Congrats to Dr. Brian Chu, students Denise Guarino and Christina Mele for publishing an article on Cognitive and Behavioral Practice journal

Feb, 2019

Congrats to GSAPP faculty Dr. Brian Chu, students Denise Guarino and Christina Mele for publishing an article "Developing an Online Early Detection System for School Attendance Problems: Results From a Research-Community Partnership" on Cognitive and Behavioral Practice journal! 

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Developing an Online Early Detection System for School Attendance Problems: Results From a Research-Community Partnership

Brian C. Chu, Denise Guarino, Christina Mele, Jean O’Connell, Patricia Coto

Highlights

• Introduces an online early identification tool to detect youth at risk for school attendance problems

• Describes the iterative process of developing the tool within the context of a research-community partnership

• School absenteeism is a common and costly problem and technology can be used to enhance early identification.

Abstract

School refusal and other school attendance problems are vexing problems for school-aged youth, families, school personnel, and clinicians. However, few resources exist to detect problematic attendance. The current report describes three steps of a research-community partnership to develop an early identification program to detect youth at risk for problematic attendance. First, a survey was conducted to estimate the scope and cost of school refusal across grades K–12. School administrators estimated relatively few youth exhibiting significant school refusal (missing 5 or more days per year) but estimated the costs associated with services for these youth to be very high (mean cost of in-district programs: $94,052; mean cost of out-of-district placements: $496,657). Second, elementary school counselors were tasked with tracking absenteeism among at-risk youth using an online attendance tracking prototype. Counselors identified a high number of youth who showed elevated absences, lates, or early departures (17.2% of enrolled students), and counselor ratings were significantly related to whether the student (a) had received an individualized education plan or 504 plan, (b) had a sibling with similar attendance problems, (c) was older, or (d) had divorced or separated parents. In a final step, counselor feedback was sought and revisions were incorporated in the attendance tracker. Findings reinforce the prevalence and cost of school attendance problems, provide guidance for using technology to monitor attendance and related indices (tardies, early departures), and direct attention to youth factors that may be useful in identifying youth at risk for poor attendance.

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