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The purpose of this sequential multiple-assignment randomization treatment pilot study was to examine if (a) adding working memory training to contingency management (CM) for youth with cannabis use disorder (CUD) and (b) switching nonresponding youth to higher magnitude CM incentives boosts outcomes. In Phase 1, youth with CUD ( n = 59, M age = 16, male = 71%) attending an intensive outpatient program were randomly assigned to 14 weeks of CM only or CM plus working memory training (WMT). In Week 4, a Phase 2 treatment was assigned. Those with negative urine drug tests (responders) continued in their Phase 1 treatment. Those who were drug positive (nonresponders) were randomly assigned to remain in their Phase 1 treatment or to higher magnitude CM. Zero-inflated negative binomial models comparing those assigned to CM versus CM + WMT indicated no differences in the likelihood of having ≥ 1 week of continuous abstinence or longer abstinence duration. Those assigned to WMT showed greater but nonsignificant improvements in working memory ( n = 35; β = .69, p = .06). Working memory improvements were associated with achieving any abstinence (odds ratio = 3.50, 95% CI [1.01, 12.10], p = .05). Phase 2 randomization to higher magnitude CM did not boost outcomes. Overall results suggest that WMT appears promising, but the sample size was small, attrition was high, and replication is important. Alternative strategies should continue to be explored to improve outcomes for adolescent substance use disorders, such as different approaches for nonresponders, tailoring to other baseline or response characteristics, or more robust first-line interventions. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Lifetime co-occurring substance use disorders are common at the time of presentation for treatment of a first episode of primary psychosis and persistent substance use disorder (SUD) leads to poorer outcomes. We assessed whether the NAVIGATE program, a coordinated specialty care service that includes optional substance abuse content reduced substance use compared to usual care in 404 individuals in the Recovery After Initial Schizophrenia Episode-Early Treatment Program (RAISE-ETP) study. Participants were randomized to two years of NAVIGATE (n = 223) or usual care (n = 181) and assessed monthly for substance use. At baseline, over one-half (51.7%) of the participants met criteria for a lifetime SUD, including over one-third with alcohol use disorder (36.4%) and with cannabis use disorder (34.7%). Contrary to our hypothesis, there was no treatment group by time interaction effect on days of self-reported substance use over the two-year follow-up. Participant exposure to the substance abuse component of the NAVIGATE program was low, suggesting that modifications to the program and training method for clinicians may be needed. Further research is needed to determine the most effective strategies for addressing substance use disorders in persons recovering from a first episode of psychosis., (Copyright © 2018. Published by Elsevier B.V.)

Cannabis is one of the most commonly used psychoactive substances among adolescents in the United States. Adolescent cannabis use has multiple consequences including academic, health, and psychiatric problems. The Marijuana Adolescent Problem Inventory (MAPI) is a 23-item scale adapted from the Rutgers Alcohol Problem Index and used in the current literature to assess cannabis use problem severity. Psychometric testing for the MAPI has yet to be reported. The current investigation assessed the psychometric characteristics of the MAPI with cannabis-using adolescents (n=727) from school and outpatient settings who enrolled in five separate randomized clinical trials focused on treatment of substance use. Findings suggested that the MAPI is internally consistent and reliable. Factor structure analyses suggested that the MAPI measures one latent construct, with no differences in factor structure between the outpatient and school settings, supporting a one-factor model. External validity of the MAPI was also demonstrated as evidenced by significant relations with concurrent diagnosis of cannabis dependence and abuse, longitudinal frequency of cannabis use, and mean times used per day. Overall, this initial test of the psychometric characteristics of the MAPI suggests that it can be considered a reliable and valid measure of problems associated with cannabis use among adolescents. Future work is now needed to replicate these findings by testing the psychometric properties of the MAPI in more diverse samples and developing a short version to be used as a brief assessment tool., (Copyright © 2017. Published by Elsevier Ltd.)

