Linda Collins
Linda Collins
Scroll
Professor of Social and Behavioral Sciences
-
Professional overview
-
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.
-
Education
-
BA, Psychology, University of Connecticut, Storrs, CTPhD, Quantitative Psychology, University of Southern California, Los Angeles, CA
-
Honors and awards
-
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)
-
Areas of research and study
-
Behavioral ScienceCost EffectivenessCost-effective Health Programs and PoliciesDissemination and Implementation of Evidence-based Programs
-
Publications
Publications
Control systems engineering for understanding and optimizing smoking cessation interventions
AbstractTimms, K. P., Rivera, D. E., Collins, L., & Piper, M. E. (n.d.).Publication year
2013Page(s)
1964-1969AbstractCigarette smoking remains a major public health issue. Despite a variety of treatment options, existing intervention protocols intended to support attempts to quit smoking have low success rates. An emerging treatment framework, referred to as adaptive interventions in behavioral health, addresses the chronic, relapsing nature of behavioral health disorders by tailoring the composition and dosage of intervention components to an individual's changing needs over time. An important component of a rapid and effective adaptive smoking intervention is an understanding of the behavior change relationships that govern smoking behavior and an understanding of intervention components' dynamic effects on these behavioral relationships. As traditional behavior models are static in nature, they cannot act as an effective basis for adaptive intervention design. In this article, behavioral data collected daily in a smoking cessation clinical trial is used in development of a dynamical systems model that describes smoking behavior change during cessation as a self-regulatory process. Drawing from control engineering principles, empirical models of smoking behavior are constructed to reflect this behavioral mechanism and help elucidate the case for a control-oriented approach to smoking intervention design.Correction : Advancing behavioral interventions for African American/Black and Latino persons living with HIV using a new conceptual model that integrates critical race theory, harm reduction, and self-determination theory: a qualitative exploratory study (International Journal for Equity in Health, (2022), 21, 1, (97), 10.1186/s12939-022-01699-0)
AbstractGwadz, M., Cluesman, S. R., Freeman, R., Collins, L., Dorsen, C., Hawkins, R. L., Cleland, C. M., Wilton, L., Ritchie, A. S., Torbjornsen, K., Leonard, N. R., Martinez, B. Y., Silverman, E., Israel, K., & Kutnick, A. (n.d.).Publication year
2022Journal title
International Journal for Equity in HealthVolume
21Issue
1AbstractAfter publication of this article [1], the authors reported that the caption to Fig. 2 (‘IIT-ICM core elementsfor ICM1’) should have read ‘Core elements and key characteristics of the Intervention Innovations Team integrated conceptual model (IIT-ICM) to guide behavioral intervention development’. The original article [1] has been corrected.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~Cost-Effectiveness of Smoking Cessation Approaches in Emergency Departments
AbstractMiller, T. R., Johnson, M. B., Dziura, J. D., Weiss, J., Carpenter, K. M., Grau, L. E., Pantalon, M. V., Abroms, L., Collins, L., Toll, B. A., & Bernstein, S. L. (n.d.).Publication year
2023Journal title
American journal of preventive medicineAbstractIntroduction: Americans of lower SES use tobacco products at disproportionately high rates and are over-represented as patients of emergency departments. Accordingly, emergency department visits are an ideal time to initiate tobacco treatment and aftercare for this vulnerable and understudied population. This research estimates the costs per quit of emergency department smoking-cessation interventions and compares them with those of other approaches. Methods: Previously published research described the effectiveness of 2 multicomponent smoking-cessation interventions, including brief negotiated interviewing, nicotine replacement therapy, quitline referral, and follow-up communication. Study 1 (collected in 2010–2012) only analyzed the combined interventions. Study 2 (collected in 2017–2019) analyzed the intervention components independently. Costs per participant and per quit were estimated separately, under distinct intervention with dedicated staff and intervention with repurposed staff assumptions. The distinction concerns whether the intervention used dedicated staff for delivery or whether time from existing staff was repurposed for intervention if available. Results: Data were analyzed in 2021–2022. In the first study, the cost per participant was $860 (2018 dollars), and the cost per quit was $11,814 (95% CI=$7,641, $25,423) (dedicated) and $227 per participant and $3,121 per quit (95% CI=$1,910, $7,012) (repurposed). In Study 2, the combined effect of brief negotiated interviewing, nicotine replacement therapy, and quitline cost $808 per participant and $6,100 per quit (dedicated) (95% CI=$4,043, $12,274) and $221 per participant and $1,669 per quit (95% CI=$1,052, $3,531) (repurposed). Conclusions: Costs varied considerably per method used but were comparable with those of other smoking-cessation interventions.Crossvalidation of Latent Class Models of Early Substance Use Onset
