Nonlinearity in the Epidemiology of Complex Health and Disease Processes

Theoretical Medicine and Bioethics - The challenges posed by chronic illness have pointed out to epidemiologists the multifactorial complex nature of disease causality. This notion has been...     

汉字材料的性质对视觉短时记忆广度影响的实验研究

汉字材料的熟悉性和复杂性对视觉短时记忆（ＶＳＴＭ）广度的影响研究存在分析。本研究在实验设计上区分了汉语字词的熟悉性和复杂性维度,探讨了它们对ＶＳＴＭ广义的不同影响程度,结果表明：（１）材料的熟悉性是影响汉语字词ＶＳＴＭ广度的最重要因素,材料的复杂性影响不大;（２）在材料熟悉程度一致,被试在１１－２０岁年龄范围条件下,汉语字词ＶＳＴＭ广义将保持相对恒定（３）在承认“组块假说”的前提,汉语字词ＶＳＴＭ     

The impact of task complexity on information use in multi-attribute decision making

This study presents a process analysis of multi-attribute decision making. The decision problems concerned the selection of the most suitable candidate for a job opening. The problems varied in terms of complexity, i.e. the number of candidates and the number of attributes used to describe these alternatives. Results show that with an increasing number of alternatives, subjects (N = 48) used fewer attributes for the evaluation of alternatives, and made, on average, less references to the alternatives. The type of judgment most often used was absolute dimensional (comparison of an attribute to an absolute standard) and was used more often at the beginning than toward the end of the decision process. Overall, judgments were predominantly positive. The percentage of positive judgments decreased with increasing complexity, and toward the end of the decision process. Significantly more judgments, particularly positive ones, concerned the finally chosen alternative as compared to the rest of the alternatives. Finally, analysis of subjects' usage of decision rules revealed that increasing the number of alternatives resulted in an increasing use of elimination strategies. Implications of these findings for the design of decision aids will be discussed.     

Coding infant engagement in the Face-to-Face Still-Face paradigm using deep neural networks

BackgroundThe Face-to-Face Still-Face (FFSF) task is a validated and commonly used observational measure of mother-infant socio-emotional interactions. With the ascendence of deep learning-based facial emotion recognition, it is possible that common complex tasks, such as the coding of FFSF videos, could be coded with a high degree of accuracy by deep neural networks (DNNs). The primary objective of this study was to test the accuracy of four DNN image classification models against the coding of infant engagement conducted by two trained independent manual raters.Methods68 mother-infant dyads completed the FFSF task at three timepoints. Two trained independent raters undertook second-by-second manual coding of infant engagement into one of four classes: 1) positive affect, 2) neutral affect, 3) object/environment engagement, and 4) negative affect.ResultsTraining four different DNN models on 40,000 images, we achieved a maximum accuracy of 99.5% on image classification of infant frames taken from recordings of the FFSF task with a maximum inter-rater reliability (Cohen's κ-value) of 0.993.LimitationsThis study inherits all sampling and experimental limitations of the original study from which the data was taken, namely a relatively small and primarily White sample.ConclusionsBased on the extremely high classification accuracy, these findings suggest that DNNs could be used to code infant engagement in FFSF recordings. DNN image classification models may also have the potential to improve the efficiency of coding all observational tasks with applications across multiple fields of human behavior research.     

Perceived self-efficacy by Under-10 tennis players when scaling the equipment and play area

The modification of child-sports aims to develop an optimal learning environment that facilitates the emergence of desirable psychological outcomes (e.g., self-efficacy). The aim of the study was to assess the effect of reducing net height and court size on self-efficacy and shot-efficacy of U-10 tennis players in a real-game context. Twenty U-10 tennis players (M = 9.46, SD = 0.66 years of age; M = 3.65, SD = 1.53 years of tennis experience) played two round-robin tournaments one week apart in the same order and schedule. The first tournament was played under the International Tennis Federation’s Tennis 10s regulation at green stage (GT). Afterwards, the modified tournament (MT) was played with the same regulation GT, however, net height (0.91 m–0.80 m) and court size (23.77 m × 8.23 m–18.00 m × 8.23 m) were reduced. Results accomplished using Bayesian and Frequentist inferences showed an increase in players’ self-efficacy when serving in MT than GT (BF₁₀ = 4.796; δ = −0.576; and p = .011). This is increase may be due to a reduction in their serving faults in MT (BF₁₀ = 6.169; δ = −0.591; and p = .010). Therefore, reducing net height and court size enhances the serve performance and self-efficacy and thus promotes positive tennis experiences.     

Association of parent,coach, and peer motivational climate with high school athlete burnout and engagement: Comparing mediation and moderation models

The purpose of this study was to (1) examine the direct association of parent-, coach-, and peer-initiated motivational climate with high school athlete burnout and engagement and (2) evaluate whether peer-initiated motivational climate mediates or moderates the association of coach-initiated motivational climate with burnout and engagement. Athletes (n = 150) completed a survey on their perceptions of parent-, coach-, and peer-initiated motivational climate, burnout, and engagement. Findings supported the mediation model, but not the moderation model. In addition to mastery and performance climate direct effects, significant medium-to-large indirect pathways from coach mastery climate → peer mastery climate → burnout, β = -.15, 95% CI [-.333, −.009], and coach mastery climate → peer mastery climate → engagement, β = .19, 95% CI [.020, .293] were observed. Findings support that a parent, coach, and peer-initiated mastery motivational climate was associated with burnout and engagement while a performance climate was mostly unrelated to these indices of athlete well-being. In addition to direct associations with burnout and engagement, coaches also had an indirect association through peer mastery-initiated motivational climate. Findings advance understanding of how parents, coaches, and peers conjointly shape athlete burnout and engagement.     

Aggressive and affiliative behavior in green monkeys with differing housing complexity

Eleven green monkeys (Cercopithecus aethiops) were combined into three social groups (two heterosexual, one all-male) in enclosures with similar volume but different levels of environmental complexity (two or four compartments). Agonistic and affiliative interactions were recorded over a 21-week period. The two heterosexual groups had their environmental complexity reduced (number of compartments reduced by one-half and volume/floorspace reduced by one-third) for a 5-week period in the middle of the study. Rates of contact aggression were low throughout the study. In the group with complexity reduced to one compartment, rates of noncontact aggression and affiliative behavior increased, and remained high after complexity was restored. In the group reduced to two compartments, rates of affiliative behavior increased but rates of noncontact aggression decreased, trends which continued after complexity was restored. The all-male group exhibited low rates of affiliative behavior throughout. Two compartments appear to foster successful group formation, but any change in a group's enclosure can have long-term effects on rates of aggression. © 1992 Wiley-Liss, Inc.     

绩效评价的若干问题

通过对绩效的内涵、绩效评价标准的确定、评量指标体系的构建以及多样性评量指标的整合意义与方法等四个绩效评价的最基本问题进行反思 ,提出如下观点 :(1 )对绩效进行考量时必须同时考虑时间、方式和结果三个维度。 (2 )绩效评价标准的确定应先于具体评量指标的选择 ,且应保持一定的稳定性 ,不可随意增删 ;(3 )评量指标体系的构建应本着贵精不贵多、贵明确不贵模糊、贵敏感不贵迟钝 ,贵关键不贵空泛的原则进行 ;(4)多样性评量指标是否整合需根据具体的需要而定 ,整合时要考虑评量指标本身的权重差异以及不同评价者由于对标准尺度掌握的松紧不一和评判角度不同所带来的对最终评价结果的影响。     

Young children combine sensory cues with learned information in a statistically efficient manner: But task complexity matters

Human adults are adept at mitigating the influence of sensory uncertainty on task performance by integrating sensory cues with learned prior information, in a Bayes‐optimal fashion. Previous research has shown that young children and infants are sensitive to environmental regularities, and that the ability to learn and use such regularities is involved in the development of several cognitive abilities. However, it has also been reported that children younger than 8 do not combine simultaneously available sensory cues in a Bayes‐optimal fashion. Thus, it remains unclear whether, and by what age, children can combine sensory cues with learned regularities in an adult manner. Here, we examine the performance of 6‐ to 7‐year‐old children when tasked with localizing a ‘hidden’ target by combining uncertain sensory information with prior information learned over repeated exposure to the task. We demonstrate that 6‐ to 7‐year‐olds learn task‐relevant statistics at a rate on par with adults, and like adults, are capable of integrating learned regularities with sensory information in a statistically efficient manner. We also show that variables such as task complexity can influence young children's behavior to a greater extent than that of adults, leading their behavior to look sub‐optimal. Our findings have important implications for how we should interpret failures in young children's ability to carry out sophisticated computations. These ‘failures’ need not be attributed to deficits in the fundamental computational capacity available to children early in development, but rather to ancillary immaturities in general cognitive abilities that mask the operation of these computations in specific situations.     

How drivers adapt their behaviour to changes in task complexity: The role of secondary task demands and road environment factors

The present study investigates the impact of different sources of task complexity such as driving demands and secondary task demands on driver behaviour. Although much research has been dedicated to understanding the impact of secondary task demands or specific road traffic environments on driving performance, there is little information on how drivers adapt their behaviour to their combined presence. This paper aims to describe driver behaviour while negotiating different sources of task complexity, including mobile phone use while driving (i.e., calling and texting) and different road environments (i.e., straight segments, curves, hills, tunnels, and curves on hills). A driving simulator experiment was conducted to explore the effects of different road scenarios and different types of distraction while driving. The collected data was used to estimate driving behaviour through a Generalized Linear Mixed Model (GLMM) with repeated measures. The analysis was divided into two phases. Phase one aimed to evaluate driver performance under the presence and absence of pedestrians and oncoming traffic, different lanes width and different types of distraction. The second phase analysed driver behaviour when driving through different road geometries and lane widths and under different types of distraction. The results of the experiment indicated that drivers are likely to overcorrect position in the vehicle lane in the presence of pedestrians and oncoming traffic. The effect of road geometry on driver behaviour was found to be greater than the effect of mobile phone distraction. Curved roads and hills were found to influence preferred speeds and lateral position the most. The results of this investigation also show that drivers under visual-manual distraction had a higher standard deviation of speed and lateral position compared to the cognitive distraction and the non-distraction condition.