scholarly journals COVID Feel Good – A Self-Help Virtual Therapeutic Experience for Overcoming the Psychological Distress of the COVID-19 Pandemic: Results from a European Multicentric Trial

2021 ◽  
Author(s):  
Giuseppe Riva ◽  
Daniele Di Lernia ◽  
Cosimo Tuena ◽  
Luca Bernardelli ◽  
Jose Gutiérrez Maldonado ◽  
...  
Keyword(s):  
Perceived Stress ◽  
Effect Size ◽  
Random Effect ◽  
Social Connection ◽  
Mixed Effect ◽  
Psychological Burden ◽  
Therapeutic Experience ◽  
Summary Estimate ◽  
Self Help ◽  
General Distress

The primary aim of the present study was to investigate the efficacy of a self-help virtual therapeutic experience (COVID Feel Good) for reducing the psychological burden experienced during the COVID-19 lockdown across different countries. For this purpose, we focused on participants recruited from June 2020 to May 2021 in the context of a European multicenter project including four university/academic sites. Primary outcome measures were depression, anxiety and stress symptoms, perceived stress levels and hopelessness. Secondary outcomes were the experienced social connectedness and the level of fear experienced during the COVID-19 pandemic. To assess the efficacy of the intervention in a multicentric context, we evaluated the strength of evidence supporting the COVID Feel Good computing a single summary estimate of the effect across the different countries. Using separate linear mixed-effect models, the most consistent result across the different countries was an improvement of the perceived stress level after the participation in the COVID Feel Good intervention. By pooling the results of the models using a random-effect meta-analysis, we found that COVID Feel Good intervention was associated a decrease in the perceived general distress [mean standardized effect size for general distress in the treatment groups compared to the control conditions was 0.52 (p = 0.007, 95% CI: 0.14, 0.89] and with an increase the perceived social connection [mean standardized effect size for social connection using COVID Feel Good compared to the control conditions was -0.50 (p = < 0.001, 95% CI: -0.76, -0.25)]. Globally findings suggest the efficacy of the proposed protocol and contribute the growing literature supporting the use of digital psychological interventions to reduce the psychological stress among general population during the COVID-19 crisis.

scholarly journals Diagnostic Value of Clinical Features to Distinguish Enteric Fever From Other Febrile Illnesses in Bangladesh, Nepal, and Pakistan

2020 ◽  
Vol 71 (Supplement_3) ◽  
pp. S257-S265 ◽  
Author(s):  
Kristen Aiemjoy ◽  
Dipesh Tamrakar ◽  
Shampa Saha ◽  
Shiva R Naga ◽  
Alexander T Yu ◽  
...  
Keyword(s):  
Blood Culture ◽  
Clinical Features ◽  
Diagnostic Performance ◽  
Enteric Fever ◽  
Random Effect ◽  
Clinical Signs ◽  
Febrile Illness ◽  
Diagnostic Value ◽  
Case Definition ◽  
Mixed Effect

Abstract Background Enteric fever, a bacterial infection caused by Salmonella enterica serotypes Typhi and Paratyphi A, frequently presents as a nonlocalizing febrile illness that is difficult to distinguish from other infectious causes of fever. Blood culture is not widely available in endemic settings and, even when available, results can take up to 5 days. We evaluated the diagnostic performance of clinical features, including both reported symptoms and clinical signs, of enteric fever among patients participating in the Surveillance for Enteric Fever in Asia Project (SEAP), a 3-year surveillance study in Bangladesh, Nepal, and Pakistan. Methods Outpatients presenting with ≥3 consecutive days of reported fever and inpatients with clinically suspected enteric fever from all 6 SEAP study hospitals were eligible to participate. We evaluated the diagnostic performance of select clinical features against blood culture results among outpatients using mixed-effect regression models with a random effect for study site hospital. We also compared the clinical features of S. Typhi to S. Paratyphi A among both outpatients and inpatients. Results We enrolled 20 899 outpatients, of whom 2116 (10.1%) had positive blood cultures for S. Typhi and 297 (1.4%) had positive cultures for S. Paratyphi A. The sensitivity of absence of cough was the highest among all evaluated features, at 65.5% (95% confidence interval [CI], 55.0–74.7), followed by measured fever at presentation at 59.0% (95% CI, 51.6–65.9) and being unable to complete normal activities for 3 or more days at 51.0% (95% CI, 23.8–77.6). A combined case definition of 3 or more consecutive days of reported fever and 1 or more of the following (a) either the absence of cough, (b) fever at presentation, or (c) 3 or more consecutive days of being unable to conduct usual activity--yielded a sensitivity of 94.6% (95% CI, 93.4–95.5) and specificity of 13.6% (95% CI, 9.8–17.5). Conclusions Clinical features do not accurately distinguish blood culture–confirmed enteric fever from other febrile syndromes. Rapid, affordable, and accurate diagnostics are urgently needed, particularly in settings with limited or no blood culture capacity.