AbstractCollins, L., Graham, J. W., Long, J. D., & Hansen, W. B. (n.d.).Publication year
1994Journal title
Multivariate Behavioral ResearchVolume
29Issue
2Page(s)
165-183AbstractCudeck and Browne (1983) were among the first to discuss the advantages of taking a crossvalidation approach to testing of covariance structure models. The purpose of this paper is to expand on Cudeck and Browne's work in two directions. The first direction of expansion is into testing of latent class models. The second direction of expansion involves using crossvalidation to examine differences between groups, where groups may be formed by gender, ethnicity, region, etc. In the present article crossvalidation is used to help select models of early substance use onset in a sample of young adolescents. The results suggest that the nature of the substance use onset process and the rate of movement through the process are the same for males and females at seventh and eighth grade. However, the present study did find evidence for gender differences in substance use experience at the beginning of seventh grade, with males somewhat more advanced in the onset process. The results also suggest that double crossvalidation is greatly to be preferred over single crossvalidation.Customizing treatment to the patient : Adaptive treatment strategies
AbstractCollins, L., Murphy, S. A., Collins, L. M., & Rush, A. J. (n.d.).Publication year
2007Journal title
Drug and alcohol dependenceVolume
88Issue
SUPPL. 2Page(s)
S1-S3Abstract~Decision-making in the multiphase optimization strategy : Applying decision analysis for intervention value efficiency to optimize an information leaflet to promote key antecedents of medication adherence
AbstractGreen, S. M., Smith, S. G., Collins, L., & Strayhorn, J. C. (n.d.).Publication year
2024Journal title
Translational Behavioral MedicineVolume
14Issue
8Page(s)
461-471AbstractAdvances in the multiphase optimization strategy (MOST) have suggested a new approach, decision analysis for intervention value efficiency (DAIVE), for selecting an optimized intervention based on the results of a factorial optimization trial. The new approach opens possibilities to select optimized interventions based on multiple valued outcomes. We applied DAIVE to identify an optimized information leaflet intended to support eventual adherence to adjuvant endocrine therapy for women with breast cancer. We used empirical performance data for five candidate leaflet components on three hypothesized antecedents of adherence: beliefs about the medication, objective knowledge about AET, and satisfaction with medication information. Using data from a 25 factorial trial (n = 1603), we applied the following steps: (i) We used Bayesian factorial analysis of variance to estimate main and interaction effects for the five factors on the three outcomes. (ii) We used posterior distributions for main and interaction effects to estimate expected outcomes for each leaflet version (32 total). (iii) We scaled and combined outcomes using a linear value function with predetermined weights indicating the relative importance of outcomes. (iv) We identified the leaflet that maximized the value function as the optimized leaflet, and we systematically varied outcome weights to explore robustness. The optimized leaflet included two candidate components, side-effects, and patient input, set to their higher levels. Selection was generally robust to weight variations consistent with the initial preferences for three outcomes. DAIVE enables selection of optimized interventions with the best-expected performance on multiple outcomes.Design of Experiments With Multiple Independent Variables : A Resource Management Perspective on Complete and Reduced Factorial Designs
AbstractCollins, L., Dziak, J. J., & Li, R. (n.d.).Publication year
2009Journal title
Psychological MethodsVolume
14Issue
3Page(s)
