Explicit moments of decision times for single- and double-threshold drift-diffusion processes

We derive expressions for the first three moments of the decision time (DT) distribution produced via first threshold crossings by sample paths of a drift-diffusion equation. The "pure" and "extended" diffusion processes are widely used to model two-alternative forced choice decisions, and, while simple formulae for accuracy, mean DT and coefficient of variation are readily available, third and higher moments and conditioned moments are not generally available. We provide explicit formulae for these, describe their behaviors as drift rates and starting points approach interesting limits, and, with the support of numerical simulations, discuss how trial-to-trial variability of drift rates, starting points, and non-decision times affect these behaviors in the extended diffusion model. Both unconditioned moments and those conditioned on correct and erroneous responses are treated. We argue that the results will assist in exploring mechanisms of evidence accumulation and in fitting parameters to experimental data

Improving Microbiological Safety and Quality Characteristics of Wheat and Barley by High Voltage Atmospheric Cold Plasma Closed Processing

Contamination of cereal grains as a key global food resource with insects or microorganisms is a persistent concern for the grain industry due to irreversible damage to quality and safety characteristics and economic losses. Atmospheric cold plasma presents an alternative to conventional grain decontamination methods owing to the high antimicrobial potential of reactive species generated during the treatment, but effects against product specific microflora are required to understand how to optimally develop this approach for grains. This work investigated the influence of ACP processing parameters for both cereal grain decontamination and grain quality as important criteria for grain or seed use. A high voltage (HV) (80 kV) dielectric barrier discharge (DBD) closed system was used to assess the potential for control of native microflora and pathogenic bacterial and fungal challenge microorganisms, in tandem with effects on grain functional properties. Response surface modelling of experimental data probed the key factors in relation to microbial control and seed germination promotion. The maximal reductions of barley background microbiota were 2.4 and 2.1 log10 CFU/g and of wheat - 1.5 and 2.5 log10 CFU/g for bacteria and fungi, respectively, which required direct treatment for 20 min followed by a 24 h sealed post-treatment retention time. In the case of challenge organisms inoculated on barley grains, the highest resistance was observed for Bacillus atrophaeus endospores, which, regardless of retention time, were maximally reduced by 2.4 log10 CFU/g after 20 min of direct treatment. The efficacy of the plasma treatment against selected microorganisms decreased in the following order: E. coli \u3e P. verrucosum (spores) \u3e B. atrophaeus (vegetative cells) \u3e B. atrophaeus (endospores). The challenge microorganisms were more susceptible to ACP treatment than naturally present background microbiota. No major effect of short term plasma treatment on the retention of quality parameters was observed. Germination percentage measured after 7 days cultivation was similar for samples treated for up to 5 min, but this was decreased after 20 min of direct treatment. Overall, ACP proved effective for cereal grain decontamination, but it is noted that the diverse native micro-flora may pose greater resistance to the closed, surface decontamination approach than the individual fungal or bacterial challenges, which warrants investigation of grain microbiome responses to ACP

Sequential effects in two-choice reaction time tasks: decomposition and synthesis of mechanisms

Performance on serial tasks is influenced by first- and higher-order sequential effects, respectively due to the immediately previous and earlier trials. As response-to-stimulus interval (RSI) increases, the pattern of reaction times transits from a benefit-only mode, traditionally ascribed to automatic facilitation (AF), to a cost-benefit mode, due to strategic expectancy (SE). To illuminate the sources of such effects, we develop a connectionist network of two mutually-inhibiting neural decision units subject to feedback from previous trials. A study of separate biasing mechanisms shows that residual decision unit activity can lead only to first-order AF, but higher-order AF can result from strategic priming mediated by conflict-monitoring, which we instantiate in two distinct versions. A further mechanism mediates expectation-related biases that grow during RSI toward saturation levels determined by weighted repetition (or alternation) sequence lengths. Equipped with these mechanisms, the network, consistent with known neurophysiology, accounts for several sets of behavioral data over a wide range of RSIs. The results also suggest that practice speeds up all the mechanisms rather than adjusting their relative strengths

Dysfunctional beliefs and attitudes about sleep (DBAS) mediate outcomes in dCBT-I on psychological distress, fatigue, and insomnia severity

Objective/background Digital cognitive behavioral therapy for insomnia (dCBT-I) improves several sleep and health outcomes in individuals with insomnia. This study investigates whether changes in Dysfunctional Beliefs and Attitudes about Sleep (DBAS) during dCBT-I mediate changes in psychological distress, fatigue, and insomnia severity. Patients/methods The study presents a secondary planned analysis of data from 1073 participants in a randomized control trial (Total sample = 1721) of dCBT-I compared with patient education (PE). Self-ratings with the Dysfunctional Beliefs and Attitudes about Sleep (DBAS), the Hospital Anxiety Depression Scale (HADS), the Chalder Fatigue Scale (CFQ), and the Insomnia Severity Index (ISI) were obtained at baseline and 9-week follow-up. Hayes PROCESS mediation analyses were conducted to test for mediation. Results and conclusion sDBAS scores were significantly reduced at 9-week follow-up for those randomized to dCBT-I (n = 566) compared with PE (n = 507). The estimated mean difference was −1.49 (95% CI -1.66 to −1.31, p < .001, Cohen's d. = 0.93). DBAS mediated all the effect of dCBT-I on the HADS and the CFQ, and 64% of the change on the ISI (Estimated indirect effect −3.14, 95% CI -3.60 to −2.68) at 9-week follow-up compared with PE. Changes in the DBAS fully mediated the effects of dCBT-I on psychological distress and fatigue, and the DBAS partially mediated the effects on insomnia severity. These findings may have implications for understanding how dCBT-I works and highlights the role of changing cognitions in dCBT-I.publishedVersio

