Ahnalee M. Brincks

Overview of Meta-Analyses of the Prevention of Mental Health,Substance Use and Conduct Problems

This review presents findings from an overview of meta-analyses of the effects of prevention and promotion programs to prevent mental health, substance use, and conduct problems. The review of 48 meta-analyses found small but significant changes that reduce depression, anxiety, antisocial behavior, and substance use. Furthermore, the results were sustained over time. Meta-analyses often found that the effects were heterogeneous. A conceptual model is proposed to guide the study of moderators of program effects in future meta-analyses, and methodological issues in synthesizing findings across preventive interventions are discussed.

Preventing Internalizing Symptoms Among Hispanic Adolescents: A Synthesis Across Familias Unidas Trials

Studies document that there are efficacious interventions to prevent adolescent depression and internalizing symptoms, including several family-focused interventions. Questions remain about for whom interventions work (moderation) and by what mechanisms they work (mediation) to prevent internalizing symptoms. Unfortunately, single trials are often underpowered to address moderation and mediation, an issue addressed in this paper. This synthesis study combined individual-level, longitudinal data from 721 adolescents across 3 randomized clinical trials of Familias Unidas, a family-focused prevention intervention for Hispanic youth. Using integrative data analysis (IDA) methods applied to trials, the study examined intervention moderation and mediation effects on internalizing symptoms. Baseline internalizing symptoms were a significant moderator of the intervention’s effects on internalizing symptoms, while baseline externalizing symptoms did not moderate intervention effects. Baseline parent–adolescent communication, a modifiable risk factor and hypothesized mechanism by which the intervention works, significantly moderated the intervention’s effects. Specifically, the intervention was more efficacious in its impact on internalizing symptoms for youth with lower initial levels of parent–adolescent communication compared to those with higher communication levels. Moderated mediation analyses showed that parent–adolescent communication changes mediated the intervention’s effects on internalizing symptoms, with stronger effects for those with poorer baseline communication. Results suggest a potential benefit of identifying youth risks prior to interventions, and targeting specific modifiable mediators that lead to reductions of internalizing problems of adolescents. Findings also highlight advantages of utilizing data from combined trials and IDA for examining intervention moderators and mediators.

A Randomized Controlled Trial of Structural Ecosystems Therapy for HIV Medication Adherence and Substance Abuse Relapse Prevention

BACKGROUND Substance abuse in women with HIV/AIDS overshadows other priorities, including health care. Substance abuse may cause women to avoid health care systems and not adhere to their medication regimen. METHODS A randomized controlled trial tested the efficacy of Structural Ecosystems Therapy (SET) relative to a psychoeducational Health Group (HG) in 126 HIV+ women in recovery. SET, a 4-month intervention, focused on building family support for relapse prevention and HIV medication adherence. Over 12-month follow-up, women were assessed for drug use and medication adherence every 2 months; CD4 T-cell count and HIV viral load were assessed every 4 months. RESULTS Levels of drug use did not differ by condition. There was a significant difference in curvature of the rates of change in drug use with SET increasing and then decreasing and HG decreasing and then increasing. Women in SET were more likely to increase substance abuse services in response to relapse and separate from drug using household members than were women in HG. These two changes explained the decline in drug use observed within SET between 6 and 12 months. SET showed declines in medication adherence but increases in CD4 T-cell count relative to HG. The increase in CD4 T-cell count in SET was related to increasing proportions of women in SET taking antiretroviral medications. CONCLUSION The results of the trial were mixed. Women in SET did not show better drug use or medication adherence outcomes, but did show improvement in CD4 T-cell count and theoretical mechanisms of action on drug relapse.

The Efficacy of Structural Ecosystems Therapy for HIV Medication Adherence With African American Women

A systemic family therapy intervention, Structural Ecosystems Therapy (SET; Mitrani, Szapocznik, & Robinson-Batista, 2000; Szapocznik et al., 2004), has been shown to promote adaptation to living with HIV by reducing psychological distress and family hassles. This investigation examines the effect of SET on HIV medication adherence relative to a person-centered condition and a community control condition. Medication adherence was assessed on 156 trial participants. Results of a 2-part model showed that SET was significantly more likely to move women to high levels of adherence (defined as at least 95% adherence) than a person-centered therapy. Family hassles were also significantly reduced by SET, though the effect of SET on medication adherence did not appear related to this change in family hassles.

The influence of health locus of control on the patient-provider relationship

The physician–patient relationship is important to the successful delivery of health care. Health locus of control (HLOC) of the patient, the extent to which individuals attribute their health to their own actions or to external agents, may affect the patient–provider relationship. This study examined the influences of HIV and HLOC on trust in physician among a population of predominantly minority women and their family members. Powerful others HLOC demonstrated a positive relationship with trust in physician and chance HLOC had a negative relationship with trust in physician. HIV moderated both of these relationships.

