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 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.A randomized controlled trial of an optimized smoking treatment delivered in primary care
AbstractPiper, M. E., Cook, J. W., Schlam, T. R., Jorenby, D. E., Smith, S. S., Collins, L., Mermelstein, R., Fraser, D., Fiore, M. C., & Baker, T. B. (n.d.).Publication year
2018Journal title
Annals of Behavioral MedicineVolume
52Issue
10Page(s)
854-864AbstractBackground: The effectiveness of smoking cessation treatment is limited in real-world use, perhaps because we have not selected the components of such treatments optimally nor have treatments typically been developed for and evaluated in real-world clinical settings.Purpose: To validate an optimized smoking cessation treatment package that comprises intervention components identified as effective in factorial screening experiments conducted as per the Multiphase Optimization Strategy (MOST).Methods: Adult smokers motivated to quit were recruited from primary care clinics (N = 623). Participants were randomized to receive either recommended usual care (R-UC; 10 min of in-person counseling, 8 weeks of nicotine patch, and referral to quitline services) or abstinence-optimized treatment (A-OT; 3 weeks of prequit mini-lozenges, 26 weeks of nicotine patch + mini-lozenges, three in-person and eight phone counseling sessions, and 7-11 automated calls to prompt medication use). The key outcomes were self-reported and biochemically confirmed (carbon monoxide, COHealthy Campus Trial : A multiphase optimization strategy (MOST) fully factorial trial to optimize the smartphone cognitive behavioral therapy (CBT) app for mental health promotion among university students: Study protocol for a randomized controlled trial
AbstractUwatoko, T., Luo, Y., Sakata, M., Kobayashi, D., Sakagami, Y., Takemoto, K., Collins, L., Watkins, E., Hollon, S. D., Wason, J., Noma, H., Horikoshi, M., Kawamura, T., Iwami, T., & Furukawa, T. A. (n.d.).Publication year
2018Journal title
TrialsVolume
19Issue
1AbstractBACKGROUND: Youth in general and college life in particular are characterized by new educational, vocational, and interpersonal challenges, opportunities, and substantial stress. It is estimated that 30-50% of university students meet criteria for some mental disorder, especially depression, in any given year. The university has traditionally provided many channels to promote students' mental health, but until now only a minority have sought such help, possibly owing to lack of time and/or to stigma related to mental illness. Smartphone-delivered cognitive behavioral therapy (CBT) shows promise for its accessibility and effectiveness. However, its most effective components and for whom it is more (or less) effective are not known.METHODS/DESIGN: Based on the multiphase optimization strategy framework, this study is a parallel-group, multicenter, open, fully factorial trial examining five smartphone-delivered CBT components (self-monitoring, cognitive restructuring, behavioral activation, assertion training, and problem solving) among university students with elevated distress, defined as scoring 5 or more on the Patient Health Questionnaire-9 (PHQ-9). The primary outcome is change in PHQ-9 scores from baseline to week 8. We will estimate specific efficacy of the five components and their interactions through the mixed-effects repeated-measures analysis and propose the most effective and efficacious combinations of components. Effect modification by selected baseline characteristics will be examined in exploratory analyses.DISCUSSION: The highly efficient experimental design will allow identification of the most effective components and the most efficient combinations thereof among the five components of smartphone CBT for university students. Pragmatically, the findings will help make the most efficacious CBT package accessible to a large number of distressed university students at reduced cost; theoretically, they will shed light on the underlying mechanisms of CBT and help further advance CBT for depression.TRIAL REGISTRATION: UMIN, CTR-000031307 . Registered on February 14, 2018.Just-in-time adaptive interventions (JITAIs) in mobile health : Key components and design principles for ongoing health behavior support
AbstractNahum-Shani, I., Smith, S. N., Spring, B. J., Collins, L., Witkiewitz, K., Tewari, A., & Murphy, S. A. (n.d.).Publication year
2018Journal title
Annals of Behavioral MedicineVolume
52Issue
6Page(s)
