Linda Collins

Linda Collins
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
Patterns of Crime in a Birth Cohort
Collins, L., Cliff, N., Cudeck, R. A., McCormick, D. J., & Zatkin, J. L. (n.d.).Publication year
1983Journal title
Multivariate Behavioral ResearchVolume
18Issue
3Page(s)
235-257AbstractMost attempts at developing typologies of criminal behavior have not involved empirical research. This paper describes an exploratory empirical approach to identifying patterns in criminal behavior. Two data-reduction techniques, factor analysis and cluster analysis, are applied to the official arrest records of a Danish birth cohort of 28,879 men. Four factors emerged from the factor analysis: GENERAL CRIME, TRAFFIC OFFENSES, WHITE-COLLAR CRIME, and SEX OFFENSES. The cluster analysis revealed GENERAL CRIME and TRAFFIC OFFENSES clusters. A substantial number of offenses are shown by both analyses to be independent of any pattern. The results show good split-sample cross-validation and for the most part are robust across the two analytic approaches.Patterns of substance use onset among Hispanics in Puerto Rico and the United States
Maldonado-Molina, M. M., Collins, L., Lanza, S. T., Prado, G., Ramírez, R., & Canino, G. (n.d.).Publication year
2007Journal title
Addictive BehaviorsVolume
32Issue
10Page(s)
2432-2437AbstractPurpose: Examine patterns of progression in substance use among Hispanic youth 13 to 17 years of age from two longitudinally representative studies. Method: Patterns of substance use among youth in Puerto Rico were examined using a longitudinal study (n = 663) of adolescents living on the island. The National Longitudinal Study of Youth was used to examine patterns of substance use among Hispanics living in the United States (n = 1445). Latent transition analysis was used to estimate the probability of membership in each stage of substance use and incidence of transitions between different substance use stages over time. Results: Six stages best described the heterogeneity in substance use among youth in Puerto Rico. Five stages were sufficient to describe patterns of substance use among youth in the United States. Youth living in Puerto Rico reported lower rates of smoking and illicit drug use, but higher rates of alcohol use, when compared with rates among Hispanics in the United States. Discussion: Similar patterns of substance use were identified for Hispanic youth living in the United States and youth living in Puerto Rico.Predictors of smoking cessation attempts and success following motivation-phase interventions among people initially unwilling to quit smoking
Klemperer, E. M., Mermelstein, R., Baker, T. B., Hughes, J. R., Fiore, M. C., Piper, M. E., Schlam, T. R., Jorenby, D. E., Collins, L., & Cook, J. W. (n.d.).Publication year
2020Journal title
Nicotine and Tobacco ResearchVolume
22Issue
9Page(s)
1446-1452AbstractIntroduction: Most people who smoke cigarettes are not willing (ie, not ready) to make a quit attempt (QA) at any given time. Unfortunately, interventions intended to increase QAs and the success of QAs are only modestly effective. Identifying processes leading to QAs and quitting success could guide intervention development. Aims and Methods: This is a secondary analysis of a randomized factorial trial of 6 weeks of motivation-phase interventions among primary care patients (N = 517) who were initially unwilling to quit but were willing to reduce their smoking. Using logistic regression, we controlled for treatment condition and tested whether baseline or change in smoking-related constructs after 6 weeks of treatment predicted (1) making an at least 24 h QA between weeks 6 and 26 and (2) quitting success at week 26 (7-day point-prevalence abstinence among those who made a QA). Predictors included cigarettes/day, time to first cigarette, motivation to quit, quitting self-efficacy, anticipated urges to smoke if quit, positive affect, negative affect, and time spent around others who smoke. Results: In multivariable models that included all smoking-related constructs, changes in the following variables predicted initiating a QA above and beyond other variables: greater baseline time to first cigarette (odds ratio [OR] = 1.60), increases in time to first cigarette (OR = 1.27), and increases in quitting self-efficacy (OR = 1.14). Increased motivation to quit predicted conversion of a QA into quitting success at 26 weeks (OR = 1.36). Conclusion: Predictors of making a QA differed from predictors of quitting success. Predictors of QAs and success could each serve as important treatment targets of motivation-phase interventions. Implications: Motivation-phase interventions for people initially unwilling to quit smoking cigarettes may be improved by striving to increase their (1) time to first cigarette and quitting self-efficacy to promote QAs and (2) motivation to quit to promote quit success. Future experimental tests of such interventions are needed to identify causal determinants of QAs and quitting success.Preventing mental health problems in children after high conflict parental separation/divorce study : An optimization randomized controlled trial protocol
