Leonard A Jason1, Mike Stoolmiller2, John Light2. 1. Psychology Department, DePaul University, Chicago, Illinois, USA. 2. Oregon Research Institute, Eugene, Oregon, USA.
Abstract
Background: Our study explored whether latent classes adequately represented the social capital recovery indicators at the resident level and whether latent class membership predicted subsequent exits from the recovery homes. Method: Our sample included about 600 residents in 42 recovery homes. Over a 2-year period of time, every 4 months, data were collected on eight elements of recovery capital. Results: We found 5 latent classes were optimal for representing 8 elements of recovery capital. Representing 79% of the sample, 3 of the 5 latent class profiles of the means of the 8 recovery indicators were roughly parallel and differed only in level, but the remaining 2 latent class profiles, representing 21% of the sample, were not parallel to the first 3, suggesting that a single quantitative dimension of perceived recovery may capture most but not all of the important details of the recovery process. Next, using longitudinal data from homes, the distal outcomes of resident eviction and voluntary exit were found to be related to latent class membership. Resident level pre-existing predictors (e.g., employment status, educational attainment, gender, Latinx ethnicity) and house level pre-existing predictors (e.g., financial health, poverty level of typical population served, new resident acceptance rate) significantly discriminated the classes. In a model that combined both pre-existing predictors and distal outcomes, latent class membership was still the strongest predictor of evictions controlling for the pre-existing predictors. Conclusions: These classes help to clarify the different aspects of the recovery latent score, and point to classes that have different ethnic and gender characteristics as well as outcomes in the recovery homes. For example, the high levels of self-confidence found in class 3 suggest that Latinx might be at higher risk for having some difficulties within these recovery communities.
Background: Our study explored whether latent classes adequately represented the social capital recovery indicators at the resident level and whether latent class membership predicted subsequent exits from the recovery homes. Method: Our sample included about 600 residents in 42 recovery homes. Over a 2-year period of time, every 4 months, data were collected on eight elements of recovery capital. Results: We found 5 latent classes were optimal for representing 8 elements of recovery capital. Representing 79% of the sample, 3 of the 5 latent class profiles of the means of the 8 recovery indicators were roughly parallel and differed only in level, but the remaining 2 latent class profiles, representing 21% of the sample, were not parallel to the first 3, suggesting that a single quantitative dimension of perceived recovery may capture most but not all of the important details of the recovery process. Next, using longitudinal data from homes, the distal outcomes of resident eviction and voluntary exit were found to be related to latent class membership. Resident level pre-existing predictors (e.g., employment status, educational attainment, gender, Latinx ethnicity) and house level pre-existing predictors (e.g., financial health, poverty level of typical population served, new resident acceptance rate) significantly discriminated the classes. In a model that combined both pre-existing predictors and distal outcomes, latent class membership was still the strongest predictor of evictions controlling for the pre-existing predictors. Conclusions: These classes help to clarify the different aspects of the recovery latent score, and point to classes that have different ethnic and gender characteristics as well as outcomes in the recovery homes. For example, the high levels of self-confidence found in class 3 suggest that Latinx might be at higher risk for having some difficulties within these recovery communities.
Entities:
Keywords:
Latent profile analysis; Oxford Houses; recovery homes; social networks
Authors: C R Snyder; C Harris; J R Anderson; S A Holleran; L M Irving; S T Sigmon; L Yoshinobu; J Gibb; C Langelle; P Harney Journal: J Pers Soc Psychol Date: 1991-04
Authors: Leonard A Jason; Mayra Guerrero; Meghan Salomon-Amend; Gabrielle Lynch; Ed Stevens; John M Light; Mike Stoolmiller; Nathan J Doogan Journal: Int J Drug Policy Date: 2020-11-24