446-462AbstractBackground: The just-in-time adaptive intervention (JITAI) is an intervention design aiming to provide the right type/amount of support, at the right time, by adapting to an individual's changing internal and contextual state. The availability of increasingly powerful mobile and sensing technologies underpins the use of JITAIs to support health behavior, as in such a setting an individual's state can change rapidly, unexpectedly, and in his/her natural environment.Purpose: Despite the increasing use and appeal of JITAIs, a major gap exists between the growing technological capabilities for delivering JITAIs and research on the development and evaluation of these interventions. Many JITAIs have been developed with minimal use of empirical evidence, theory, or accepted treatment guidelines. Here, we take an essential first step towards bridging this gap.Methods: Building on health behavior theories and the extant literature on JITAIs, we clarify the scientific motivation for JITAIs, define their fundamental components, and highlight design principles related to these components. Examples of JITAIs from various domains of health behavior research are used for illustration.Conclusions: As we enter a new era of technological capacity for delivering JITAIs, it is critical that researchers develop sophisticated and nuanced health behavior theories capable of guiding the construction of such interventions. Particular attention has to be given to better understanding the implications of providing timely and ecologically sound support for intervention adherence and retention.Multilevel factorial designs with experiment-induced clustering
AbstractNahum-Shani, I., Dziak, J. J., & Collins, L. (n.d.).Publication year
2018Journal title
Psychological MethodsVolume
23Issue
3Page(s)
458-479AbstractFactorial experimental designs have many applications in the behavioral sciences. In the context of intervention development, factorial experiments play a critical role in building and optimizing high-quality, multicomponent behavioral interventions. One challenge in implementing factorial experiments in the behavioral sciences is that individuals are often clustered in social or administrative units and may be more similar to each other than to individuals in other clusters. This means that data are dependent within clusters. Power planning resources are available for factorial experiments in which the multilevel structure of the data is due to individuals' membership in groups that existed before experimentation. However, in many cases clusters are generated in the course of the study itself. Such experiment-induced clustering (EIC) requires different data analysis models and power planning resources from those available for multilevel experimental designs in which clusters exist prior to experimentation. Despite the common occurrence of both experimental designs with EIC and factorial designs, a bridge has yet to be built between EIC and factorial designs. Therefore, resources are limited or nonexistent for planning factorial experiments that involve EIC. This article seeks to bridge this gap by extending prior models for EIC, developed for single-factor experiments, to factorial experiments involving various types of EIC. We also offer power formulas to help investigators decide whether a particular experimental design involving EIC is feasible. We demonstrate that factorial experiments can be powerful and feasible even with EIC. We discuss design considerations and directions for future research. (PsycINFO Database RecordOptimization of a technology-supported physical activity intervention for breast cancer survivors : Fit2Thrive study protocol
AbstractPhillips, S. M., Collins, L., Penedo, F. J., Courneya, K. S., Welch, W., Cottrell, A., Lloyd, G. R., Gavin, K., Cella, D., Ackermann, R. T., Siddique, J., & Spring, B. (n.d.).Publication year
2018Journal title
Contemporary Clinical TrialsVolume
66Page(s)
9-19AbstractFit2Thrive is a theory-guided physical activity promotion trial using the Multiphase Optimization Strategy (MOST) to test efficacy for improving physical activity of five technology-supported physical activity promotion intervention components among breast cancer survivors. This trial will recruit 256 inactive breast cancer survivors nationwide. All participants will receive the core intervention which includes a Fitbit and standard self-monitoring Fit2Thrive smartphone application which will be downloaded to their personal phone. Women will be randomized to one of 32 conditions in a factorial design involving five factors with two levels: support calls (No vs. Yes), app type (standard vs. deluxe), text messaging (No