The fourteen-factor Processes of Change Scale for Sun Protection assesses behavioral and experiential strategies that underlie the process of sun protection acquisition and maintenance. Variations of this measure have been used effectively in several randomized sun protection trials, both for evaluation and as a basis for intervention. However, there are no published studies, to date, that evaluate the psychometric properties of the scale. The present study evaluated factorial invariance and scale reliability in a national sample (N = 1360) of adults involved in a Transtheoretical model tailored intervention for exercise and sun protection, at baseline. Invariance testing ranged from least to most restrictive: Configural Invariance (constraints only factor structure and zero loadings); Pattern Identity Invariance (equal factor loadings across target groups); and Strong Factorial Invariance (equal factor loadings and measurement errors). Multi-sample structural equation modeling tested the invariance of the measurement model across seven subgroups: age, education, ethnicity, gender, race, skin tone, and Stage of Change for Sun Protection. Strong factorial invariance was found across all subgroups. Internal consistency coefficient Alpha and factor rho reliability, respectively, were .83 and .80 for behavioral processes, .91 and .89 for experiential processes, and .93 and .91 for the global scale. These results provide strong empirical evidence that the scale is consistent, has internal validity and can be used in research interventions with population-based adult samples.

The purpose of this study was to conduct a randomized test of clinic- and home-based incentives plus parent training for adolescent problem alcohol use. Adolescents (N = 75) with alcohol misuse, with or without other substance misuse, were enrolled. All youth received individual Motivational Enhancement Therapy/Cognitive Behavior Therapy and weekly urine drug testing. The experimental condition (EXP) included Abstinence Incentives (clinic-based incentives for abstinence from all substances) plus weekly behavioral parent training that included a parent-delivered, abstinence-based, substance monitoring contract. The comparison condition (CONTROL) included Attendance Incentives (ATTI). All adolescents met DSM-IV criteria for alcohol abuse or dependence or reported recent binge drinking, and 77% (N = 58) met criteria for a cannabis use disorder or had recent cannabis use at baseline. Alcohol and cannabis use outcomes were compared across treatment conditions. A similar percentage of youth maintained complete alcohol abstinence across the 36-week follow-up in both conditions. However, among youth not entirely abstinent from alcohol, EXP resulted in a lower percentage of days using alcohol during the 36 weeks after the end of treatment than CONTROL. Among youth who also used cannabis at baseline, results showed similar benefits of EXP on cannabis use days. Combined individual and family based treatment, plus abstinence based incentives can reduce substance use days during and after treatment over and above individual evidence-based psychosocial treatment plus attendance incentives. Future research should focus on identifying cost-effective components and incentive levels and delivery via technology to facilitate dissemination. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

Introduction: Cigarette smoking initiation remains prevalent in adolescence. Effective prevention methods are needed to dissuade this behavior. Demographic factors are identified as important risk factors in the developmental nature of smoking in adolescence. The current study investigates potential demographic differences for two new trans-theoretical model measures, the Decisional Balance Inventory (pros and cons) for Smoking Prevention and the Temptations to Try Smoking Scale., Methods: A sample of 6th grade Rhode Island students from 20 middle schools (N = 4151) who were participating in a longitudinal and computer-delivered intervention for substance abuse prevention was assessed on these measures at baseline. Three MANOVA tests were conducted to assess the impact of race (White vs. Non-White), ethnicity (Hispanic vs. Non-Hispanic) and gender (male vs female)., Results: Significant effects for race and ethnicity were found for Decisional Balance and Temptations to Try Smoking. For race, Whites reported lesser pros (p <.0001) and Non-Whites reported higher cons (p <.0001) and temptations to try smoking (p <.0001). Differences for ethnicity showed that Hispanics were higher on pros (p <.0001) and temptations to try smoking (p <.0001) than Non-Hispanics. Non-Hispanics reported higher cons (p <.0001). Gender differences were noted only for temptations to try smoking, and showed females were higher on this construct than males (p <.0001). The effect sizes were .01 or below., Conclusions: The results did not demonstrate a strong association between these demographics and constructs, suggesting that tailored prevention methods based solely on these factors may not dissuade smoking in this group., Competing Interests: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported., (© 2017 Sillice M. A.)