O'Hara, K. L., Wolchik, S. A., Sandler, I. N., West, S. G., Reis, H. T., Collins, L., Lyon, A. R., & Cummings, E. M. (n.d.).Publication year
2023Journal title
Mental Health and PreventionVolume
32AbstractParental divorce is a childhood stressor that affects approximately 1.1 million children in the U.S. annually. The children at greatest risk for deleterious mental health consequences are those exposed to high interparental conflict (IPC) following the separation/divorce. Research shows that children's emotional security and coping efficacy mediate the impact of IPC on their mental health. Interventions targeting their adaptive coping in response to IPC events may bolster their emotional security and coping efficacy. However, existing coping interventions have not been tested with children exposed to high post-separation/divorce IPC, nor has any study assessed the effects of individual intervention components on children's coping with IPC and their mental health. This intensive longitudinal intervention study examines the mechanisms through which coping intervention components impact children's responses to interactions in interparental relationships. A 23 factorial experiment will assess whether, and to what extent, three candidate intervention components demonstrate main and interactive effects on children's coping and mental health. Children aged 9–12 (target N = 144) will be randomly assigned to one of eight combinations of three components with two levels each: (1) reappraisal (present vs. absent), (2) distraction (present vs. absent), (3) relaxation (present vs. absent). The primary outcomes are child-report emotional security and coping efficacy at one-month post-intervention. Secondary outcomes include internalizing and externalizing problems at the three-month follow-up. Based on data from this optimization phase RCT, intervention components will be selected to comprise a multi-component intervention and assessed for effectiveness in a subsequent evaluation phase RCT.PROC LCA : A SAS procedure for latent class analysis
Lanza, S. T., Collins, L., Lemmon, D. R., & Schafer, J. L. (n.d.).Publication year
2007Journal title
Structural Equation ModelingVolume
14Issue
4Page(s)
671-694AbstractLatent class analysis (LCA) is a statistical method used to identify a set of discrete, mutually exclusive latent classes of individuals based on their responses to a set of observed categorical variables. In multiple-group LCA, both the measurement part and structural part of the model can vary across groups, and measurement invariance across groups can be empirically tested. LCA with covariates extends the model to include predictors of class membership. In this article, we introduce PROC LCA, a new SAS procedure for conducting LCA, multiple-group LCA, and LCA with covariates. The procedure is demonstrated using data on alcohol use behavior in a national sample of high school seniors.Psychosocial Predictors of Young Adolescent Cigarette Smoking : A Sixteen‐Month, Three‐Wave Longitudinal Study
Collins, L., Sussman, S., Rauch, J. M., Dent, C. W., Johnson, C. A., Hansen, W. B., & Flay, B. R. (n.d.).Publication year
1987Journal title
Journal of Applied Social PsychologyVolume
17Issue
6Page(s)
554-573AbstractUnderstanding the psychosocial factors that predict cigarette smoking onset in young people is of crucial importance for prevention efforts. The present study examined prospective psychosocial predictors of smoking in a three‐wave longitudinal data set. Similar in design to an earlier study by Chassin, Presson, Sherman, Corty, and Olshavsky (1984), the present study replicated their work, and extended it by (a) using composite predictors derived from exploratory factor analysis, (b) including prior behavior as a predictor, (c) using a design extended over three waves of data collection, and (d) using a sample composed primarily of urban teenagers. Subjects were 3295 7th‐grade students at the beginning of the study. The subjects completed a questionnaire containing items tapping cigarette smoking behavior and psychosocial items that have previously been shown to predict smoking behavior. Forty‐one psychosocial items on the Wave 1 (initial) questionnaire were factor analyzed, and five factors were retained. Subscale scores were constructed based on these factors and were used as predictors. Regression analyses were performed using the subscales and pretest smoking frequency to predict a