vs. Yes), online gym (No vs. Yes) and Fitbit Buddy (No vs. Yes). The proposed trial examines the effects of the components on physical activity at 12 and 24 weeks. Results will support the selection of a final package of intervention components that has been optimized to maximize physical activity and is subject to an upper limit of cost. The optimized intervention will be tested in a future trial. Fit2Thrive is the first trial to use the MOST framework to develop and test a physical activity promotion intervention in breast cancer survivors and will lead to an improved understanding of how to effectively change survivors' physical activity. These findings could result in more scalable, effective physical activity interventions for breast cancer survivors, and, ultimately, improve health and disease outcomes.Optimizing a Positive Psychology Intervention to Promote Health Behaviors after an Acute Coronary Syndrome : The Positive Emotions after Acute Coronary Events III (PEACE-III) Randomized Factorial Trial
AbstractCelano, C. M., Albanese, A. M., Millstein, R. A., Mastromauro, C. A., Chung, W. J., Campbell, K. A., Legler, S. R., Park, E. R., Healy, B. C., Collins, L., Januzzi, J. L., & Huffman, J. C. (n.d.).Publication year
2018Journal title
Psychosomatic MedicineVolume
80Issue
6Page(s)
526-534AbstractObjective Despite the clear benefits of physical activity and related behaviors on prognosis, most patients experiencing an acute coronary syndrome (ACS) remain nonadherent to these behaviors. Deficits in positive psychological constructs (e.g., optimism) are linked to reduced participation in health behaviors, supporting the potential utility of a positive psychology (PP)-based intervention in post-ACS patients. Accordingly, we aimed to identify optimal components of a PP-based intervention to promote post-ACS physical activity. Methods As part of a multiphase optimization strategy, we completed a randomized factorial trial with eight conditions in 128 post-ACS patients to efficiently identify best-performing intervention components. All participants received a PP-based intervention, with conditions varying in duration (presence/absence of booster sessions), intensity (weekly/daily PP exercises), and content (PP alone or combined with motivational interviewing), allowing three concurrent comparisons within the trial. The study aims included assessments of the overall feasibility, acceptability, and impact of the intervention, along with the primary aim of determining which components were associated with objectively measured physical activity and self-reported health behavior adherence at 16 weeks, assessed using longitudinal models. Results The intervention was well accepted and associated with substantial improvements in behavioral and psychological outcomes. Booster sessions were associated with greater activity to a nearly significant degree (β = 8.58, 95% confidence interval =-0.49-17.65, effect size difference =.43, p =.064), motivational interviewing was associated with overall adherence (β = 0.95, 95% confidence interval = 0.02-1.87, effect size difference =.39, p =.044), and weekly exercise completion was generally superior to daily. Conclusions These findings will enable optimization of the PP-based intervention in preparation for a well-powered controlled trial. Clinical Trial Registration Clinicaltrials.gov, NCT02754895.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.An Overview of Research and Evaluation Designs for Dissemination and Implementation
AbstractBrown, C. H., Curran, G., Palinkas, L. A., Aarons, G. A., Wells, K. B., Jones, L., Collins, L., Duan, N., Mittman, B. S., Wallace, A., Tabak, R. G., Ducharme, L., Chambers, D. A., Neta, G., Wiley, T., Landsverk, J., Cheung, K., & Cruden, G. (n.d.).Publication year
2017Journal title
Annual Review of Public HealthVolume
38Page(s)
1-22AbstractThe wide variety of dissemination and implementation designs now being used to evaluate and improve health systems and outcomes warrants review of the scope, features, and limitations of these designs. This article is one product of a design workgroup that was formed in 2013 by the National Institutes of Health to address dissemination and implementation research, and whose members represented diverse methodologic backgrounds, content focus areas, and health sectors. These experts integrated their collective knowledge on dissemination and implementation designs with searches of published evaluations strategies. This article emphasizes randomized and nonrandomized designs for the traditional translational research continuum or pipeline, which builds on existing efficacy and effectiveness trials to examine how one or more evidence-based clinicalprevention interventions are adopted, scaled up, and sustained in community or service delivery systems. We also mention other designs, including hybrid designs that combine effectiveness and implementation research, quality improvement designs for local knowledge, and designs that use simulation modeling.Implementing Clinical Research Using Factorial Designs : A Primer
