Affective, Biological, and Cognitive Predictors of Depressive Symptom Trajectories in Adolescence

被引:0
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作者
Amy Mezulis
Rachel H. Salk
Janet Shibley Hyde
Heather A. Priess-Groben
Jordan L. Simonson
机构
[1] Seattle Pacific University,Department of Clinical Psychology
[2] University of Wisconsin – Madison,Department of Psychology
[3] Simpson College,Shriever Air Force Base
[4] United States Air Force,undefined
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关键词
Depression; Trajectories; Temperament; Puberty; Cognitive risk factors; Adolescence;
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摘要
Heterogeneity in the longitudinal course of depressive symptoms was examined using latent growth mixture modeling among a community sample of 382 U.S. youth from ages 11 to 18 (52.1 % female). Three latent trajectory classes were identified: Stable Low (51 %; displayed low depressive symptoms at all assessments), Increasing (37 %; reported low depressive symptoms at age 11, but then significantly higher depressive symptoms than the Stable Low class at ages 13, 15, and 18), and Early High (12 %; reported high early depressive symptoms at age 11, followed by symptoms that declined over time yet remained significantly higher than those of the Stable Low class at ages 13, 15, and 18). By age 15, rates of Major Depressive Disorder diagnoses among the Early High (25.0 %) and Increasing (20.4 %) classes were more than twice that observed among the Stable Low class (8.8 %). Affective (negative affectivity), biological (pubertal timing, sex) and cognitive (cognitive style, rumination) factors were examined as predictors of class membership. Results indicated general risk factors for both high-risk trajectories as well as specific risk factors unique to each trajectory. Being female and high infant negative affectivity predicted membership in the Increasing class. Early puberty, high infant negative affectivity for boys, and high rumination for girls predicted membership in the Early High class. Results highlight the importance of examining heterogeneity in depression trajectories in adolescence as well as simultaneously considering risk factors across multiple domains.
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页码:539 / 550
页数:11
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