dc.contributor.author | Lee, Knoo | |
dc.contributor.author | McMorris, Barbara J. | |
dc.contributor.author | Chi, Chih-Lin | |
dc.contributor.author | Looman, Wendy S. | |
dc.contributor.author | Delaney, Connie W. | |
dc.date.issued | 2021 | eng |
dc.description.abstract | Chronic absenteeism (CA), defined as missing at least 15 school days/year, is recognized as a national problem in the U.S. with devastating long-term impacts for students. Previous studies have been guided by a mixture of diverse CA definitions and measurements which could potentially harm the applicability of findings. Despite the number of CA-associated factors identified, studies utilizing a unified theoretical system to a wide range of risk and protective factors has been scarce. | eng |
dc.identifier.uri | https://hdl.handle.net/10355/88261 | |
dc.language | English | eng |
dc.publisher | University of Missouri--Columbia | eng |
dc.relation.ispartofcommunity | University of Missouri--Columbia. Health Sciences Research Day | eng |
dc.rights | OpenAccess. | eng |
dc.rights.license | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. | eng |
dc.title | Data-driven analytics to identify school absenteeism associated risk and protective factors for secondary school students | eng |
dc.type | Presentation | eng |