events? The Isfahan cohort study of adults in Eastern Mediterranean Regional Office.

Psychological factors are among the most suspected indicators which may cause atherosclerosis. Coping strategies modifying psychological stress may be significantly associated with health outcomes. However, little is known about the influence of adaptive and maladaptive coping strategies on major adverse cardiovascular disease (CVD) events. The purpose of this study is to examine this idea among a sample of adults. Design: cohort study. The Isfahan cohort study (ICS) is a longitudinal population-based, prospective study. Participants (N=6323 individuals aged 35 years or greater at baseline) were selected by multistage random sampling with 6-year intervals (i.e. 2001: 6323 individuals, 2007: 3296 individuals, and 2013: 1706 individuals). Adaptive and maladaptive coping strategies were evaluated by a multicomponent self-administered stress management paper-based questionnaire. All CVD events were confirmed by a blinded panel of experts and a marginal cox regression model was used to model the survival data. Adaptive coping strategies could be protective against CVD events with hazard ratios (95% confidence interval) [0.97 (0.95-0.99)] and maladaptive coping strategies seem to be a risk factor, 1.02 (1.01-1.04) in the whole population. Individuals younger than 60 showed similar results, with 0.96 (0.93-0.98) and 1.04 (1.01-1.07) for adaptive and maladaptive coping strategies, respectively. However, these findings were not replicated among seniors older than age 60. Based on our results, coping strategies have an important role in cardiovascular events, particularly among young adults. According to the results, informing patients about adaptive stress management may promote primary prevention of CVD events.

Pulse Arrival Time - A Sensitive Vital Parameter for the Detection of Mental Stress

Abstract Mental stress triggers positive inotropic and chronotropic effects as well as peripheral vasoconstriction. This alters the pulse arrival time (PAT), the duration between electrical excitation of the ventricles and arrival of the pulse wave in the periphery. We conducted a study to examine PAT during five rest blocks and under mental stress utilizing the Mannheim Multicomponent Stress Test. Electrocardiograms as well as finger and earlobe photoplethysmograms were recorded. PAT was calculated for over 135,000 heartbeats from 42 healthy volunteers as the time duration between the R peak in the electrocardiogram and the following pulse onset in the respective photoplethysmogram. To identify the effect of mental stress, block-wise PAT means were statistically analyzed with repeated measures ANOVA. The analyses showed significant differences between the block means for both PAT measures (p &lt; 0.001). Post-hoc tests revealed significantly reduced PAT during the stress block compared to all rest blocks for both PAT measures (p &lt; 0.001). We found no significant differences between the rest blocks. Our results support that PAT is a sensitive vital parameter for the detection of mental stress in healthy volunteers. This holds true for both measurement positions, the finger and the earlobe.

On the reliability estimation of multicomponent stress–strength model for Burr XII distribution using progressively first-failure censored samples

In this article, we consider the classical and Bayesian estimation of the multicomponent stress–strength reliability (MSSR) for the Burr XII distribution based on progressively first-failure censored samples. Both stress and strength random variables follow Burr XII distribution with common first shape parameter. The maximum likelihood estimator, asymptotic, boot-p and boot-t confidence interval of MSSR are studied. The Bayes estimator along with the Bayesian credible and highest posterior density credible intervals are derived. The uniformly minimum variance unbiased estimator of MSSR is discussed. A simulation study is performed to illustrate the proposed censoring and different estimation methods. At the end, two different real data sets are analysed for comparing different censoring schemes and estimation methods.

Interval estimation of multicomponent stress–strength reliability based on inverse Weibull distribution

This paper considers interval estimation of stress–strength reliability of k-out-of-n system when the stress and strength components follow inverse Weibull distributions. Besides the asymptotic and bootstrap confidence intervals, we derive HPD credible intervals when the shape parameter is known or unknown. We also propose the pivotal quantity and generalized confidence interval of reliability. We study the estimation of multicomponent stress–strength reliability using lower record values. Generalized, asymptotic, and bootstrap confidence intervals are derived using lower record values. We also derive confidence intervals of multicomponent stress–strength reliability assuming the shape parameters are different. We propose HPD credible intervals, generalized and bootstrap confidence intervals. Monte Carlo simulation is performed to compare the confidence intervals. Real data examples are presented to demonstrate the practicability of the confidence intervals.

