Networks of prospective thoughts: The organisational role of emotion and its impact on well-being

Recent research has shown that many prospective thoughts are organised in networks of related events, but the relational dimensions that contribute to the formation of such networks are not fully understood. Here, we investigated the organisational role of emotion by using cues of different valence for eliciting event networks. We found that manipulating the emotional valence of cues influenced the characteristics of events within networks, and that members of a network were more similar to each other on affective components than they were to members of other networks. Furthermore, a substantial proportion of events within networks were part of thematic clusters and cluster membership significantly modulated the impact of represented events on current well-being, in part through an intensification of the emotion felt when thinking about these events. These findings demonstrate that emotion contributes to the organisation of future thoughts in networks that can affect people's well-being.     

Sequential validation of cluster analytic subtypes of homeless veterans

To identify subgroups within the homeless population, a number of researchers have employed cluster analytic statistical procedures. Although this is an appropriate application of cluster analysis, many studies have not employed important statistical safeguards against arbitrary results. This study demonstrates a cluster analytic procedure—sequential validation—that enhances the replicability, external validity, and cross-validity of cluster solutions. The procedure is applied to a nationwide sample of 745 homeless veterans. After 12 different clustering procedures were subjected to derivation, replication, external validation, and cross-validation phases, a 4-cluster Ward solution emerged as the most sound. Substantively, the clusters were an alcoholic subtype, a psychiatrically impaired subtype, a best functioning subtype, and a multiproblem subtype. The generalizability of these subgroups to other contexts was assessed by comparing them to subgroups identified in other homelessness research. Suggestions were made for improving the quality of cluster analytic research in community psychology.     

Order-Constrained Solutions in <Emphasis Type="Italic">K</Emphasis>-Means Clustering: Even Better Than Being Globally Optimal

This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that although the usual K-means sum-of-squared-error criterion is not guaranteed to be minimal, a true underlying cluster structure may be more accurately recovered. Also, substantive interpretability seems generally improved when constrained solutions are considered. We illustrate the procedure with several data sets from the literature.     

Optimal Partitioning of a Data Set Based on the p-Median Model

Although the K-means algorithm for minimizing the within-cluster sums of squared deviations from cluster centroids is perhaps the most common method for applied cluster analyses, a variety of other criteria are available. The p-median model is an especially well-studied clustering problem that requires the selection of p objects to serve as cluster centers. The objective is to choose the cluster centers such that the sum of the Euclidean distances (or some other dissimilarity measure) of objects assigned to each center is minimized. Using 12 data sets from the literature, we demonstrate that a three-stage procedure consisting of a greedy heuristic, Lagrangian relaxation, and a branch-and-bound algorithm can produce globally optimal solutions for p-median problems of nontrivial size (several hundred objects, five or more variables, and up to 10 clusters). We also report the results of an application of the p-median model to an empirical data set from the telecommunications industry.     

海船驾驶员身心素质测评指标的建构

采用主次因素排列图法,确定了海船驾驶员身心素质的主要因素：应用变量()指标)聚类分析,对海船驾驶员身心素质结构的维度进行了研究,建构了海船驾驶员身心素质的10项测评指标;经新旧样本聚类结果比较,其效度符合心理测量学要求。本研究结果为我国海船驾驶员身心素质测评指标的界定提供了理论依据。     

Ethological analysis of the male rat's socioagonistic behavior in a resident-intruder paradigm

The object of the present study was to assess the rat's socioagonistic behavior by means of ethological procedures. Two groups of male Wistar rats were used: 33 residents and 66 intruders. To allow reliable characterization of social and agonistic patterns, social interactions were increased by the isolation of residents and, on the other hand, both offense in residents and defense in intruders were increased by differences in weight, agonistic experience, and habituation to the enclosure. Encounters were videotaped, and the animals' behavior was analyzed by a 27-pattern ethogram and a software package made up to this end. Several patterns parameters were quantified, and two ethological mathematical models were employed: sequential analysis of preferential directions and cluster analysis based on similarities between patterns. Following mean latencies of the most frequent elements, the first four pattern sequences appeared to be the same in both groups of animals. From the fifth pattern on, residents displayed mainly dominance and threat, whereas intruders showed defensive and submissive patterns. Attack was also displayed by residents, but less frequently than dominance and threat. The alpha status was established by two sorts of domination, either through dominance and threat or by attack. The mean frequency of the intraindividual transition of patterns was higher in residents than in intruders. Pathway graphs, derived from sequential analysis, showed some common dyads, triads, or quadrads of patterns, but they basically defined different behavior structures in residents and intruders. Dendrograms, obtained by cluster analysis, allowed classification of patterns into behavior categories. The categories in residents were exploration, dominance, threat, and attack, and they encompassed 18 elements; in intruders the categories were exploration, dominance, and defense, and they consisted of nine patterns. A submissive category composed of three patterns could be also deduced considering similarity results. To summarize, six behavior categories were obtained: one “socioindividual” (exploration) and five “agonistic” (dominance, threat, attack, submission, and defense). In conclusion, the present study shows how ethological procedures may help to elucidate the rat's socioagonistic behavior and to classify the observed patterns into behavior categories.     

