Depressive symptoms and attributional style were assessed in a sample of 7- to 11-year-old children at two time points. Findings revealed that boys and girls did not differ in their level of depressive symptoms over 1 year. At baseline, boys were more likely than girls to make stable attributions for negative events. Boys made fewer stable attributions for positive events than did girls. Moderational analyses suggested that attributional style more strongly predicted changes in the number of depressive symptoms 1 year later in boys when compared to girls. Findings emphasize the need to address vulnerability factors in preadolescent boys that may put them at risk for the development of later depressive symptoms.
Eating disorders, which encompass a broad spectrum of diagnoses, typically emerge in adolescence or young adulthood. This chapter focuses on eating or food-related disorders and malnutrition in children and adolescents. The chapter provides a general description of eating disorders in children and adolescents, assessment and treatment considerations, and resources for school-based clinicians who work with children and adolescents diagnosed with an eating disorder. Information about common school-related concerns, such as cognitive difficulties, frequent school absences, nutritional intake, and engagement in physical activities, is included, with specific strategies for the school-based professional to adopt when working with students with eating disorders. The chapter concludes with a list of helpful resources and a framework for guiding the development of an individualized education plan or 504 plan for students who need additional educational accommodations or interventions.
An abundance of unstructured and loosely structured data on disasters exists and can be analyzed using network methods. This paper overviews the use of qualitative data in quantitative social network analysis in disaster research. We discuss two types of networks, each with a relevant major topic in disaster research (i.e., whole network approaches to emergency management networks and personal network approaches to the social support of survivors) and four usable forms of qualitative data. We explain five opportunities afforded by these approaches revolving around their flexibility and ability to account for complex network structures. Next, we present an empirical illustration that extends our previous work examining the sources and types of support and barrier experienced by households during long‐term recovery from Superstorm Sandy, wherein we utilized quantitative social network analysis on two qualitative datasets (Lee et al., 2020). We discuss three challenges for these approaches related to the samples, coding, and bias.
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