28 research outputs found

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

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    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

    Your Path to Transplant: A randomized controlled trial of a tailored computer education intervention to increase living donor kidney transplant

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    Background: Because of the deceased donor organ shortage, more kidney patients are considering whether to receive kidneys from family and friends, a process called living donor kidney transplantation (LDKT). Although Blacks and Hispanics are 3.4 and 1.5 times more likely, respectively, to develop end stage renal disease (ESRD) than Whites, they are less likely to receive LDKTs. To address this disparity, a new randomized controlled trial (RCT) will assess whether Black, Hispanic, and White transplant patients’ knowledge, readiness to pursue LDKT, and receipt of LDKTs can be increased when they participate in the Your Path to Transplant (YPT) computer-tailored intervention. Methods/Design: Nine hundred Black, Hispanic, and White ESRD patients presenting for transplant evaluation at University of California, Los Angeles Kidney and Pancreas Transplant Program (UCLA-KPTP) will be randomly assigned to one of two education conditions, YPT or Usual Care Control Education (UC). As they undergo transplant evaluation, patients in the YPT condition will receive individually-tailored telephonic coaching sessions, feedback reports, video and print transplant education resources, and assistance with reducing any known socioeconomic barriers to LDKT. Patients receiving UC will only receive transplant education provided by UCLA-KPTP. Changes in transplant knowledge, readiness, pros and cons, and self-efficacy to pursue LDKT will be assessed prior to presenting at the transplant center (baseline), during transplant evaluation, and 4- and 8-months post-baseline, while completion of transplant evaluation and receipt of LDKTs will be assessed at 18-months post-baseline. The RCT will determine, compared to UC, whether Black, Hispanic, and White patients receiving YPT increase in their readiness to pursue LDKT and transplant knowledge, and become more likely to complete transplant medical evaluation and pursue LDKT. It will also examine how known patient, family, and healthcare system barriers to LDKT act alone and in combination with YPT to affect patients’ transplant decision-making and behavior. Statistical analyses will be performed under an intent-to-treat approach. Discussion: At the conclusion of the study, we will have assessed the effectiveness of an innovative and cost-effective YPT intervention that could be utilized to tailor LDKT discussion and education based on the needs of individual patients of different races in many healthcare settings. Trial Registration: ClinicalTrials.gov, number NCT02181114

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

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    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

    Extending Theory-Based Quantitative Predictions to New Health Behaviors

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    Background Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. Purpose A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. Method This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Results Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Conclusion Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data
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