童年中期儿童社会能力与学业成就的交叉滞后研究

本研究采用同伴提名法、问卷法,对武汉市一所小学3、4、5、6年级儿童进行6个月的追踪调查。采用交叉时序滞后设计,考察了同伴关系4个特征水平(群体水平、双向关系水平、人际互动水平和个体特征水平)的变量与学业成就的相互预测关系。结果表明,在控制了前测学业成就后,前测的社会喜好、积极友谊质量、社交领导行为可以分别正向预测后测的学业成就,而前测的攻击行为可以负向预测后期的学业成就;在控制了前测的社交自我知觉后,学业成就可以正向预测后期的社交自我知觉。     

Making sense of social robots: A structural analysis of the layperson's social representation of robots

IntroductionGiven their novelty, social robots (i.e., robots using natural language, displaying and recognizing emotions) will generate uncertainty among users. Social representations allow making sense of the new, drawing from existing knowledge.ObjectiveA free association questionnaire was administered to 212 Portuguese adults to identify the social representation of robot.MethodData was analysed with EVOC 2000 and SIMI 2000 software.ResultsThe social representation of robot is organized around the ideas of technology, help and future. Differences in the representation according to age, gender and level of education where also identified.ConclusionThe social representation of robot is marked by the conception of it as a tool. This contrasts with the concept of social robots as social agents. Implications for social robot's acceptance are discussed.     

Key players in sport teams. An exploratory study on the effects of attachment styles on intra-team relational networks

Relationship issues in sport are considered vital for the overall wellbeing of athletes (Jowett, 2005). The way athletes interact, create and maintain relationships is thought to be powerfully influenced by the athletes' attachment states of mind (Thomson & Jaque, 2018). To our knowledge, no study so far has investigated the impact players' attachment styles, as personality dispositions, have on overall intra-team relationship dynamics. This paper examines intra-team social relational networks from the perspective of adult attachment theory. Cross-sectional data were collected from 10 sport teams (158 players) from different sports. Self-report data were collected to assess attachment style and social relationships with teammates. Social network analyses (SNA) were used to calculate players' centrality scores based on incoming and outgoing relational nominations. Multilevel linear analysis was further performed to check inferential relationships between the study variables. Data showed that attachment styles of players, as personality dispositions, affected partly centrality degree positions within the various team social relational networks. The study offers an innovative perspective on the interactional and dynamic world of social relationships in sports teams and confirms that attachment style differences among players predispose them to particular positions within the team social relational networks. Although the current research has an exploratory character, it shows a new direction in the study of groups and sport team dynamics.     

Molecular (moment-to-moment) and molar (aggregate) analyses of behavior

Ten meanings or usages of the terms molecular and molar analyses are based on (1) numbers of responses, (2) durations of activities, (3) levels, (4) scales, (5) contiguity versus correlation, (6) behavioral standards, (7) function with or without structure, (8) local versus global phenomena, and (9) control by shaping of sequential moment-to-moment behavior. These usages reveal divisive viewpoints along with ambiguities in the Law of Effect, the definition of an operant, response strength, response probability, random behavior, time allocation, shaping, controlled versus uncontrolled operants, and roles for ordinary language. Usage 10 is less divisive and combines, and in that sense unifies, molecular behavior, defined as shaped moment-to-moment sequential behaving, and molar, defined as averages of aggregates of those shaped responses. It combines shaping, that establishes and changes operant behaviors, and strengthening that changes the amounts of those shaped behaviors. I conclude that general behavioral theory will combine strengthening with such methods as parametric, hybrid, or nonparametric shaping, and will use computational methods to simulate moment-to-moment behavior streams from which any aggregates of theoretical interest may be computed. Such a synthesis may not require different levels, scales, or new scientific paradigms.     

The Latent Structure of Substance Use Among American Indian Adolescents: An Example Using Categorical Variables

Researchers frequently have only categorical data to analyze and cannot, for theoretical or methodological reasons, assume that the observed variables are discrete representations of an underlying continuous variable. We present latent class analysis as an alternative method of measuring latent variables in these circumstances. Latent class analysis does not require the assumptions of factor analyses about the nature of manifest and latent variables, but does allow the use of more precise model selection than techniques such as cluster analysis. We modeled the lifetime substance use of American Indian youth. The latent class model of American Indian teenagers' substance use had four classes: Abstaining, Predominantly Alcohol, Predominantly Alcohol and Marijuana, and Plural Substance. We then demonstrated the usefulness of this latent variable by using it to differentiate levels of several variables in a manner consistent with Social Cognitive Theory.     

