Cited by 159Youth Substance Use and School AttendanceSchool Health and Nursing EducationEducational Environments and Student Outcomes

The DOI matches its Crossref record; the references it cites are not checked yet.

How school climate relates to chronic absence: A multi–level latent profile analysis

Van Eck, Kathryn, Johnson, Stacy R., Bettencourt, Amie, Johnson, Sarah Lindstrom·2017·Journal of School Psychology

Abstract

Chronic absence is a significant problem in schools. School climate may play an important role in influencing chronic absence rates among schools, yet little research has evaluated how school climate constructs relate to chronic absence. Using multilevel latent profile analysis, we evaluated how profiles of student perceptions of school climate at both the student and school level differentiated school-level rates of chronic absence. Participants included 25,776 middle and high school students from 106 schools who completed a district administered school climate survey. Students attended schools in a large urban school district where 89% of 6th through 12th grade students were African-American and 61% were eligible for the federally subsidized school meals program. Three student-level profiles of perceptions of school climate emerged that corresponded to "positive," "moderate," and "negative" climate. Two predominant patterns regarding the distribution of these profiles within schools emerged that corresponded to the two school-level profiles of "marginal climate" and "climate challenged" schools. Students reporting "moderate" and "negative" climate in their schools were more likely to attend schools with higher chronic absence rates than students reporting that their school had "positive" climate. Likewise, "climate challenged" schools had significantly higher chronic absence rates than "marginal climate" schools. These results suggest that school climate shares an important relation with chronic absence among adolescent students attending urban schools. Implications for prevention and intervention programs are discussed.

Overview

Integrity signals

Registry

Crossref · 10.1016/j.jsp.2016.10.001

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

The citation lists haven’t been fetched yet

References 72 · Cited by 159

Research works printed but not linked: 2

  1. Every Student Succeeds Act, Pub. L. No. 114-95, § 1005, 129 Stat. 1802, 1848 (2015) (codified at 20 U.S.C. § 6311(h)(1)(C)(viii)(I)).
  2. Neild, 2007, An early warning system, Educational Leadership, 65, 28

Metadata

Authors
Van Eck, K., Johnson, S. R., Bettencourt, A., & Johnson, S. L.
Affiliations
Johns Hopkins University (US)
Venue
Journal of School Psychology
Publisher
Elsevier BV
Published
2017-04
Volume
61
Pages
89-102
ISSN
0022-4405 (ISSN-L)
OpenAlex
W2550355017
Cited by
159
References
72
Citations by year
2026: 15 · 2025: 13 · 2024: 21 · 2023: 13 · 2022: 18 · 2021: 16 · 2020: 19 · 2019: 15 · 2018: 26 · 2017: 3
FWCI
65.11
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of School Psychology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • U.S. Department of Energy
  • Centers for Disease Control and Prevention
Topics
  • Social Sciences › Education › Youth Substance Use and School Attendance
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › School Health and Nursing Education
  • Social Sciences › Education › Educational Environments and Student Outcomes
Keywords
school climate, chronic absenteeism, urban schools, adolescent students, African American students, prevention and intervention programs
MeSH terms
Absenteeism, Adolescent, Adolescent Behavior, Child, Child Behavior, Female, Humans, Male, Schools, Students, Models, Statistical

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review