Subtypes, Severity, and Structural Stability of Peer Victimization: What Does Latent Class Analysis Say?

Department of Education, University of California, Los Angeles, GSE&IS Box 951521, 2027 Moore Hall, Los Angeles, CA 90095-1521, USA.
Child Development (Impact Factor: 4.72). 11/2007; 78(6):1706-22. DOI: 10.1111/j.1467-8624.2007.01097.x
Source: PubMed


This study uses latent class analysis (LCA) to empirically identify victimization groups during middle school. Approximately 2,000 urban, public middle school students (mean age in sixth grade = 11.57) reported on their peer victimization during the Fall and Spring semesters of their sixth, seventh, and eighth grades. Independent LCA analyses at each semester yielded 3 victim classes based on victimization degree rather than type (e.g., physical vs. relational). The most victimized class always represented the smallest proportion of the sample, decreasing from 20% in sixth grade to 6% by the end of eighth grade. This victimized class also always reported feeling less safe at school concurrently and more depressed than others 1 semester later, illustrating the validity of the LCA approach.

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Available from: Karen Nylund-Gibson, Feb 23, 2015
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    • "Consistent with this notion, a body of evidence indicates that victimization by peers during adolescence constitutes a significant risk factor for internalizing symptoms and disorders (Reijntjes et al. 2010). In contrast to overt victimization (i.e., physical threat or harm), relational victimization, which is characterized by social exclusion, gossiping, and reputational threat, increases during the middle school transition (Nylund et al. 2007) and may be particularly likely to lead to depressive and anxiety symptoms. Indeed, numerous studies indicate that relational peer victimization is concurrently and longitudinally associated with increases in depressive and social anxiety symptoms (e.g., Desjardins and Leadbeater 2011; Siegel et al. 2009), and is more strongly associated with internalizing symptoms than is overt victimization (Prinstein et al. 2001). "
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    ABSTRACT: Social anxiety and depressive symptoms dramatically increase and frequently co-occur during adolescence. Although research indicates that general interpersonal stressors, peer victimization, and familial emotional maltreatment predict symptoms of social anxiety and depression, it remains unclear how these stressors contribute to the sequential development of these internalizing symptoms. Thus, the present study examined the sequential development of social anxiety and depressive symptoms following the occurrence of interpersonal stressors, peer victimization, and familial emotional maltreatment. Participants included 410 early adolescents (53 % female; 51 % African American; Mean age =12.84 years) who completed measures of social anxiety and depressive symptoms at three time points (Times 1-3), as well as measures of general interpersonal stressors, peer victimization, and emotional maltreatment at Time 2. Path analyses revealed that interpersonal stressors, peer victimization, and emotional maltreatment predicted both depressive and social anxiety symptoms concurrently. However, depressive symptoms significantly mediated the pathway from interpersonal stressors, peer victimization, and familial emotional maltreatment to subsequent levels of social anxiety symptoms. In contrast, social anxiety did not mediate the relationship between these stressors and subsequent depressive symptoms. There was no evidence of sex or racial differences in these mediational pathways. Findings suggest that interpersonal stressors, including the particularly detrimental stressors of peer victimization and familial emotional maltreatment, may predict both depressive and social anxiety symptoms; however, adolescents who have more immediate depressogenic reactions may be at greater risk for later development of symptoms of social anxiety.
    Journal of Abnormal Child Psychology 07/2015; DOI:10.1007/s10802-015-0049-0
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    • "Otherwise, the Entropy is good for two classes but drops noticeably for three or more classes. When comparing measurement models, it is important to consider not only the statistical indicators but also the substantive meaning of each of the classes when interpreting the results yielded with LPA (Nylund et al., 2007 "
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    ABSTRACT: This study aimed to: (a) identify motivational profiles among a sample of 141 young table-tennis players involved in intensive training settings; (b) examine the consistency or change of motivational profiles for the same athlete over time; and (c) investigate differences between these profiles on burnout, coping, stress and recovery. Latent profile transition analysis revealed two or three distinct profiles that are similar for the three measurement occasions: Self-determined profile, moderate profile, and low profile. Motivational profiles exhibited both stability and changes over time from an intra-individual perspective. Athletes from the self-determined profile were characterized by the best psychological adjustment.
    Journal of Applied Sport Psychology 05/2015; 27:268-287. DOI:10.1080/10413200.2014.993485
    • "Classes comprised of less than 10% of the total sample suggest possible over-fitting of the data. Monte Carlo simulation studies using a variety of sample sizes suggest that the BIC and BLRT are the most robust fit indices and thus were given the most weight [53]. Additional statistics used with LCA to assign patients into specific groups or classes included the analysis of their highest posterior probabilities for membership in each of the classes and entropy, which is an index derived from the posterior probabilities across classes. "
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    ABSTRACT: Background: Epidemiologic autopsy studies show mixed Alzheimer's disease (AD)/vascular pathology in many patients. Moreover, clinical research shows that it is not uncommon for AD and vascular dementia (VaD) patients to be equally impaired on memory, executive, or other neurocognitive tests. However, this clinical heterogeneity has not been incorporated into the new diagnostic criteria for AD (Dubois et al., 2010; McKhann et al., 2011). Objective: The current research applied Latent Class Analysis (LCA) to a protocol of six neuropsychological parameters to identify phenotypic subtypes from a large group of AD/VaD participants. Follow-up analyses examined difference between groups on neuroradiological parameters and neuropsychological measures of process and errors. Methods: 223 AD/VaD patients were administered a comprehensive neuropsychological protocol. Measures of whole brain and hippocampal volume were available for a portion of the sample (n = 76). Results: LCA identified four distinct groups: moderate/mixed dementia (n = 54; 24.21%), mild/mixed dementia (n = 91; 40.80%); dysexecutive (n = 49, 21.97%), and amnestic (n = 29, 13.00%). Follow-up analyses comparing the groups on neuropsychological process and error scores showed that the dysexecutive group exhibited difficulty sustaining mental set. The moderate/mixed group evidenced pronounced impairment on tests of lexical retrieval/naming along with significant amnesia. Amnestic patients also presented with gross amnesia, but showed relative sparing on other neuropsychological measures. Mild/mixed patients exhibited milder memory deficits that were intermediary between the amnestic and moderate/mixed groups. Conclusions: There are distinct neuropsychological profiles in patients independent of clinical diagnosis, suggesting that the two are not wholly separate and that this information should be integrated into new AD diagnostic paradigms.
    Journal of Alzheimer's disease: JAD 07/2014; 42(3). DOI:10.3233/JAD-132147
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Questions & Answers about this publication

