A Tribute to the Mind, Methodology and Mentoring of Wayne Velicer.

Wayne Velicer is remembered for a mind where mathematical concepts and calculations intrigued him, behavioral science beckoned him, and people fascinated him. Born in Green Bay, Wisconsin on March 4, 1944, he was raised on a farm, although early influences extended far beyond that beginning. His Mathematics BS and Psychology minor at Wisconsin State University in Oshkosh, and his PhD in Quantitative Psychology from Purdue led him to a fruitful and far-reaching career. He was honored several times as a high-impact author, was a renowned scholar in quantitative and health psychology, and had more than 300 scholarly publications and 54,000+ citations of his work, advancing the arenas of quantitative methodology and behavioral health. In his methodological work, Velicer sought out ways to measure, synthesize, categorize, and assess people and constructs across behaviors and time, largely through principal components analysis, time series, and cluster analysis. Further, he and several colleagues developed a method called Testing Theory-based Quantitative Predictions, successfully applied to predicting outcomes and effect sizes in smoking cessation, diet behavior, and sun protection, with the potential for wider applications. With $60,000,000 in external funding, Velicer also helped engage a large cadre of students and other colleagues to study methodological models for a myriad of health behaviors in a widely applied Transtheoretical Model of Change. Unwittingly, he has engendered indelible memories and gratitude to all who crossed his path. Although Wayne Velicer left this world on October 15, 2017 after battling an aggressive cancer, he is still very present among us.

The Brief Situational Confidence Questionnaire for alcohol: A psychometric assessment with incarcerated youth.

The factor structure, measurement invariance, validity, reliability, and stability of scores on the Brief Situational Confidence Questionnaire (BSCQ) were evaluated for use with incarcerated youth. The BSCQ is an 8-item measure that assesses self-efficacy to resist alcohol use in tempting situations. The brevity of the measure may make it a useful tool for clinicians and researchers in a forensic setting. Analyses were conducted with 2 separate samples (N = 205 and N = 189) of incarcerated youth (M age = 16.90 and 17.12 years, respectively; 88% and 86% male). Based on prior theory and confirmatory factor analyses (CFAs), results indicated that a correlated 2-factor model best fit the data. Multisample CFAs suggested that BSCQ scores demonstrated configural and metric invariance across our 2 samples. Further, the BSCQ scores demonstrated sufficient test-retest stability in Samples 1 and 2 (Pearson's r = .66, .55) and internal consistency (Cronbach's α = .84 and .86, respectively). Negative binomial regressions showed that the overall BSCQ scores were significantly associated with concurrent alcohol use (number of drinking days, number of heavy drinking days, average drinks per week) and significantly predicted future alcohol use. Scores on the BSCQ demonstrated sufficient stability, internal consistency, and validity, and the 2-factor structure was largely invariant across 2 separate samples of incarcerated youth. Given its brevity, the BSCQ may provide valid and reliable scores to use with this population when time and resources are scarce. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Longitudinal analysis of intervention effects on temptations and stages of change for dietary fat using parallel process latent growth modeling.

The Dietary Guidelines for Americans recommend a 20-35 percent daily intake of fat. Resisting the temptation to eat high-fat foods, in conjunction with stage of readiness to avoid these foods, has been shown to influence healthy behavior change. Data ( N = 6516) from three randomized controlled trials were pooled to examine the relationships among direct intervention effects on temptations and stage of change for limiting high-fat foods. Findings demonstrate separate simultaneous growth processes in which baseline level of temptations, but not the rate of change in temptations, was significantly related to the change in readiness to avoid high-fat foods.

Keep Your Stats in the Cloud! Evaluating the Use of Google Sheets to Teach Quantitative Methods.

Teaching quantitative methods at the undergraduate level is a difficult yet rewarding endeavor due to the challenges instructors face in presenting the material. One way to bolster student learning is through the use of statistical software packages. Google Sheets is a cloud-based spreadsheet program capable of many basic statistical procedures, which has yet to be evaluated for use in quantitative methods courses. This article contains pros and cons to using Google Sheets in the classroom, and provides an evaluation of student attitudes towards using Google Sheets in an introductory quantitative methods class. The results suggest favorable student attitudes towards Google Sheets and, that attitudes towards Google Sheets show a positive relationship with quantitative self-efficacy. Thus, based on the positive student attitudes and the unique features of Google Sheets, it is a viable program to use in introductory methods classes. However, due to limited functionality, Google Sheets may not be useful for more advanced courses. Future research may want to evaluate the use of third-party Google Sheets applications, which can increase functionality, and the use of Google Sheets in online classes.