AbstractBaker, T. B., Smith, S. S., Bolt, D. M., Loh, W. Y., Mermelstein, R., Piper, M. E., Fiore, M. C., & Collins, L. (n.d.).Publication year
2017Journal title
Behavior TherapyVolume
48Issue
4Page(s)
567-580AbstractFactorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers’ increased and careful execution of such designs.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.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.Using the multiphase optimization strategy (MOST) to optimize an HIV care continuum intervention for vulnerable populations : A study protocol
AbstractGwadz, M. V., Collins, L., Cleland, C. M., Leonard, N. R., Wilton, L., Gandhi, M., Scott Braithwaite, R., Perlman, D. C., Kutnick, A., & Ritchie, A. S. (n.d.).Publication year
2017Journal title
BMC public healthVolume
17Issue
1AbstractBackground: More than half of persons living with HIV (PLWH) in the United States are insufficiently engaged in HIV primary care and not taking antiretroviral therapy (ART), mainly African Americans/Blacks and Hispanics. In the proposed project, a potent and innovative research methodology, the multiphase optimization strategy (MOST), will be employed to develop a highly efficacious, efficient, scalable, and cost-effective intervention to increase engagement along the HIV care continuum. Whereas randomized controlled trials are valuable for evaluating the efficacy of multi-component interventions as a package, they are not designed to evaluate which specific components contribute to efficacy. MOST, a pioneering, engineering-inspired framework, addresses this problem through highly efficient randomized experimentation to assess the performance of individual intervention components and their interactions. We propose to use MOST to engineer an intervention to increase engagement along the HIV care continuum for African American/Black and Hispanic PLWH not well engaged in care and not taking ART. Further, the intervention will be optimized for cost-effectiveness. A similar set of multi-level factors impede both HIV care and ART initiation for African American/Black and Hispanic PLWH, primary among them individual- (e.g., substance use, distrust, fear), social- (e.g., stigma), and structural-level barriers (e.g., difficulties accessing ancillary services). Guided by a multi-level social cognitive theory, and using the motivational interviewing approach, the study will evaluate five distinct culturally based intervention components (i.e., counseling sessions, pre-adherence preparation, support groups, peer mentorship, and patient navigation), each designed to address a specific barrier to HIV care and ART initiation. These components are well-grounded in the empirical literature and were found acceptable, feasible, and promising with respect to efficacy in a preliminary study. Methods/design: Study aims are: 1) using a highly efficient fractional factorial experimental design, identify which of five intervention components contribute meaningfully to improvement in HIV viral suppression, and secondary outcomes of ART adherence and engagement in HIV primary care; 2) identify mediators and moderators of intervention component efficacy; and 3) using a mathematical modeling approach, build the most cost-effective and efficient intervention package from the efficacious components. A heterogeneous sample of African American/Black and Hispanic PLWH (with respect to age, substance use, and sexual minority status) will be recruited with a proven hybrid sampling method using targeted sampling in community settings and peer recruitment (N = 512). Discussion: This is the first study to apply the MOST framework in the field of HIV prevention and treatment. This innovative study will produce a culturally based HIV care continuum intervention for the nation's most vulnerable PLWH, optimized for cost-effectiveness, and with exceptional levels of efficacy, efficiency, and scalability. Trial registration: ClinicalTrials.gov, NCT02801747, Registered June 8, 2016.Advancing Models and Theories for Digital Behavior Change Interventions
