Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use

Introduction: Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Methods: Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N = 4059) and alcohol (N = 3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Results: Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Conclusions: Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions

Psychometric assessment of the Temptations to Try Alcohol Scale

Effective interventions require an understanding of the behaviors and cognitions that facilitate positive change as well as the development of psychometrically sound measures. This paper reports on the psychometric properties of the Temptations to Try Alcohol Scale (TTAS), including factorial invariance across different subgroups. Data were collected from 3565 6th grade RI middle school students. Structural equation modeling was used to determine the appropriate factorial invariance model for the 9-item TTAS. The measure consists of three correlated subscales: Social Pressure, Social Anxiety, and Opportunity. Three levels of invariance, ranging from the least to the most restrictive, were examined: Configural Invariance, which constrains only the factor structure and zero loadings; Pattern Identity Invariance, which requires factor loadings to be equal across the groups; and Strong Factorial Invariance, which requires factor loadings and error variances to be constrained. Separate analyses evaluated the invariance across two levels of gender (males vs. females), race (white vs. black) ethnicity (Hispanic vs. Non-Hispanic) and school size (small, meaning \u3c 200 6th graders, or large). The highest level of invariance, Strong Factorial Invariance, provided a good fit to the model for gender (CFI: .95), race (CFI: .94), ethnicity (CFI: .94), and school size (CFI: .97). Coefficient Alpha was .90 for Social Pressure, .81 for Social Anxiety, and .82 for Opportunity. These results provide strong empirical support for the psychometric structure and construct validity of the TTAS in middle school students

Ratio of electron donor to acceptor influences metabolic specialization and denitrification dynamics in Pseudomonas aeruginosa in a mixed carbon medium

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zhang, I. H., Mullen, S., Ciccarese, D., Dumit, D., Martocello, D. E., Toyofuku, M., Nomura, N., Smriga, S., & Babbin, A. R. Ratio of electron donor to acceptor influences metabolic specialization and denitrification dynamics in Pseudomonas aeruginosa in a mixed carbon medium. Frontiers in Microbiology, 12, (2021): 711073, https://doi.org/10.3389/fmicb.2021.711073.Denitrifying microbes sequentially reduce nitrate (NO3–) to nitrite (NO2–), NO, N2O, and N2 through enzymes encoded by nar, nir, nor, and nos. Some denitrifiers maintain the whole four-gene pathway, but others possess partial pathways. Partial denitrifiers may evolve through metabolic specialization whereas complete denitrifiers may adapt toward greater metabolic flexibility in nitrogen oxide (NOx–) utilization. Both exist within natural environments, but we lack an understanding of selective pressures driving the evolution toward each lifestyle. Here we investigate differences in growth rate, growth yield, denitrification dynamics, and the extent of intermediate metabolite accumulation under varying nutrient conditions between the model complete denitrifier Pseudomonas aeruginosa and a community of engineered specialists with deletions in the denitrification genes nar or nir. Our results in a mixed carbon medium indicate a growth rate vs. yield tradeoff between complete and partial denitrifiers, which varies with total nutrient availability and ratios of organic carbon to NOx–. We found that the cultures of both complete and partial denitrifiers accumulated nitrite and that the metabolic lifestyle coupled with nutrient conditions are responsible for the extent of nitrite accumulation.Funding for this work was provided by Simons Foundation award 622065 and an MIT Environmental Solutions Initiative seed grant to AB. Additional support was received by the MIT Ferry Fund

Prevention of smoking in Middle School Students: Psychometric assessment of the Temptations to Try Smoking Scale

Establishment of psychometrically sound measures is critical to the development of effective interventions. The current study examined the psychometric properties, including factorial invariance, of a six item Temptations to Try Smoking Scale on a sample of middle school students. The sample of 6th grade students (N = 3527) was from 20 Rhode Island middle schools and was 52% male and 84% white. The Temptations to Try Smoking Scale consisted of two correlated subscales: Positive Social and Curiosity/Stress. Structural equation modeling was implemented to evaluate the factorial invariance across four different subgroups defined by gender (male/female), race (white/black), ethnicity (Hispanic/Non-Hispanic), and school size (\u3c 200/ \u3e 200 6th graders). A model is factorially invariant when the measurement model is the same in each of the subgroups. Three levels of invariance were examined in sequential order: 1) Configural Invariance (unconstrained nonzero factor loadings); 2) Pattern Identity Invariance (equal factor loadings); and 3) Strong Factorial Invariance (equal factor loadings and measurement errors). Strong Factorial Invariance provided a good fit to the model across gender (CFI = .96), race (CFI = .96), ethnicity (CFI = .94), and school size (CFI = .97). Coefficient Alphas for the two subscales, Positive Social and Curiosity/Stress, were .87 and .86, respectively. These findings provide empirical support for the construct validity of the Temptations to Try Smoking Scale in middle school students

Prevention of alcohol use in middle school students: Psychometric assessment of the decisional balance inventory