A readability analysis of online mental health resources.

Analyzing the reading grade level of online mental health information is an important first step in ensuring that information is largely accessible by the general public, so as not to perpetuate existing health disparities across socioeconomic groups. The present study systematically examined grade-level readability of mental health information related to various psychiatric diagnoses, obtained from 6 highly utilized mental health websites, using a generalized estimating equations approach. Results suggest that, in general, the readability of mental health information is largely well above the 6th-to-8th grade level recommended by several national health organizations, including the CDC and NIH (Kutner, Greenberg, Jin, & Paulsen, 2006; National Institutes of Health, 2001, 2017), with reading-grade-level estimates from the model ranging from 5.62 to 17.9. Further efforts are required to ensure that writers of online health information do not exacerbate existing health disparities by ignoring these guidelines. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Creation and validation of the barriers to alcohol reduction (BAR) scale using classical test theory and item response theory.

Those who binge drink are at increased risk for alcohol-related consequences when compared to non-binge drinkers. Research shows individuals may face barriers to reducing their drinking behavior, but few measures exist to assess these barriers. This study created and validated the Barriers to Alcohol Reduction (BAR) scale. Participants were college students (n = 230) who endorsed at least one instance of past-month binge drinking (4+ drinks for women or 5+ drinks for men). Using classical test theory, exploratory structural equation modeling found a two-factor structure of personal/psychosocial barriers and perceived program barriers. The sub-factors, and full scale had reasonable internal consistency (i.e., coefficient omega = 0.78 (personal/psychosocial), 0.82 (program barriers), and 0.83 (full measure)). The BAR also showed evidence for convergent validity with the Brief Young Adult Alcohol Consequences Questionnaire (r = 0.39, p < .001) and discriminant validity with Barriers to Physical Activity (r = -0.02, p = .81). Item Response Theory (IRT) analysis showed the two factors separately met the unidimensionality assumption, and provided further evidence for severity of the items on the two factors. Results suggest that the BAR measure appears reliable and valid for use in an undergraduate student population of binge drinkers. Future studies may want to re-examine this measure in a more diverse sample.

Modeling multiple health behaviors and general health.

Multiple Health Behavior Change assumes health behaviors are related to one another, although research evidence is mixed. More research is needed to understand which behaviors are most closely related and how they collectively predict health. Principle component analysis and structural equation modeling were used to establish a model showing relations between health behaviors, including fruit/vegetable consumption, aerobic and strength exercise, alcohol intake, and smoking, and how these behaviors relate to general physical and mental health functioning in a large, national sample. Although health behaviors were found to coalesce into a health-promoting factor of diet, and exercise, a better overall model fit was found when all behaviors were modeled as separate independent variables. Results suggest that health behaviors relate to one another in complex ways, with perceived health status serving as a mediating variable between specific health behaviors and a factor of physical and mental health. Future research should further investigate how other health behaviors relate to perceptions and overall health, especially among subpopulations.

Reporting Practices and Use of Quantitative Methods in Canadian Journal Articles in Psychology.

With recent focus on the state of research in psychology, it is essential to assess the nature of the statistical methods and analyses used and reported by psychological researchers. To that end, we investigated the prevalence of different statistical procedures and the nature of statistical reporting practices in recent articles from the four major Canadian psychology journals. The majority of authors evaluated their research hypotheses through the use of analysis of variance (ANOVA), t-tests, and multiple regression. Multivariate approaches were less common. Null hypothesis significance testing remains a popular strategy, but the majority of authors reported a standardized or unstandardized effect size measure alongside their significance test results. Confidence intervals on effect sizes were infrequently employed. Many authors provided minimal details about their statistical analyses and less than a third of the articles presented on data complications such as missing data and violations of statistical assumptions. Strengths of and areas needing improvement for reporting quantitative results are highlighted. The paper concludes with recommendations for how researchers and reviewers can improve comprehension and transparency in statistical reporting.

Cluster reduction in patients in a pilot treatment trial for psychogenic nonepileptic seizures.

