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More behavioral recommendations produce more change: A meta-analysis of efficacy of multibehavior recommendations to reduce nonmedical substance use.

ABSTRACT: Death and morbidity associated with substance use have risen continuously over the last few decades, increasing the need for rigorous examination of promising programs. Interventions attempting to change multiple behaviors have been designed to address interconnected problems such as use of both alcohol and drugs. This meta-analysis aimed to examine the efficacy of multibehavior interventions to curb nonmedical substance use in relation to the theoretical relation among different substance use behaviors. Specifically, our synthesis aimed to estimate the optimal number of recommendations for intervention efficacy and evaluate the impact of different combinations of recommendations on intervention efficacy. A synthesis of multibehavior interventions addressing nonmedical substance use was conducted to measure behavioral changes between the pretest and the follow-up. These changes were then compared across different numbers of recommendations. Sixty-nine reports and 233 effect sizes (k of conditions = 155, n = 28,295) were included. A positive linear relation was found between the number of targeted behaviors and intervention efficacy, which was stronger for drug use than alcohol use. Furthermore, recommendations on drug use worked better when paired with recommendations targeting other behaviors, whereas recommendations on alcohol use worked more independently. Lastly, multibehavior interventions were especially efficacious when delivered by experts. Overall, our synthesis indicated that targeting multiple substances is beneficial for changing drug use outcomes, but less so for alcohol use outcomes. Therefore, in the current substance use epidemic, innovative multibehavior programs appear to hold promise, especially to combat nonmedical drug use. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

SUBMITTER: Dai W

PROVIDER: S-EPMC7572872 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectiveTo examine whether sources of nonmedical use of prescription drugs (NMUPD) involving anxiolytics, opioids, and stimulants were associated with sociodemographic characteristics, NMUPD characteristics (eg, frequency), and other substance use.MethodNationally representative samples of US high school seniors (N = 18,549) were surveyed by self-administered questionnaires (2009-2016). Design-based latent class analysis and Rao-Scott χ2 tests were used to test associations among sociodemographic characteristics, NMUPD characteristics, other substance use behaviors (eg, binge drinking, cigarette smoking, marijuana use), and NMUPD sources.ResultsApproximately 11.0% of high school seniors reported past-year NMUPD (n = 1,917). A substantial proportion of nonmedical users obtained the prescription drugs from multiple sources (44.2%). Latent class analysis identified 5 subgroups of NMUPD sources (friend/relative sources, friend/purchased sources, own leftover prescription, multiple sources, and other sources). Nonmedical users who obtained prescription drugs from friend/purchased sources were more likely to be adolescent boys, whereas those who used their own leftover prescriptions were more likely to be adolescent girls. Nonmedical users who obtained prescription drugs from multiple sources were more involved in substance use. In contrast, adolescent nonmedical users who used their own leftover prescriptions were less involved in substance use.ConclusionGrowing evidence indicates that different NMUPD sources are associated with different substance use behaviors. All NMUPD sources should be discouraged, because they place individuals, families, and communities at risk. Patients and their families should receive education on how to manage and properly dispose of controlled medications to avoid diversion into the community. Prescribers are encouraged to check prescription monitoring programs and screen adolescents for substance use/misuse when prescribing controlled medications.

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More behavioral recommendations produce more change: A meta-analysis of efficacy of multibehavior recommendations to reduce nonmedical substance use.

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