Linda Collins
Linda Collins
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Professor of Social and Behavioral Sciences
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Professional overview
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Linda M. Collins is Professor of Global Public Health in the Department of Social and Behavioral Sciences, with a secondary appointment in the Department of Biostatistics. She earned her B.A. in Psychology at the University of Connecticut and her Ph.D. in Quantitative Psychology at the University of Southern California.
Collins’ research interests are focused on the development, dissemination, and application of the multiphase optimization strategy (MOST), a framework for the optimization of behavioral, biobehavioral, and social-structural interventions. The objective of MOST is to improve intervention effectiveness, efficiency, economy, and scalability. She is currently collaborating on research applying MOST in the areas of smoking cessation, the prevention of excessive drinking and risky sex in college students, and HIV services.
Collins’ research has been funded by the National Institute on Drug Abuse, the National Institute on Alcohol Abuse and Alcoholism, and the National Science Foundation, among others. She has given more than 150 presentations on MOST around the world, and her publications have appeared in journals in the fields of behavioral science, quantitative methodology, medicine, and engineering.
Collins has held tenured faculty positions at the University of Southern California and at Penn State University, where she was Distinguished Professor of Human Development and Family Studies and Director of The Methodology Center. She is a Fellow of the American Psychological Association, the Association for Psychological Science, the Society of Behavioral Medicine, and is a past president of the Society of Multivariate Experimental Psychology and the Society for Prevention Research.
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Education
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BA, Psychology, University of Connecticut, Storrs, CTPhD, Quantitative Psychology, University of Southern California, Los Angeles, CA
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Honors and awards
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Fulbright Specialist, National University of Ireland Galway (2018)Pauline Schmitt Russell Distinguished Career Award, Pennsylvania State University’s College of Health and Human Development (2017)Evan G. and Helen G. Pattishall Outstanding Research Achievement Award, Pennsylvania State University’s College of Health and Human Development (2011)President’s Award, Society for Prevention Research (2004)Faculty Scholar Medal for the Social and Behavioral Sciences, Pennsylvania State University (2000)Psychology Department Teacher of the Year, University of Southern California (1992)Psychology Department Mentorship Award, University of Southern California (1991)Society of Multivariate Experimental Psychology Award for Distinguished Early Career Contributions to Multivariate Behavioral Research (1991)
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Areas of research and study
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Behavioral ScienceCost EffectivenessCost-effective Health Programs and PoliciesDissemination and Implementation of Evidence-based Programs
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Publications
Publications
The multiphase optimization strategy (MOST) from a conceptual perspective
Collins, L. (n.d.).Publication year
2023The Multiphase Optimization Strategy (MOST) in Child Maltreatment Prevention Research
AbstractGuastaferro, K., Strayhorn, J. C., & Collins, L. (n.d.).Publication year
2021Journal title
Journal of Child and Family StudiesVolume
30Issue
10Page(s)
2481-2491AbstractEach year hundreds of thousands of children and families receive behavioral interventions designed to prevent child maltreatment; yet rates of maltreatment have not declined in over a decade. To reduce the prevalence and prevent the life-long negative consequences of child maltreatment, behavioral interventions must not only be effective, but also affordable, scalable, and efficient to meet the demand for these services. An innovative approach to intervention science is needed. The purpose of this article is to introduce the multiphase optimization strategy (MOST) to the field of child maltreatment prevention. MOST is an engineering-inspired framework for developing, optimizing, and evaluating multicomponent behavioral interventions. MOST enables intervention scientists to empirically examine the performance of each intervention component, independently and in combination. Using a hypothetical example of a home visiting intervention and artificial data, this article demonstrates how MOST may be used to optimize the content of a parent-focused in-home intervention and the engagement strategies of an intervention to increase completion rate to identify an intervention that is effective, efficient, economical, and scalable. We suggest that MOST will ultimately improve prevention science and hasten the progress of translational science to prevent child maltreatment.The multiphase optimization strategy for developing and evaluating behavioral interventions
AbstractGuastaferro, K., Shenk, C. E., & Collins, L. (n.d.).Publication year
2020Page(s)
