An integrated data analysis approach to investigating measurement equivalence of DSM nicotine dependence symptoms

Psychosocial Indicators of Adolescent Alcohol, Cigarette, and Marijuana Use: An Analysis of Normalized, Harmonized, and Pooled Data

We normalized, harmonized, and pooled 344,429 surveys collected from 106,470 research participants from 25 research studies that assessed past 30-day alcohol use, drunkenness, smoking cigarettes, using marijuana, and a host of psychosocial variables. After normalizing and harmonizing psychosocial measures, we completed analyses to examine the ability of psychosocial variables to serve as proxy indicators of use. Intentionality, peer descriptive normative beliefs, and age emerged as being of primary importance in indicating use. Additional variables - peer injunctive norms, beliefs about the positive and negative consequences of use, and attitudes - were also demonstrated to have the potential to serve as proxies in the assessment of substance use risk. There were developmental patterns in how intentionality and descriptive normative beliefs changed with age. Young adolescents had scores that are protective; they have positive intentionality and do not see the prevalence of alcohol and other drug use as widespread. These and other psychosocial variable's mean scores generally erode with age while the distribution of scores widens as youth grow older. The goal of analyses was to define age-related psychosocial profiles that can be used prospectively to estimate substance use risk. These profiles are useful in creating virtual control cases for evaluating disseminated prevention programs.

Linking Scores with Patient-Reported Health Outcome Instruments:A VALIDATION STUDY AND COMPARISON OF THREE LINKING METHODS

The psychometric process used to establish a relationship between the scores of two (or more) instruments is generically referred to as linking. When two instruments with the same content and statistical test specifications are linked, these instruments are said to be equated. Linking and equating procedures have long been used for practical benefit in educational testing. In recent years, health outcome researchers have increasingly applied linking techniques to patient-reported outcome (PRO) data. However, these applications have some noteworthy purposes and associated methodological questions. Purposes for linking health outcomes include the harmonization of data across studies or settings (enabling increased power in hypothesis testing), the aggregation of summed score data by means of score crosswalk tables, and score conversion in clinical settings where new instruments are introduced, but an interpretable connection to historical data is needed. When two PRO instruments are linked, assumptions for equating are typically not met and the extent to which those assumptions are violated becomes a decision point around how (and whether) to proceed with linking. We demonstrate multiple linking procedures-equipercentile, unidimensional IRT calibration, and calibrated projection-with the Patient-Reported Outcomes Measurement Information System Depression bank and the Patient Health Questionnaire-9. We validate this link across two samples and simulate different instrument correlation levels to provide guidance around which linking method is preferred. Finally, we discuss some remaining issues and directions for psychometric research in linking PRO instruments.

Psychometric Data Linking Across HIV and Substance Use Cohorts

Psychometric data linking of psychological and behavioral questionnaires can facilitate the harmonization of data across HIV and substance use cohorts. Using data from the Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO), we demonstrate how to capitalize on previous linking work with a common linked depression metric across multiple questionnaires. Cohorts were young men who have sex with men (MSM), substance-using MSM, HIV/HCV cocaine users, and HIV-positive patients. We tested for differential item functioning (DIF) by comparing C3PNO cohort data with general population data. We also fit a mixed-effects model for depression, entering HIV-status and recent opioid/heroin use as fixed effects and cohort as a random intercept. Our results suggest a minimal level of DIF between the C3PNO cohorts and general population samples. After linking, descriptive statistics show a wide range of depression score means across cohorts. Our model confirmed an expected positive relationship between substance use and depression, though contrary to expectations, no significant association with HIV status. The study reveals the likely role of cohort differences, associated patient characteristics, study designs, and administration settings.

Harmonizing altered measures in integrative data analysis: A methods analogue study

In the current study, we used an analogue integrative data analysis (IDA) design to test optimal scoring strategies for harmonizing alcohol- and drug-use consequence measures with varying degrees of alteration across four study conditions. We evaluated performance of mean, confirmatory factor analysis (CFA), and moderated nonlinear factor analysis (MNLFA) scores based on traditional indices of reliability (test-retest, internal, and score recovery or parallel forms) and validity. Participants in the analogue study included 854 college students (46% male; 21% African American, 5% Hispanic/Latino, 56% European American) who completed two versions of the altered measures at two sessions, separated by 2 weeks. As expected, mean, CFA, and MNLFA scores all resulted in scales with lower reliability given increasing scale alteration (with less fidelity to formerly developed scales) and shorter scale length. MNLFA and CFA scores, however, showed greater validity than mean scores, demonstrating stronger relationships with external correlates. Implications for measurement harmonization in the context of IDA are discussed.