202-224AbstractAn investigator who plans to conduct an experiment with multiple independent variables must decide whether to use a complete or reduced factorial design. This article advocates a resource management perspective on making this decision, in which the investigator seeks a strategic balance between service to scientific objectives and economy. Considerations in making design decisions include whether research questions are framed as main effects or simple effects; whether and which effects are aliased (confounded) in a particular design; the number of experimental conditions that must be implemented in a particular design and the number of experimental subjects the design requires to maintain the desired level of statistical power; and the costs associated with implementing experimental conditions and obtaining experimental subjects. In this article 4 design options are compared: complete factorial, individual experiments, single factor, and fractional factorial. Complete and fractional factorial designs and single-factor designs are generally more economical than conducting individual experiments on each factor. Although relatively unfamiliar to behavioral scientists, fractional factorial designs merit serious consideration because of their economy and versatility.Developing a Psychological-Behavioral Intervention in Cardiac Patients Using the Multiphase Optimization Strategy : Lessons Learned from the Field
AbstractHuffman, J. C., Millstein, R. A., Celano, C. M., Healy, B. C., Park, E. R., & Collins, L. (n.d.).Publication year
2019Journal title
Annals of Behavioral MedicineVolume
54Issue
3Page(s)
151-163AbstractBackground: The Multiphase Optimization Strategy (MOST) is an approach to systematically and efficiently developing a behavioral intervention using a sequence of experiments to prepare and optimize the intervention. Purpose: Using a 6 year MOST-based behavioral intervention development project as an example, we outline the results - and resulting decision-making process - related to experiments at each step to display the practical challenges present at each stage. Methods: To develop a positive psychology (PP) based intervention to promote physical activity after an acute coronary syndrome (N = 255 across four phases), we utilized qualitative, proof-of-concept, factorial design, and randomized pilot experiments, with iterative modification of intervention content and delivery. Results: Through this multiphase approach, we ultimately developed a 12 week, phone-delivered, combined PP-motivational interviewing intervention to promote physical activity. Across stages, we learned several important lessons: (a) participant and interventionist feedback is important, even in later optimization stages; (b) a thoughtful and systematic approach using all information sources is required when conflicting results in experiments make next steps unclear; and (3) new approaches in the field over a multiyear project should be integrated into the development process. Conclusions: A MOST-based behavioral intervention development program can be efficient and effective in developing optimized new interventions, and it may require complex and nuanced decision-making at each phase.Developing multicomponent interventions using fractional factorial designs
AbstractChakraborty, B., Collins, L., Strecher, V. J., & Murphy, S. A. (n.d.).Publication year
2009Journal title
Statistics in MedicineVolume
28Issue
21Page(s)
2687-2708AbstractMulticomponent interventions composed of behavioral, delivery, or implementation factors in addition to medications are becoming increasingly common in health sciences. A natural experimental approach to developing and refining such multicomponent interventions is to start with a large number of potential components and screen out the least active ones. Factorial designs can be used efficiently in this endeavor. We address common criticisms and misconceptions regarding the use of factorial designs in these screening studies. We also provide an operationalization of screening studies. As an example, we consider the use of a screening study in the development of a multicomponent smoking cessation intervention. Simulation results are provided to support the discussions.Developmental pathways to alcohol abuse and dependence in young adulthood
AbstractCollins, L., Guo, J., Collins, L. M., Hill, K. G., & Hawkins, J. D. (n.d.).Publication year
2000Journal title
Journal of Studies on AlcoholVolume
61Issue
6Page(s)