Modeling Site Effects in the Design and Analysis of Multi-site Trials

Background: Careful consideration of site effects is important in the analysis of multi-site clinical trials for drug abuse treatment. The statistical choices for modeling these effects have implications for both trial planning and interpretation of findings. Objectives: Three broad approaches for modeling site effects are presented: omitting site from the analysis; modeling site as a fixed effect; and modeling site as a random effect. Both the direct effect of site and the interaction of site and treatment are considered. Methods: The statistical model, and consequences, for each approach are presented along with examples from existing clinical trials. Power analysis calculations provide sample size requirements for adequate statistical power for studies utilizing 6, 8, 10, 12, 14, and 16 treatment sites. Results: Results of the power analyses showed that the total sample required falls rapidly as the number of sites increases in the random effect approach. In the fixed effect approach in which the interaction of site and treatment is considered, the required number of participants per site decreases as the number of sites increases. Conclusions: Ignoring site effects is not a viable option in multi-site clinical trials. There are advantages and disadvantages to the fixed effect and random effect approaches to modeling site effects. Scientific Significance: The distinction between efficacy trials and effectiveness trials is rarely sharp. The choice between random effect and fixed effect statistical modeling can provide different benefits depending on the goals of the study.

Toward Scientific Equity for the Prevention of Depression and Depressive Symptoms in Vulnerable Youth

Certain subgroups of youth are at high risk for depression and elevated depressive symptoms, and experience limited access to quality mental health care. Examples are socioeconomically disadvantaged, racial/ ethnic minority, and sexual minority youth. Research shows that there are efficacious interventions to prevent youth depression and depressive symptoms. These preventive interventions have the potential to play a key role in addressing these mental health disparities by reducing youth risk factors and enhancing protective factors. However, there are comparatively few preventive interventions directed specifically to these vulnerable subgroups, and sample sizes of diverse subgroups in general prevention trials are often too low to assess whether preventive interventions work equally well for vulnerable youth compared to other youth. In this paper, we describe the importance and need for “scientific equity,” or equality and fairness in the amount of scientific knowledge produced to understand the potential solutions to such health disparities. We highlight possible strategies for promoting scientific equity, including the following: increasing the number of prevention research participants from vulnerable subgroups, conducting more data synthesis analyses and implementation science research, disseminating preventive interventions that are efficacious for vulnerable youth, and increasing the diversity of the prevention science research workforce. These strategies can increase the availability of research evidence to determine the degree to which preventive interventions can help address mental health disparities. Although this paper utilizes the prevention of youth depression as an illustrative case example, the concepts are applicable to other health outcomes for which there are disparities, such as substance use and obesity.

Multiple imputation for harmonizing longitudinal non-commensurate measures in individual participant data meta-analysis

There are many advantages to individual participant data meta-analysis for combining data from multiple studies. These advantages include greater power to detect effects, increased sample heterogeneity, and the ability to perform more sophisticated analyses than meta-analyses that rely on published results. However, a fundamental challenge is that it is unlikely that variables of interest are measured the same way in all of the studies to be combined. We propose that this situation can be viewed as a missing data problem in which some outcomes are entirely missing within some trials and use multiple imputation to fill in missing measurements. We apply our method to five longitudinal adolescent depression trials where four studies used one depression measure and the fifth study used a different depression measure. None of the five studies contained both depression measures. We describe a multiple imputation approach for filling in missing depression measures that makes use of external calibration studies in which both depression measures were used. We discuss some practical issues in developing the imputation model including taking into account treatment group and study. We present diagnostics for checking the fit of the imputation model and investigate whether external information is appropriately incorporated into the imputed values.

An Application of the Complier Average Causal Effect Analysis to Examine the Effects of a Family Intervention in Reducing Illicit Drug Use among High‐Risk Hispanic Adolescents

The Complier Average Causal Effect (CACE) method has been increasingly used in prevention research to provide more accurate causal intervention effect estimates in the presence of noncompliance. The purpose of this study was to provide an applied demonstration of the CACE analytic approach to evaluate the relative effects of a family-based prevention intervention, Familias Unidas, in preventing/reducing illicit drug use for those participants who received the intended dosage. This study is a secondary data analysis of a randomized controlled trial designed to evaluate the relative efficacy of Familias Unidas with high-risk Hispanic youth. A total of 242 high-risk Hispanic youth aged 12-17 years and their primary caregivers were randomized to either Familias Unidas or Community Practice and assessed at baseline, 6 months and 12 months postbaseline. CACE models were estimated with a finite growth mixture model. Predictors of engagement were included in the CACE model. Findings indicate that, relative to the intent-to-treat (ITT) analytic approach, the CACE analytic approach yielded stronger intervention effects among both initially engaged and overall engaged participants. The CACE analytic approach may be particularly helpful for studies involving parent/family-centered interventions given that participants may not receive the intended dosage. Future studies should consider implementing the CACE analysis in addition to ITT analysis when examining the effects of family-based prevention programs to determine whether, and the extent to which, the CACE analysis has more power to uncover intervention effects.

Multilevel Modeling in Psychosomatic Medicine Research

The primary purpose of this study is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The article begins with a general introduction to multilevel modeling. Multilevel regression modeling at two levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated data sets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive-behavioral stress management intervention in prostate cancer.