Preventive intervention research dictates that new techniques are needed to elucidate what types of interventions work best for whom to prevent behavioral problems. The current investigation applies a latent class modeling structure to identify the constellation of characteristics—or profile—in urban male adolescents (n = 125, aged 15) that interrelatedly predict responses to a brief administration of an evidence-based program, Positive Adolescent Choices Training (PACT). Individual-level characteristics were selected as predictors on the basis of their association with risk behaviors and their implication in intervention outcomes (e.g., mental health, stress exposure, temperament, cognitive function, stress reactivity and emotion perception). Outcome measures included virtual reality vignettes and questionnaire-style role play scenarios to gauge orientations around aggressive conflict resolution, communication, emotional control, beliefs supporting aggression and hostility. A three-class model was found to best fit the data: “NORMative” (NORM), with relatively low symptomatology; “Mental Health” problems (MH-I) with elevated internalizing symptoms; and “Mental Health-E + Cognitive Deficit” (MH-E + Cog) with elevated mental health symptoms paired with cognitive decrements. The NORM class had positive PACT effects for communication, conflict resolution, and aggressive beliefs. Moderation was evidenced by lack of positive PACT effects for the MH-I and MH-E + Cog groups. Also, PACT classes with MH issues showed marginally significant worsening of aggressive beliefs compared to control students in the same class. Results suggest that a latent class model may identify “signatures” or profiles of traits, experiences and other influences that collectively—and more realistically—predict variable intervention outcomes with implications for more effectively targeting interventions than singular factors.

预防性干预研究表明，需要新技术来阐明哪种类型的干预最适合谁来预防行为问题。当前的调查采用了潜在的类别建模结构，以识别城市男性青少年（n = 125，15岁）的特征或轮廓，这些特征相互关联地预测对基于证据的计划“积极的青少年选择训练”的简短管理的反应（协议）。根据个人水平特征与风险行为的关系及其对干预结果的影响（例如，心理健康，压力暴露，气质，认知功能，压力反应性和情感知觉），选择个体水平特征作为预测因子。结果措施包括虚拟现实渐晕和问卷式角色扮演场景，以评估围绕积极解决冲突，沟通，情绪控制，支持侵略和敌意的信念的方向。发现了一个三类模型最适合该数据：“ NORMative”（NORM），症状相对较低；“ NORMative”（NORM）。内部化症状加剧的“精神健康”问题（MH-I）；以及心理健康症状升高和认知减退的“心理健康-E +认知缺陷”（MH-E +齿轮）。NORM班级在沟通，解决冲突和激进信念方面具有积极的PACT效果。MH-I和MH-E + Cog组缺乏积极的PACT效应证明适度。还，与同班的控制学生相比，出现MH问题的PACT班显示积极信念的恶化程度很小。结果表明，潜在的阶级模型可以识别特征，经验和其他影响的“特征”或特征，这些特征可以共同地（更现实地）预测可变干预结果，与单因素相比，具有更有效地针对性干预的含义。