Classical and Bayesian estimation of multicomponent stress–strength reliability for exponentiated Pareto distribution

Classical and Bayesian estimation of multicomponent stress–strength reliability for exponentiated Pareto distribution

Impact of hydrogen peroxide on microalgae cultivated in varying salt-nitrate-phosphate conditions

Microalgal biomass has received a great deal of attention as renewable and environmental-friendly biofuel feedstock as a rebuttal to climate change, energy crisis, and global warming. To improve the commercial viability of algal biodiesel production, the rise in lipid accretion and the enrichment of algal fatty acid profile are of utmost importance. In this experiment, lipid content and fatty acid methyl ester profiling of the microalgal strain, Scenedesmus sp. is done to understand the intercalating effect of different media composition for its suitability in context to biodiesel production. Various nutrient combinations (sodium nitrate, NaNO3) and di-potassium hydrogen phosphate, (K2HPO4) were incorporated along with salinity (sodium chloride) exposure for first 48 h stage of algal cultivation, followed by oxidative stress via hydrogen peroxide (H2O2) for the second 24 h stage of cultivation. The results show that the presence of 100 mM NaCl, 35.29 mM NaNO3, and 5.74 mM K2HPO4 followed by the addition of 10 mM H2O2 (S100H10N35.29P5.74) to the algal growth media led to the accumulation of maximum total lipid content (226.49 ± 16.6 μg/mg). Another nutrient combination, S0H10N35.29P0, increased the saturated fatty acid composition (C16:0) to 31.7%. Principal component analysis (PCA) also demonstrated the combined effect of multiple nutrient components and their relative concentrations on the growth parameters and algal biochemical profile, such as biomass, chlorophyll, lipid, carbohydrate, alongwith fatty acid profiling. Hence, this study demonstrate the potential of Scenedesmus sp. in response to a multi-component stress environment that has influenced the fate of fatty acid methyl esters (FAME) composition and significantly improved the quality of algal biofuels produced over a short period.

Statistical inference of reliability in multicomponent stress strength model for pareto distribution based on upper record values

ABSTRACT In this article, inferences about the multicomponent stress strength reliability are drawn under the assumption that strength and stress follow independent Pareto distribution with different shapes and common scale parameter under the setup of upper record values. The maximum likelihood estimator, Bayes estimator under-squared error and Linear exponential loss function, of multicomponent stress-strength reliability are constructed with corresponding highest posterior density interval for unknown For known uniformly minimum variance unbiased estimator and asymptotic distribution of multicomponent stress-strength reliability with asymptotic confidence interval is discussed. Also, various Bootstrap confidence intervals are constructed. A simulation study is conducted to numerically compare the performances of various estimators of multicomponent stress-strength reliability. Finally, a real life example is presented to show the applications of derived results in real life scenarios. Several researchers have attempted such problems under different distributions e.g., [1] considered the Weibull distribution for estimation of multicomponent stress-strength reliability, [2] considered generalized Rayleigh distribution for the reliability estimation of multicomponent stress-strength setup.

Estimation of reliability for multi-component stress–strength model based on modified Weibull distribution

This paper is devoted to estimating the reliability of a multi-component stress–strength model in an s-out-m ( $$s \le m$$ ) system under progressively type-II censored modified Weibull data. This type of systems functions only if at least s out of m strengths exceed the stress. Maximum likelihood and Bayes estimators of the stress–strength reliability based on conjugate prior are obtained. The associated confidence and credible intervals are also developed. The Lindley’s approximation and Markov chain Monte Carlo methods are used to compute approximate Bayes estimates. Two real data sets representing the excessive drought of Shasta Reservoir in California, USA and failure times of software model are analyzed for illustrative purposes. Further, Monte Carlo simulations are performed to compare the so developed estimates.

Gly-Pro and Adaptive Reactions in Multicomponent Stress

We report here studies on the effects of the peptide glycylproline (Gly-Pro) on measures of reactivity and adaptive potential on stimulation of the parasympathetic nervous system with carbachol in conditions of sequential exposure to the combined actions of three stress factors: immobilization, surgery, and an injection procedure. Sequential combination of surgery (application of a ligature to the pylorus of the stomach), immobilization, and the procedure of injecting physiological saline on the background of carbachol allowed four types of response in rats to be identified. These variants were characterized by different combinations of levels of corticosterone and different leukocyte subpopulations. All response variants were accompanied by development of stress, as indicated by the adaptation intensity index. The most profound stress reactions were seen in animals after immobilization and surgery and the combination of injection of physiological saline and carbachol. By modulating the parasympathetic compartment of the autonomic nervous system and, probably, a direct influence on the adrenals, Gly-Pro altered the corticosterone content and different leukocyte subpopulations and the adaptation intensity index in multicomponent stress. When peptide was given simultaneously with carbachol, it appeared to act via the resistance (counteraction) pathway of adaption, while when given in advance, before carbachol, it operated via the tolerance (stamina, endurance) pathway.