Integrative Data Analysis of Gender and Ethnic Measurement Invariance in Nicotine Dependence Symptoms

Little research has evaluated whether conflicting evidence for gender and racial/ethnic differences in nicotine dependence (ND) may be attributed to differences in psychometric properties of ND symptoms, particularly for young Hispanic smokers. Inadequate racial/ethnic diversity and limited smoking exposure variability has hampered research in young smokers. We used integrative data analysis (IDA) to pool DSM-IV ND symptom data for current smokers aged 12-25 (N = 20,328) from three nationally representative surveys (1999, 2000 National Surveys on Drug Use and Health (NSDUH) and Wave 1 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Moderated nonlinear factor analysis (MNLFA) tested symptom measurement invariance in the pooled sample containing greater ethnic and smoking exposure variability. There was study noninvariance for most symptoms. NESARC participants were more likely to report tolerance, using larger amounts or for longer periods, inability to cut down/quit, and more time spent smoking at higher levels of ND severity, but reported emotional/physical health problems at lower ND severity. Four symptoms showed gender or race/ethnicity noninvariance, but observed differences were small. An ND severity factor score adjusting for symptom noninvariance related to study membership, gender, and race/ethnicity did not differ substantively from traditional DSM-IV diagnosis and number of endorsed symptoms in estimated gender and race/ethnicity differences in ND. Results were consistent with studies finding minimal gender and racial/ethnic differences in ND, and suggest that symptom noninvariance is not a major contributor to observed differences. Results support IDA as a potentially promising approach for testing novel ND hypotheses not possible in independent studies.

Recovering Predictor-Criterion Relations Using Covariate-Informed Factor Score Estimates

Although it is currently best-practice to directly model latent factors whenever feasible, there remain many situations in which this approach is not tractable. Recent advances in covariate-informed factor score estimation can be used to provide manifest scores that are used in second-stage analysis, but these are currently understudied. Here we extend our prior work on factor score recovery to examine the use of factor score estimates as predictors both in the presence and absence of the same covariates that were used in score estimation. Results show that whereas the relation between the factor score estimates and the criterion are typically well recovered, substantial bias and increased variability is evident in the covariate effects themselves. Importantly, using covariate-informed factor score estimates substantially, and often wholly, mitigates these biases. We conclude with implications for future research and recommendations for the use of factor score estimates in practice.

Advancing the Study of Adolescent Substance Use Through the Use of Integrative Data Analysis

A wealth of information is currently known about the epidemiology, etiology, and evaluation of drug and alcohol use across the life span. Despite this corpus of knowledge, much has yet to be learned. Many factors conspire to slow the pace of future advances in the field of substance use including the need for long-term longitudinal studies of often hard-to-reach subjects who are reporting rare and episodic behaviors. One promising option that might help move the field forward is integrative data analysis (IDA). IDA is a principled set of methodologies and statistical techniques that allow for the fitting of statistical models to data that have been pooled across multiple, independent samples. IDA offers a myriad of potential advantages including increased power, greater coverage of rare behaviors, more rigorous psychometric assessment of theoretical constructs, accelerated developmental time period under study, and enhanced reproducibility. However, IDA is not without limitations and may not be useful in a given application for a variety of reasons. The goal of this article is to describe the advantages and limitations of IDA in the study of individual development over time, particularly as it relates to trajectories of substance use. An empirical example of the measurement of polysubstance use is presented and this article concludes with recommendations for practice.

Improving Factor Score Estimation Through the Use of Observed Background Characteristics

A challenge facing nearly all studies in the psychological sciences is how to best combine multiple items into a valid and reliable score to be used in subsequent modelling. The most ubiquitous method is to compute a mean of items, but more contemporary approaches use various forms of latent score estimation. Regardless of approach, outside of large-scale testing applications, scoring models rarely include background characteristics to improve score quality. The current paper used a Monte Carlo simulation design to study score quality for different psychometric models that did and did not include covariates across levels of sample size, number of items, and degree of measurement invariance. The inclusion of covariates improved score quality for nearly all design factors, and in no case did the covariates degrade score quality relative to not considering the influences at all. Results suggest that the inclusion of observed covariates can improve factor score estimation.

Gender and ethnicity as moderators: Integrative data analysis of multidimensional family therapy randomized clinical trials

This study examined gender and ethnicity as moderators of Multidimensional Family Therapy (MDFT) effectiveness for adolescent drug abuse and illustrated the utility of integrative data analysis (IDA; Bauer & Hussong, 2009) for assessing moderation. By pooling participant data from 5 independent MDFT randomized clinical trials (RCTs), IDA increased power to test moderation. Participants were 646 adolescents receiving treatment for drug use, aged 11 to 17 years (M = 15.31, SD = 1.30), with 19% female (n = 126), 14% (n = 92) European American, 35% (n = 225) Hispanic, and 51% (n = 329) African American. Participants were randomized to MDFT or active comparison treatments, which varied by study. Drug use involvement (i.e., frequency and consequences) was measured at study entry, 6-, and 12-months by a 4-indicator latent variable. Growth curve change parameters from multiple calibration samples were regressed on treatment effects overall and by moderator subgroups. MDFT reduced drug use involvement (p < .05) for all participant groups. Pooled comparison groups reduced drug use involvement only for females and Hispanics (ps < .05). MDFT was more effective than comparisons for males, African Americans, and European Americans (ps <.05; Cohen's d = 1.17, 1.95, and 1.75, respectively). For females and Hispanics, there were no significant differences between MDFT and pooled comparison treatments, Cohen's d = 0.63 and 0.19, respectively. MDFT is an effective treatment for drug use among adolescents of both genders and varied ethnicity with males, African American, and European American non-Hispanic adolescents benefitting most from MDFT.