AbstractHekler, E. B., Michie, S., Pavel, M., Rivera, D. E., Collins, L., Jimison, H. B., Garnett, C., Parral, S., & Spruijt-Metz, D. (n.d.).Publication year
2016Journal title
American journal of preventive medicineVolume
51Issue
5Page(s)
825-832AbstractTo be suitable for informing digital behavior change interventions, theories and models of behavior change need to capture individual variation and changes over time. The aim of this paper is to provide recommendations for development of models and theories that are informed by, and can inform, digital behavior change interventions based on discussions by international experts, including behavioral, computer, and health scientists and engineers. The proposed framework stipulates the use of a state-space representation to define when, where, for whom, and in what state for that person, an intervention will produce a targeted effect. The “state” is that of the individual based on multiple variables that define the “space” when a mechanism of action may produce the effect. A state-space representation can be used to help guide theorizing and identify crossdisciplinary methodologic strategies for improving measurement, experimental design, and analysis that can feasibly match the complexity of real-world behavior change via digital behavior change interventions.Comparative effectiveness of intervention components for producing long-term abstinence from smoking : A factorial screening experiment
AbstractSchlam, T. R., Fiore, M. C., Smith, S. S., Fraser, D., Bolt, D. M., Collins, L., Mermelstein, R., Piper, M. E., Cook, J. W., Jorenby, D. E., Loh, W. Y., & Baker, T. B. (n.d.).Publication year
2016Journal title
AddictionVolume
111Issue
1Page(s)
142-155AbstractAims: To identify promising intervention components that help smokers attain and maintain abstinence during a quit attempt. Design: A 2×2×2×2×2 randomized factorial experiment. Setting: Eleven primary care clinics in Wisconsin, USA. Participants: A total of 544 smokers (59% women, 86% white) recruited during primary care visits and motivated to quit. Interventions: Five intervention components designed to help smokers attain and maintain abstinence: (1) extended medication (26 versus 8 weeks of nicotine patch+nicotine gum); (2) maintenance (phone) counseling versus none (3) medication adherence counseling versus none (4) automated (medication) adherence calls versus none and (5) electronic medication monitoring with feedback and counseling versus electronic medication monitoring alone. Measurements: The primary outcome was 7-day self-reported point-prevalence abstinence 1 year after the target quit day. Findings: Only extended medication produced a main effect. Twenty-six versus 8 weeks of medication improved point-prevalence abstinence rates (43 versus 34% at 6 months; 34 versus 27% at 1 year; P =0.01 for both). There were four interaction effects at 1 year, showing that an intervention component's effectiveness depended upon the components with which it was combined. Conclusions: Twenty-six weeks of nicotine patch+nicotine gum (versus 8 weeks) and maintenance counseling provided by phone are promising intervention components for the cessation and maintenance phases of smoking treatment.Comparative effectiveness of motivation phase intervention components for use with smokers unwilling to quit : A factorial screening experiment
AbstractCook, J. W., Collins, L., Fiore, M. C., Smith, S. S., Fraser, D., Bolt, D. M., Baker, T. B., Piper, M. E., Schlam, T. R., Jorenby, D., Loh, W. Y., & Mermelstein, R. (n.d.).Publication year
2016Journal title
AddictionVolume
111Issue
1Page(s)
117-128AbstractAims: To screen promising intervention components designed to reduce smoking and promote abstinence in smokers initially unwilling to quit. Design: A balanced, four-factor, randomized factorial experiment. Setting: Eleven primary care clinics in southern Wisconsin, USA. Participants: A total of 517 adult smokers (63.4% women, 91.1% white) recruited during primary care visits who were willing to reduce their smoking but not quit. Interventions: Four factors contrasted intervention components designed to reduce smoking and promote abstinence: (1) nicotine patch versus none (2) nicotine gum versus none (3) motivational interviewing (MI) versus none and (4) behavioral reduction counseling (BR) versus none. Participants could request cessation treatment at any point during the study. Measurements: The primary outcome was percentage change in cigarettes smoked per day at 26weeks post-study enrollment; the secondary outcomes were percentage change at 12 weeks and point-prevalence abstinence at 