Abstract. Nine call center employees wore a skin conductance sensor on the wrist for a week at work and reported stress levels of each call. Although everyone had the same job profile, we found large differences in how individuals reported stress levels, with similarity from day to day within the same participant, but large differences across the participants. We examined two ways to address the individual differences to automatically recognize classes of stressful/non-stressful calls, namely modifying the loss function of Support Vector Machines (SVMs) to adapt to the varying priors, and giving more importance to training samples from the most similar people in terms of their skin conductance lability. We tested the methods on 1500 calls and achieved an accuracy across participants of 78.03% when trained and tested on different days from the same person, and of 73.41% when trained and tested on different people using the proposed adaptations to SVMs.
Stress is considered to be a modern day "global epidemic"; so given the widespread nature of this problem, it would be beneficial if solutions that help people to learn how to cope better with stress were scalable beyond what individual or group therapies can provide today. Therefore, in this work, we study the potential of smart-phones as a pervasive medium to provide "crowd therapy". The work melds two novel contributions: first, a microintervention authoring process that focuses on repurposing popular web applications as stress management interventions; and second, a machine-learning based intervention recommender system that learns how to match interventions to individuals and their temporal circumstances over time. After four weeks, participants in our user study reported higher self-awareness of stress, lower depression-related symptoms and having learned new simple ways to deal with stress. Furthermore, participants receiving the machine-learning recommendations without option to select different ones showed a tendency towards using more constructive coping behaviors.
Central serous chorioretinopathy (CSC) is characterized by leakage of fluid from the choroid into the subretinal space and, consequently, loss of central vision. The disease is triggered by endogenous and exogenous corticosteroid imbalance and psychosocial stress and is much more prevalent in men. We studied the association of genetic variation in 44 genes from stress response and corticosteroid metabolism pathways with the CSC phenotype in two independent cohorts of 400 CSC cases and 1,400 matched controls. The expression of cadherin 5 (CDH5), the major cell–cell adhesion molecule in vascular endothelium, was downregulated by corticosteroids which may increase permeability of choroidal vasculature, leading to fluid leakage under the retina. We found a significant association of four common CDH5 SNPs with CSC in male patients in both cohorts. Two common intronic variants, rs7499886:A>G and rs1073584:C>T, exhibit strongly significant associations with CSC; P = 0.00012; odds ratio (OR) = 1.5; 95%CI [1.2;1.8], and P = 0.0014; OR = 0.70; 95%CI [0.57;0.87], respectively. A common haplotype was present in 25.4% male CSC cases and in 35.8% controls (P = 0.0002; OR = 0.61, 95% CI [0.47–0.79]). We propose that genetically predetermined variation in CDH5, when combined with triggering events such as corticosteroid treatment or severe hormonal imbalance, underlie a substantial proportion of CSC in the male population.
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