Contribution of past and future self-defining event networks to personal identity

Personal identity is nourished by memories of significant past experiences and by the imagination of meaningful events that one anticipates to happen in the future. The organisation of such self-defining memories and prospective thoughts in the cognitive system has received little empirical attention, however. In the present study, our aims were to investigate to what extent self-defining memories and future projections are organised in networks of related events, and to determine the nature of the connections linking these events. Our results reveal the existence of self-defining event networks, composed of both memories and future events of similar centrality for identity and characterised by similar identity motives. These self-defining networks expressed a strong internal coherence and frequently organised events in meaningful themes and sequences (i.e., event clusters). Finally, we found that the satisfaction of identity motives in represented events and the presence of clustering across events both contributed to increase in the perceived centrality of events for the sense of identity. Overall, these findings suggest that personal identity is not only nourished by representations of significant past and future events, but also depends on the formation of coherent networks of related events that provide an overarching meaning to specific life experiences.     

The relationship between maladaptive personality functioning and problematic technology use in adolescence: A cluster analysis approach

In the last two decades, scientific research has explored the problematic use of internet, videogames and mobile phones. However, there is still little consistent knowledge regarding the co-occurrence of problematic technology use and the role of maladaptive personality characteristics in adolescence. The present study aimed to investigate adolescents' styles of technology use with a cluster analysis approach focusing on personality functioning. The sample comprised 408 Italian adolescents (46.3% males) aged 11 to 18 years (M _age = 13.80; SD = 2.08). Data were collected using the Internet Addiction Test, the Videogame Dependency Scale, the Test of Mobile-Phone Dependence Brief Form and the Personality Inventory for DSM5 Brief Form. Results provided a four-cluster solution based on the co-occurrence of problematic technology use. The four clusters were labeled as follows: cluster 1: “Above average internet and mobile-phone use”; cluster 2: “Below average technology use”; cluster 3: “Above average videogame use”; and cluster 4: “Problematic technology use.” Analyses on demographic variables (e.g., gender and age) demonstrated significant differences between the four groups. Adolescents with high levels of problematic technology use reported greater overall personality dysfunction than the other three groups. This finding supported our hypothesis on maladaptive personality functioning in adolescents at risk for addiction. Finally, the Antagonism domain played a specific role in differentiating the severity of adolescents' involvement in technology use. Further studies are needed to confirm our findings and to plan preventive interventions as well as therapeutic treatments.     

Adjusting for information inflation due to local dependency in moderately large item clusters

When multiple items are clustered around a reading passage, the local independence assumption in item response theory is often violated. The amount of information contained in an item cluster is usually overestimated if violation of local independence is ignored and items are treated as locally independent when in fact they are not. In this article we provide a general method that adjusts for the inflation of information associated with a test containing item clusters. A computational scheme was presented for the evaluation of the factor of adjustment for clusters in the restrictive case of two items per cluster, and the general case of more than two items per cluster. The methodology was motivated by a study of the NAEP Reading Assessment. We present a simulated study along with an analysis of a NAEP data set.The research was supported under the National Assessment of Educational Progress (Grant No. R999G30002) as administered by the Office of Educational Research and Improvement, U.S. Department of Education. This work was started when the author was at the Division of Statistics and Psychometrics at the Educational Testing Service. The author thanks Juliet Shaffer, Bob Mislevy, Eric Bradlow, three reviewers and an associate editor for their helpful comments on the paper.