799-808AbstractObjective: To determine if people who were diagnosed with alcohol abuse or dependence (AAD) at age 21 had different developmental patterns of alcohol use in adolescence than non-AAD individuals. Method: An ethnically diverse urban sample of 808 children was surveyed at age 10 in 1985 and followed prospectively to age 21 in 1996. AAD at age 21 was assessed following DSM-IV criteria. Latent Transition Analysis (LTA) was used to identify four statuses of alcohol use (nonuse, initiation only, current use only, heavy episodic drinking), as well as transition probabilities between these four statuses from elementary school to middle school and from middle school to high school among the AAD and non-AAD group. Results: The prevalence of alcohol use statuses during elementary school was similar in the two groups. Differences in alcohol use emerged in middle school and became more pronounced in high school. In middle school, AAD individuals were more likely to have initiated or been current drinkers than non-AAD individuals. However, the two groups did not differ in the prevalence of heavy episodic drinking in middle school. In high school, most AAD individuals were in the heavy episodic drinking status (54%), while most non-AAD individuals were in the initiation only (33%) or current use only (34%) statuses. Conclusions: These findings suggest preventive intervention targets for different developmental periods. Alcohol abuse and dependence at age 21 may be prevented by delaying alcohol initiation, by reducing current use in middle school and by reducing heavy episodic drinking in high school.Does individual risk moderate the effect of contextual-level protective factors? a latent class analysis of substance use
AbstractCleveland, M. J., Collins, L., Lanza, S. T., Greenberg, M. T., & Feinberg, M. E. (n.d.).Publication year
2010Journal title
Journal of Prevention and Intervention in the CommunityVolume
38Issue
3Page(s)
213-228AbstractThe current study investigated how individual risk factors interact with social contextual-level protective factors to predict problematic substance use among a sample of 12th-grade students (n=8,879, 53% female). Results suggested six latent classes of substance use: (1) Non-Users; (2) Alcohol Experimenters; (3) Alcohol, Tobacco, and Other Drug (ATOD) Experimenters; (4) Current Smokers; (5) Binge Drinkers; and (6) Heavy Users. Binary logistic regression models provided evidence that individual risk, family, school, and community protective factors were associated with membership in the substance use latent classes. However, the significance of interaction terms suggested that these protective influences differed according to the level of individual risk. Adolescents with high levels of individual risk benefited less from a positive family or neighborhood context than adolescents with low levels of individual risk. These findings suggest that the individual risk factors may undermine the protective effect of parental supervision, discipline, and other family factors, as well as protective aspects of cohesive neighborhoods, among these adolescents. Multi-component and adaptive intervention efforts that account for different levels of ATOD use involvement, as well as distinct profiles of risk and protection, are likely to be most effective in preventing problematic substance use.Dynamic energy-balance model predicting gestational weight gain
AbstractThomas, D. M., Navarro-Barrientos, J. E., Rivera, D. E., Heymsfield, S. B., Bredlau, C., Redman, L. M., Martin, C. K., Lederman, S. A., Collins, L., & Butte, N. F. (n.d.).Publication year
2012Journal title
American Journal of Clinical NutritionVolume
95Issue
1Page(s)
115-122AbstractBackground: Gestational weight gains (GWGs) that exceed the 2009 Institute of Medicine recommended ranges increase risk of long-term postpartum weight retention; conversely, GWGs within the recommended ranges are more likely to result in positive maternal and fetal outcomes. Despite this evidence, recent epidemiologic studies have shown that the majority of pregnant women gain outside the target GWG ranges. A mathematical model that predicts GWG and energy intake could provide a clinical tool for setting precise goals during early pregnancy and continuous objective feedback throughout pregnancy. Objective: The purpose of this study was to develop and validate a differential equation model for energy balance during pregnancy that predicts GWG that results from changes in energy intakes. Design: A set of prepregnancy BMI - dependent mathematical models that predict GWG were developed by using data from a longitudinal study that measured gestational-changes in fat-free mass, fat mass, total body water, and total energy expenditure in 63 subjects. Results: Mathematical models developed for women with low, normal, and high prepregnancy BMI were shown to fit the original data. In 2 independent studies used for validation, model predictions of fat-free mass, fat mass, and total body water matched actual measurements within 1 kg. Conclusions: Our energy-balance model provides plausible predictions of GWG that results from changes in energy intakes. Because the model was implemented as a Web-based applet, it can be widely used by pregnant women and their health care providers.Effects of Behavioral Intervention Components for African American/Black and Latino Persons Living with HIV with Non-suppressed Viral Load Levels : Results of an Optimization Trial
