Behavioral Complexity: A Review

The theoretical basis of behavioral complexity theory is reviewed. A selection of recent research data are considered under topics of interest to behavioral science and related disciplines.     

The Measurement of Cognitive Complexity and Its Relationship With Political Extremism

Three studies tested the relationship between political extremism and cognitive complexity in an adult sample (N = 135), a sample of students (N = 145), and a sample of political party members (N = 47). According to value pluralism theory, advocates of extreme ideologies exhibit low levels of cognitive complexity. Context theory, in contrast, states that extremists think in a more complex and sophisticated way about politics. In accordance with context theory, significant positive correlations between cognitive complexity and extremist ideology were found in all samples. The results of these studies also revealed weak correlations among the cognitive complexity instruments used in previous research. Problems concerning the measurement of cognitive style and cognitive complexity are discussed.     

Behavioral Complexity Is in the Eye of the Beholder Effects of Cognitive Complexity and Message Complexity on Impressions of the Source of Comforting Messages

Recent theorizing suggests that exposure to sophisticated or behaviorally complex messages (i.e., messages that reflect a concern with multiple goals) may enhance the cognitiue development of message recipients. Reasoning that persons attempt to accommodate their cognitive structuring of an environment to the level of complexity in that environment, it was hypothesized that persons exposed to behaviorally complex messages would form more differentiated impressions of the message source than would persons exposed to less complex messages. It was also hypothesized that persons with complex systems of interpersonal constructs would form more differentiated impressions of the message source. Further, because persons with complex systems of interpersonal constructs should better appreciate the richness of behaviorally complex messages, it was hypothesized that message complexity would exert the strongest effect on impression differentiation for those with high levels of cognitive complexity. Participants in the study (410 college students) read a conversation containing comforting messages representing one of three levels of behavioral complexity; they subsequently wrote impressions of the source of these messages and these impressions were scored for the number of attributes they contained. Interpersonal cognitive complexity was assessed with Crockett's (1965) Role Category Questionnaire. Consistent with hypotheses, main effects for behavioral complexity and cognitive complexity were observed on impression differentiation; in addition, the anticipated interaction between message complexity and cognitive complexity was observed.     

Complexity Theory: Predictions Based on the Confluence of Science-Wide and Behavioral Theories

Views of behavioral and science wide complexity theories are briefly summarized. Theory-based predictions for human cognition and behavior based on both theories are advanced.
Streufert (in this special issue) has discussed the confluence of science-wide and behavioral complexity theory. Even though the former attempts to find common processes in all the sciences and the latter theory has, to date, limited itself to human behavior, there are many similarities in approach and in explanations of observed phenomena. Differences between the two theories are minor in comparison to their commonalities. Considering the many similarities, it may be useful to confirm (and possibly extend) behavioral complexity theory. A number of theorems, many familiar, some slightly modified, some new, will be provided at the end of this paper.     

职前教师情绪复杂性对情绪面孔加工的影响——来自行为、ERP和眼动的证据

采用ERP和眼动技术考察职前教师情绪复杂性对情绪面孔加工的影响。实验采用面孔识别范式,分别比较高低情绪复杂性的职前教师在加工4类基本情绪时的ERP和眼动差异。行为结果显示,除愉快情绪外,高分组在其他3种情绪加工的正确率上显著高于低分组,反应时上则显著短于低分组;ERP结果显示,高分组在P100、N170和LPP三个成分的幅值上均显著高于低分组,而在VPP、P200和N200三个成分的幅值上则显著低于低分组;眼动结果显示,高分组在总注视点个数、注视频率和瞳孔直径上高于低分组,而在眼跳时间和眼跳幅度上则小于低分组。这些结果表明情绪复杂性影响情绪面孔的加工,高情绪复杂性促使个体在情绪信息加工时对情绪类别信息更敏感,且采用更高的加工效率和更优的加工模式。     

The Accuracy of Behavioral Intention Versus Behavioral Expectation for Predicting Behavioral Goals

Researchers have largely overlooked the distinction between behavioral intention and behavioral expectation as predictors of one's own behavior. Moreover, the distinction between purely volitional behavior and behavioral goals, the latter of which may be impeded by such nonvolitional factors as lack of ability, lack of opportunity, habit, and environmental impediments, has also been blurred in the literature. Behavioral expectation is theorized to be based on a cognitive appraisal of one's behavioral intention and all other behavioral determinants of which one is aware. The present study argues and gives evidence that, although behavioral expectation and behavioral intention may have similar predictive accuracy for volitional behaviors, behavioral expectation is adequate, but behavioral intention may be inadequate for prediction of the accomplishment of behavioral goals.     