INTRODUCTION: The present study examined seizure clusters as a primary outcome in patients receiving treatment for PNES. Cluster reduction is examined longitudinally using frequency threshold and statistical definitions of seizure cluster for patients. Possible risk factors for clustering will be examined along with clustering as a risk factor for poorer secondary outcomes. METHODS: Participants were from a pilot randomized treatment trial for PNES where they received cognitive behavioral therapy-informed psychotherapy (CBT-ip), sertraline, combination therapy, or treatment as usual. Seizure data are from patients' seizure dairies. RESULTS: Cluster reduction was observed for those receiving CBT-ip or combination treatment using all definitions of daily clusters and weekly clusters. No risk factors of clustering were observed. Those who were identified as having clusters during the trial had poorer secondary outcomes on several measures at baseline relative to those who were not identified as having clusters. DISCUSSION: This is the first study known to the authors to not only examined seizure clusters as a primary outcome for those with PNES, but also the first study to suggest that CBT-ip and combination therapy may be effective in reducing the frequency of clusters.

Identifying seizure clusters in patients with psychogenic nonepileptic seizures.

The present study explored how seizure clusters may be defined for those with psychogenic nonepileptic seizures (PNES), a topic for which there is a paucity of literature. The sample was drawn from a multisite randomized clinical trial for PNES; seizure data are from participants' seizure diaries. Three possible cluster definitions were examined: 1) common clinical definition, where ≥3 seizures in a day is considered a cluster, along with two novel statistical definitions, where ≥3 seizures in a day are considered a cluster if the observed number of seizures statistically exceeds what would be expected relative to a patient's: 1) average seizure rate prior to the trial, 2) observed seizure rate for the previous seven days. Prevalence of clusters was 62-68% depending on cluster definition used, and occurrence rate of clusters was 6-19% depending on cluster definition. Based on these data, clusters seem to be common in patients with PNES, and more research is needed to identify if clusters are related to triggers and outcomes.

Intervention Effects on Stage of Change Membership and Transitions among Adolescent Energy Balance Behaviors.

The transition from childhood to adolescence is a crucial period for the development of healthy behaviors to be sustained later in life. With obesity a leading public health problem, the promotion of healthy behaviors has the potential to make a huge impact. The current study evaluated Stage of Change progression in a large (N = 4158) computer-delivered, Transtheoretical Model-tailored intervention focusing on physical activity and fruit and vegetable consumption (FV). Markov models were used to explore stage transitions and patterns of discrete change from sixth to ninth grade. Nested model comparisons examined the consistency of these patterns across time and intervention condition. Major findings supported models in which participants were free to transition forward and backward to any of the stages, but higher probabilities were observed for remaining in the same stage or for transitioning one or two stages forward. Participants in the intervention group had higher probabilities of transitioning toward Maintenance, with more change occurring relative to the comparison group during transitions from grades six to eight but not for grades eight to nine.

The making of Psychological Methods.

Psychological Methods celebrated its 20-year anniversary recently, having published its first quarterly issue in March 1996. It seemed time to provide a brief overview of the history, the highlights over the years, and the current state of the journal, along with tips for submissions. The article is organized to discuss (a) the background and development of the journal; (b) the top articles, authors, and topics over the years; (c) an overview of the journal today; and (d) a summary of the features of successful articles that usually entail rigorous and novel methodology described in clear and understandable writing and that can be applied in meaningful and relevant areas of psychological research. (PsycINFO Database Record

Big data in psychology: Introduction to the special issue.

The introduction to this special issue on psychological research involving big data summarizes the highlights of 10 articles that address a number of important and inspiring perspectives, issues, and applications. Four common themes that emerge in the articles with respect to psychological research conducted in the area of big data are mentioned, including: (a) The benefits of collaboration across disciplines, such as those in the social sciences, applied statistics, and computer science. Doing so assists in grounding big data research in sound theory and practice, as well as in affording effective data retrieval and analysis. (b) Availability of large data sets on Facebook, Twitter, and other social media sites that provide a psychological window into the attitudes and behaviors of a broad spectrum of the population. (c) Identifying, addressing, and being sensitive to ethical considerations when analyzing large data sets gained from public or private sources. (d) The unavoidable necessity of validating predictive models in big data by applying a model developed on 1 dataset to a separate set of data or hold-out sample. Translational abstracts that summarize the articles in very clear and understandable terms are included in Appendix A, and a glossary of terms relevant to big data research discussed in the articles is presented in Appendix B. (PsycINFO Database Record

Increasing Literacy in Quantitative Methods: The Key to the Future of Canadian Psychology.

