The longitudinal links between shame and increasing hostility during adolescence

Little research has examined changes in emotional experience in adolescents. We hypothesized that the experience of shame would lead adolescents to become increasingly hostile. We report a one-year longitudinal study involving 765 high school students (392 males and 373 females; mean age = 14.41 yrs) in Grade 9 at Time 1 and 670 students (335 males and 335 females) in Grade 10 at Time 2. Shame and hostility showed high levels of stability over one-year. Structural equation modelling showed that higher shame in Grade 9 was predictive of increases in hostility in Grade 10, whereas hostility was not predictive of increases in shame. These results are discussed with reference to the nature of shame and its potential to provoke antisocial behaviour.     

Measuring Moral Progress

The study provides an in-depth analysis of two young adult subjects from a longitudinal study who underwent successive and significant developmental changes. Their developmental patterns, however, are only revealed by a new conception of moral stages, which is both more comprehensive and more detailed than Kohlberg’s original approach. In particular, the suggested alternative taxonomy neatly accommodates what appears as developmental anomalies in the Kohlbergian frame of reference. What is more, apart from merely matching with the observed data, the new theory also explains why the subjects developed the way they did, since it reveals the inherent cognitive conflicts at each stage and how these are resolved at the following one. Although the theory stands against the Kohlberg theory as it is, it may be understood as an extension and further development of the latter, in the sense that Kohlbergian stages are differentiated, supplemented, and theoretically substantiated within the new framework.

Expressions of positive emotion in photographs,personality, and later-life marital and health outcomes

A previous study of females at an elite liberal arts college found that the degree of positive emotion expressed in persons’ college yearbook photos was correlated with personality, marital, and health outcomes decades later in life. We examine whether the same pattern is observed among respondents in the Wisconsin Longitudinal Study, using high school yearbook photographs and outcome measures obtained mostly when respondents were in their fifties. Despite some seeming advantages of our design, we were unable, with a few exceptions, to replicate the findings of the previous study. Possible explanations for this divergence in findings are discussed, including differences in measurement, the sample, and the photographic occasion itself.     

Sequelae of Aggression in Acutely Suicidal Adolescents

The consequences of aggression on problem course and suicide risk were examined in 270 acutely suicidal adolescents (ages 12-17 years; 184 girls). Participants were assessed during psychiatric hospitalization (T1), 6-months post-hospitalization (T2), and 15 or more months post-hospitalization (T3). Study variables included self- and parent-reported aggression; self-reported internalizing symptoms, suicidal ideation, suicide attempt, and adverse events; and clinician-rated suicidal behavior. Aggression was not directly related to suicide attempt concurrently or prospectively. However, among more aggressive youth, internalizing symptoms were more predictive of T3 suicide attempt than among less aggressive youth. T1 aggression predicted aggressive incidents and the likelihood of incarceration prior to T3. Two-level hierarchical linear modeling indicated that self-reported aggression and internalizing problems were linked in terms of severity and rates of decline over time. Overall, parent-reported aggression was negatively associated with suicidal ideation. Findings highlight (a) the continuity and consequences of aggression, (b) a possible role of aggression in worsening suicide risk factors and potentiating suicide attempt, and (c) the importance of ongoing research on subtypes of suicidal adolescents.     

Linkages Between Children's Social and Academic Competence: A Longitudinal Analysis

The relation between social and academic competence was examined in a group of school-age children (N = 163) using structural equation modeling to determine the direction of influence between these two domains across time. A model posing that a reciprocal relation exists between the two domains was tested. The two nested models within the reciprocal model were also tested. To test these models, social acceptance as well as prosocial and aggressive behaviors were assessed by teachers and peers, and children's academic achievement was measured by language and math report-card grades and work skills. Results supported the reciprocal model, indicating that academic achievement directly influenced social competence from both first to second and second to third grade, and social competence was reciprocally related to academic achievement from second to third grade. Implications of these findings for the education process are discussed.     