A measurement model should be equivalent across the different subgroups of a target population. The Decisional Balance Inventory for the Prevention of Alcohol Use is a 2-factor correlated model with 3 items for Pros of alcohol use and 3 items for Cons. The measure is part of a tailored intervention for middle school students. This study evaluated the important psychometric assumptions of factorial invariance and scale reliability with a large sample of sixth grade students (N = 3565) from 20 schools. A measure is factorially invariant when the model is the same across subgroups. Three levels of invariance were assessed, from least restrictive to most restrictive: 1) Configural Invariance (unconstrained nonzero factor loadings); 2) Pattern Identity Invariance (equal factor loadings); and 3) Strong Factorial Invariance (equal factor loadings and measurement errors). Structural equation modeling was used to assess invariance over two levels of gender (male and female), race (white and black), ethnicity (Hispanic and non-Hispanic), and school size (large, indicating \u3e 200 students per grade, or small). The strongest level of invariance, Strong Factorial Invariance, was a good fit for the model across all of the subgroups: gender (CFI: 0.94), race (CFI: 0.96), ethnicity (CFI: 0.93), and school size (CFI: 0.97). Coefficient alpha was 0.61 for the Pros and 0.67 for Cons. Together, invariance and reliability provide strong empirical support for the validity of the measure

Reducing Sun Exposure for Prevention of Skin Cancers: Factorial Invariance and Reliability of the Self-Efficacy Scale for Sun Protection

The Self-Efficacy Scale for Sun Protection consists of two correlated factors with three items each for Sunscreen Use and Avoidance. This study evaluated two crucial psychometric assumptions, factorial invariance and scale reliability, with a sample of adults ( = 1356) participating in a computer-tailored, population-based intervention study. A measure has factorial invariance when the model is the same across subgroups. Three levels of invariance were tested, from least to most restrictive: (1) Configural Invariance (nonzero factor loadings unconstrained); (2) Pattern Identity Invariance (equal factor loadings); and (3) Strong Factorial Invariance (equal factor loadings and measurement errors). Strong Factorial Invariance was a good fit for the model across seven grouping variables: age, education, ethnicity, gender, race, skin tone, and Stage of Change for Sun Protection. Internal consistency coefficient Alpha and factor rho scale reliability, respectively, were .84 and .86 for Sunscreen Use, .68 and .70 for Avoidance, and .78 and .78 for the global (total) scale. The psychometric evidence demonstrates strong empirical support that the scale is consistent, has internal validity, and can be used to assess population-based adult samples

Treated individuals who progress to action or maintenance for one behavior are more likely to make similar progress on another behavior: Coaction results of a pooled data analysis of three trials

Objective: This study compared, in treatment and control groups, the phenomena of coaction, which is the probability that taking effective action on one behavior is related to taking effective action on a second behavior. Methods: Pooled data from three randomized trials of Transtheoretical Model (TTM) tailored interventions (n = 9461), completed in the U.S. in 1999, were analyzed to assess coaction in three behavior pairs (diet and sun protection, diet and smoking, and sun protection and smoking). Odds ratios (ORs) compared the likelihood of taking action on a second behavior compared to taking action on only one behavior. Results: Across behavior pairs, at 12 and 24 months, the ORs for the treatment group were greater on an absolute basis than for the control group, with two being significant. The combined ORs at 12 and 24 months, respectively, were 1.63 and 1.85 for treatment and 1.20 and 1.10 for control. Conclusions: The results of this study with addictive, energy balance and appearance-related behaviors were consistent with results found in three studies applying TTM tailoring to energy balance behaviors. Across studies, there was more coaction within the treatment group. Future research should identify predictors of coaction in more multiple behavior change interventions

Denitrifying bacteria respond to and shape microscale gradients within particulate matrices

Heterotrophic denitrification enables facultative anaerobes to continue growing even when limited by oxygen (O₂) availability. Particles in particular provide physical matrices characterized by reduced O₂ permeability even in well-oxygenated bulk conditions, creating microenvironments where microbial denitrifiers may proliferate. Whereas numerical particle models generally describe denitrification as a function of radius, here we provide evidence for heterogeneity of intraparticle denitrification activity due to local interactions within and among microcolonies. Pseudomonas aeruginosa cells and microcolonies act to metabolically shade each other, fostering anaerobic processes just microns from O₂-saturated bulk water. Even within well-oxygenated fluid, suboxia and denitrification reproducibly developed and migrated along sharp 10 to 100 µm gradients, driven by the balance of oxidant diffusion and local respiration. Moreover, metabolic differentiation among densely packed cells is dictated by the diffusional supply of O₂, leading to distinct bimodality in the distribution of nitrate and nitrite reductase expression. The initial seeding density controls the speed at which anoxia develops, and even particles seeded with few bacteria remain capable of becoming anoxic. Our empirical results capture the dynamics of denitrifier gene expression in direct association with O₂ concentrations over microscale physical matrices, providing observations of the co-occurrence and spatial arrangement of aerobic and anaerobic processes.Simons Foundation (Award 622065