AIMS: For well over a decade, the Important People Inventory (IP, Clifford and Longabaugh, 1991; Clifford et al., 1992) has been used to collect a wide range of valuable information regarding network support for alcohol use. However, because of psychometric limitations and varied adaptations of the IP, the following study performed factor analyses to develop a more structurally consistent model of the scaleas compared to the existing model. METHODS: A first principal components analysis (Varimax rotation) was run on the indices of the IP using data from a national investigation of residents within a recovery community (N=897). Next, a second principal components analysis was run using data collected from participants recruited from inpatient treatment settings (N=150). RESULTS: Results indicated a nine-index, three-factor model, which explained about two thirds of the common variance. These three factors included: Support for Drinking from Network Members (3 items), Drinking Behaviours of Network Members (3 items), and General Social Support (3 items). CONCLUSIONS: Results of both studies suggest that the IP fits a multi-component structure. It is recommended that Drinking Behaviours of Network Members be examined for predictive validity and that General Social Support be removed from the scale or have additional items added.
AIMS: For well over a decade, the Important People Inventory (IP, Clifford and Longabaugh, 1991; Clifford et al., 1992) has been used to collect a wide range of valuable information regarding network support for alcohol use. However, because of psychometric limitations and varied adaptations of the IP, the following study performed factor analyses to develop a more structurally consistent model of the scaleas compared to the existing model. METHODS: A first principal components analysis (Varimax rotation) was run on the indices of the IP using data from a national investigation of residents within a recovery community (N=897). Next, a second principal components analysis was run using data collected from participants recruited from inpatient treatment settings (N=150). RESULTS: Results indicated a nine-index, three-factor model, which explained about two thirds of the common variance. These three factors included: Support for Drinking from Network Members (3 items), Drinking Behaviours of Network Members (3 items), and General Social Support (3 items). CONCLUSIONS: Results of both studies suggest that the IP fits a multi-component structure. It is recommended that Drinking Behaviours of Network Members be examined for predictive validity and that General Social Support be removed from the scale or have additional items added.
Authors: Andrea M Flynn; Josefina Alvarez; Leonard A Jason; Bradley D Olson; Joseph R Ferrari; Margaret I Davis Journal: J Prev Interv Community Date: 2006