A comparison of girls' and boys' aggressive-disruptive behavior trajectories across elementary school: Prediction to young adult antisocial outcomes.

Schaeffer, Cindy M.; Petras, Hanno; Ialongo, Nicholas S.; Masyn, Katherine E.; Hubbard, Scott; Poduska, Jeanne M.; Kellam, Sheppard G.

doi:10.1037/0022-006x.74.3.500

Cited by 133 publications

(153 citation statements)

References 48 publications

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“…Unlike Schaeffer et al [2006], we found similar percentages of boys and girls in the persistently high aggression trajectory (19 and 15%, respectively, in the pooled GMM), whereas they found a substantially higher percentage of boys than girls in a similar persistent aggression-disruption class. This difference may be attributable to the younger elementary school sample studied by Schaeffer and colleagues.…”

Section: Discussioncontrasting

confidence: 74%

“…Using latent GMM, we identified four distinct developmental trajectories over a 5-year period from early to late adolescence. Three of these trajectories-Low/No Aggression, Desisting Aggression, and Persistent High Aggression-have been identified in prior developmental studies [e.g., Brame et al, 2001;Broidy et al, 2003;Schaeffer et al, 2006]. The fourth trajectory, Adolescent Aggression, is consistent with developmental theory [e.g., Loeber and Stouthamer-Loeber, 1998;Moffitt, 1993;Patterson and Yoerger, 1993] but has not typically been found in past studies.…”

Section: Discussionmentioning

confidence: 74%

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Multiple trajectories of physical aggression among adolescent boys and girls

Martino

Ellickson

Klein

et al. 2007

Aggressive Behavior

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Latent growth mixture modeling was used to identify discrete patterns of physical aggression from Grades 7 to 11 among a sample of 1,877 youth. Four trajectory classes adequately explained the development of physical aggression in both boys and girls: Low/No Aggression; Persistent High Aggression; Desisting Aggression, characterized by decreasing risk throughout adolescence; and Adolescent Aggression, characterized by low early risk that increases until Grade 9, levels out, and then declines in late adolescence. Girls were less likely than boys were to be in any trajectory besides the Low/No Aggression trajectory. Parental supervision, deviant peer association, academic orientation, impulsivity, and emotional distress at Grade 7 were all strongly associated with trajectory class membership. These associations did not differ by gender. These findings strongly suggest that the processes involved in the development of physical aggression in adolescence operate similarly in boys and girls.

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Section: Discussioncontrasting

confidence: 74%

Section: Discussionmentioning

confidence: 74%

Multiple trajectories of physical aggression among adolescent boys and girls

Martino

Ellickson

Klein

et al. 2007

Aggressive Behavior

View full text Add to dashboard Cite

show abstract

“…In recent years, LGMM has been successfully used to identify longitudinal patterns of adjustment in relation to a wide variety of life events and circumstances, including drinking among college students (Greenbaum, Del Boca, Darkes, Wang, & Goldman, 2005), childhood aggression (Schaeffer et al, 2006;Schaeffer, Petras, Ialongo, Poduska, & Kellam, 2003), retirement in late life (Pinquart & Schindler, 2007), life-threatening medical procedures (Deshields et al, 2006;Lam et al, 2010), and traumatic injury (deRoonCassini et al, 2010).…”

Section: Latent Growth Mixture Modelingmentioning

confidence: 99%

Weighing the Costs of Disaster

Bonanno

Brewin

Kaniasty

et al. 2010

Psychol Sci Public Interest

952

443

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SummaryDisasters typically strike quickly and cause great harm. Unfortunately, because of the spontaneous and chaotic nature of disasters, the psychological consequences have proved exceedingly difficult to assess. Published reports have often overestimated a disaster's psychological cost to survivors, suggesting, for example, that many if not most survivors will develop posttraumatic stress disorder (PTSD); at the same time, these reports have underestimated the scope of the disaster's broader impact in other domains. We argue that such ambiguities can be attributed to methodological limitations. When we focus on only the most scientifically sound research-studies that use prospective designs or include multivariate analyses of predictor and outcome measures-relatively clear conclusions about the psychological parameters of disasters emerge. We summarize the major aspects of these conclusions in five key points and close with a brief review of possible implications these points suggest for disaster intervention.1. Disasters cause serious psychological harm in a minority of exposed individuals. People exposed to disaster show myriad psychological problems, including PTSD, grief, depression, anxiety, stress-related health costs, substance abuse, and suicidal ideation. However, severe levels of these problems are typically observed only in a relatively small minority of exposed individuals. In adults, the proportion rarely exceeds 30% of most samples, and in the vast majority of methodologically sound studies, the level is usually considerably lower. Among youth, elevated symptoms are common in the first few months following a high-impact disaster, but again, chronic symptom elevations rarely exceed 30% of the youth sampled.2. Disasters produce multiple patterns of outcome, including psychological resilience. In addition to chronic dysfunction, other patterns of disaster outcome are typically observed. Some survivors recover their psychological equilibrium within a period ranging from several months to 1 or 2 years. A sizeable proportion, often more than half of those exposed, experience only transient distress and maintain a stable trajectory of healthy functioning or resilience. Resilient outcomes have been evidenced across different methodologies, including recent studies that identified patterns of outcome using relatively sophisticated data analytic approaches, such as latent growth mixture modeling.3. Disaster outcome depends on a combination of risk and resilience factors. As is true for most highly aversive events, individual differences in disaster outcomes are informed by a number of unique risk and resilience factors, including variables related to the context in which the disaster occurs, variables related to proximal exposure during the disaster, and variables related to distal exposure in the disaster's aftermath. Multivariate studies indicate that there is no one single dominant predictor of disaster outcomes. Rather, as with traumatic life events more generally, most predictor variables exert small...

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“…In a similar application, Morin et al (2011) used GMM to assess fluctuations in elevated levels of anxiety for adolescents over time and reported five latent classes representing different patterns of anxiety. Finally, Schaeffer et al (2006) used GMM to model patterns of aggression and disruptive behavior in children throughout elementary school years; they found three substantively different latent classes for boys and girls.…”

mentioning

confidence: 99%

Mixture class recovery in GMM under varying degrees of class separation: Frequentist versus Bayesian estimation.

Depaoli

2013

Psychological Methods

119

147

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Growth mixture modeling (GMM) represents a technique that is designed to capture change over time for unobserved subgroups (or latent classes) that exhibit qualitatively different patterns of growth. The aim of the current article was to explore the impact of latent class separation (i.e., how similar growth trajectories are across latent classes) on GMM performance. Several estimation conditions were compared: maximum likelihood via the expectation maximization (EM) algorithm and the Bayesian framework implementing diffuse priors, "accurate" informative priors, weakly informative priors, data-driven informative priors, priors reflecting partial-knowledge of parameters, and "inaccurate" (but informative) priors. The main goal was to provide insight about the optimal estimation condition under different degrees of latent class separation for GMM. Results indicated that optimal parameter recovery was obtained though the Bayesian approach using "accurate" informative priors, and partial-knowledge priors showed promise for the recovery of the growth trajectory parameters. Maximum likelihood and the remaining Bayesian estimation conditions yielded poor parameter recovery for the latent class proportions and the growth trajectories.

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A comparison of girls' and boys' aggressive-disruptive behavior trajectories across elementary school: Prediction to young adult antisocial outcomes.

Cited by 133 publications

References 48 publications

Multiple trajectories of physical aggression among adolescent boys and girls

Multiple trajectories of physical aggression among adolescent boys and girls

Weighing the Costs of Disaster

Mixture class recovery in GMM under varying degrees of class separation: Frequentist versus Bayesian estimation.

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