267-278AbstractThis chapter introduces the multiphase optimization strategy (MOST), an engineering-inspired framework for optimizing multicomponent behavioral interventions. The chapter contrasts the typical development of interventions with the MOST framework and discusses the potential to achieve steady, systematic progress in intervention science. In contrast to the typical development of a multicomponent intervention wherein the intervention is tested en bloc via a randomized controlled trial (RCT), MOST introduces a phase of optimization prior to the RCT wherein the effect of individual components and the interaction between components is empirically tested. The objective of MOST is to arrive at an optimized intervention that is highly effective, but also efficient, economical, and scalable. This chapter provides an overview of the MOST framework and demonstrates its application using a hypothetical example of the optimization of a clinical intervention targeting posttraumatic stress disorder symptoms among children who have experienced maltreatment.The multiphase optimization strategy for developing and evaluating psychological interventions
AbstractGuastaferro, K., Shenk, C. E., & Collins, L. (n.d.).Publication year
2020Page(s)
267-278Abstract~The multiphase optimization strategy for engineering effective tobacco use interventions
AbstractCollins, L., Baker, T. B., Mermelstein, R. J., Piper, M. E., Jorenby, D. E., Smith, S. S., Christiansen, B. A., Schlam, T. R., Cook, J. W., & Fiore, M. C. (n.d.).Publication year
2011Journal title
Annals of Behavioral MedicineVolume
41Issue
2Page(s)
208-226AbstractThe multiphase optimization strategy (MOST) is a new methodological approach for building, optimizing, and evaluating multicomponent interventions. Conceptually rooted in engineering, MOST emphasizes efficiency and careful management of resources to move intervention science forward steadily and incrementally. MOST can be used to guide the evaluation of research evidence, develop an optimal intervention (the best set of intervention components), and enhance the translation of research findings, particularly type II translation. This article uses an ongoing study to illustrate the application of MOST in the evaluation of diverse intervention components derived from the phase-based framework reviewed in the companion article by Baker et al. (Ann Behav Med, in press, 2011). The article also discusses considerations, challenges, and potential benefits associated with using MOST and similar principled approaches to improving intervention efficacy, effectiveness, and cost-effectiveness. The applicability of this methodology may extend beyond smoking cessation to the development of behavioral interventions for other chronic health challenges.The Positive Emotions after Acute Coronary Events behavioral health intervention : Design, rationale, and preliminary feasibility of a factorial design study
AbstractHuffman, J. C., Albanese, A. M., Campbell, K. A., Celano, C. M., Millstein, R. A., Mastromauro, C. A., Healy, B. C., Chung, W. J., Januzzi, J. L., Collins, L., & Park, E. R. (n.d.).Publication year
2017Journal title
Clinical TrialsVolume
14Issue
2Page(s)
128-139AbstractBackground: Positive psychological constructs, such as optimism, are associated with greater participation in cardiac health behaviors and improved cardiac outcomes. Positive psychology interventions, which target psychological well-being, may represent a promising approach to improving health behaviors in high-risk cardiac patients. However, no study has assessed whether a positive psychology intervention can promote physical activity following an acute coronary syndrome. Objective: In this article we will describe the methods of a novel factorial design study to aid the development of a positive psychology-based intervention for acute coronary syndrome patients and aim to provide preliminary feasibility data on study implementation. Methods: The Positive Emotions after Acute Coronary Events III study is an optimization study (planned N = 128), subsumed within a larger multiphase optimization strategy iterative treatment development project. The goal of Positive Emotions after Acute Coronary Events III is to identify the ideal components of a positive psychology-based intervention to improve post-acute coronary syndrome physical activity. Using a 2 × 2 × 2 factorial design, Positive Emotions after Acute Coronary Events III aims to: (1) evaluate the relative merits of using positive psychology exercises alone or combined with motivational interviewing, (2) assess whether weekly or daily positive psychology exercise completion is optimal, and (3) determine the utility of booster sessions. The study's primary outcome measure is moderate-to-vigorous physical activity at 16 weeks, measured via accelerometer. Secondary outcome measures include psychological, functional, and adherence-related behavioral outcomes, along with metrics of feasibility and acceptability. For the primary study outcome, we will use a mixed-effects model with a random intercept (to account for repeated measures) to assess the main effects of each component (inclusion of motivational interviewing in the exercises, duration of the intervention, and inclusion of booster sessions) from a full factorial model controlling for baseline activity. Similar analyses will be performed on self-report measures and objectively-measured medication adherence over 16 weeks. We hypothesize that the combined positive psychology and motivational interviewing intervention, weekly exercises, and booster sessions will be associated with superior physical activity. Results: Thus far, 78 participants have enrolled, with 72% of all possible exercises fully completed by participants. Conclusion: The Positive Emotions after Acute Coronary Events III study will help to determine the optimal content, intensity, and duration of a positive psychology intervention in post-acute coronary syndrome patients prior to testing in a randomized trial. This study is novel in its use of a factorial design within the multiphase optimization strategy framework to optimize a behavioral intervention and the use of a positive psychology intervention to promote physical activity in high-risk cardiac patients.The proximal association between smoking and alcohol use among first year college students
