Threat of resource loss: The role of self-regulation in adaptive task performance

Changes at work are often accompanied with the threat of, or actual, resource loss. Through an experiment, we investigated the detrimental effect of the threat of resource loss on adaptive task performance. Self-regulation (i.e., task focus and emotion control) was hypothesized to buffer the negative relationship between the threat of resource loss and adaptive task performance. Adaptation was conceptualized as relearning after a change in task execution rules. Threat of resource loss was manipulated for 100 participants undertaking an air traffic control task. Using discontinuous growth curve modeling, 2 kinds of adaptation—transition adaptation and reacquisition adaptation—were differentiated. The results showed that individuals who experienced the threat of resource loss had a stronger drop in performance (less transition adaptation) and a subsequent slower recovery (less reacquisition adaptation) compared with the control group who experienced no threat. Emotion control (but not task focus) moderated the relationship between the threat of resource loss and transition adaptation. In this respect, individuals who felt threatened but regulated their emotions performed better immediately after the task change (but not later on) compared with those individuals who felt threatened and did not regulate their emotions as well. However, later on, relearning (reacquisition adaptation) under the threat of resource loss was facilitated when individuals concentrated on the task at hand.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

The treatment of recurrent abdominal pain in children : a controlled comparison of cognitive-behavioral family intervention and standard pediatric care

This study describes the results of a controlled clinical trial involving 44 7- to 14-year-old children with recurrent abdominal pain who were randomly allocated to either cognitive-behavioral family intervention (CBFI) or standard pediatric care (SPC). Both treatment conditions resulted in significant improvements on measures of pain intensity and pain behavior. However, the children receiving CBFI had a higher rate of complete elimination of pain, lower levels of relapse at 6- and 12-month follow-up, and lower levels of interference with their activities as a result of pain and parents reported a higher level of satisfaction with the treatment than children receiving SPC. After controlling for pretreatment levels of pain, children's active self-coping and mothers' caregiving strategies were significant independent predictors of pain behavior at posttreatment.

MRI-based fatigue analysis predicts plaque vulnerability: A study comparing symptomatic and asymptomatic individuals

BACKGROUND: Rupture of atheromatous plaque in the carotid artery often leads to thrombosis and subsequent stroke. The mechanism of plaque rupture is not entirely clear but is thought to be a multi-factorial process involving thinning and weakening of the fibrous cap and biomechanical stress as the trigger leading to plaque rupture. As the cardiovascular system is a classic fatigue environment, the weakening of plaque leading to rupture may be a fatigue process, which is a symptomatically quiescent but potentially progressive failure process. In this study, we used a fatigue analysis based on in vivo magnetic resonance imaging (MRI) to investigate the rupture initiation location, crack propagation path and fatigue life within plaques of asymptomatic and symptomatic individuals. METHODS: Forty non-consecutive subjects (20 symptomatic and 20 asymptomatic) underwent high-resolution multi-sequence in vivo MRI of the carotid bifurcation. Fatigue analysis was performed based on the plaque geometry derived from in vivo MRI of the carotid artery at the point of maximum stenosis. Paris’ Law in fracture mechanics is adopted to determine the fatigue crack growth rate. Incremental crack propagation was dynamically simulated based on stress distributions. Plaque initiation location, crack propagation path and fatigue cycle of symptomatic and asymptomatic individuals were compared. RESULTS: Cracks were often found to begin at the lumen wall at areas of stress concentration. The preferred rupture direction was radial from the lumen center. The crack initially advanced slowly but accelerated as it developed, depending on plaque morphology. The fatigue cycles of symptomatic plaques were significantly less than those in the asymptomatic group (2.3 ± 0.9 vs 3.1 ± 0.7 (x106); p = 0.003). CONCLUSIONS: The number of cycles to rupture in symptomatic patients was higher than those predicted in asymptomatic patients by fatigue analysis, suggesting the possibility that plaques with a less fatigue life may be more prone to be symptomatic and rupture. If further validated by large-scale longitudinal studies, fatigue analysis based on high resolution in vivo MRI could potentially act as a useful tool for risk assessment of carotid atheroma.

Iron oxide particles for atheroma imaging

The selection of patients for vascular interventions has been solely based on luminal stenosis and symptomatology. However, histological data from both the coronary and carotid vasculature suggest that other plaque features such as inflammation may be more important in predicting future thromboembolic events. Ultrasmall superparamagnetic iron oxide (USPIO) contrast agents have been used for noninvasive MRI assessment of atherosclerotic plaque inflammation in humans. It has reached the stage of development to have been recently used in an interventional drug study to not only assess inflammatory progression but also select patients at high risk. This article reviews the basic science behind the use of USPIO contrast agents in atheroma MR imaging, experimental work in animals, and how this has led to the emergence of this promising targeted imaging platform for assessment of high risk carotid atherosclerosis in humans.