Antenatal determinants of early childhood talking delay and behavioural difficulties

The determinants of talking delay alone or its comorbidity with behavioural difficulties was examined in 5768 two-year-old members of the Growing Up in New Zealand longitudinal study. Using the MacArthur-Bates Communicative Development inventories and the total difficulties score from the preschool Strengths and Difficulties Questionnaire, a composite measure was created so that children were categorised as showing no language or behavioural concerns (72.5%), behavioural only difficulties (6.1%), language only difficulties (18.1%), and comorbid language and behavioural difficulties (3.3%). Analyses revealed that antenatal factors such as maternal perceived stress, inadequate folate intake, vitamin intake, alcohol consumption during the first trimester and maternal smoking all had a significant effect on child outcomes. In particular, low multivitamin intake and perceived stress during pregnancy were associated with coexisting language and behavioural difficulties. These findings support international research in showing that maternal factors during pregnancy are associated with developmental outcomes in the early childhood period, and demonstrate these associations within a NZ context. Interventions which address maternal stress management and health behaviours during pregnancy could be beneficial to offspring development.     

On scaling models applied to data from several groups

Statistical methods are presented to facilitate a more complete analysis of results obtained when a scaling model is applied to data from two or more groups. These methods can be used to (a) compare the corresponding estimated latent distributions obtained using the scaling model applied to the different groups, (b) compare the corresponding estimated item reliabilities (or item response error rates) for the different groups, and (c) test whether the scaling model applied to the several groups can be replaced by a more parsimonious scaling model that includes various homogeneity constraints (i.e., constraints that describe which parameters in the model are the same for the several groups). Various kinds of scaling models are considered here in the multiple-group context.Support for this research was provided in part by the National Science Foundation, to Clogg by Grant No. SES-7823759 and to Goodman by Grant No. SES-8303838. Clogg and Goodman were Fellows at the Center for Advanced Study in the Behavioral Sciences when part of the research was done, with financial support provided in part by National Science Foundation grant BNS-8011494 to the Center. The authors are indebted to Mark P. Becker and James W. Shockey for helpful comments.     

The integration of multidimensional scaling and multivariate analysis with optimal transformations

The recent history of multidimensional data analysis suggests two distinct traditions that have developed along quite different lines. In multidimensional scaling (MDS), the available data typically describe the relationships among a set of objects in terms of similarity/dissimilarity (or (pseudo-)distances). In multivariate analysis (MVA), data usually result from observation on a collection of variables over a common set of objects. This paper starts from a very general multidimensional scaling task, defined on distances between objects derived from one or more sets of multivariate data. Particular special cases of the general problem, following familiar notions from MVA, will be discussed that encompass a variety of analysis techniques, including the possible use of optimal variable transformation. Throughout, it will be noted how certain data analysis approaches are equivalent to familiar MVA solutions when particular problem specifications are combined with particular distance approximations.This research was supported by the Royal Netherlands Academy of Arts and Sciences (KNAW). An earlier version of this paper was written during a stay at McGill University in Montréal; this visit was supported by a travel grant from the Netherlands Organization for Scientific Research (NWO). I am grateful to Jim Ramsay and Willem Heiser for their encouragement and helpful suggestions, and to the Editor and referees for their constructive comments.     

On the robustness of maximum likelihood scaling for violations of the error model

A Monte Carlo study was conducted to investigate the robustness of the assumed error distribution in maximum likelihood estimation models for multidimensional scaling. Data sets generated according to the lognormal, the normal, and the rectangular distribution were analysed with the log-normal error model in Ramsay's MULTISCALE program package. The results show that violations of the assumed error distribution have virtually no effect on the estimated distance parameters. In a comparison among several dimensionality tests, the corrected version of thex ² test, as proposed by Ramsay, yielded the best results, and turned out to be quite robust against violations of the error model.     

Probabilistic multidimensional scaling: Complete and incomplete data

Simple procedures are described for obtaining maximum likelihood estimates of the location and uncertainty parameters of the Hefner model. This model is a probabilistic, multidimensional scaling model, which assigns a multivariate normal distribution to each stimulus point. It is shown that for such a model, standard nonmetric and metric algorithms are not appropriate. A procedure is also described for constructing incomplete data sets, by taking into consideration the degree of familiarity the subject has for each stimulus. Maximum likelihood estimates are developed both for complete and incomplete data sets. This research was supported by National Science Grant No. SOC76-20517. The first author would especially like to express his gratitude to the Netherlands Institute for Advanced Study for its very substantial help with this research.