scholarly journals Acceptance and efficacy of a metacognitive self-help intervention in an Arabic-speaking mixed patient sample with depression and/or obsessive–compulsive disorder: A randomized controlled trial

2019 ◽  
Vol 10 (1) ◽  
pp. 204380871882068 ◽  
Author(s):  
Steffen Moritz ◽  
Schaimaa Irshaid ◽  
Annabel Beiner ◽  
Marit Hauschildt ◽  
Franziska Miegel
Keyword(s):  
Obsessive Compulsive Disorder ◽  
Effect Size ◽  
Retention Rates ◽  
Evidence Based ◽  
Completion Rates ◽  
Large Effect Size ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Self Help ◽  
Arabic Speaking

Objective: In Arabic-speaking countries, most individuals with depression or obsessive–compulsive disorder (OCD) do not seek or receive evidence-based treatment due to a dearth of facilities, shame/self-stigma, or religious concerns. The feasibility and effectiveness of “Western” psychotherapeutic concepts have rarely been evaluated for Arabic-speaking populations. The present study examined the efficacy of My Metacognitive Training (myMCT), a trans-therapeutic self-help manual, in a mixed sample of participants with depression and/or OCD. We considered both participants with depression and/or OCD because a number of cognitive biases and dysfunctional beliefs are shared by the two disorders. Method: The myMCT manual was translated into Arabic. A total of 160 individuals with either self-reported OCD and/or self-reported depression were recruited. Individuals were assessed at baseline and then randomized either to myMCT ( n = 84) or to a wait-list control condition ( n = 76). Six weeks later, individuals were invited to the post assessment. The Beck Depression Inventory (BDI-II) served here as the primary outcome. Secondary outcomes were the Obsessive–Compulsive Inventory–Revised (OCI-R) and the self-rating version of the Yale-Brown Obsessive Compulsive Scale (OCD patients only). Individuals were reimbursed with a 17€ voucher. Results: Completion rates were similarly low in the two groups (myMCT: 37%, controls: 35%). Presumably because of the high rate of noncompletion and nonadherence (29%), the intention-to-treat analyses failed to yield a significant effect. Those who had at least started the myMCT intervention improved significantly on the BDI-II at a large effect size. A significantly larger improvement among those who had started or completed the myMCT intervention was also seen on the OCI-R at a large effect size. Conclusions: Individuals who studied the myMCT manual showed large improvement on the BDI-II, irrespective of their primary symptomatology. However, the results are seriously compromised by the low completion rates in both conditions. Importantly, evaluations using the same manual in other language populations (and with other background cultures) produced good to excellent retention rates. The study demonstrates that self-help manuals may not represent a suitable medium for large-scale dissemination of evidence-based self-help material in an Arab population and corroborates prior findings suggesting low adherence in this population. Whether smartphone apps and Internet interventions represent more viable alternatives than self-help manuals needs to be tested, as well as specific barriers preventing dissemination and completion in this population.

scholarly journals Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Da Yao ◽  
Qing Chang ◽  
Qi-Jun Wu ◽  
Shan-Yan Gao ◽  
Huan Zhao ◽  
...  
Keyword(s):  
Cohort Studies ◽  
Central Obesity ◽  
English Language ◽  
Meta Analysis ◽  
Random Effect ◽  
Subcutaneous Fat ◽  
Fat Distribution ◽  
Summary Estimate ◽  
Study Characteristics ◽  
Design And Methods

Objective. Nowadays, body mass index (BMI) is used to evaluate the risk stratification of obesity-related pregnancy complications in clinics. However, BMI cannot reflect fat distribution or the proportion of adipose to nonadipose tissue. The objective of this study is to evaluate the association of maternal first or second trimester central obesity with the risk of GDM. Research Design and Methods. We searched in PubMed, Embase, and Web of Science for English-language medical literature published up to 12 May 2019. Cohort studies were only included in the search. Abdominal subcutaneous fat thickness, waist circumference, waist-hip ratio or body fat distribution were elected as measures of maternal central obesity, and all diagnostic criteria for GDM were accepted. The random effect meta-analysis was performed to evaluate the relationship between central obesity and the risk of GDM. Results. A total of 11 cohort studies with an overall sample size of 27,675 women and 2,226 patients with GDM were included in the analysis. The summary estimate of GDM risk in the central obesity pregnant women was 2.76 (95% confidence interval [CI]: 2.35–3.26) using the adjusted odds ratio (OR). The degree of heterogeneity among the studies was low (I2=14.4, P=0.307). The subgroup analyses showed that heterogeneity was affected by selected study characteristics (methods of exposure and trimesters). After adjusting for potential confounds, the OR of adjusted BMI was significant (OR=3.07, 95% CI: 2.35–4.00). Conclusions. Our findings indicate that the risk of GDM was positively associated with maternal central obesity.