12 and 26 weeks post-study enrollment. Findings: There were few main effects, but a significant four-way interaction at 26weeks post-study enrollment (P=0.01, β=0.12) revealed relatively large smoking reductions by two component combinations: nicotine gum combined with BR and BR combined with MI. Further, BR improved 12-week abstinence rates (P=0.04), and nicotine gum, when used without MI, increased 26-week abstinence after a subsequent aided quit attempt (P=0.01). Conclusions: Motivation-phase nicotine gum and behavioral reduction counseling are promising intervention components for smokers who are initially unwilling to quit.Enhancing the effectiveness of smoking treatment research : Conceptual bases and progress
AbstractBaker, T. B., Collins, L., Mermelstein, R., Piper, M. E., Schlam, T. R., Cook, J. W., Bolt, D. M., Smith, S. S., Jorenby, D. E., Fraser, D., Loh, W. Y., Theobald, W. E., & Fiore, M. C. (n.d.).Publication year
2016Journal title
AddictionVolume
111Issue
1Page(s)
107-116AbstractBackground and aims: A chronic care strategy could potentially enhance the reach and effectiveness of smoking treatment by providing effective interventions for all smokers, including those who are initially unwilling to quit. This paper describes the conceptual bases of a National Cancer Institute-funded research program designed to develop an optimized, comprehensive, chronic care smoking treatment. Methods: This research is grounded in three methodological approaches: (1) the Phase-Based Model, which guides the selection of intervention components to be experimentally evaluated for the different phases of smoking treatment (motivation, preparation, cessation, and maintenance); (2) the Multiphase Optimization Strategy (MOST), which guides the screening of intervention components via efficient experimental designs and, ultimately, the assembly of promising components into an optimized treatment package and (3) pragmatic research methods, such as electronic health record recruitment, that facilitate the efficient translation of research findings into clinical practice. Using this foundation and working in primary care clinics, we conducted three factorial experiments (reported in three accompanying papers) to screen 15 motivation, preparation, cessation and maintenance phase intervention components for possible inclusion in a chronic care smoking treatment program. Results: This research identified intervention components with relatively strong evidence of effectiveness at particular phases of smoking treatment and it demonstrated the efficiency of the MOST approach in terms both of the number of intervention components tested and of the richness of the information yielded. Conclusions: A new, synthesized research approach efficiently evaluates multiple intervention components to identify promising components for every phase of smoking treatment. Many intervention components interact with one another, supporting the use of factorial experiments in smoking treatment development.Evaluating Digital Health Interventions : Key Questions and Approaches
AbstractMurray, E., Hekler, E. B., Andersson, G., Collins, L., Doherty, A., Hollis, C., Rivera, D. E., West, R., & Wyatt, J. C. (n.d.).Publication year
2016Journal title
American journal of preventive medicineVolume
51Issue
5Page(s)
843-851AbstractDigital health interventions have enormous potential as scalable tools to improve health and healthcare delivery by improving effectiveness, efficiency, accessibility, safety, and personalization. Achieving these improvements requires a cumulative knowledge base to inform development and deployment of digital health interventions. However, evaluations of digital health interventions present special challenges. This paper aims to examine these challenges and outline an evaluation strategy in terms of the research questions needed to appraise such interventions. As they are at the intersection of biomedical, behavioral, computing, and engineering research, methods drawn from all of these disciplines are required. Relevant research questions include defining the problem and the likely benefit of the digital health intervention, which in turn requires establishing the likely reach and uptake of the intervention, the causal model describing how the intervention will achieve its intended benefit, key components, and how they interact with one another, and estimating overall benefit in terms of effectiveness, cost effectiveness, and harms. Although RCTs are important for evaluation of effectiveness and cost effectiveness, they are best undertaken only when: (1) the intervention and its delivery package are stable; (2) these can be implemented with high fidelity; and (3) there is a reasonable likelihood that the overall benefits will be clinically meaningful (improved outcomes or equivalent outcomes at lower cost). Broadening the portfolio of research questions and evaluation methods will help with developing the necessary knowledge base to inform decisions on policy, practice, and research.Identifying effective intervention components for smoking cessation : A factorial screening experiment