continuous measure of smoking, and discriminant analyses were performed to predict transitions between qualitative levels of smoking. Prior smoking behavior was the most important predictor of future smoking. Four of the subscales, Social Disapproval, Risk Taking/Rebelliousness, Perceived Smoking Prevalence, and Motivation to Comply, were significant predictors. One subscale, Physical Consequences from Smoking, was not predictive of smoking in any of the analyses. The effect sizes cross‐validated well. It is suggested that an integrative model of smoking initiation developed by Flay, d'Avernas, Best, Kersell, and Ryan (1983) best summarizes the results of the present study.Pubertal timing and the onset of substance use in females during early adolescence
Lanza, S. T., & Collins, L. (n.d.).Publication year
2002Journal title
Prevention ScienceVolume
3Issue
1Page(s)
69-82AbstractThe goal of this study is to examine in detail the relationship between pubertal timing and substance use onset using a sample of females from The National Longitudinal Study of Adolescent Health. The sample includes 966 females who were in 7th grade at Wave 1 and 8th grade at Wave 2. Participants in the sample are approximately 69% White, 20% African American, 4% Asian or Pacific Islander, 2% American Indian, 4% other, of Hispanic origin, and 1% other, not of Hispanic origin. Twenty percent of the females were identified as early maturers based on self-reports of body changes (increased breast size and body curviness) measured in 7th grade. These participants are hypothesized to be at increased risk for substance use onset. Important differences in substance use onset were found between early maturers and their on-time and late-maturing counterparts. During 7th grade, females in the early-maturing group are three times more likely to be in the most advanced stage of substance use (involving alcohol use, drunkenness, cigarette use, and marijuana use) than are those in the on-time/late group. Prevalence rates indicate that early maturers are more likely to have tried alcohol, tried cigarettes, been drunk, and tried marijuana. Prospective findings show that early developers are significantly more likely to transition out of the "No Substance Use" stage between 7th and 8th grade (47% for early developers vs. 22% for on-time and late developers). In addition, early developers are more likely to advance in substance use in general, regardless of their level of use at Grade 7.Recruiting and engaging smokers in treatment in a primary care setting : Developing a chronic care model implemented through a modified electronic health record
Piper, M. E., Baker, T. B., Mermelstein, R., Collins, L., Fraser, D. L., Jorenby, D. E., Smith, S. S., Christiansen, B. A., Schlam, T. R., Cook, J. W., Oguss, M., & Fiore, M. C. (n.d.).Publication year
2013Journal title
Translational Behavioral MedicineVolume
3Issue
3Page(s)
253-263AbstractAlmost 35 million U.S. smokers visit primary care clinics annually, creating a need and opportunity to identify such smokers and engage them in evidence-based smoking treatment. The purpose of this study is to examine the feasibility and effectiveness of a chronic care model of treating tobacco dependence when it is integrated into primary care systems using electronic health records (EHRs). The EHR prompted primary care clinic staff to invite patients who smoked to participate in a tobacco treatment program. Patients who accepted and were eligible were offered smoking reduction or cessation treatment. More than 65 % of smokers were invited to participate, and 12.4 % of all smokers enrolled in treatment-30 % in smoking reduction and 70 % in cessation treatment. The chronic care model developed for treating tobacco dependence, integrated into the primary care system through the EHR, has the potential to engage up to 4.3 million smokers in treatment a year.Recruiting and retaining first-year college students in online health research : Implementation considerations
Collins, L., Guastaferro, K., Tanner, A. E., Rulison, K. L., Miller, A. M., Milroy, J. J., Wyrick, D. L., & Collins, L. M. (n.d.).Publication year
2022Journal title
Journal of American College HealthAbstractObjective: Decreasing participation in intervention research among college students has implications for the external validity of behavioral intervention research. We describe recruitment and retention strategies used to promote participation in intervention research across a series of four randomized experiments. Method: We report the recruitment and retention rates by school for each experiment and qualitative feedback from students about recommendations for improving research participation. Results: There was considerable variation among schools’ recruitment (4.9% to 64.7%) and retention (12% to 67.8%) rates. Student feedback suggested study timing (e.g., early in the semester), communication strategies (e.g., social media), and incentive structure (e.g., guaranteed incentives) could improve research participation. The highest survey participation rate was observed at the university which mandated students to complete the intervention (but not the survey). Conclusions: Intervention scientists must consider the population and study context to make informed decisions related to recruitment and retention strategies.Replication in Prevention Science