AbstractDierker, L., Lloyd-Richardson, E., Stolar, M., Flay, B., Tiffany, S., Collins, L., Bailey, S., Nichter, M., Clayton, R., Abrams, D. S., Balster, R., Dahl, R., Giovino, G., Henningfield, J., Koob, G., McMahon, R., Merikangas, K., Shiffman, S., Prager, D., … Stroud, L. (n.d.).Publication year
2006Journal title
Drug and alcohol dependenceVolume
81Issue
1Page(s)
1-9AbstractObjective: This study was undertaken to evaluate the association between patterns of day-to-day smoking and drinking among first year college students. Method: Using 210 days of weekly time-line follow-back diary data, the authors examined the within-person relationships between smoking and drinking. Bivariate time series procedures were utilized. Results: Findings revealed a high degree of significant cross-correlations between smoking and drinking in which the amount of use of one substance could be predicted by current, as well as past and future use of the other. For the majority of participants, smoking and drinking were positively associated with the alternate behavior. The most common pattern of prediction for individuals was within day (i.e. synchronous correlations). When examining rates of individuals showing significant cross-correlations according to their level of either smoking or drinking, those smoking less than one cigarette on average per day were found to be less likely to demonstrate a synchronous cross-correlation between the two behaviors than those smoking at higher rates. No significant association was found between level of drinking and the rate of significant synchronous cross-correlations between smoking and drinking. Conclusions: Reports of daily behavior over long periods of time have the potential to provide insight into the more proximal influences of smoking and alcohol use on one another. Future research is needed to establish the specific factors (i.e. third variables) and related mechanisms that may drive both behaviors.The selection of comparators for randomized controlled trials of health-related behavioral interventions : recommendations of an NIH expert panel
AbstractCollins, L. (n.d.).Publication year
2019Journal title
Journal of Clinical EpidemiologyVolume
110Page(s)
74-81AbstractObjectives: To provide recommendations for the selection of comparators for randomized controlled trials of health-related behavioral interventions. Study Design and Setting: The National Institutes of Health Office of Behavioral and Social Science Research convened an expert panel to critically review the literature on control or comparison groups for behavioral trials and to develop strategies for improving comparator choices and for resolving controversies and disagreements about comparators. Results: The panel developed a Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials. The model indicates that the optimal comparator is the one that best serves the primary purpose of the trial but that the optimal comparator's limitations and barriers to its use must also be taken into account. Conclusion: We developed best practice recommendations for the selection of comparators for health-related behavioral trials. Use of the Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials can improve the comparator selection process and help resolve disagreements about comparator choices.Tobacco dependence treatment in the emergency department : A randomized trial using the Multiphase Optimization Strategy
AbstractBernstein, S. L., Dziura, J., Weiss, J., Miller, T., Vickerman, K. A., Grau, L. E., Pantalon, M. V., Abroms, L., Collins, L., & Toll, B. (n.d.).Publication year
2018Journal title
Contemporary Clinical TrialsVolume
66Page(s)
1-8AbstractBackground: Tobacco dependence remains the leading preventable cause of death in the developed world. Smokers are disproportionately from lower socioeconomic groups, and may use the hospital emergency department (ED) as an important source of care. A recent clinical trial demonstrated the efficacy of a multicomponent intervention to help smokers quit, but the independent contributions of those components is unknown. Methods: This is a full-factorial (16-arm) randomized trial in a busy hospital ED of 4 tobacco dependence interventions: brief motivational interviewing, nicotine replacement therapy, referral to a telephone quitline, and a texting program. The trial utilizes the Multiphase Optimization Strategy (MOST) and a novel mixed methods analytic design to assess clinical efficacy, cost effectiveness, and qualitative participant feedback. The primary endpoint is tobacco abstinence at 3 months, verified by participants' exhaled carbon monoxide. Results: Study enrollment began in February 2017. As of April 2017, 52 of 1056 planned participants (4.9%) were enrolled. Telephone-based semi-structured participant interviews and in-person biochemical verification of smoking abstinence are completed at the 3-month follow-up. Efficacy and cost effectiveness analyses will be conducted after follow-up is completed. Discussion: The goal of this study is to identify a clinically efficacious, cost-effective intervention package for the initial treatment of tobacco dependence in ED patients. The efficacy of this combination can then be tested in a subsequent confirmatory trial. Our approach incorporates qualitative feedback from study participants in evaluating which intervention components will be tested in the future trial. Trial registration: Trial (NCT02896400) registered in ClinicalTrials.gov on September 6, 2016.Tobacco, alcohol, and marijuana use among first-year U.S. college students : A time series analysis