  • Mary C R Wilson added an answer in Latent Class Analysis:
    Do you know any articles on latent class analysis that helped to indicate qualitative differences between groups (rather than only quantitative)?

    It would be helpful if the LCA was used in mental health, physical health, substance use, social support areas etc. 

    Mary C R Wilson

    Hello Whitold

    These papers have qualitative analysis. The first is available on ResearchGate, and gives a qualitative description of the classes:

    Laska, M. N., Pasch, K. E., Lust, K., Story, M., & Ehlinger, E. (2009). Latent class analysis of lifestyle characteristics and health risk behaviors among college youth. Prevention Science, 10(4), 376-386.

    This RG paper (below) references the paper suggested in the answer above, from Béatrice Marianne; however, I am not sure whether this Nylund et al. paper has sufficient qualitative data to meet your criteria:

    Nylund, K., Bellmore, A., Nishina, A., & Graham, S. (2007). Subtypes, severity, and structural stability of peer victimization: What does latent class analysis say?. Child development, 78(6), 1706-1722.

    Likewise, this paper below  may not meet your qualitative criteria:

    Golder, S., Connell, C. M., & Sullivan, T. P. (2012). Psychological Distress and Substance Use Among Community-Recruited Women Currently Victimized by Intimate Partners A Latent Class Analysis and Examination of Between-Class Differences. Violence Against Women, 18(8), 934-957.

    I was unable to access the full text of this paper but I think that there might be qualitative aspects:

    Yampolskaya, S., Greenbaum, P. E., & Berson, I. R. (2009). Profiles of child maltreatment perpetrators and risk for fatal assault: A latent class analysis. Journal of Family Violence, 24(5), 337-348.

    Although the title of this book suggests quantitative, but may be worth dipping into:

    Collins, L. M., & Lanza, S. T. (2013). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences (Vol. 718). John Wiley & Sons.

    Very best wishes


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      ABSTRACT: Few studies have examined the context of a wide range of risk behaviors among emerging adults (ages 18-25 years), approximately half of whom in the USA enroll in post-secondary educational institutions. The objective of this research was to examine behavioral patterning in weight behaviors (diet and physical activity), substance use, sexual behavior, stress, and sleep among undergraduate students. Health survey data were collected among undergraduates attending a large, public US university (n = 2,026). Latent class analysis was used to identify homogeneous, mutually exclusive "classes" (patterns) of ten leading risk behaviors. Resulting classes differed for males and females. Female classes were defined as: (1) poor lifestyle (diet, physical activity, sleep), yet low-risk behaviors (e.g., smoking, binge drinking, sexual risk, drunk driving; 40.0% of females), (2) high risk (high substance use, intoxicated sex, drunk driving, poor diet, inadequate sleep) (24.3%), (3) moderate lifestyle, few risk behaviors (20.4%), (4) "health conscious" (favorable diet/physical activity with some unhealthy weight control; 15.4%). Male classes were: (1) poor lifestyle, low risk (with notably high stress, insufficient sleep, 9.2% of males), (2) high risk (33.6% of males, similar to class 2 in females), (3) moderate lifestyle, low risk (51.0%), and (4) "classic jocks" (high physical activity, binge drinking, 6.2%). To our knowledge, this is among the first research to examine complex lifestyle patterning among college youth, particularly with emphasis on the role of weight-related behaviors. These findings have important implications for targeting much needed health promotion strategies among emerging adults and college youth.
      Prevention Science 07/2009; 10(4):376-86. DOI:10.1007/s11121-009-0140-2

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