关系-表征复杂性模型

基于已有理论和研究背景所提出的关系-表征复杂性模型可以用作任务关系复杂性和儿童对其表征水平的分析框架,对于认知发展研究有较为普遍的意义。本文对关系复杂性(等级复杂性、关系内的和关系间的水平复杂性)、表征复杂性(表征广度、表征深度)以及各自的从属概念进行了理论界定。     

个体心理治疗的复杂性

本文尝试从复杂适应系统理论的角度对个体心理治疗的复杂性加以阐述。依据复杂适应系统理论,心理紊乱并不必然是心理健康的敌人;在个体心理治疗的动力发展过程中,治疗师与来访者相互适应突现配对联盟,来访者的心理变化或新的心理结构的突现具有不可预测性;心理治疗的目标是使得僵化有序、封闭、适应不良的系统朝向日益复杂、开放、灵活适应的状态转化。复杂适应系统理论为探索人类的心理体验与发展提供了新的思路和方法。     

The Complexity of Deviant Lifestyles

This article examines the complexity of the concept deviant lifestyle. A two-dimensional conceptual paradigm is developed. A horizontal depiction of eight deviant routines constituent to lifestyles and examples of these deviant activities is provided. The vertical dimension of the paradigm depicts five modes of frequency of occurrence of certain routine behavior.     

The Irreducible Complexity of Objectivity

The terms ``objectivity'' and ``objective'' are among the mostused yet ill-defined terms in the philosophy of science and epistemology. Common to all thevarious usages is the rhetorical force of ``I endorse this and you should too'', orto put it more mildly, that one should trust the outcome of the objectivity-producing process.The persuasive endorsement and call to trust provide some conceptual coherenceto objectivity, but the reference to objectivity is hopefully not merely an attemptat persuasive endorsement. What, in addition to epistemological endorsement,does objectivity carry with it? Drawing on recent historical and philosophical work,I articulate eight operationally accessible and distinct senses of objectivity.While there are links among these senses, providing cohesion to the concept, I argue thatnone of the eight senses is strictly reducible to the others, giving objectivity itsirreducible complexity.     

The Functional Complexity of Scientific Evidence

This article sketches the main features of traditional philosophical models of evidence, indicating idealizations in such models that it regards as doing more harm than good. It then proceeds to elaborate on an alternative model of evidence that is functionalist, complex, dynamic, and contextual, a view the author calls dynamic evidential functionalism (DEF). This alternative builds on insights from philosophy of scientific practice, Kuhnian philosophy of science, pragmatist epistemology, philosophy of experimentation, and functionalist philosophy of mind. Along the way, the article raises concerns about the total evidence condition, requirements of certainty or incorrigibility on evidence, and accounts that restrict the type of things that can serve as evidence (to, for example, sense data, facts about particulars). DEF can also help us see the special value of novel predictions and experiments as evidence, as well as help us think about how to critically evaluate the putative evidence to determine whether it is evidence.     

The Behavioral Genetics of Alcoholism

Twin and adoption studies consistently implicate the importance of genetic influences on alcoholism risk, especially in men. Heritability estimates suggest that approximately 50% to 60% of the variability in alcoholism liability is associated with genetic factors. Although there has been progress in identifying specific genes that predispose toward alcoholism, we know relatively little about the nature of the genetic influence on alcoholism risk. We also know relatively little about how genetic factors combine with environmental factors to affect alcoholism risk. Genotype-environment interaction models posit that alcoholism occurs when individuals both inherit a vulnerability to develop alcoholism and are reared in a provocative environment. Such models hold great promise for understanding alcoholism's etiology.     

The Behavioral Genetics of Religiousness

Behavioral geneticists have sought to characterize the genetic and environmental contributions to individual differences in religiousness. Behavioral genetic methodology is described and twin and adoption studies of religiousness are reviewed. It is concluded that familial resemblance for religiousness is due largely to shared environmental factors in childhood and adolescence, but to genetic factors in adulthood. Additional evidence shows that there is a genetic correlation between religiousness and antisocial and altruistic behavior. Claims for the discovery of a “God gene” are premature and unlikely, as any genetic influence is likely to represent the aggregate effect of many genetic factors.     

The Importance of Complexity in Model Selection

Model selection should be based not solely on goodness-of-fit, but must also consider model complexity. While the goal of mathematical modeling in cognitive psychology is to select one model from a set of competing models that best captures the underlying mental process, choosing the model that best fits a particular set of data will not achieve this goal. This is because a highly complex model can provide a good fit without necessarily bearing any interpretable relationship with the underlying process. It is shown that model selection based solely on the fit to observed data will result in the choice of an unnecessarily complex model that overfits the data, and thus generalizes poorly. The effect of over-fitting must be properly offset by model selection methods. An application example of selection methods using artificial data is also presented. Copyright 2000 Academic Press.