Intervention impact on alcohol use, alcohol harms, and a combination of both: A latent class, secondary analysis of results from a randomized controlled trial. (1st October 2021)

• Record Type: Journal Article
• Authors: Padgett, R. Noah; Andretta, James R.; Cole, Jon C.; Percy, Andrew; Sumnall, Harry R.; McKay, Michael T.
• Is Part Of: Drug and alcohol dependence. Volume 227(2021)
• Publication Date: 2021-10-01
• Subjects: Adolescent -- Latent class analysis -- Growth mixture modelling -- Alcohol -- STAMPP Trial -- United Kingdom; Drug abuse -- Periodicals; Alcoholism -- Periodicals; 616.86
• DOI: 10.1016/j.drugalcdep.2021.108944
• Languages: English
• ISSNs: 0376-8716

Abstract

Highlights: Growth mixture modelling was used to identify trajectory classes. Five alcohol classes were identified. The intervention was most strongly related to Late and Delayed Onset drinking. For harms. The Delayed Onset class was significantly related to the intervention. Abstract: Background. Alcohol use and alcohol-related harm (ARH) among adolescents places a substantial burden on health, and public services more generally. To date, attempts to intervene at a universal level have yielded results varying from iatrogenic to null, although some skill-enhancing universal interventions have successfully impacted drinking behaviors. One such intervention is SHAHRP. The present study is a secondary analysis of data from the STAMPP Trial, providing new, and more nuanced findings. Methods. A total of 13, 914 adolescents (41.7% female) participated in this cRCT where schools were randomly assigned to a control or intervention group. Growth mixture modelling was used to identify trajectory classes from baseline through third follow-up (+33 months) of adolescents on heavy episodic drinking (HED) and ARH. Extracted classes were related to school intervention participation using multinomial logistic regression. Results. Five trajectory classes of the HED and ARH composite were identified: Low (62%), Late Onset (16%), Early Onset (13%), Delayed Onset (7%), and Unstable (3%). The intervention was most strongly related to Late Onset (OR = 0.50, 95%CI [0.25, 1.01]) and Delayed Onset (OR = 0.55, 95%CI [0.26, 1.16]), although not statistically significant. With classes constructed with ARH only, the Delayed Onset class was significantly related to the intervention (OR = 0.60, 95%CI [0.43, 0.84]). Conclusions. These results support those previously reported on the STAMPP Trial and provide a more nuanced insight into the effects of the intervention.