Introduction: Outpatient treatments for adolescent substance use demonstrate clinically meaningful reductions in substance use, but effect sizes are often low, relapse rates are high, and response to treatment is heterogeneous across participants. The present study utilized cluster analysis to identify subgroups of treatment response among adolescents from three randomized clinical trials evaluating behavioral treatments for substance use., Methods: Analyses were performed on a sample of 194 adolescents (average age=15.8, 81.4% male) who reported cannabis use during the past 30days or had a cannabis-positive urine test. Clustering was based on percent days cannabis use at 5 time periods (intake, end of treatment, 3, 6, and 9months post-treatment). Participants in the identified subgroups were then compared across a number of variables not involved in the clustering (e.g., substance use, demographics, and psychopathology) to test for predictors of cluster membership., Results: Four clusters were identified based on statistical indices and visual inspection of the resulting cluster profiles: Low Use Responders (n=109, low baseline level, sustained decrease); High Use Responders (n=45, high baseline level, sustained decrease); Relapsers (n=25, medium baseline level, decrease, rapid increase post-treatment); and Non-Responders (n=15; consistently high level of use). Cannabis dependence, mean cannabis uses per day, and socioeconomic status were predictive of cluster membership., Conclusions: Cluster analysis empirically identified different patterns of treatment response over time for adolescent outpatients. Investigating homogenous subgroups of participants provides insight into study outcomes, and variables associated with clusters have potential utility to identify participants that may benefit from more intensive treatment., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2014. Published by Elsevier Ltd.)

To improve complex behaviors such as adherence to medical recommendations, a better understanding of behavior change over time is needed. The focus of this study was adherence to treatment for obstructive sleep apnea (OSA). Adherence to the most common treatment for OSA is poor. This study involved a sample of 161 participants, each with approximately 180 nights of data. First, a time series analysis was performed for each individual. Time series parameters included the mean (average hours of use per night), level, slope, variance, and autocorrelation. Second, a dynamic cluster analysis was performed to find homogenous subgroups of individuals with similar adherence patterns. A four-cluster solution was found, and the subgroups were labeled: Great Users (17.2%; high mean and level, no slope), Good Users (32.8%; moderate mean and level, no slope), Low Users (22.7%; low mean and level, negative slope), and Slow Decliners (moderate mean and level, negative slope, high variance). Third, participants in the identified subgroups were compared to establish external validity. These steps represent a Typology of Temporal Patterns (TTP) approach. Combining time series analysis and dynamic cluster analysis is a useful way to evaluate longitudinal patterns at both the individual level and subgroup level.

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 (N = 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.