AbstractDierker, L., Stolar, M., Lloyd-Richardson, E., Tiffany, S., Flay, B., Collins, L., Nichter, M., Bailey, S., Clayton, R., Abrams, D. S., Balster, R., Dahl, R., Giovino, G., Henningfield, J., Koob, G., McMahon, R., Merikangas, K., Shiffman, S., Prager, D., … Stroud, L. (n.d.).Publication year
2008Journal title
Substance Use and MisuseVolume
43Issue
5Page(s)
680-699AbstractThe present study sought to evaluate the day-to-day patterns of tobacco, alcohol, and marijuana use among first-year college students in the United States. Using 210 days of weekly time-line follow-back diary data collected in 2002 to 2003, the authors examined within-person patterns of use. The sample was 48% female and 90% Caucasian. Sixty-eight percent of the participants were permanent residents of Indiana. Univariate time series analysis was employed to evaluate behavioral trends for each substance across the academic year and to determine the predictive value of day-to-day substance use. Some of the most common trends included higher levels of substance use at the beginning or end of the academic year. Use on any given day could be predicted best from the amount of corresponding substance use 1 day prior. Conclusions: Although universal intervention might best be focused in the earliest weeks on campus and at the end of the year when substance use is at its highest, the diversity of substance use trajectories suggests the need for more targeted approaches to intervention. Study limitations are noted.Toward precision smoking cessation treatment I : Moderator results from a factorial experiment
AbstractPiper, M. E., Schlam, T. R., Cook, J. W., Smith, S. S., Bolt, D. M., Loh, W. Y., Mermelstein, R., Collins, L., Fiore, M. C., & Baker, T. B. (n.d.).Publication year
2017Journal title
Drug and alcohol dependenceVolume
171Page(s)
59-65AbstractBackground The development of tobacco use treatments that are effective for all smokers is critical to improving clinical and public health. The Multiphase Optimization Strategy (MOST) uses highly efficient factorial experiments to evaluate multiple intervention components for possible inclusion in an optimized tobacco use treatment. Factorial experiments permit analyses of the influence of patient characteristics on main and interaction effects of multiple, relatively discrete, intervention components. This study examined whether person-factor and smoking characteristics moderated the main or interactive effects of intervention components on 26-week self-reported abstinence rates. Methods This fractional factorial experiment evaluated six smoking cessation intervention components among primary care patients (N = 637): Prequit Nicotine Patch vs. None, Prequit Nicotine Gum vs. None, Preparation Counseling vs. None, Intensive Cessation In-Person Counseling vs. Minimal, Intensive Cessation Telephone Counseling vs. Minimal, and 16 vs. 8 Weeks of Combination Nicotine Replacement Therapy (NRT; nicotine patch + nicotine gum). Results Both psychiatric history and smoking heaviness moderated intervention component effects. In comparison with participants with no self-reported history of a psychiatric disorder, those with a positive history showed better response to 16- vs. 8-weeks of combination NRT, but a poorer response to counseling interventions. Also, in contrast to light smokers, heavier smokers showed a poorer response to counseling interventions. Conclusions Heavy smokers and those with psychiatric histories demonstrated a differential response to intervention components. This research illustrates the use of factorial designs to examine the interactions between person characteristics and relatively discrete intervention components. Future research is needed to replicate these findings.Toward precision smoking cessation treatment II : Proximal effects of smoking cessation intervention components on putative mechanisms of action
AbstractPiper, M. E., Cook, J. W., Schlam, T. R., Smith, S. S., Bolt, D. M., Collins, L., Mermelstein, R., Fiore, M. C., & Baker, T. B. (n.d.).Publication year
2017Journal title
Drug and alcohol dependenceVolume
171Page(s)
50-58AbstractBackground Understanding how smoking cessation treatments exert their effects can inform treatment development and use. Factorial designs allow researchers to examine whether multiple intervention components affect hypothesized change mechanisms, and whether the affected mechanisms are related to cessation. Methods This is a secondary data analysis of smokers recruited during primary care visits (N = 637, 55% women, 87% white) who were motivated to quit. Participants in this fractional factorial experiment were randomized to one level of each of six intervention factors: Prequit Nicotine Patch vs None, Prequit Nicotine Gum vs None, Preparation Counseling vs None, Intensive In-Person Counseling vs Minimal, Intensive Phone Counseling vs Minimal, and 16 vs 8 Weeks of Combination Nicotine Replacement (nicotine patch + nicotine gum). Data on putative mechanisms (e.g., medication use, withdrawal, self-efficacy) and smoking status were gathered using daily assessments and during follow-up assessment calls. Results Some intervention components influenced hypothesized mechanisms. Prequit Gum and Patch each reduced prequit smoking and enhanced prequit coping and self-efficacy. In-Person Counseling increased prequit motivation to quit, postquit self-efficacy, and postquit perceived intratreatment support. Withdrawal reduction and reduced prequit smoking produced the strongest effects on cessation. The significant effect of combining Prequit Gum and In-Person Counseling on 26-week abstinence was mediated by increased prequit self-efficacy. Conclusions This factorial experiment identified which putative treatment mechanisms were influenced by discrete intervention components and which mechanisms influenced cessation. Such information supports the combined use of prequit nicotine gum and intensive in-person counseling as cessation interventions that operate via increased prequit self-efficacy.Trajectories of smoking among freshmen college students with prior smoking history and risk for future smoking : Data from the University Project Tobacco Etiology Research Network (UpTERN) study