Valentine, J. C., Biglan, A., Boruch, R. F., Castro, F. G., Collins, L., Flay, B. R., Kellam, S., Mościcki, E. K., & Schinke, S. P. (n.d.).Publication year
2011Journal title
Prevention ScienceVolume
12Issue
2Page(s)
103-117AbstractReplication research is essential for the advancement of any scientific field. In this paper, we argue that prevention science will be better positioned to help improve public health if (a) more replications are conducted; (b) those replications are systematic, thoughtful, and conducted with full knowledge of the trials that have preceded them; and (c) state-of-the art techniques are used to summarize the body of evidence on the effects of the interventions. Under real-world demands it is often not feasible to wait for multiple replications to accumulate before making decisions about intervention adoption. To help individuals and agencies make better decisions about intervention utility, we outline strategies that can be used to help understand the likely direction, size, and range of intervention effects as suggested by the current knowledge base. We also suggest structural changes that could increase the amount and quality of replication research, such as the provision of incentives and a more vigorous pursuit of prospective research registers. Finally, we discuss methods for integrating replications into the roll-out of a program and suggest that strong partnerships with local decision makers are a key component of success in replication research. Our hope is that this paper can highlight the importance of replication and stimulate more discussion of the important elements of the replication process. We are confident that, armed with more and better replications and state-of-the-art review methods, prevention science will be in a better position to positively impact public health.Research Design and Methods
Collins, L., & Collins, L. M. (n.d.).Publication year
2007Page(s)
V2-433-V2-442Abstract~Self-initiated smoking cessation among high school students
Hansen, W. B., Collins, L., Johnson, C. A., & Graham, J. W. (n.d.).Publication year
1985Journal title
Addictive BehaviorsVolume
10Issue
3Page(s)
265-271AbstractThe purpose of this study was to examine psychosocial predictors of self-initiated smoking cessation among high school students. Students from nine high schools were pretested using a questionnaire which assessed smoking behavior, beliefs about positive and negative consequences of smoking, moral attitudes toward smoking, normative expectations about smoking, rebelliousness, peer smoking and parent smoking. Smokers identified at pretest were reexamined three months and fifteen months later. Three variables, moral attitudes, peer smoking and positive beliefs about smoking significantly discriminated continuing smokers from quitters at the three-month posttest. Three different variables, negative beliefs about smoking, parental smoking and rebelliousness significantly discriminated between those who quit and later relapsed and those who quit and maintained their non-smoking status at the 15 month posttest. Smoking characteristics at pretest failed to discriminate either those who would quit or those who would maintain their non-smoking status. Results support the development of public information programs which encourage early cessation of smoking which feature the development of appropriate attitudes and beliefs and which foster social support.Seven ways to increase power without increasing N
Collins, L., Hansen, W. B., & Collins, L. M. (n.d.).Publication year
1994Journal title
NIDA Research Monograph SeriesIssue
142Page(s)
184-195AbstractMany readers of this monograph may wonder why a chapter on statistical power was included. After all, by now the issue of statistical power is in many respects mundane. Everyone knows that statistical power is a central research consideration, and certainly most National Institute on Drug Abuse grantees or prospective grantees understand the importance of including a power analysis in research proposals.Some design, measurement, and analysis pitfalls in drug abuse prevention research and how to avoid them : Let your model be your guide
Collins, L., & Collins, L. M. (n.d.).Publication year
1994Journal title