The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 1 and 2: review and summary of findings

PURPOSE

The NESARC, a "third-generation" psychiatric epidemiologic survey that integrated detailed measures of alcohol and drug use and problems has been the data source for over >850 publications. A comprehensive review of NESARC findings and their implications is lacking.

METHOD

NESARC was a survey of 43,093 participants that covered alcohol, drug and psychiatric disorders, risk factors, and consequences. Wave 1 of the NESARC was conducted in 2001-2002. Three years later, Wave 2 follow-up re-interviews were conducted with 34,653 of the original participants. Scopus and Pubmed were used to search for NESARC papers, which were sorted into topic areas and summarized.

RESULT

The most common disorders were alcohol and posttraumatic stress disorders, and major depression. Females had more internalizing disorders and males had more externalizing disorders, although the preponderance of males with alcohol disorders (the "gender gap") was less pronounced than it was in previous decades. A race/ethnic "paradox" (lower risk among disadvantaged minorities than whites) remains unexplained. Younger participants had higher risk for substance and personality disorders, but not unipolar depressive or anxiety disorders. Psychiatric comorbidity was extensive and often formed latent trans-diagnostic domains. Since 1991-1992, risk for marijuana and prescription drug disorders increased, while smoking decreased, although smoking decreases were less pronounced among those with comorbidity. A nexus of comorbidity, social support, and stress predicted transitions in diagnostic status between Waves 1 and 2. Childhood maltreatment predicted psychopathology. Alcohol and drug use disorders were seldom treated; attitudinal barriers (little perceived need, perceived alcoholism stigma, pessimism about efficacy) were more important in predicting non-treatment than financial barriers.

CONCLUSIONS

Understanding comorbidity and the effects of early stressors will require research incorporating biologic components, e.g., genetic variants and brain imaging. The lack of treatment for alcohol and drug disorders, predicted by attitudinal rather than financial variables, suggests an urgent need for public and professional education to reduce the stigma associated with these disorders and increase knowledge of treatment options.

Measurement of multiple nicotine dependence domains among cigarette, non-cigarette and poly-tobacco users: Insights from item response theory

BACKGROUND

Nicotine dependence (ND) is a key construct that organizes physiological and behavioral symptoms associated with persistent nicotine intake. Measurement of ND has focused primarily on cigarette smokers. Thus, validation of brief instruments that apply to a broad spectrum of tobacco product users is needed.

METHODS

We examined multiple domains of ND in a longitudinal national study of the United States population, the United States National Epidemiological Survey of Alcohol and Related Conditions (NESARC). We used methods based in item response theory to identify and validate increasingly brief measures of ND that included symptoms to assess ND similarly among cigarette, cigar, smokeless, and poly tobacco users.

RESULTS

Confirmatory factor analytic models supported a single, primary dimension underlying symptoms of ND across tobacco use groups. Differential Item Functioning (DIF) analysis generated little support for systematic differences in response to symptoms of ND across tobacco use groups. We established significant concurrent and predictive validity of brief 3- and 5-symptom indices for measuring ND.

CONCLUSIONS

Measuring ND across tobacco use groups with a common set of symptoms facilitates evaluation of tobacco use in an evolving marketplace of tobacco and nicotine products.

What is the evidence for hardening in the cigarette smoking population? Trends in nicotine dependence in the U.S., 2002-2012

BACKGROUND

It is unclear whether declines in cigarette smoking in the U.S. have resulted in a hardened population of "hardcore" smokers. We studied changes in nicotine dependence severity from 2002 to 2012, using data from the National Survey on Drug Use and Health.

METHODS

We used generalized non-linear factor analysis to examine whether individual Nicotine Dependence Syndrome Scale (NDSS) items functioned differently over time, and whether average NDSS scores changed in a sample of 130,637 current smokers. We also examined trends for individual NDSS sub-scales and whether trends were moderated by tobacco consumption and socio-demographic factors.

RESULTS

Consumption levels and dependence severity both declined over the study period. This decline was driven by priority (e.g., avoiding smoke-free locations) and tolerance dimensions of dependence, while drive (e.g., craving and smoking to relieve negative affect) and continuity (e.g., stability) of smoking did not change. Declines for tolerance were greatest among those without serious psychological distress and among middle-aged smokers. Drive and continuity increased among women and low income smokers.

CONCLUSIONS

We did not find evidence of hardening at the population level for smokers in the U.S., 2002-2012. However, there is evidence of hardening when considering drive and continuity-related nicotine dependence among women and low-income smokers, suggesting these sub-groups are experiencing greater severity of craving, smoking to relieve negative affect, and regularity of smoking despite reduced consumption.