scholarly journals 4088 Longitudinal Assessment of Metabolic Syndrome as a Modifiable Risk factor of World Trade Center Particulate Matter Exposure Associated Lung Disease

2020 ◽  
Vol 4 (s1) ◽  
pp. 49-50
Author(s):  
Sophia Kwon ◽  
Myeonggyun Lee ◽  
Theresa Schwartz ◽  
Rachel Zeig-Owens ◽  
David Prezant ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Risk Factor ◽  
Effect Size ◽  
World Trade ◽  
World Trade Center ◽  
Time Dependent ◽  
Mixed Effect ◽  
High Exposure ◽  
Single Index ◽  
Trade Center

OBJECTIVES/GOALS: Metabolic syndrome (MetSyn) is a risk for World Trade Center-Lung Injury (WTC-LI; defined as developing FEV1<lower limit of normal [LLN]). Metabolic health is a modifiable disease risk factor. We propose to characterize how time-dependent covariates of MetSyn are longitudinally associated with WTC-LI. METHODS/STUDY POPULATION: WTC-particulate exposed firefighters, consented, with pre-9/11 FEV1 LLN (N = 5,746). Data assessed from last pre-9/11 till August 1, 2017. Longitudinal MetSyn characteristics were assessed using 3 models: i. A linear mixed effect model to assess the effect size of longitudinal MetSyn and its components on longitudinal FEV1% predicted as an outcome; ii. a time-dependent Cox regression to assess the associations of MetSyn to time of onset of WTC-LI; iii. a novel, partially linear single index regression model with repeatedly measured MetSyn to assess their joint effects and delineate their relative contribution on the longitudinal lung function in the WTC-FDNY cohort. RESULTS/ANTICIPATED RESULTS: In Model I, BMI 30 kg/m2 had the largest effect size compared to ever-smoking, with −2.524 (95%CI: −2.708,−2.340) compared to −1.681(−2.325,−1.038) respectively. Having MetSyn, defined as 3/5 risk factors, had an effect size of −2.319(−2.526,−2.112). In Model II, hazards of triglycerides 150mg/dL were highest at 1.497(1.336, 1.677), followed by BMI 30 kg/m2 at 1.406(1.256, 1.575), and HDL<40mg/dL 1.355(1.176-1.561), compared to ever-smoking (1.201, p = 0.002). Having high exposure to PM by being present in the morning of 9/11 was a significant covariate only in Model II investigating HDL<40mg/dL or triglycerides 150mg/dL. Model III The proposed methods will be applied to our cohort study. DISCUSSION/SIGNIFICANCE OF IMPACT: MetSyn is both a predictor and concurrent marker of WTC-LI. The single index model can not only reduce dimensionality of the covariates, but also provides efficient estimates of the joint MetSyn effects, allowing linear or nonlinear effects. Future studies will investigate dietary intervention as a potential disease-modifying factor. CONFLICT OF INTEREST DESCRIPTION: NA, nothing to disclose.

scholarly journals Variation of Efficacy of Filtering Face Pieces Respirators over Time in a Dental Setting: A Pilot Study

2021 ◽  
Vol 9 (4) ◽  
pp. 36
Author(s):  
Vittorio Checchi ◽  
Marco Montevecchi ◽  
Luigi Checchi
Keyword(s):  
Fixed Effects ◽  
Random Effect ◽  
Wilcoxon Test ◽  
Linear Mixed Effect Model ◽  
Clinical Activity ◽  
Time Data ◽  
Paired Data ◽  
Mixed Effect ◽  
Protective Function ◽  
Over Time

Since aerosol continuously persists in dental settings, where different procedures and patients come in succession, the use of oronasal masks is highly recommended. Among them, respirators known as Filtering Face Pieces (FFP) show a protective superiority compared to surgical masks. Even concerning respirators classified as non-reusable, it is not known how many hours of use are necessary to compromise their filtering capacity. The aim of this study is to investigate the variations of filtering capacity of an FFP2 respirator over time, in order to safely optimize the timing of its use. Five respirators were worn by the same operator during clinical activity for different usage times (8, 16, 24, 32, 40 h), and one respirator was kept unused. All respirators underwent a bacterial filtration efficacy (BFE) test. T-test for paired data with Bootstrap technique and Wilcoxon test for paired data compared BFE values of the five tested FFP2s respectively at each time, and the areas with the corresponding values of the control respirator (FFp2-F). A generalized linear mixed effect model (GLM) was applied considering type of respirator and time as fixed effects and intercept as random effect. No significant statistical differences were present in the BFE of each time. Data obtained by the present study highlight the important ability of FFP2s to maintain their BFE over time, suggesting a long lasting protective function.