AbstractColder, C. R., Flay, B. R., Segawa, E., Hedeker, D., Abrams, D. B., Agnew, C., Balster, R. L., Clayton, R. R., Collins, L., Dahl, R. E., Dierker, L. C., Donny, E. C., Dorn, L., Eissenberg, T., Flaherty, B. P., Giovino, G. A., Henningfield, J., Koob, G. F., Liang, L., … Tiffany, S. (n.d.).Publication year
2008Journal title
AddictionVolume
103Issue
9Page(s)
1534-1543AbstractAims: Little is known about smoking during the transition to college. The current study examined trajectories of smoking among college freshmen, how trajectories predicted later smoking and the social context of smoking. Design: Weekly assessments of daily smoking were collected via the web during the first year of college for a large cohort with a previous history of smoking. Participants and setting: A total of 193 college freshmen from a large public university with a previous history of smoking who smoked frequently enough to be included in trajectory analysis. Measurements: Measures included weekly reports of daily smoking, family smoking, perceived peer attitudes and smoking, social norms and social smoking environment. Findings: Seven trajectories were identified: one of low-level sporadic smoking, one of low-level smoking with a small increase during the year, two classes with a substantial decrease during the year, two classes with relatively small decreases and one class with a substantial increase in smoking. Trajectories of smoking in the freshman year predicted levels of sophomore year smoking, and some social context variables tended to change as smoking increased or decreased for a given trajectory class. Conclusions: The transition into college is marked by changes in smoking, with smoking escalating for some students and continuing into the sophomore year. Shifts in social context that support smoking were associated with trajectories of smoking. Despite the focus of developmental models on smoking in early adolescence, the transition into college warrants further investigation as a dynamic period for smoking.Translational Research in South Africa : Evaluating Implementation Quality Using a Factorial Design
AbstractCaldwell, L. L., Smith, E. A., Collins, L., Graham, J. W., Lai, M., Wegner, L., Vergnani, T., Matthews, C., & Jacobs, J. (n.d.).Publication year
2012Journal title
Child and Youth Care ForumVolume
41Issue
2Page(s)
119-136AbstractBackground: HealthWise South Africa: Life Skills for Adolescents (HW) is an evidence-based substance use and sexual risk prevention program that emphasizes the positive use of leisure time. Since 2000, this program has evolved from pilot testing through an efficacy trial involving over 7,000 youth in the Cape Town area. Beginning in 2011, through 2015, we are undertaking a new study that expands HW to all schools in the Metro South Education District. Objective: This paper describes a research study designed in partnership with our South African collaborators that examines three factors hypothesized to affect the quality and fidelity of HW implementation: enhanced teacher training; teacher support, structure and supervision; and enhanced school environment. Methods: Teachers and students from 56 schools in the Cape Town area will participate in this study. Teacher observations are the primary means of collecting data on factors affecting implementation quality. These factors address the practical concerns of teachers and schools related to likelihood of use and cost-effectiveness, and are hypothesized to be "active ingredients" related to high-quality program implementation in real-world settings. An innovative factorial experimental design was chosen to enable estimation of the individual effect of each of the three factors. Results: Because this paper describes the conceptualization of our study, results are not yet available. Conclusions: The results of this study may have both substantive and methodological implications for advancing Type 2 translational research.Twenty years of intervention optimization
AbstractCollins, L., & Collins, L. M. (n.d.).Publication year
2025Journal title
Annals of Behavioral MedicineVolume
59Issue
1Page(s)