AbstractPiper, M. E., Fiore, M. C., Smith, S. S., Fraser, D., Bolt, D. M., Collins, L., Mermelstein, R., Schlam, T. R., Cook, J. W., Jorenby, D. E., Loh, W. Y., & Baker, T. B. (n.d.).Publication year
2016Journal title
AddictionVolume
111Issue
1Page(s)
129-141AbstractAims: To identify promising intervention components intended to help smokers to attain and maintain abstinence in their quit smoking attempts. Design: A fully crossed, six-factor randomized fractional factorial experiment. Setting: Eleven primary care clinics in southern Wisconsin, USA. Participants: A total of 637 adult smokers (55% women, 88% white) motivated to quit smoking who visited primary care clinics. Interventions: Six intervention components designed to prepare smokers to quit, and achieve and maintain abstinence (i.e. for the preparation, cessation and maintenance phases of smoking treatment): (1) preparation nicotine patch versus none (2) preparation nicotine gum versus none (3) preparation counseling versus none (4) intensive cessation in-person counseling versus minimal; (5) intensive cessation telephone counseling versus minimal; and (6) 16 versus 8weeks of combination nicotine replacement therapy (nicotine patch + nicotine gum). Measurements: Seven-day self-reported point-prevalence abstinence at 16weeks. Findings: Preparation counseling significantly improved week 16 abstinence rates (P = .04), while both forms of preparation nicotine replacement therapy interacted synergistically with intensive cessation in-person counseling (PImplementing multifactorial psychotherapy research in online virtual environments (IMPROVE-2) : Study protocol for a phase III trial of the MOST randomized component selection method for internet cognitive-behavioural therapy for depression
AbstractWatkins, E., Newbold, A., Tester-Jones, M., Javaid, M., Cadman, J., Collins, L., Graham, J., & Mostazir, M. (n.d.).Publication year
2016Journal title
BMC psychiatryVolume
16Issue
1AbstractBackground: Depression is a global health challenge. Although there are effective psychological and pharmaceutical interventions, our best treatments achieve remission rates less than 1/3 and limited sustained recovery. Underpinning this efficacy gap is limited understanding of how complex psychological interventions for depression work. Recent reviews have argued that the active ingredients of therapy need to be identified so that therapy can be made briefer, more potent, and to improve scalability. This in turn requires the use of rigorous study designs that test the presence or absence of individual therapeutic elements, rather than standard comparative randomised controlled trials. One such approach is the Multiphase Optimization Strategy, which uses efficient experimentation such as factorial designs to identify active factors in complex interventions. This approach has been successfully applied to behavioural health but not yet to mental health interventions. Methods/Design: A Phase III randomised, single-blind balanced fractional factorial trial, based in England and conducted on the internet, randomized at the level of the patient, will investigate the active ingredients of internet cognitive-behavioural therapy (CBT) for depression. Adults with depression (operationalized as PHQ-9 score ≥ 10), recruited directly from the internet and from an UK National Health Service Improving Access to Psychological Therapies service, will be randomized across seven experimental factors, each reflecting the presence versus absence of specific treatment components (activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, absorption, self-compassion training) using a 32-condition balanced fractional factorial design (2IV 7-2). The primary outcome is symptoms of depression (PHQ-9) at 12 weeks. Secondary outcomes include symptoms of anxiety and process measures related to hypothesized mechanisms. Discussion: Better understanding of the active ingredients of efficacious therapies, such as CBT, is necessary in order to improve and further disseminate these interventions. This study is the first application of a component selection experiment to psychological interventions in depression and will enable us to determine the main effect of each treatment component and its relative efficacy, and cast light on underlying mechanisms, so that we can systematically enhance internet CBT. Trial registration: Current Controlled Trials ISRCTN24117387. Registered 26 August 2014.Mining health app data to find more and less successful weight loss subgroups