AbstractCleland, C. M., Gwadz, M., Collins, L., Wilton, L., Leonard, N. R., Ritchie, A. S., Martinez, B. Y., Silverman, E. A., Sherpa, D., & Dorsen, C. (n.d.).Publication year
2023Journal title
AIDS and BehaviorAbstractThere is an urgent need for efficient behavioral interventions to increase rates of HIV viral suppression for populations with serious barriers to engagement along the HIV care continuum. We carried out an optimization trial to test the effects of five behavioral intervention components designed to address barriers to HIV care continuum engagement for African American/Black and Latino persons living with HIV (PLWH) with non-suppressed HIV viral load levels: motivational interviewing sessions (MI), focused support groups (SG), peer mentorship (PM), pre-adherence skill building (SB), and navigation with two levels, short (NS) and long (NL). The primary outcome was HIV viral suppression (VS) and absolute viral load (VL) and health-related quality of life were secondary outcomes. Participants were 512 African American/Black and Latino PLWH poorly engaged in HIV care and with detectable HIV viral load levels in New York City, recruited mainly through peer referral. Overall, VS increased to 37%, or 45% in a sensitivity analysis. MI and SG seemed to have antagonistic effects on VS (z = − 1.90; p = 0.057); the probability of VS was highest when either MI or SG was assigned, but not both. MI (Mean Difference = 0.030; 95% CI 0.007–0.053; t(440) = 2.60; p = 0.010) and SB (Mean Difference = 0.030; 95% CI 0.007–0.053; t(439) = 2.54; p = 0.012) improved health-related quality of life. This is the first optimization trial in the field of HIV treatment. The study yields a number of insights into approaches to improve HIV viral suppression in PLWH with serious barriers to engagement along the HIV care continuum, including chronic poverty, and underscores challenges inherent in doing so.Effects of Chatbot Components to Facilitate Mental Health Services Use in Individuals With Eating Disorders Following Online Screening: An Optimization Randomized Controlled Trial
AbstractCollins, L., Fitzsimmons-Craft, E. E., Rackoff, G. N., Shah, J., Strayhorn, J. C., D’Adamo, L., DePietro, B., Howe, C. P., Firebaugh, M. L., Newman, M. G., Collins, L. M., Taylor, C., & Wilfley, D. E. (n.d.).Publication year
2024Journal title
International Journal of Eating DisordersVolume
57Issue
11AbstractObjective: Few individuals with eating disorders (EDs) receive treatment. Innovations are needed to identify individuals with EDs and address care barriers. We developed a chatbot for promoting services uptake that could be paired with online screening. However, it is not yet known which components drive effects. This study estimated individual and combined contributions of four chatbot components on mental health services use (primary), chatbot helpfulness, and attitudes toward changing eating/shape/weight concerns (“change attitudes,” with higher scores indicating greater importance/readiness). Methods: Two hundred five individuals screening with an ED but not in treatment were randomized in an optimization randomized controlled trial to receive up to four chatbot components: psychoeducation, motivational interviewing, personalized service recommendations, and repeated administration (follow-up check-ins/reminders). Assessments were at baseline and 2, 6, and 14 weeks. Results: Participants who received repeated administration were more likely to report mental health services use, with no significant effects of other components on services use. Repeated administration slowed the decline in change attitudes participants experienced over time. Participants who received motivational interviewing found the chatbot more helpful, but this component was also associated with larger declines in change attitudes. Participants who received personalized recommendations found the chatbot more helpful, and receiving this component on its own was associated with the most favorable change attitude time trend. Psychoeducation showed no effects. Discussion: Results indicated important effects of components on outcomes; findings will be used to finalize decision making about the optimized intervention package. The chatbot shows high potential for addressing the treatment gap for EDs.Effects of motivation phase intervention components on quit attempts in smokers unwilling to quit : A factorial experiment
AbstractEngle, J. L., Mermelstein, R., Baker, T. B., Smith, S. S., Schlam, T. R., Piper, M. E., Jorenby, D. E., Collins, L., & Cook, J. W. (n.d.).Publication year
2019Journal title
Drug and alcohol dependenceVolume
197Page(s)
149-157AbstractBACKGROUND: Smoking reduction treatment is a promising approach to increase abstinence amongst smokers initially unwilling to quit. However, little is known about which reduction treatment elements increase quit attempts and the uptake of cessation treatment amongst such smokers.METHODS: This study is a secondary analysis of a 4-factor randomized factorial experiment conducted amongst primary care patients (N = 517) presenting for regular healthcare visits in Southern Wisconsin who were unwilling to quit smoking but willing to cut down. We evaluated the main and interactive effects of Motivation-phase intervention components on whether participants: 1) made a quit attempt (intentional abstinence ≥24 h) by 6- and 26-weeks post-study enrollment and, 2) used cessation treatment. We also evaluated the relations of quit attempts with abstinence. The four intervention components evaluated were: 1) Nicotine Patch vs. None; 2) Nicotine Gum vs. None; 3) Motivational Interviewing (MI) vs. None; and 4) Behavioral Reduction Counseling (BR) vs. None. Intervention components were administered over 6 weeks, with an option to repeat treatment; participants could request cessation treatment at any point.RESULTS: Nicotine gum significantly increased the likelihood of making a quit attempt by 6 weeks (23% vs. 15% without gum; p < .05). Conversely, nicotine patch reduced quit attempts when used with BR. Patch also discouraged use of cessation treatment (15.8% vs. 23% without patch; p < .05). Aided vs. unaided quit attempts produced abstinence in 42% vs. 10% of participants, respectively.CONCLUSION: Nicotine gum is a promising Motivation-phase intervention that may spur quit attempts amongst smokers initially unwilling to quit.Engineering control approaches for the design and analysis of adaptive behavioral interventions
AbstractRivera, D. E., & Collins, L. (n.d.).Publication year
2008Abstract~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.Erratum : Comparison of a phased experimental approach and a single randomized clinical trial for developing multicomponent behavioural interventions (Clinical Trials (2009) vol. 6 (5-15) 10.1177/1740774508100973)
AbstractCollins, L., Chakraborty, B., Murphy, S. A., & Strecher, V. (n.d.).Publication year
2009Journal title
Clinical TrialsVolume
6Issue
3Page(s)
289Abstract~Erratum : New methods for tobacco dependence treatment research (Annals of Behavioral Medicine (2011) 41:2 (192-207) DOI: 10.1007/s12160-010-9252-y)
AbstractBaker, T. B., Mermelstein, R. J., Collins, L., 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
42Issue
1Page(s)
139Abstract~Europe Needs a Central, Transparent, and Evidence-Based Approval Process for Behavioural Prevention Interventions
AbstractFaggiano, F., Allara, E., Giannotta, F., Molinar, R., Sumnall, H., Wiers, R., Michie, S., Collins, L., & Conrod, P. (n.d.).Publication year
2014Journal title
PLoS MedicineVolume
11Issue
10Abstract~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.Evaluating four motivation-phase intervention components for use with primary care patients unwilling to quit smoking : a randomized factorial experiment
AbstractCook, J. W., Baker, T. B., Fiore, M. C., Collins, L., Piper, M. E., Schlam, T. R., Bolt, D. M., Smith, S. S., Zwaga, D., Jorenby, D. E., & Mermelstein, R. (n.d.).Publication year
2021Journal title
AddictionVolume
116Issue
11Page(s)
3167-3179AbstractAims: To assess the effectiveness of intervention components designed to increase quit attempts and promote abstinence in patients initially unwilling to quit smoking. Design: A four-factor, randomized factorial experiment. Setting: Sixteen primary care clinics in southern Wisconsin. Participants: A total of 577 adults who smoke (60% women, 80% White) recruited during primary care visits who were currently willing to reduce their smoking but unwilling to try to quit. Interventions. Four factors contrasted intervention components administered over a 1-year period: (i) nicotine mini-lozenge versus none; (ii) reduction counseling versus none; (iii) behavioral activation (BA) counseling versus none; and (iv) motivational 5Rs counseling versus none. Participants could request cessation treatment at any time. Measurements: The primary outcome was 7-day point-prevalence abstinence at 52 weeks post enrollment; secondary outcomes were point-prevalence abstinence at 26 weeks and making a quit attempt by weeks 26 and 52. Findings: No abstinence main effects were found but a mini-lozenge × reduction counseling × BA interaction was found at 52 weeks; P = 0.03. Unpacking this interaction showed that the mini-lozenge alone produced the highest abstinence rate (16.7%); combining it with reduction counseling produced an especially low abstinence rate (4.1%). Reduction counseling decreased the likelihood of making a quit attempt by 52 weeks relative to no reduction counseling (P = 0.01). Conclusions: Nicotine mini-lozenges may increase smoking abstinence in people initially unwilling to quit smoking, but their effectiveness declines when used with smoking reduction counseling or other behavioral interventions. Reduction counseling decreases the likelihood of making a quit attempt in people initially unwilling to quit smoking.Evaluating individual intervention components : making decisions based on the results of a factorial screening experiment
AbstractCollins, L., Trail, J. B., Kugler, K. C., Baker, T. B., Piper, M. E., & Mermelstein, R. J. (n.d.).Publication year
2014Journal title
Translational Behavioral MedicineVolume
4Issue
3Page(s)
238-251AbstractThe multiphase optimization strategy (MOST) is a framework for not only evaluating but also optimizing behavioral interventions. A tool critical for MOST is the screening experiment, which enables efficient gathering of information for deciding which components to include in an optimized intervention. This article outlines a procedure for making decisions based on data from a factorial screening experiment. The decision making procedure is illustrated with artificial data generated to resemble empirical data. The illustration suggests that this approach is useful for selecting intervention components and settings based on the results of a factorial screening experiment. It is important to develop methods for making decisions based on factorial screening experiments. The approach demonstrated here is potentially useful, but has limited generalizability. Future research should develop additional decision making procedures for a variety of situations.Exploring behavioral intervention components for African American/Black and Latino persons living with HIV with non-suppressed HIV viral load in the United States : a qualitative study
AbstractCluesman, S. R., Gwadz, M., Freeman, R., Collins, L., Cleland, C. M., Wilton, L., Hawkins, R. L., Leonard, N. R., Silverman, E., Maslow, C. B., Israel, K., Ritchie, A., & Ory, S. (n.d.).Publication year
2023Journal title
International Journal for Equity in HealthVolume
22Issue
1AbstractBackground: The persistence of racial/ethnic inequities in rates of engagement along the HIV care continuum signals the need for novel approaches. We developed six behavioral intervention components for use in an optimization trial, grounded in a model that integrates critical race theory, harm reduction, and self-determination theory, designed to address various barriers that African American/Black and Latino persons living with HIV (PLWH) experience to the HIV care continuum. The components were: health education, motivational interviewing sessions, pre-adherence skill building, peer mentorship, focused support groups, and navigation. The present qualitative exploratory study describes participants’ perspectives on the components’ acceptability, feasibility, and impact. Methods: Participants were African American/Black and Latino PLWH poorly engaged in HIV care and with non-suppressed HIV viral load in New York City. From a larger trial, we randomly selected 46 participants for in-depth semi-structured interviews. Interviews were audio-recorded and transcribed verbatim, and data were analyzed using directed content analysis. Quantitative data on sociodemographic and background characteristics and components’ acceptability and feasibility were also collected. Results: On average, participants were 49 years old and had lived with HIV for 19 years. Most were cisgender-male and African American/Black. Participants reported a constellation of serious social and structural challenges to HIV management including chronic poverty, unstable housing, and stigma. Across components, a non-judgmental and pressure-free approach and attention to structural and cultural factors were seen as vital to high levels of engagement, but lacking in most medical/social service settings. Prominent aspects of individual components included establishing trust (health education); developing intrinsic motivation, goals, and self-reflection (motivational interviewing sessions); learning/practicing adherence strategies and habits (pre-adherence skill building); reducing social isolation via peer role models (peer mentorship); reflecting on salient goals and common challenges with peers without stigma (focused support groups); and circumventing structural barriers to HIV management with support (navigation). Components were found acceptable and feasible. Findings suggested ways components could be improved. Conclusions: The present study advances research on interventions for African American/Black and Latino PLWH, who experience complex barriers to engagement along the HIV care continuum. Future study of the components is warranted to address racial/ethnic health inequities in HIV.