kaae076AbstractIn the classical paradigm for intervention research, the components that are to make up an intervention are identified, pilot tested, and then immediately assembled into a treatment package and subjected to an evaluation randomized controlled trial (RCT) to assess the performance of the entire package. Intervention optimization, which adapts ideas from technological fields to intervention science in order to hasten scientific progress, is an alternative to the classical paradigm. The first article introducing intervention optimization via the multiphase optimization strategy (MOST) was published in Annals of Behavioral Medicine in 2005. In this commentary, I reflect on the evolution of intervention optimization from that first publication to today, and on what the future could hold if the intervention science field continues to adopt the optimization paradigm. I propose that if intervention optimization became standard operating procedure, the field would accumulate a coherent base of knowledge about what specific intervention strategies work, for whom, under which circumstances, and why; every intervention produced would contain only components that contribute enough to justify their resource requirements; interventions would be readily implementable; and as the knowledge base grew, interventions would be improved continually.The dominant way of developing evidence-based behavioral and biobehavioral interventions has been to construct the intervention a priori, and then determine via a standard evaluation randomized controlled trial (RCT) whether the intervention as a package has a statistically detectable effect. This approach makes it impossible to assess the performance of individual intervention components. Consequently, when an intervention shows a detectable effect, it is unknown which components were contributing to the effect and whether they are all necessary. Moreover, when an intervention does not show a detectable effect, it is unknown what went wrong and what the next steps should be. Other fields that have made considerable scientific progress in recent decades, such as technological fields, do not operate this way. This commentary discusses a new approach to development of evidence-based behavioral and biobehavioral interventions, namely intervention optimization via the multiphase optimization strategy (MOST). Based on principles drawn from fields such as engineering, economics, decision science, and implementation science, MOST will enable intervention science to hasten its progress. This commentary suggests that if intervention optimization became standard operating procedure, interventions would become more economical and implementable; the scientific knowledge base would expand; and the public health impact of interventions would increase.Twenty years of intervention optimization
AbstractCollins, L. (n.d.).Publication year
2025Journal title
Annals of Behavioral MedicineVolume
59Issue
1AbstractIn the classical paradigm for intervention research, the components that are to make up an intervention are identified, pilot tested, and then immediately assembled into a treatment package and subjected to an evaluation randomized controlled trial (RCT) to assess the performance of the entire package. Intervention optimization, which adapts ideas from technological fields to intervention science in order to hasten scientific progress, is an alternative to the classical paradigm. The first article introducing intervention optimization via the multiphase optimization strategy (MOST) was published in Annals of Behavioral Medicine in 2005. In this commentary, I reflect on the evolution of intervention optimization from that first publication to today, and on what the future could hold if the intervention science field continues to adopt the optimization paradigm. I propose that if intervention optimization became standard operating procedure, the field would accumulate a coherent base of knowledge about what specific intervention strategies work, for whom, under which circumstances, and why; every intervention produced would contain only components that contribute enough to justify their resource requirements; interventions would be readily implementable; and as the knowledge base grew, interventions would be improved continually.Understanding heterogeneity of responses to, and optimizing clinical efficacy of, exercise training in older adults : NIH NIA Workshop summary
AbstractErickson, M. L., Allen, J. M., Beavers, D. P., Collins, L., Davidson, K. W., Erickson, K. I., Esser, K. A., Hesselink, M. K., Moreau, K. L., Laber, E. B., Peterson, C. A., Reusch, J. E., Thyfault, J. P., Youngstedt, S. D., Zierath, J. R., Goodpaster, B. H., LeBrasseur, N. K., Buford, T. W., & Sparks, L. M. (n.d.).Publication year
2022Journal title
GeroScienceAbstractExercise is a cornerstone of preventive medicine and a promising strategy to intervene on the biology of aging. Variation in the response to exercise is a widely accepted concept that dates back to the 1980s with classic genetic studies identifying sequence variations as modifiers of the VO2max response to training. Since that time, the literature of exercise response variance has been populated with retrospective analyses of existing datasets that are limited by a lack of statistical power from technical error of the measurements and small sample sizes, as well as diffuse outcomes, very few of which have included older adults. Prospective studies that are appropriately designed to interrogate exercise response variation in key outcomes identified a priori and inclusive of individuals over the age of 70 are long overdue. Understanding the underlying intrinsic (e.g., genetics and epigenetics) and extrinsic (e.g., medication use, diet, chronic disease) factors that determine robust versus poor responses to various exercise factors will be used to improve exercise prescription to target the pillars of aging and optimize the clinical efficacy of exercise training in older adults. This review summarizes the proceedings of the NIA-sponsored workshop entitled, “Understanding Heterogeneity of Responses to, and Optimizing Clinical Efficacy of, Exercise Training in Older Adults” and highlights the importance and current state of exercise response variation research, particularly in older adults, prevailing challenges, and future directions.Understanding long-term HIV survivorship among African American/Black and Latinx persons living with HIV in the United States : A qualitative exploration through the lens of symbolic violence