AbstractSerrano, K. J., Yu, M., Coa, K. I., Collins, L., & Atienza, A. A. (n.d.).Publication year
2016Journal title
Journal of medical Internet researchVolume
18Issue
6AbstractBackground: More than half of all smartphone app downloads involve weight, diet, and exercise. If successful, these lifestyle apps may have far-reaching effects for disease prevention and health cost-savings, but few researchers have analyzed data from these apps. Objective: The purposes of this study were to analyze data from a commercial health app (Lose It!) in order to identify successful weight loss subgroups via exploratory analyses and to verify the stability of the results. Methods: Cross-sectional, de-identified data from Lose It! were analyzed. This dataset (n=12,427,196) was randomly split into 24 subsamples, and this study used 3 subsamples (combined n=972,687). Classification and regression tree methods were used to explore groupings of weight loss with one subsample, with descriptive analyses to examine other group characteristics. Data mining validation methods were conducted with 2 additional subsamples. Results: In subsample 1, 14.96% of users lost 5% or more of their starting body weight. Classification and regression tree analysis identified 3 distinct subgroups: "the occasional users" had the lowest proportion (4.87%) of individuals who successfully lost weight; "the basic users" had 37.61% weight loss success; and "the power users" achieved the highest percentage of weight loss success at 72.70%. Behavioral factors delineated the subgroups, though app-related behavioral characteristics further distinguished them. Results were replicated in further analyses with separate subsamples. Conclusions: This study demonstrates that distinct subgroups can be identified in "messy" commercial app data and the identified subgroups can be replicated in independent samples. Behavioral factors and use of custom app features characterized the subgroups. Targeting and tailoring information to particular subgroups could enhance weight loss success. Future studies should replicate data mining analyses to increase methodology rigor.Optimization of Multicomponent Behavioral and Biobehavioral Interventions for the Prevention and Treatment of HIV/AIDS
AbstractCollins, L., Kugler, K. C., & Gwadz, M. V. (n.d.).Publication year
2016Journal title
AIDS and BehaviorVolume
20Page(s)
197-214AbstractTo move society toward an AIDS-free generation, behavioral interventions for prevention and treatment of HIV/AIDS must be not only effective, but also cost-effective, efficient, and readily scalable. The purpose of this article is to introduce to the HIV/AIDS research community the multiphase optimization strategy (MOST), a new methodological framework inspired by engineering principles and designed to develop behavioral interventions that have these important characteristics. Many behavioral interventions comprise multiple components. In MOST, randomized experimentation is conducted to assess the individual performance of each intervention component, and whether its presence/absence/setting has an impact on the performance of other components. This information is used to engineer an intervention that meets a specific optimization criterion, defined a priori in terms of effectiveness, cost, cost-effectiveness, and/or scalability. MOST will enable intervention science to develop a coherent knowledge base about what works and does not work. Ultimately this will improve behavioral interventions systematically and incrementally.Utilizing MOST frameworks and SMART designs for intervention research
AbstractWilbur, J. E., Kolanowski, A. M., & Collins, L. (n.d.).Publication year
2016Journal title
Nursing outlookVolume
64Issue
4Page(s)
287-289Abstract~Corrigendum to "Optimization of remotely delivered intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy : Opt-IN study protocol" [Contemp. Clin. Trials 38 (2014) 251-259] DOI: 10.1016/j.cct.2014.05.007
AbstractPellegrini, C. A., Hoffman, S. A., Collins, L., & Spring, B. (n.d.).Publication year
2015Journal title
Contemporary Clinical TrialsVolume
45Page(s)
468-469Abstract~