OBJECTIVE: Because of psychometric limitations and varied adaptations of the Important People Inventory (IP; a measure of alcohol social support), Groh et al. (7) performed factor analyses and created a three-factor model (i.e., Support for Drinking from Network Members, Drinking Behaviors of Network Members, and General Social Support). This present study examined the ability of the three-factor model to predict alcohol use. METHODS: This study consisted of 293 women and 604 men who were US residents of a network of self-run recovery homes known as Oxford House (OH). Logistic regression models were run. The first model examined which of the three IP factors was the best predictor of alcohol use over a 4-month period; next, models compared Drinking Behaviors of Network Members (the three-factor model) and Network Support for Drinking from Network Members (the original two-factor model) as predictors of 4-month alcohol use. RESULTS: Of the three factors measuring general support, network drinking behaviors, and support for drinking, Drinking Behaviors of Network Members was the only significant predictor of alcohol use over a 4-month period. Additionally, this component was a better predictor of drinking than the Support for Drinking from Network Members summary score from the original model. CONCLUSIONS: Compared to the original model, this new three-factor model of the IP is shorter, has stronger internal reliability, and is a better predictor of alcohol use over time. It is strongly recommended that researchers continue to explore the utility of this new model.
OBJECTIVE: Because of psychometric limitations and varied adaptations of the Important People Inventory (IP; a measure of alcohol social support), Groh et al. (7) performed factor analyses and created a three-factor model (i.e., Support for Drinking from Network Members, Drinking Behaviors of Network Members, and General Social Support). This present study examined the ability of the three-factor model to predict alcohol use. METHODS: This study consisted of 293 women and 604 men who were US residents of a network of self-run recovery homes known as Oxford House (OH). Logistic regression models were run. The first model examined which of the three IP factors was the best predictor of alcohol use over a 4-month period; next, models compared Drinking Behaviors of Network Members (the three-factor model) and Network Support for Drinking from Network Members (the original two-factor model) as predictors of 4-month alcohol use. RESULTS: Of the three factors measuring general support, network drinking behaviors, and support for drinking, Drinking Behaviors of Network Members was the only significant predictor of alcohol use over a 4-month period. Additionally, this component was a better predictor of drinking than the Support for Drinking from Network Members summary score from the original model. CONCLUSIONS: Compared to the original model, this new three-factor model of the IP is shorter, has stronger internal reliability, and is a better predictor of alcohol use over time. It is strongly recommended that researchers continue to explore the utility of this new model.
Authors: David R Groh; Bradley D Olson; Leonard A Jason; Margaret I Davis; Joseph R Ferrari Journal: Alcohol Alcohol Date: 2007-05-17 Impact factor: 2.826