Digital cognitive behaviour therapy for insomnia in individuals with self-reported insomnia and chronic fatigue: A secondary analysis of a large scale randomized controlled trial

Insomnia is associated with fatigue, but it is unclear whether response to cognitive behaviour therapy for insomnia is altered in individuals with co-occurring symptoms of insomnia and chronic fatigue. This is a secondary analysis using data from 1717 participants with self-reported insomnia in a community-based randomized controlled trial of digital cognitive behaviour therapy for insomnia compared with patient education. We employed baseline ratings of the Chalder Fatigue Questionnaire to identify participants with more or fewer symptoms of self-reported chronic fatigue (chronic fatigue, n = 592; no chronic fatigue, n = 1125). We used linear mixed models with Insomnia Severity Index, Short Form-12 mental health, Short Form-12 physical health, and the Hospital Anxiety and Depression Scale separately as outcome variables. The main covariates were main effects and interactions for time (baseline versus 9-week follow-up), intervention, and chronic fatigue. Participants with chronic fatigue reported significantly greater improvements following digital cognitive behaviour therapy for insomnia compared with patient education on the Insomnia Severity Index (Cohen's d = 1.36, p < 0.001), Short Form-12 mental health (Cohen's d = 0.19, p = 0.029), and Hospital Anxiety and Depression Scale (Cohen's d = 0.18, p = 0.010). There were no significant differences in the effectiveness of digital cognitive behaviour therapy for insomnia between chronic fatigue and no chronic fatigue participants on any outcome. We conclude that in a large community-based sample of adults with insomnia, co-occurring chronic fatigue did not moderate the effectiveness of digital cognitive behaviour therapy for insomnia on any of the tested outcomes. This may further establish digital cognitive behaviour therapy for insomnia as an adjunctive intervention in individuals with physical and mental disorders.publishedVersio

Socio-demographic and lifestyle factors associated with overweight in a representative sample of 11-15 year olds in France: Results from the WHO-Collaborative Health Behaviour in School-aged Children (HBSC) cross-sectional study

<p>Abstract</p> <p>Background</p> <p>The prevalence of overweight in children and adolescents is high and overweight is associated with poor health outcomes over short- and long-term. Lifestyle factors can interact to influence overweight. Comprehensive studies linking overweight concomitantly with several demographic and potentially-modifiable lifestyle factors and health-risk behaviours are limited in adolescents - an age-group characterized by changes in lifestyle behaviours and high prevalence of overweight. Thus, the objective of the current study was to examine the association of overweight with several socio-demographic and lifestyle variables simultaneously in a representative sample of adolescents.</p> <p>Methods</p> <p>A nationally representative sample of 11-15 year-olds (n = 7154) in France participated as part of the WHO-Collaborative Health Behaviour in School-aged Children (HBSC) study. Students reported data on their age, height, weight, socio-demographic variables, lifestyle factors including nutrition practices, physical activity at two levels of intensity (moderate and vigorous), sedentary behaviours, as well as smoking and alcohol consumption patterns using standardized HBSC protocols. Overweight (including obesity) was defined using the IOTF reference. The multivariate association of overweight with several socio-demographic and lifestyle factors was examined with logistic regression models.</p> <p>Results</p> <p>The adjusted odds ratios for the association with overweight were: 1.80 (95% CI: 1.37-2.36) for low family affluence; 0.73 (0.60-0.88) for eating breakfast daily; 0.69 (0.56-0.84) for moderate to vigorous physical activity (MVPA); and 0.71 (0.59-0.86) for vigorous physical activity (VPA). Significant interactions between age and gender as well as television (TV) viewing and gender were noted: for boys, overweight was not associated with age or TV viewing; in contrast, for girls overweight correlated negatively with age and positively with TV viewing. Fruit and vegetable intake, computer and video-games use, smoking and alcohol consumption were not associated with overweight.</p> <p>Conclusions</p> <p>In multivariate model, family affluence, breakfast consumption and moderate to vigorous as well as vigorous physical activity were negatively associated with overweight. These findings extend previous research to a setting where multiple risk and protective factors were simultaneously examined and highlight the importance of multi-faceted approaches promoting physical activity and healthy food choices such as breakfast consumption for overweight prevention in adolescents.</p

Addressing climate change with behavioral science: a global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors