贝叶斯统计方法的应用与现状

贝叶斯统计方法是心理学数据分析的热门方法。研究全面论述贝叶斯方法在心理学领域的应用与方向。现阶段贝叶斯方法以模拟研究为主,应用方向为心理学研究常用的项目反应理论、认知诊断、计算机自适应、结构方程模型。同时,评述发现贝叶斯方法正逐步被国内心理学研究者所接受。最后,文章讨论了当下贝叶斯统计在心理学研究中应用的局限性及可能的原因,建议统计学者开发界面友好的贝叶斯软件,并在心理学课程中加入贝叶斯知识。     

Investigating temporal variations in pedestrian crossing behavior at semi-controlled crosswalks: A Bayesian multilevel modeling approach

“Semi-controlled” crosswalks are unsignalized, but have clear pavement markings and “yield to pedestrian” signs. At these locations, pedestrians and motorists frequently interact to determine who should proceed first. When interacting with drivers, pedestrian crossing decisions are complex events that involve a variety of human responses, as well as vehicle dynamics, traffic characteristics, and environmental conditions. In addition, these complexities can be subject to temporal effects. Without considering temporal variations in pedestrian-motorist interaction, statistical methods could lead to biased coefficient estimates and inaccurate conclusions.The study developed a Bayesian multilevel logistic regression (BMLR) model to capture heterogeneities in pedestrian interaction behavior during four different time periods. The proposed method incorporates time-specific effects that vary randomly between time-periods based on a weakly informative prior. The results indicate significant factors, some of which confirm previous research and some that are new ways to explain pedestrian behavior at the individual level. The identification of variables such as FlowOn and FlowWait sheds light on the interactions between pedestrians – providing more information than the single GroupSize measure.Some consequent safety implications are discussed from the perspectives of vehicle dynamics, vehicle flow rate and pedestrian volume. The more detailed metrics developed in this paper will provide a valuable starting point. for the design of crosswalk controls that will foster a higher degree of compliance and less delay.     

Too bored for sports? Adaptive and less-adaptive latent personality profiles for exercise behavior

Physical exercise is an effective tool for improving public health, but the general population exercises too little. Drawing on recent theorizing on the combined role of boredom and self-control in guiding goal-directed behavior, we test the hypothesis that individual differences in boredom and self-control differentiate high from low exercisers. The role of boredom as a non-adaptive disposition is of particular interest, because research on boredom in sports is scarce. Here, we investigate the role of such individual differences in self-reported weekly exercise behavior (in minutes) in a sample of N = 507 participants (n = 200 female, M_age = 36.43 (±9.54)). We used the robust variant of Mahalanobis distance to detect and remove n = 51 multivariate outliers and then performed latent profile analysis to assess if boredom (boredom proneness; exercise-related boredom) and self-control (trait self-control; if-then planning) combine into identifiable latent profiles. In line with theoretical considerations, the Bayesian Information Criterion favored a solution with two latent profiles. One profile was characterized by higher-than-average exercise-related boredom and boredom proneness and lower-than-average self-control and if-then planning values. This pattern was reversed for the second profile. A one-sided Bayesian two-sample t-test supported the hypothesis that the first profile is associated with less exercise behavior than the second profile, BF = 16.93. Our results foster the notion of self-control and if-then planning as adaptive dispositions. More importantly, they point to an important role of boredom in the exercise setting: exercise-related boredom and getting easily bored in general are associated with less exercise activity. This is in line with recent theorizing on boredoms' and self-controls’ function in guiding goal-directed behavior.     

The social dynamics involved in recovery and return to sport following a sport-related concussion: A study of three athlete-teammate-coach triads

An athlete's connection to their team and team members is an important part of their sport experience. However, researchers currently know little about the nature of these social dynamics with respect to concussed athletes. Our study explored athletes' recovery and reintegration into the team environment following a sport-related concussion. We conducted semi-structured interviews with each member of three athlete-teammate-coach triads (N = 9). We analysed the data using thematic narrative analysis and present the results as three stories that focused on each athlete's experience. For Cassie, we found two major plot points in her story: the transition in her role (and shift in identity) from athlete to student assistant coach/team manager and, once recovered, back to an athlete on the team. For Jess, we found that the main plot in her story was “pressure”. Specifically, the interplay between internal (placed on herself) and external (perceived from teammates and coaches) pressures to return to sport. In the third and final story, the main plot point was the tensions that arose from Jaden's preferences for social support and the type of support that his teammates and coaches believed he needed during his recovery. Our results highlight the interplay between athlete's personal and social identities, feelings of pressure to return and readiness, and the challenges of providing the right amount and type of social support. This research contributes to our limited understanding of the social dynamics involved in athletes' return to sport following a concussion.     

教与学的大脑：人际神经科学助推教育研究

如何从神经生理层面刻画教育活动的人际互动模式和动态性是教育神经科学面临的一个重要挑战。人际神经科学视角为其提供了可能的解决途径; 这一新兴的视角通过记录和分析进行同一认知活动时两人或多人大脑活动之间的关联, 来揭示大脑活动的群体模式。目前, 人际神经科学方法已被应用于教育研究, 例如监控教学过程、预测教学效果和识别教学影响因素, 相应的研究成果对教育活动具有重要启示。未来的研究者可以更多地关注不同学习水平的学生大脑的互动机制及人际神经科学方法应用于技能教学及线上教学评估的巨大潜力。     

A systematic review of the effectiveness of machine learning for predicting psychosocial outcomes in acquired brain injury: Which algorithms are used and why?

Clinicians working in the field of acquired brain injury (ABI, an injury to the brain sustained after birth) are challenged to develop suitable care pathways for an individual client’s needs. Being able to predict psychosocial outcomes after ABI would enable clinicians and service providers to make advance decisions and better tailor care plans. Machine learning (ML, a predictive method from the field of artificial intelligence) is increasingly used for predicting ABI outcomes. This review aimed to examine the efficacy of using ML to make psychosocial predictions in ABI, evaluate the methodological quality of studies, and understand researchers’ rationale for their choice of ML algorithms. Nine studies were reviewed from five databases, predicting a range of psychosocial outcomes from stroke, traumatic brain injury, and concussion. Eleven types of ML were employed with a total of 75 ML models. Every model was evaluated as having high risk of bias, unable to provide adequate evidence for predictive performance due to poor methodological quality. Overall, there was limited rationale for the choice of ML algorithms and poor evaluation of the methodological limitations by study authors. Considerations for overcoming methodological shortcomings are discussed, along with suggestions for assessing the suitability of data and suitability of ML algorithms for different ABI research questions.     

Visual aspects of centrally elicited attack behavior in the cat: “Patterned reflexes” associated with selection of and approach to a rat

It has been previously suggested that the electrical brain stimulation which elicits quiet-biting attack in the cat actively affects the way the central nervous system processes visual and tactile information concerned with the reflexes involved in the terminal aspects of attack. In order to examine the effects of brain stimulation on a nonterminal aspect of attack – the stimulated cat's selection of and approach to a rat – cats were implanted with attack-eliciting electrodes in both the lateral hypothalamus and the midbrain ventral tegmental area. These cats were then tested in an 8-ft-long cage, one end of which was divided into three, 2-ft-long parallel compartments, whose openings faced the end of the cage from which the cat commenced its approach. An anesthetized rat was placed at the back of one compartment, a bowl of food at the back of another compartment, and the third compartment contained no object. It was found in the first experiment that the attack elicited by nearly all electrodes was selectively directed at the rat. However, the success of the cat in finding the compartment containing the rat varied dramatically for different electrodes in the same cat. Further, these differences were stable and did not change as the cat gained experience with the task. The results suggested that the stimulation of different brain sites in the same cat differentially affected the visual neural mechanisms involved in guiding a cat to a rat. Previous studies have also suggested that the effects of brain stimulation which elicits quiet-biting attack are largely lateralized to the side of the brain stimulated. In order to determine if the effects of stimulation on the neural mechanisms mediating the visually guided approach of a cat to a rat were also lateralized, attempts were made in a second experiment to disrupt the visual input to one side of the brain by unilaterally transecting the optic tract. It was found that this manipulation interfered with the visually guided selective approach to a rat, if the cat was stimulated through hypothalamic or mid-brain electrodes ipsilateral to the optic tract transection, but not if the hypothalamic or midbrain stimulation was on the contralateral (visually intact) side of the brain. However, any final interpretation of the results was confounded by the finding in all of these cats of a complex syndrome of neglect of all contralateral sensory information.     

Information seeking on Bayesian conditional probability problems: A fuzzy-trace theory account

Recently, the ‘heuristics and biases’ approach to the study of decision making has been criticized, with a call for better integrated theory. Three experiments stemming from fuzzy-trace theory addressed information seeking on probability problems, and the cognitive representation of hit-rates, base-rates, and the contrapositive. As predicted by the fuzzy-trace principle of ‘denominator neglect’, many subjects exhibited ‘conversion errors’, confusing the hit-rate, P(A|B), with the answer, P(B|A). These subjects sought base-rates less often than other subjects. On causal problems, more subjects correctly represented base-rates, sought base-rates more often, and produced more accurate estimates than on non-causal problems. Subjects tutored on the meaning of the hit-rate sought the base-rate more often, and were more accurate than control subjects. Results are explained by fuzzy-trace theory principles of gist extraction, fuzzy processing preference, denominator neglect, and output interference.     

Regression II. Development through regression

As shown in our previous paper (‘Regression I. Experimental approaches to regression’, JAP, 65, 2, 345-65), the common mechanism of regression can be described as reversible dedifferentiation, which is understood as a relative increase of the proportion of low-differentiated (older) systems in actualized experience. Experimental data show that regression following disease (chronic tension headache) is followed by adaptation and an increase in system differentiation in that experience domain which contains systems responsible for that adaptation. The results of mathematical modelling support the idea that reversible dedifferentiation can be one of the mechanisms for increasing the effectiveness of adaptation through learning. Reversible dedifferentiation, which is phenomenologically described as regression, is a general mechanism for restructuring the organism-environment interactions in situations where behaviours that were effective in the past become ineffective. Reversible dedifferentiation has evolved as a component of adaptation when new behaviours are formed and large-scale modifications in the existing behaviours are required in the face of changes in the external and/or internal environment. Thus, the authors believe that this article provides evidence for Jung’s view that regression is not only a ‘return’ to past forms of thinking, affects and behaviour, but that regressive processes provide a significant impetus for psychological growth and development.     

Cerebral blood flow in 5‐ to 8‐month‐olds: Regional tissue maturity is associated with infant affect

Infancy is marked by rapid neural and emotional development. The relation between brain function and emotion in infancy, however, is not well understood. Methods for measuring brain function predominantly rely on the BOLD signal; however, interpretation of the BOLD signal in infancy is challenging because the neuronal‐hemodynamic relation is immature. Regional cerebral blood flow (rCBF) provides a context for the infant BOLD signal and can yield insight into the developmental maturity of brain regions that may support affective behaviors. This study aims to elucidate the relations among rCBF, age, and emotion in infancy. One hundred and seven mothers reported their infants' (infant age M ± SD = 6.14 ± 0.51 months) temperament. A subsample of infants completed MRI scans, 38 of whom produced usable perfusion MRI during natural sleep to quantify rCBF. Mother‐infant dyads completed the repeated Still‐Face Paradigm, from which infant affect reactivity and recovery to stress were quantified. We tested associations of infant age at scan, temperament factor scores, and observed affect reactivity and recovery with voxel‐wise rCBF. Infant age was positively associated with CBF in nearly all voxels, with peaks located in sensory cortices and the ventral prefrontal cortex, supporting the formulation that rCBF is an indicator of tissue maturity. Temperamental Negative Affect and recovery of positive affect following a stressor were positively associated with rCBF in several cortical and subcortical limbic regions, including the orbitofrontal cortex and inferior frontal gyrus. This finding yields insight into the nature of affective neurodevelopment during infancy. Specifically, infants with relatively increased prefrontal cortex maturity may evidence a disposition toward greater negative affect and negative reactivity in their daily lives yet show better recovery of positive affect following a social stressor.