Unpacking Technical Assistance (TA) Strategies Within a State-Level Prevention Support System: A Mixed-Method Study in Determining Types and Amount of TA.

The research-practice gap between evidence-based intervention efficacy and its uptake in real-world contexts remains a central challenge for prevention and implementation science. Providing technical assistance (TA) is considered a crucial support mechanism that can help narrow the gap. However, empirical measurement of TA strategies and their variation is often lacking. The current study unpacks the black box of TA, highlighting different TA strategies, amounts, and their relation to intervention characteristics. First, we qualitatively categorized interactions between TA providers and implementers. Second, we explored how characteristics of implementing organizations and the intervention related to variations in the amount of TA delivered. Using data spanning six years, we analyzed over 10,000 encounters between TA providers and implementers. Content analysis yielded four distinct strategies: Consultation (27.2%), Coordination Logistics (24.5%), Monitoring (16.5%), and Resource Delivery (28.2%). Organizations with prior experience required less monitoring and resource delivery. Additionally, characteristics of the intervention were significantly associated with the amount of consultation, monitoring, coordination logistics, and resource delivery provided. The specific features of the intervention showed significant variation in their relation to TA strategies. These findings provide initial insights into the implications of intervention characteristics in determining how much of which TA strategies are needed to support implementations in real-world settings.

Youth risk profiles and their prediction of distal cannabis and tobacco co-use in the Population Assessment of Tobacco Health (PATH).

Background: Co-use of cannabis and tobacco is common and increases negative behavioral, physical and mental health consequences. This study aimed to describe latent profiles of youth internalizing and externalizing problems, sensation seeking, and family environment in the US and their relationships with substance co-use. Methods: Data come from the Population Assessment of Tobacco Health (PATH). Using latent profile analysis with a distal outcome, we conducted a secondary data analysis examining relationships between latent profiles and the distal outcome of cannabis/tobacco use and co-use one year later. Participants were a nationally representative sample of youth ages 12-17 (N = 13,651). Results: We identified five youth subgroups: (1;11%) Family Risk, (2;32%) Family Protection with Very Low Internalizing, (3;21%) Family Protection with High Youth Risk, (4;24%) Family Protection with Moderate Youth Risk, (5;12%) Family Risk with High Youth Risk. Relationships between group membership and tobacco/cannabis outcomes, one year later, indicated that the least likely tobacco/cannabis users were the Family Protection with Very Low Internalizing class (no lifetime use probability (PR)=0.86, standard error (SE)=0.007; no 30-day use PR = 0.96, SE = 0.004). In contrast, the Family Risk with High Youth Risk class had the highest probability of both co-use (lifetime co-use PR = 0.33; SE = 0.014; 30-day co-use PR = 0.10; SE = 0.010) and single substance use (probability of lifetime single substance use PR = 0.30; SE = 0.013; 30-day single substance use PR = 0.24; SE = 0.014). Conclusions: A "protective but reactive" risk buffering pattern effect of family factors on youth factors was observed in that the lowest rates of co-use were observed in the three classes with family protection. These findings highlight the need for interventions addressing multiple domains and focusing on youth and family risk factors.

Who benefits most from Head Start? Using latent class moderation to examine differential treatment effects.

Head Start (HS) is the largest federally funded preschool program for disadvantaged children. Research has shown relatively small impacts on cognitive and social skills; therefore, some have questioned its effectiveness. Using data from the Head Start Impact Study (3-year-old cohort; N = 2,449), latent class analysis was used to (a) identify subgroups of children defined by baseline characteristics of their home environment and caregiver and (b) test whether the effects of HS on cognitive, and behavioral and relationship skills over 2 years differed across subgroups. The results suggest that the effectiveness of HS varies quite substantially. For some children there appears to be a significant, and in some cases, long-term, positive impact. For others there is little to no effect.