Quantitative methods (QM) dominate empirical research in psychology. Unfortunately most researchers in psychology receive inadequate training in QM. This creates a challenge for researchers who require advanced statistical methods to appropriately analyze their data. Many of the recent concerns about research quality, replicability, and reporting practices are directly tied to the problematic use of QM. As such, improving quantitative literacy in psychology is an important step towards eliminating these concerns. The current paper will include two main sections that discuss quantitative challenges and opportunities. The first section discusses training and resources for students and presents descriptive results on the number of quantitative courses required and available to graduate students in Canadian psychology departments. In the second section, we discuss ways of improving quantitative literacy for faculty, researchers, and clinicians. This includes a strong focus on the importance of collaboration. The paper concludes with practical recommendations for improving quantitative skills and literacy for students and researchers in Canada.

A Meta-View of Multivariate Statistical Inference Methods in European Psychology Journals.

We investigated the extent and nature of multivariate statistical inferential procedures used in eight European psychology journals covering a range of content (i.e., clinical, social, health, personality, organizational, developmental, educational, and cognitive). Multivariate methods included those found in popular texts that focused on prediction, group difference, and advanced modeling: multiple regression, logistic regression, analysis of covariance, multivariate analysis of variance, factor or principal component analysis, structural equation modeling, multilevel modeling, and other methods. Results revealed that an average of 57% of the articles from these eight journals involved multivariate analyses with a third using multiple regression, 17% using structural modeling, and the remaining methods collectively comprising about 50% of the analyses. The most frequently occurring inferential procedures involved prediction weights, dichotomous p values, figures with data, and significance tests with very few articles involving confidence intervals, statistical mediation, longitudinal analyses, power analysis, or meta-analysis. Contributions, limitations and future directions are discussed.

Associations of Sexual Victimization, Depression, and Sexual Assertiveness with Unprotected Sex: A Test of the Multifaceted Model of HIV Risk Across Gender.

This study examined whether the Multifaceted Model of HIV Risk (MMOHR) would predict unprotected sex based on predictors including gender, childhood sexual abuse (CSA), sexual victimization (SV), depression, and sexual assertiveness for condom use. A community-based sample of 473 heterosexually active men and women, aged 18-46 years completed survey measures of model variables. Gender predicted several variables significantly. A separate model for women demonstrated excellent fit, while the model for men demonstrated reasonable fit. Multiple sample model testing supported the use of MMOHR in both men and women, while simultaneously highlighting areas of gender difference. Prevention interventions should focus on sexual assertiveness, especially for CSA and SV survivors, as well as targeting depression, especially among men.

Applying the transtheoretical model to ethnically diverse women at risk for HIV.

The purpose of this study is to compare the reliability and predictability of transtheoretical model (TTM) constructs when applied to minority and White women at risk for HIV. Participants consisted of 332 women, including Blacks, Asians, Hispanics, Native Americans, other non-Whites, and Whites. The results supported the reliability and validity of the TTM variables for minority women as well as for White women. Hierarchical multiple regressions demonstrated that TTM variables were able to predict over and above demographic variables. Structural equation models indicate strong support for a mediational model in which the pros and cons predict condom stage of change and unprotected sex though the mediation of self-efficacy. This study provides strong support for TTM scales applied to minority as well as White women at risk for HIV. The authors discuss how these variables might be incorporated into interventions aimed at increasing condom use in minority women.

A measurement model of women's behavioral risk taking.

The current study was designed to gain a better understanding of the nature of the relationship between substance use and sexual risk taking within a community sample of women (N = 1,004). Using confirmatory factor analysis, the authors examined the factor structure of sexual risk behaviors and substance use to determine whether they are best conceptualized as domains underlying a single, higher order, risk-taking propensity. A 2 higher order factor model (sexual risk behavior and substance use) provided the best fit to the data, suggesting that these 2 general risk domains are correlated but independent factors. Sensation seeking had large general direct effects on the 2 risk domains and large indirect effects on the 4 first-order factors and the individual indicators. Negative affect had smaller, yet still significant, effects. Impulsivity and anxiety were unrelated to sexual health risk domains.