Cross-Cultural Generalizability of CBCL Syndromes Across Three Continents: From the USA and Holland to Australia

The study asked how well Achenbach's 8-factor cross-informant model for the Child Behavior Checklist (Achenbach, 1991a, 1991b, 1991c) fits clinic data in the USA, Holland, and Australia. DeGroot et al.'s Dutch 8-factor model (DeGroot, Koot, & Verhulst 1994) was also tested for its cross-cultural generalizability. Achenbach's matched clinical sample data (N = 2110) were analyzed and contrasted with the previously reported Dutch findings (N = 2335), as well as a new data set collected on clinic referred children and adolescents in Australia (N = 2237). Confirmatory factor analyses supported the Dutch as much as the American model in the USA, Holland, and Australia. Although about 90% of items showed convergent validity across models and countries, the attention and especially the social problems factor found least support. Most double loadings in the current models were not upheld. Instead, additional analyses discovered a number of unmodelled loadings including many cross-loadings. This led to the redefinition of the social problems factor as a mean aggression factor (with associated social problems) whereas the original aggression factor focuses on emotional acting out and the delinquent factor describes an evasive, covert type of antisocial behavior. Overall most support was obtained for the withdrawn, somatic, anxious/depressed, thought problems, and aggressive factors.     

Multilevel covariance structure analysis of sibling substance use and intrafamily conflict

Conventional covariance structure analysis, such as factor analysis, is often applied to data that are obtained in a hierarchical fashion, such as siblings observed within families. A more appropriate specification is demonstrated which explicitly models the within-level and between-level covariance matrices of sibling substance use and intrafamily conflict. Participants were 267 target adolescents (mean age=13.11 years) and 318 siblings (mean age=15.03 years). The level of homogeneity within sibling clusters, and heterogeneity among families, was sufficient to conduct a multilevel covariance structure analysis (MCA). Parental and family-level variables consisting of marital status, socioeconomic status, marital discord, parent use, and modeling of substances were used to explain heterogeneity among families. Marital discord predicted intrafamily conflict, and parent marital status and modeling of substances predicted sibling substance use. Advantages and uses of hierarchical designs and conventional covariance structure software for multilevel data are discussed.     

Response acquisition under targeted percentile schedules: a continuing quandary for molar models of operant behavior.

The number of responses rats made in a "run" of consecutive left-lever presses, prior to a trial-ending right-lever press, was differentiated using a targeted percentile procedure. Under the nondifferential baseline, reinforcement was provided with a probability of .33 at the end of a trial, irrespective of the run on that trial. Most of the 30 subjects made short runs under these conditions, with the mean for the group around three. A targeted percentile schedule was next used to differentiate run length around the target value of 12. The current run was reinforced if it was nearer the target than 67% of those runs in the last 24 trials that were on the same side of the target as the current run. Programming reinforcement in this way held overall reinforcement probability per trial constant at .33 while providing reinforcement differentially with respect to runs more closely approximating the target of 12. The mean run for the group under this procedure increased to approximately 10. Runs approaching the target length were acquired even though differentiated responding produced the same probability of reinforcement per trial, decreased the probability of reinforcement per response, did not increase overall reinforcement rate, and generally substantially reduced it (i.e., in only a few instances did response rate increase sufficiently to compensate for the increase in the number of responses per trial). Models of behavior predicated solely on molar reinforcement contingencies all predict that runs should remain short throughout this experiment, because such runs promote both the most frequent reinforcement and the greatest reinforcement per press. To the contrary, 29 of 30 subjects emitted runs in the vicinity of the target, driving down reinforcement rate while greatly increasing the number of presses per pellet. These results illustrate the powerful effects of local reinforcement contingencies in changing behavior, and in doing so underscore a need for more dynamic quantitative formulations of operant behavior to supplement or supplant the currently prevalent static ones.     

The beck anxiety inventory: Psychometric properties in a community population

This study presents data on the norms and psychometric properties of the Beck Anxiety Inventory (BAI), using a sample of 225 community adult volunteers. Maximum-likelihood confirmatory factor analyses of previously published models of the BAI: a two-factor model and a five-factor model, showed that the fit of each model was unacceptable. Also, the fit of the single-factor model was poor. Exploratory principal-components analyses with varimax and oblique rotations suggested four BAI components within this sample. Satisfactory levels of reliability were established for the BAI subscales. Finally, the relations between the BAI total and subscale scores and a related measure of anxiety and with another self-report measure of psychological distress were examined.This paper was presented at the 27th Annual Convention of the Association for Advancement of Behavior Therapy, Atlanta, Georgia, November 1993.