Estimation of Reliability in a Multicomponent Stress–Strength Model Based on Power Transformed Half-Logistic Distribution

This paper deals with the study of the reliability of multicomponent stress–strength model assuming that the strength components are independently and identically distributed as power transformed half-logistic (PHL) distribution. The strength components which are subject to a common stress are assumed to be independent with either Weibull distribution or PHL distribution. The maximum likelihood estimates of the multicomponent stress–strength reliability and its asymptotic confidence interval under the above said conditions are obtained. The Bayes estimates of the multicomponent stress–strength reliability are also obtained under squared error loss function and using gamma priors for the parameters. To evaluate the performance of the procedure, a simulation study is considered. For illustration purpose of the proposed model, two real life examples are given.

Estimation of Reliability in a Multicomponent Stress–Strength Model for a General Class of Inverted Exponentiated Distributions Under Progressive Censoring

We consider estimation of the multicomponent stress–strength reliability for a general class of inverted exponentiated distributions under progressive type-II censoring. We assume that both stress and strength variables follow this general class of distributions with a common parameter. Different point and interval estimates for the reliability of this system are obtained by using maximum likelihood and Bayesian approaches when the common parameter is known and unknown. The uniformly minimum variance unbiased estimate and exact Bayes estimate under the squared error loss function are derived when the common parameter is known. Bayes estimates are also obtained by using Lindley, Tierney–Kadane and Markov chain Monte Carlo methods. The asymptotic confidence and highest posterior density credible intervals are constructed. Proposed methods are compared numerically using Monte Carlo simulations. Finally, a progressively censored real data set is analyzed for illustration purposes.

Reliability analysis of multicomponent stress–strength reliability from a bathtub-shaped distribution

In this paper, inference for a multicomponent stress–strength model is studied. When latent strength and stress random variables follow a bathtub-shaped distribution and the failure times are Type-II censored, the maximum likelihood estimate of the multicomponent stress–strength reliability (MSR) is established when there are common strength and stress parameters. Approximate confidence interval is also constructed by using the asymptotic distribution theory and delta method. Furthermore, another alternative generalized point and confidence interval estimators for the MSR are constructed based on pivotal quantities. Moreover, the likelihood and the pivotal quantities-based estimates for the MSR are also provided under unequal strength and stress parameter case. To compare the equivalence of the stress and strength parameters, the likelihood ratio test for hypothesis of interest is also provided. Finally, simulation studies and a real data example are given for illustration.

Multicomponent stress-strength system reliability estimation for generalized exponential-poison distribution

This study deals with (s -out of- k) Multicomponent Stress (Y) and Strength (X) System Reliability Estimation. Both stress and strength assumed to have Generalized Exponential-Poisson Distribution with common and known scale parameters (θ and λ). The aim here is to estimate the unknown shape parameters (α and β) for X and Y respectively using two methods of estimation ML and Bayes analysis by one prior with five loss functions. Then estimate Reliability using the same methods and compared the results by Mean square error criteria from simulation study to find the best performance of the estimators. the results show that the best estimator for R(s,k) is Bayes estimator under Quadratic loss function using Gamma prior function, followed by GD, GW, GP, MLE and GS estimators, respectively.

Reliability inference for a multicomponent stress–strength model based on Kumaraswamy distribution

In this paper, inference for a multicomponent stress–strength (MSS) model is studied under censored data. When both latent strength and stress random variables follow Kumaraswamy distributions with common shape parameters, the maximum likelihood estimate of MSS reliability is established and associated approximate confidence interval is constructed using the asymptotic distribution theory and delta method. Moreover, pivotal quantities based generalized point and confidence interval estimates are presented for the MSS reliability. Furthermore, likelihood and generalized pivotal based estimates are also presented when the strength and stress variables have unequal shape parameters. For complementary and comparison, bootstrap confidence intervals are provided as well under common and unequal parameter cases. In addition, to compare the equivalence between strength and stress shape parameters, the likelihood ratio test for hypothesis of interest is also discussed. Finally, simulation study and a real data example are provided to investigate the performance of proposed procedures.

A modification in generalized classes of distributions: A new Topp–Leone class as an example

In this article, we have proposed a wider class of distributions by modifying the distribution function of the baseline density. This new class is a generalization of many well–known generators such as beta family, Kumaraswamy family, Kummer beta generalized family and Topp–Leone family. Furthermore, we have introduced a subcase, known as G–Fixed–Topp–Leone class, with different properties and have provided the expression for the reliability in the multicomponent stress–strength model. Additionally, we have studied the exponential–fixed–Topp–Leone distribution as an example; some structural properties of this three-parameter exponential distribution are driven which also include the derivations of incomplete moments, mean deviation, measures of uncertainty, reliability in multicomponent stress-stress model, order statistics, Lorenz, Bonferroni and Zenga curves. The estimation of the unknown parameters is done by the method of maximum likelihood. We have also included a real-life application of this new three-parameter exponential distribution to two datasets. A numerical study for the reliability in the multicomponent stress–strength model for the exponential–fixed–Topp–Leone distribution, using the Markov Chain and Monte Carlo (MCMC) method, is also performed.