scholarly journals Hamiltonian Monte Carlo with Random Effect for Analyzing Cyclist Crash Severity

Signals ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 527-539
Author(s):  
Mahdi Rezapour ◽  
Khaled Ksaibati
Keyword(s):  
Monte Carlo ◽  
Mixture Model ◽  
Random Effect ◽  
Finite Mixture Model ◽  
Finite Mixture ◽  
Model Fit ◽  
Crash Severity ◽  
Optimum Amount ◽  
Mixed Effect ◽  
Hamiltonian Monte Carlo

Vulnerable traffic users, such as bikers and pedestrians, account for a significant number of fatalities on the roadways. Extensive research has been conducted in the literature review to identify factors to those crashes. Studying factors to those crashes is especially important in the Western state in the US, due to one of the highest fatality rates in the nation and its unique geographic conditions. The first step in identifying factors to the severity of cyclist crashes is to find the underlying factors to that type of crash, while accounting for the heterogeneity in the dataset. Various techniques such as mixed parameter or mixed effect models have been employed in the literature to account for the heterogeneity of the dataset. In the mixed effect model, often the random effect parameter has been assigned subjectively, and based on some attributes and engineering intuitions. Those assignments are expected to account for the heterogeneity in the dataset and enhancement of the model fit. However, a question might arise whether those factors could account for an optimum amount of the heterogeneity in the dataset. A more reasonable way might be to let the algorithm such as the finite mixture model (FMM) to identify those clusters based on parameters of the Gaussian model, means and covariance matrices of the dataset, and allocate each observation to the related clusters. Thus, in this study, to capture optimum amount of heterogeneity, first we implemented the finite mixture model in the context of maximum likelihood, due the label switching issue of the method in the context of the Bayesian method. After assignment of the parameters to the observation, the main method of Hamiltonian Monte Carlo (HMC) with random effect was implemented. The results highlighted a significant improvement in the model fit, in terms of Widely Applicable Information Criterion (WAIC). The results of this study highlighted factors such as older biker age, increased number of lanes, nighttime travelling, increased posted speed limit and driving while under emotional conditions are some factors contributing to an increased severity of bikers’ crash severity. Extensive discussion has been made regarding the methodological algorithms and model parameters estimations.

scholarly journals Multiple QTL mapping in autopolyploids: a random-effect model approach with application in a hexaploid sweetpotato full-sib population

2019 ◽  
Author(s):  
Guilherme da Silva Pereira ◽  
Dorcus C. Gemenet ◽  
Marcelo Mollinari ◽  
Bode A. Olukolu ◽  
Joshua C. Wood ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Ipomoea Batatas ◽  
Random Effect ◽  
Random Effect Model ◽  
Phenotypic Data ◽  
Mixed Effect ◽  
Gene Search ◽  
Effect Model ◽  
Multiple Qtl ◽  
Model Approach

ABSTRACTIn developing countries, the sweetpotato,Ipomoea batatas(L.) Lam. (2n= 6x= 90), is an important autopolyploid species, both socially and economically. However, quantitative trait loci (QTL) mapping has remained limited due to its genetic complexity. Current fixed-effect models can only fit a single QTL and are generally hard to interpret. Here we report the use of a random-effect model approach to map multiple QTL based on score statistics in a sweetpotato bi-parental population (‘Beauregard’בTanzania’) with 315 full-sibs. Phenotypic data were collected for eight yield component traits in six environments in Peru, and jointly predicted means were obtained using mixed-effect models. An integrated linkage map consisting of 30,684 markers distributed along 15 linkage groups (LGs) was used to obtain the genotype conditional probabilities of putative QTL at every cM position. Multiple interval mapping was performed using our R package QTLPOLY and detected a total of 41 QTL, ranging from one to ten QTL per trait. Some regions, such as those on LGs 3 and 15, were consistently detected among root number and yield traits and provided basis for candidate gene search. In addition, some QTL were found to affect commercial and noncommercial root traits distinctly. Further best linear unbiased predictions allowed us to characterize additive allele effects as well as to compute QTL-based breeding values for selection. Together with quantitative genotyping and its appropriate usage in linkage analyses, this QTL mapping methodology will facilitate the use of genomic tools in sweetpotato breeding as well as in other autopolyploids.

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