University of North Carolina, Chapel Hill, North Carolina, USA.
National Prevention Science Coalition to Improve Lives, Chapel Hill, North Carolina, USA.
Res Child Adolesc Psychopathol. 2021 Sep;49(9):1139-1149. doi: 10.1007/s10802-021-00808-x. Epub 2021 Apr 5.
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.
预防干预研究表明，需要新的技术来阐明哪些干预措施最适合哪些人，以预防行为问题。目前的研究应用潜在类别建模结构来确定特征的组合或城市男性青少年（n=125，年龄 15 岁）的特征-或特征轮廓，这些特征相互关联，预测对简短的基于证据的计划，积极青少年选择培训（PACT）的反应。个体水平的特征被选为预测因子，是基于它们与风险行为的关联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、应激反应和情绪感知）。结果测量包括虚拟现实小插曲和问卷式角色扮演场景，以衡量围绕攻击性冲突解决、沟通、情绪控制、支持攻击和敌意的信念的取向。发现三类别模型最适合数据：“规范”（NORM），症状相对较低；“心理健康”问题（MH-I），内化症状升高；和“心理健康-E+Cognitive Deficit”（MH-E+Cog），心理健康症状升高，认知能力下降。NORM 类对沟通、冲突解决和攻击性信念具有积极的 PACT 效应。缺乏 MH-I 和 MH-E+Cog 组的积极 PACT 效应证明了调节作用。此外，与同班级的对照学生相比，具有 MH 问题的 PACT 类别的攻击性信念略有恶化。结果表明，潜在类别模型可以识别“特征”或特征、经验和其他影响的特征，这些特征共同且更现实地预测了干预结果的可变性，这对更有效地针对干预措施而不是单一因素具有重要意义。