AbstractFreeman, R., Gwadz, M., Wilton, L., Collins, L., Dorsen, C., Hawkins, R. L., Silverman, E., Martinez, B. Y., Leonard, N. R., Applegate, A., & Cluesman, S. (n.d.).Publication year
2020Journal title
International Journal for Equity in HealthVolume
19Issue
1AbstractBackground: Persons living with HIV (PLWH) are living longer, although racial/ethnic and socioeconomic status (SES) disparities persist. Yet, little is known about the experience of living with and managing HIV over decades. The present study took a qualitative approach and used the lens of symbolic violence, a type of internalized, non-physical violence manifested in the power differential between social groups. We focused on adult African American/Black and Latinx (AABL) PLWH from low-SES backgrounds. Methods: Data were drawn from two studies with AABL PLWH in New York City (N = 59). After providing signed informed consent, participants engaged in in-depth semi-structured interviews on aspects of HIV management. Interviews were audio-recorded and professionally transcribed verbatim, and data were analyzed using directed qualitative content analysis. Results: Participants in the two studies were comparable on sociodemographic and background characteristics. They had lived with HIV for 20 years, on average (range 3-33 years). All were from low-SES backgrounds and most were African American/Black and men. Participants experienced a convergence of multiple social exclusions, harms, and stigmas, consistent with symbolic violence, which contributed to disengagement from HIV care and discontinuation of HIV medications. We organized results into five sub-themes: (1) participants were "ground down"over time by material, social, and emotional challenges and this diminished self-worth and, at times, the will to live; (2) social isolation and self-isolation, based in part on feeling devalued and dehumanized, served as stigma-avoidance strategies and mechanisms of social exclusion; (3) stigmatizing aspects of patient-provider interactions, both experienced and anticipated, along with (4) restricted autonomy in HIV care and other settings (e.g., parole) reduced engagement; and (5) poor HIV management was internalized as a personal failure. Importantly, resilience was evident throughout the five sub-themes. Conclusions: Symbolic violence is a useful framework for understanding long-term HIV management and survivorship among AABL PLWH from low-SES backgrounds. Indeed, forms of symbolic violence are internalized over time (e.g., experiencing devaluation, dehumanization, loss of self-worth, and anticipated stigma), thereby impeding successful HIV management, in part because avoiding HIV care and discontinuing HIV medications are primary coping strategies. Results have implications for interventions in community and health care settings.Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum : A Machine Learning Approach
AbstractHe, N., Cleland, C. M., Gwadz, M., Sherpa, D., Ritchie, A. S., Martinez, B. Y., & Collins, L. (n.d.).Publication year
2021Journal title
SAGE OpenVolume
11Issue
4AbstractMedical distrust is a potent barrier to participation in HIV care and medication use among African American/Black and Latino (AABL) persons living with HIV (PLWH). However, little is known about sociodemographic and risk factors associated with distrust. We recruited adult AABL PLWH from low socio-economic status backgrounds with insufficient engagement in HIV care (N = 512). Participants completed structured assessments on three types of distrust (of health care providers, health care systems, and counter-narratives), HIV history, and mental health. We used a type of machine learning called random forest to explore predictors of trust. On average, participants were 47 years old (SD = 11 years), diagnosed with HIV 18 years prior (SD = 9 years), and mainly male (64%) and African American/Black (69%). Depression and age were the most important predictors of trust. Among those with elevated depressive symptoms, younger participants had less trust than older, while among those without depression, trust was greater across all ages. The present study adds nuance to the literature on medical distrust among AABL PLWH and identifies junctures where interventions to build trust are needed most.Using data augmentation to obtain standard errors and conduct hypothesis tests in latent class and latent transition analysis
AbstractLanza, S. T., Collins, L., Schafer, J. L., & Flaherty, B. P. (n.d.).Publication year
2005Journal title
Psychological MethodsVolume
10Issue
1Page(s)
84-100AbstractLatent class analysis (LCA) provides a means of identifying a mixture of subgroups in a population measured by multiple categorical indicators. Latent transition analysis (LTA) is a type of LCA that facilitates addressing research questions concerning stage-sequential change over time in longitudinal data. Both approaches have been used with increasing frequency in the social sciences. The objective of this article is to illustrate data augmentation (DA), a Markov chain Monte Carlo procedure that can be used to obtain parameter estimates and standard errors for LCA and LTA models. By use of DA it is possible to construct hypothesis tests concerning not only standard model parameters but also combinations of parameters, affording tremendous flexibility. DA is demonstrated with an example involving tests of ethnic differences, gender differences, and an Ethnicity X Gender interaction in the development of adolescent problem behavior.Using decision analysis for intervention value efficiency to select optimized interventions in the multiphase optimization strategy.