Characterisation of carotid atheroma in symptomatic and asymptomatic patients using high resolution MRI

Background and purpose: To prospectively evaluate differences in carotid plaque characteristics in symptomatic and asymptomatic patients using high resolution MRI. Methods: 20 symptomatic and 20 asymptomatic patients, with at least 50% carotid stenosis as determined by Doppler ultrasound, underwent preoperative in vivo multispectral MRI of the carotid arteries. Studies were analysed both qualitatively and quantitatively in a randomised manner by two experienced readers in consensus, blinded to clinical status, and plaques were classified according to the modified American Heart Association (AHA) criteria. Results: After exclusion of poor quality images, 109 MRI sections in 18 symptomatic and 19 asymptomatic patients were available for analysis. There were no significant differences in mean luminal stenosis severity (72.9% vs 67.6%; p = 0.09) or plaque burden (median plaque areas 50 mm2 vs 50 mm 2; p = 0.858) between the symptomatic and asymptomatic groups. However, symptomatic lesions had a higher incidence of ruptured fibrous caps (36.5% vs 8.7%; p = 0.004), haemorrhage or thrombus (46.5% vs 14.0%; p<0.001), large necrotic lipid cores (63.8% vs 28.0%; p = 0.002) and complicated type VI AHA lesions (61.5% vs 28.1%; p = 0.001) compared with asymptomatic lesions. The MRI findings of plaque haemorrhage or thrombus had an odds ratio of 5.25 (95% CI 2.08 to 13.24) while thin or ruptured fibrous cap (as opposed to a thick fibrous cap) had an odds ratio of 7.94 (95% CI 2.93 to 21.51) for prediction of symptomatic clinical status. Conclusions: There are significant differences in plaque characteristics between symptomatic and asymptomatic carotid atheroma and these can be detected in vivo by high resolution MRI.

Correlation of carotid atheromatous plaque inflammation using USPIO-enhanced MR imaging with degree of luminal Stenosis

BACKGROUND AND PURPOSE Inflammation is a recognized risk factor for the vulnerable atherosclerotic plaque. The study explores the relationship between the degree of Magnetic Resonance (MR)"defined inflammation using Ultra Small Super-Paramagnetic Iron Oxide (USPIO) particles and the severity of luminal stenosis in asymptomatic carotid plaques. METHODS Seventy-one patients with an asymptomatic carotid stenosis of ĝ‰¥40% underwent multi-sequence USPIO-enhanced MR imaging. Stenosis severity was measured according to the NASCET and ECST methods. RESULTS No demonstrable relationship between inflammation as measured by USPIO-enhanced signal change and the degree of luminal stenosis was found. CONCLUSIONS Inflammation and stenosis are likely to be independent risk factors, although this needs to be further validated.

Assessment of inflammatory burden contralateral to the symptomatic carotid stenosis using high-resolution ultrasmall, superparamagnetic iron oxide-enhanced MRI

BACKGROUND AND PURPOSE It is well known that the vulnerable atheromatous plaque has a thin, fibrous cap and large lipid core with associated inflammation. This inflammation can be detected on MRI with use of a contrast medium, Sinerem, an ultrasmall superparamagnetic iron oxide (USPIO). Although the incidence of macrophage activity in asymptomatic disease appears low, we aimed to explore the incidence of MRI-defined inflammation in asymptomatic plaques in patients with known contralateral symptomatic disease. METHODS Twenty symptomatic patients underwent multisequence MRI before and 36 hours after USPIO infusion. Images were manually segmented into quadrants, and the signal change in each quadrant was calculated after USPIO administration. A mixed mathematical model was developed to compare the mean signal change across all quadrants in the 2 groups. Patients had a mean symptomatic stenosis of 77% compared with 46% on their asymptomatic side, as measured by conventional angiography. RESULTS There were 11 (55%) men, and the median age was 72 years (range, 53 to 84 years). All patients had risk factors consistent with severe atherosclerotic disease. All symptomatic carotid stenoses had inflammation, as evaluated by USPIO-enhanced imaging. On the contralateral sides, inflammatory activity was found in 19 (95%) patients. Contralaterally, there were 163 quadrants (57%) with a signal loss after USPIO when compared with 217 quadrants (71%) on the symptomatic side (P=0.007). CONCLUSIONS - This study adds weight to the argument that atherosclerosis is a truly systemic disease. It suggests that investigation of the contralateral side in patients with symptomatic carotid stenosis can demonstrate inflammation in 95% of plaques, despite a mean stenosis of only 46%. Thus, inflammatory activity may be a significant risk factor in asymptomatic disease in patients who have known contralateral symptomatic disease. Patients with symptomatic carotid disease should have their contralateral carotid artery followed up.

