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Research Article

Does school connectedness differ by student ethnicity? A latent class analysis among Canadian youth

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Pages 64-84 | Received 01 Mar 2020, Accepted 31 Jan 2021, Published online: 23 Feb 2021
 

ABSTRACT

Latent class analysis was performed to identify clusters of items on the Longitudinal Study of Adolescent Health – School Connectedness Scale among students. Cluster membership was explored by student-reported ethnicity. The sample included students attending Canadian secondary schools in two waves of the COMPASS study: Years 4 (Y4:2015/16) (N=40,436) and 7 (Y7:2018/19) (N=60,610). Results were comparable across waves. Four clusters resulted: strongly connected (Y4 66.6%; Y7 67.9%), socially disconnected (14.1%; 15.2%; perceptions of equitable treatment but lacking feelings of belonging), social belonging (11.9%; 10.3%; feelings of being part of their school and close to others, but less likely to perceive equitable treatment), and weakly connected (7.4%; 6.6%). White and Asian students were more likely to be ‘strongly connected’, while Black and ‘other’ or mixed ethnicity students were overrepresented in the ‘weakly connected’ and ‘social belonging’ clusters. Cluster variations merit attention to improve how racialized and ethnic minority youth experience school environments.

Acknowledgments

The authors would like to thank all COMPASS team members and staff, and all schools, school boards, and students that have participated in the COMPASS study.

Availability Of Data And Materials

COMPASS study data is available upon request through completion and approval of an online form: https://uwaterloo.ca/compass-system/information-researchers/data-usage-application The datasets used during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics Approval And Consent To Participate

The University of Waterloo Office of Research Ethics (ORE#17264) and participating school boards approved all procedures. All students attending participating schools were invited to participate using active-information passive-consent parental permission protocols. Students could withdraw from the study at anytime.

Disclosure Statement

The authors declare that they have no competing interests.

Additional information

Funding

The COMPASS study has been supported by a bridge grant from the CIHR Institute of Nutrition, Metabolism and Diabetes (INMD) through the ‘Obesity – Interventions to Prevent or Treat’ priority funding awards (OOP-110788; awarded to SL), an operating grant from the CIHR Institute of Population and Public Health (IPPH) (MOP-114875; awarded to SL), a CIHR project grant (PJT-148562; awarded to SL), a CIHR bridge grant (PJT-149092; awarded to KP/SL), a CIHR project grant (PJT-159693; awarded to KP), and by a research funding arrangement with Health Canada (#1617-HQ-000012; contract awarded to SL). The COMPASS-Quebec project additionally benefits from funding from the Ministère de la Santé et des Services sociaux of the province of Québec, and the Direction régionale de santé publique du CIUSSS de la Capitale-Nationale.

Notes on contributors

Karen A. Patte

Karen A. Patte is an Assistant Professor in the Faculty of Applied Health Sciences at Brock University. Applying scocioecological and systems frameworks, she studies the psychosocial, behavioural, and environmental predictors of mental health and ill-health among adolescents and emerging adults. Her research aims to advance understanding of how different contexts and exposures shape mental health trajectories over time.

Mahmood R. Gohari

Mahmood Gohari is a Post-Doctoral Fellow in the School of Public Health and Health Systems at the University of Waterloo. His research primarily focuses on different domains of physical and mental health in youth populations and developing robust statistical methods for analyzing longitudinal data.

Scott T. Leatherdale

Scott Leatherdale is a Professor in the School of Public Health and Health Systems, and a University Research Chair at the University of Waterloo. His work focuses on advancing a systems science approach to primary prevention activities, evaluating complex population-level health interventions across multiple risk factor domains, and creating research infrastructure to facilitate large population-based learning systems in chronic disease prevention.

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