AbstractCollins, L., Strayhorn, J. C., Cleland, C. M., Vanness, D. J., Wilton, L., Gwadz, M., & Collins, L. M. (n.d.).Publication year
2024Journal title
Health PsychologyVolume
43Issue
2Page(s)
89-100Abstract~Using engineering control principles to inform the design of adaptive interventions : A conceptual introduction
AbstractRivera, D. E., Pew, M. D., & Collins, L. (n.d.).Publication year
2007Journal title
Drug and alcohol dependenceVolume
88Issue
SUPPL. 2Page(s)
S31-S40AbstractThe goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.Using factorial mediation analysis to better understand the effects of interventions
AbstractStrayhorn, J. C., Collins, L., Brick, T. R., Marchese, S. H., Pfammatter, A. F., Pellegrini, C., & Spring, B. (n.d.).Publication year
2022Journal title
Translational Behavioral MedicineVolume
12Issue
1Page(s)
84-89AbstractTo improve understanding of how interventions work or why they do not work, there is need for methods of testing hypotheses about the causal mechanisms underlying the individual and combined effects of the components that make up interventions. Factorial mediation analysis, i.e., mediation analysis applied to data from a factorial optimization trial, enables testing such hypotheses. In this commentary, we demonstrate how factorial mediation analysis can contribute detailed information about an intervention's causal mechanisms. We briefly review the multiphase optimization strategy (MOST) and the factorial experiment. We use an empirical example from a 25 factorial optimization trial to demonstrate how factorial mediation analysis opens possibilities for better understanding the individual and combined effects of intervention components. Factorial mediation analysis has important potential to advance theory about interventions and to inform intervention improvements.Using growth models to relate acquisition of nicotine self-administration to break point and nicotinic receptor binding
AbstractDonny, E. C., Lanza, S. T., Balster, R. L., Collins, L., Caggiula, A., & Rowell, P. P. (n.d.).Publication year
2004Journal title
Drug and alcohol dependenceVolume
75Issue
1Page(s)
23-35AbstractGrowth modeling can be used to characterize individual and mean acquisition trajectories for drug self-administration. Individual characteristics can also be incorporated into the growth model, providing a powerful tool for investigating the relationship between acquisition and other behavioral and biological measures. We illustrate the utility of this method by examining the relationship between acquisition of nicotine self-administration and (1) break point on a progressive ratio schedule of reinforcement, and (2) the density of brain nicotinic receptors (Bmax). Daily infusion rates from male and female Sprague-Dawley rats were modeled with break point or Bmax as time-invariant covariates. Use of this model led to two novel findings regarding individual differences in acquisition. First, greater rates of change in infusions early in acquisition were related to higher break points; this relationship was mediated by a similar effect of increasing the number of responses required to obtain nicotine. Second, animals displaying more resistance to increases in the response requirement during acquisition, as indicated by a smaller drop in the rate of nicotine self-administration, generally had fewer nicotinic receptors at the end of the experiment. The relationships revealed demonstrate the usefulness of growth models in the quantitative analysis of individual differences in drug self-administration behavior.Using the Longitudinal Guttman Simplex as a Basis for Measuring Growth
AbstractCollins, L., & Cliff, N. (n.d.).Publication year
1990Journal title
Psychological bulletinVolume
108Issue
1Page(s)
128-134AbstractMany difficulties inherent in the measurement of growth stem from the use of traditional measurement methodologies. The longitudinal Guttman simplex (LGS), an alternative approach based on a model of growth, is discussed in this article. The LGS has several advantages over traditional methodology. First, interindividual differences in developmental rates are a part of the model. Second, the LGS procedure can easily handle any number of occasions of measurement. Third, the LGS is suited to nonlinear as well as linear monotonic growth. Fourth, a consistency index associated with the LGS methodology, CL, indicates the extent to which cumulative, unitary development characterizes a particular latent variable. Finally, and perhaps most important, because a model of the growth undergone by the latent variable being measured is incorporated in the LGS model the resulting instruments enjoy a high level of construct validity. The LGS is limited to cumulative, unitary development; additional measurement theories are needed for other kinds of development.