Youth Psychopathology and School Attendance Problems

描述（由申请人提供）：在青少年精神病理学的可能风险因素中，长期缺课是一个普遍存在的问题，可能是可以预防的，但其在精神疾病发展中的作用仍然知之甚少。由于美国年轻人中精神疾病的患病率很高，越来越多的注意力已经放在8-11%的美国儿童和青少年中，他们表现出长期旷课。理论表明，长期旷课会引发或加剧精神疾病，而不仅仅是预先存在的精神病理学的影响或标志。然而，以前的研究一直无法澄清的性质，由于缺乏方法学健全的纵向研究和因果关系建模的精神病理学缺勤的关系。拟议的研究旨在（a）测试缺勤的因果模型作为未来精神病理学的决定因素，（B）确定缺勤的可能原因，以告知选择性预防模型。四个全国或地区代表性的以学校为基础的纵向数据集，其特征是重复测量青少年精神病理学，入学率和相关协变量，跨越1至12年级，将用于检验假设（Ns = 20，745; 2，311; 678;和671）。在这些研究中重复进行的精神病理学测量各不相同，包括有效的诊断访谈和自我报告表，如儿童诊断访谈时间表-IV（DISC-IV，Shaffer等人，2000），儿童抑郁量表（CDI; Kovacs，1983）和教师报告表（TRF; Achenbach，1991）。通过采用多个数据集，可以测试具有不同人口统计特征的样本之间的概念模型的不变性。结构方程模型（SEM）和潜在混合马尔可夫链分析（LMM）将用于生成一个过渡为重点的分析，随着时间的推移，青年精神功能。这些因果建模技术可以测试在一个时间点被归类为长期缺席是否会增加转变为更高精神病理学类别（即，恶化）或保持在高精神病理学等级（即，在随后的几年中，相对于其他儿童，并控制先前的精神功能和相关的协变量。缺勤的潜在决定因素（例如，医疗问题、社会问题、学业困难、暴露于危险环境），然后将在平行的因果模型中进行测试，以评估它们随着时间的推移对新出现的入学问题的影响。这些以人为中心的分析将允许关于随时间推移的临床显著转变的结论，从而澄清缺勤作为真正的风险因素与精神病理学的标志物或影响的作用。这项研究可能会促进公共卫生工作，以减少精神病理学的发病率（a）提供一个经验基础，以确定青年在发展新的或恶化的精神问题的高风险，（B）通知预防干预措施的发展，以帮助这些青年避免负面的心理健康后遗症。拟议的研究将推进公共卫生工作，以识别有患精神疾病风险的美国青少年。如果学校出勤率低被认为是精神疾病的前兆，那么就可以为高危青年提供干预计划，以防止精神疾病的发生。

DESCRIPTION (provided by applicant): Among likely risk factors for youth psychopathology, chronic school absenteeism is a widespread problem that is potentially preventable, yet its role in the development of mental illness remains poorly understood. With the high prevalence rates of psychiatric disorders among youth in the U.S., increasing attention has been paid to the 8-11% of American children and adolescents who exhibit chronic absenteeism. Theory suggests that chronic absenteeism can trigger or exacerbate psychiatric disorders, and is not merely an effect or marker of pre-existing psychopathology. However, previous research has been unable to clarify the nature of the psychopathology-absenteeism relationship due to a lack of methodologically-sound longitudinal studies and causal modeling. The proposed study seeks to (a) test a causal model of absenteeism as a determinant of future psychopathology and (b) identify possible causes of absenteeism to inform selective prevention models. Four nationally or regionally representative school-based longitudinal datasets that feature repeated measures of youth psychopathology, school attendance, and relevant covariates spanning 1st through 12th grade will be employed to test hypotheses (Ns = 20,745; 2,311; 678; and 671). Measures of psychopathology administered repeatedly in these studies vary and include validated diagnostic interviews and self-report forms such as the Diagnostic Interview Schedule for Children-IV (DISC-IV, Shaffer et al., 2000), the Children's Depression Inventory (CDI; Kovacs, 1983), and the Teacher Report Form (TRF; Achenbach, 1991). By employing multiple datasets, the invariance of the conceptual model across samples with differing demographic characteristics may be tested. Structural Equation Modeling (SEM) and Latent Mixed Markov Chain Analysis (LMM) will be used to generate a transition-focused analysis of youth psychiatric functioning over time. These causal modeling techniques can test whether being categorized as chronically absent at one time point increases the probability of transitioning to a higher-psychopathology class (i.e., exacerbation) or remaining at a high- psychopathology class (i.e., persistence) in subsequent years, relative to other children and controlling for prior psychiatric functioning and relevant covariates. Potential determinants of absenteeism (e.g., medical problems, social problems, academic difficulties, exposure to risky environments) will then be tested in parallel causal models to assess their influence on emerging school attendance problems over time. These person-centered analyses will permit conclusions about clinically significant transitions over time and will thereby clarify the role of absenteeism as a true risk factor versus a marker or effect of psychopathology. This research may promote public health efforts to reduce the incidence of psychopathology by (a) providing an empirical basis for identifying youth at high risk of developing new or worsening psychiatric problems, and (b) informing the development of preventive interventions to help such youth avoid negative mental health sequelae. The proposed research will advance public health efforts to identify US youth who are at risk for developing mental illness. If poor school attendance is found to be a precursor of psychiatric disorders as hypothesized, at-risk youth may then be offered intervention programs that could prevent the onset of mental illness.