How critical is fibrous cap thickness to carotid plaque stability? A flow-plaque interaction model

Background and Purpose Acute cerebral ischemic events are associated with rupture of vulnerable carotid atheroma and subsequent thrombosis. Factors such as luminal stenosis and fibrous cap thickness have been thought to be important risk factors for plaque rupture. We used a flow-structure interaction model to simulate the interaction between blood flow and atheromatous plaque to evaluate the effect of the degree of luminal stenosis and fibrous cap thickness on plaque vulnerability. Methods A coupled nonlinear time-dependent model with a flow-plaque interaction simulation was used to perform flow and stress/strain analysis in a stenotic carotid artery model. The stress distribution within the plaque and the flow conditions within the vessel were calculated for every case when varying the fibrous cap thickness from 0.1 to 2 mm and the degree of luminal stenosis from 10% to 95%. A rupture stress of 300 kPa was chosen to indicate a high risk of plaque rupture. A 1-sample t test was used to compare plaque stresses with the rupture stress. Results High stress concentrations were found in the plaques in arteries with >70% degree of stenosis. Plaque stresses in arteries with 30% to 70% stenosis increased exponentially as fibrous cap thickness decreased. A decrease of fibrous cap thickness from 0.4 to 0.2 mm resulted in an increase of plaque stress from 141 to 409 kPa in a 40% degree stenotic artery. Conclusions There is an increase in plaque stress in arteries with a thin fibrous cap. The presence of a moderate carotid stenosis (30% to 70%) with a thin fibrous cap indicates a high risk for plaque rupture. Patients in the future may be risk stratified by measuring both fibrous cap thickness and luminal stenosis.

Robust estimation using the Huber function with a data-dependent tuning constant

Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

Criteria for working-correlation-structure selection in GEE: Assessment via simulation

Efficiency of analysis using generalized estimation equations is enhanced when intracluster correlation structure is accurately modeled. We compare two existing criteria (a quasi-likelihood information criterion, and the Rotnitzky-Jewell criterion) to identify the true correlation structure via simulations with Gaussian or binomial response, covariates varying at cluster or observation level, and exchangeable or AR(l) intracluster correlation structure. Rotnitzky and Jewell's approach performs better when the true intracluster correlation structure is exchangeable, while the quasi-likelihood criteria performs better for an AR(l) structure.

Unbiased estimating equations from working correlation models for irregularly timed repeated measures

The method of generalized estimating equation-, (GEEs) has been criticized recently for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. However, the feasibility and efficiency of GEE methods can be enhanced considerably by using flexible families of working correlation models. We propose two ways of constructing unbiased estimating equations from general correlation models for irregularly timed repeated measures to supplement and enhance GEE. The supplementary estimating equations are obtained by differentiation of the Cholesky decomposition of the working correlation, or as score equations for decoupled Gaussian pseudolikelihood. The estimating equations are solved with computational effort equivalent to that required for a first-order GEE. Full details and analytic expressions are developed for a generalized Markovian model that was evaluated through simulation. Large-sample ".sandwich" standard errors for working correlation parameter estimates are derived and shown to have good performance. The proposed estimating functions are further illustrated in an analysis of repeated measures of pulmonary function in children.

Estimating equations with nonignorably missing response data

Troxel, Lipsitz, and Brennan (1997, Biometrics 53, 857-869) considered parameter estimation from survey data with nonignorable nonresponse and proposed weighted estimating equations to remove the biases in the complete-case analysis that ignores missing observations. This paper suggests two alternative modifications for unbiased estimation of regression parameters when a binary outcome is potentially observed at successive time points. The weighting approach of Robins, Rotnitzky, and Zhao (1995, Journal of the American Statistical Association 90, 106-121) is also modified to obtain unbiased estimating functions. The suggested estimating functions are unbiased only when the missingness probability is correctly specified, and misspecification of the missingness model will result in biases in the estimates. Simulation studies are carried out to assess the performance of different methods when the covariate is binary or normal. For the simulation models used, the relative efficiency of the two new methods to the weighting methods is about 3.0 for the slope parameter and about 2.0 for the intercept parameter when the covariate is continuous and the missingness probability is correctly specified. All methods produce substantial biases in the estimates when the missingness model is misspecified or underspecified. Analysis of data from a medical survey illustrates the use and possible differences of these estimating functions.

Workplace belongingness, psychological distress and resilience in emergency service workers

- Objective Ambulance personnel provide emergency medical services to the community, often attending to highly challenging and traumatic scenes in complex and chaotic circumstances. Currently the assessment of predictors of psychological well-being remains limited. The current study investigated whether workplace belongingness was significant in predicting psychological distress as well as the presence of resilience in ambulance personnel whilst controlling for more routinely examined factors. - Method Australian ambulance officers (N = 740) completed a survey battery including the Kessler 10 (Kessler & Mroczek, 1994), Brief Resilience Scale (Smith et al., 2008) and Psychological Sense of Organisational Membership (Cockshaw & Shochet, 2010) scale. - Results Controlling for more commonly examined factors such as severity of trauma exposure and length of service, hierarchical multiple regression analyses demonstrated that workplace belongingness was significantly associated with reduced distress levels and enhanced resilience levels. - Conclusions Results suggest that strategies to enhance a sense of workplace belongingness in emergency service organisations could promote the well-being of emergency workers despite routine exposure to potentially traumatic events.