School disconnectedness: identifying adolescents at risk

• Published in: Pediatrics (Evanston) Vol. 106; no. 5; p. 1017
• Main Authors: Bonny, A E, Britto, M T, Klostermann, B K, Hornung, R W, Slap, G B
• Format: Journal Article
• Language: English
• Published: United States 01.11.2000
• Subjects: Adolescent; Factor Analysis, Statistical; Health Status; Health Status Indicators; Health Surveys; Humans; Identification (Psychology); Logistic Models; Longitudinal Studies; Personality Inventory - statistics & numerical data; Psychology, Adolescent; Psychometrics; Regression Analysis; Risk-Taking; School Health Services - statistics & numerical data; Schools; Surveys and Questionnaires
• ISSN: 1098-4275
• DOI: 10.1542/peds.106.5.1017

School connectedness, or the feeling of closeness to school personnel and the school environment, decreases the likelihood of health risk behaviors during adolescence. The objective of this study was to identify factors differentiating youth who do and do not feel connected to their schools in an effort to target school-based interventions to those at highest health risk. The study population consisted of all students attending the 7th through 12th grades of 8 public schools. The students were asked to complete a modified version of the in-school survey designed for the National Longitudinal Study of Adolescent Health (Add Health). The school connectedness score (SCS) was the summation of 5 survey items. Bivariate analyses were used to evaluate the association between SCS and 13 self-reported variables. Stepwise linear regression was conducted to identify the set of factors best predicting connectedness, and logistic regression analysis was performed to identify students with SCS >1 standard deviation below the mean. Of the 3491 students receiving surveys, 1959 (56%) submitted usable surveys. The sample was 47% white and 38% black. Median age was 15. Median grade was 9th. The SCS was normally distributed with a mean of 15.7 and a possible range of 5 to 25. Of the 12 variables associated with connectedness, 7 (gender, race, extracurricular involvement, cigarette use, health status, school nurse visits, and school area) entered the linear regression model. All but gender were significant in the logistic model predicting students with SCS >1 standard deviation below the mean. In our sample, decreasing school connectedness was associated with 4 potentially modifiable factors: declining health status, increasing school nurse visits, cigarette use, and lack of extracurricular involvement. Black race, female gender, and urban schools were also associated with lower SCS. Further work is needed to better understand the link between these variables and school connectedness. If these associations are found in other populations, school health providers could use these markers to target youth in need of assistance.