Alcohol use by middle school-aged students is a public health concern because of the numerous adverse social, health and psychological outcomes. Prevention programs attempt to intervene before alcohol use begins. A tailored, computer-delivered program for the prevention of alcohol use and a series of new transtheoretical model measures were developed, including decisional balance (Pros and Cons) of alcohol use and Situational Temptations to Try Alcohol. This study investigated if there were any demographic differences on these measures in a sample of 6th grade middle school students from 20 schools (N=4151) at baseline. Three factorial analysis of variance tests were conducted to explore the impact of race (whites vs. non-whites), ethnicity (Hispanics vs. Non-Hispanics) and gender (males vs. females). A significant two-way interaction effect was found between gender and ethnicity for Pros of Alcohol Use. A significant three-way interaction effect was found between gender, race and ethnicity for Cons of Alcohol Use. Main effects were found for the three demographic factors for Situational Temptations to Try Alcohol. However, the effect sizes for the interaction effects and main effects were very small (all below η(2)=.01), suggesting that race/ethnicity and gender alone may not be highly influential factors in the Decisional Balance for the Prevention of Alcohol and Situational Temptations to Try Alcohol in adolescence. The implications for these results and alcohol use prevention among this group are discussed., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The 8-item Decisional Balance for sun protection inventory (SunDB) assesses the relative importance of the perceived advantages (Pros) and disadvantages (Cons) of sun protective behaviors. This study examined the psychometric properties of the SunDB measure, including invariance of the measurement model, in a population-based sample of N = 1336 adults. Confirmatory factor analyses supported the theoretically based 2-factor (Pros, Cons) model, with high internal consistencies for each subscale (α ≥ .70). Multiple-sample CFA established that this factor pattern was invariant across multiple population subgroups, including gender, racial identity, age, education level, and stage of change subgroups. Multivariate analysis by stage of change replicated expected patterns for SunDB (Pros η (2) = .15, Cons η (2) = .02). These results demonstrate the internal and external validity and measurement stability of the SunDB instrument in adults, supporting its use in research and intervention.

This study examined the effectiveness of two transtheoretical model-tailored, computer-delivered interventions designed to impact multiple substance use or energy balance behaviors in a middle school population recruited in schools. Twenty middle schools in Rhode Island including sixth grade students ( N =4,158) were stratified and randomly assigned by school to either a substance use prevention (decreasing smoking and alcohol) or an energy balance (increasing physical activity, fruit and vegetable consumption, and limiting TV time) intervention group in 2007. Each intervention involved five in-class contacts over a 3-year period with assessments at 12, 24, and 36 months. Main outcomes were analyzed using random effects modeling. In the full energy balance group and in subsamples at risk and not at risk at baseline, strong effects were found for physical activity, healthy diet, and reducing TV time, for both categorical and continuous outcomes. Despite no direct treatment, the energy balance group also showed significantly lower smoking and alcohol use over time than the substance use prevention group. The energy balance intervention demonstrated strong effects across all behaviors over 3 years among middle school students. The substance use prevention intervention was less effective than the energy balance intervention in preventing both smoking and alcohol use over 3 years in middle school students. The lack of a true control group and unrepresented secular trends suggest the need for further study.

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., (Published by Elsevier Inc.)

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 (<200/ >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., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Increasing adherence to medical recommendations is crucial for improving health outcomes and reducing costs of health care. To improve adherence, we have to better understand behavior change over time. The focus of this study was adherence to treatment for obstructive sleep apnea (OSA). Adherence to positive airway pressure (PAP), the most common treatment for OSA, is poor. This study involved an international sample of 161 participants, each with approximately 180 nights of data, and had three phases. First, a separate time series analysis was performed for each individual. Time series parameters included the mean (average hours of use per night), level (the intercept), slope (the rate of change over time), variance (variability in use), and autocorrelation (a measure of dependency). Second, a dynamic cluster analysis was performed to find homogenous subgroups of individuals with similar adherence patterns. A four-cluster solution was found, and the subgroups were labeled (see Figure 1 ): Great Users (17.2%; high mean and level, no slope), Good Users (32.8%; moderate mean and level, no slope), Poor Users (22.7%; low mean and level, negative slope), and Slow Decliners (moderate mean and level, negative slope, high variance). Third, participants in the identified subgroups were compared on a number of variables that were not involved in the clustering to establish external validity. Some notable findings at later time points include the following: Great Users reported the most self-efficacy (confidence to use PAP), Poor Users reported the most sleepiness, and Great Users reported the highest quality of sleep. Combining time series analysis and dynamic cluster analysis is a useful way to evaluate adherence patterns at both the individual level and subgroup level. Psychological variables relevant to adherence patterns, such as self-efficacy, could be the focus of interventions to increase PAP usage.

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 >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., (Copyright © 2011. Published by Elsevier Ltd.)