NIDA Research Monograph SeriesIssue
139Page(s)
95-114Abstract~Some methodological considerations in theory-based health behavior research
Collins, L., MacKinnon, D. P., & Reeve, B. B. (n.d.).Publication year
2013Journal title
Health PsychologyVolume
32Issue
5Page(s)
586-591AbstractAs this special issue shows, much research in social and personality psychology is directly relevant to health psychology. In this brief commentary, we discuss three topics in research methodology that may be of interest to investigators involved in health-related psychological research. The first topic is statistical analysis of mediated and moderated effects. The second is measurement of latent constructs. The third is the Multiphase Optimization Strategy, a framework for translation of innovations from social and personality psychology into behavioral interventions.Stopping, starting, and sustaining HIV antiretroviral therapy : a mixed-methods exploration among African American/Black and Latino long-term survivors of HIV in an urban context
Gwadz, M., Cleland, C. M., Freeman, R., Wilton, L., Collins, L., L. Hawkins, R., Ritchie, A. S., Leonard, N. R., Jonas, D. F., Korman, A., Cluesman, S., He, N., & Sherpa, D. (n.d.).Publication year
2021Journal title
BMC public healthVolume
21Issue
1AbstractBackground: Although periods of HIV antiretroviral therapy (ART) discontinuation have deleterious health effects, ART is not always sustained. Yet, little is known about factors that contribute to such ART non-persistence among long-term HIV survivors. The present study applied a convergent parallel mixed-methods design to explore the phenomena of stopping/starting and sustaining ART, focusing on low-socioeconomic status African American or Black and Latino persons living with HIV (PLWH) who face the greatest challenges. Methods: Participants (N = 512) had poor engagement in HIV care and detectable HIV viral load. All received structured assessments and N = 48 were randomly selected for in-depth interviews. Quantitative analysis using negative binomial regression uncovered associations among multi-level factors and the number of times ART was stopped/started and the longest duration of sustained ART. Qualitative data were analyzed using a directed content analysis approach and results were integrated. Results: Participants were diagnosed 18.2 years ago on average (SD = 8.6), started ART a median five times (Q1 = 3, Q3 = 10), and the median longest duration of sustained ART was 18 months (Q1 = 6, Q3 = 36). Factors associated with higher rates of stops/starts were male sex, transgender identity, cannabis use at moderate-to-high-risk levels, and ART- and care-related stigma. Factors associated with lower rates of stops/starts were older age, more years since diagnosis, motivation for care, and lifetime injection drug use (IDU). Factors associated with longer durations of sustained ART were Latino/Hispanic ethnicity, motivation for ART and care, and recent IDU. Factors associated with a shorter duration were African American/Black race, alcohol use at moderate-to-high-risk levels, and social support. Qualitative results uncovered a convergence of intersecting risk factors for stopping/starting ART and challenges inherent in managing HIV over decades in the context of poverty. These included unstable housing, which contributed to social isolation, mental health distress, and substance use concerns, the latter prompting selling (“diverting”) ART. Primarily complementary quantitative and qualitative findings described mechanisms by which risk/protective factors operated and ways PLWH successfully restart and/or sustain ART. Conclusions: The field focuses substantially on ART adherence, but greater attention to reducing the frequency of ART non-persistence is needed, along with creating social/structural conditions favorable for sustained ART.Successful Optimization of Tobacco Dependence Treatment in the Emergency Department : A Randomized Controlled Trial Using the Multiphase Optimization Strategy
Bernstein, S. L., Dziura, J., Weiss, J., Brooks, A. H., Miller, T., Vickerman, K. A., Grau, L. E., Pantalon, M. V., Abroms, L., Collins, L., & Toll, B. (n.d.).Publication year
2023Journal title
Annals of Emergency MedicineVolume
81Issue
2Page(s)
209-221AbstractStudy objective: Tobacco dependence treatment initiated in the hospital emergency department (ED) is effective. However, trials typically use multicomponent interventions, making it difficult to distinguish specific components that are effective. In addition, interactions between components cannot be assessed. The Multiphase Optimization Strategy allows investigators to identify these effects. Methods: We conducted a full-factorial, 24 or 16-condition optimization trial in a busy hospital ED to examine the performance of 4 tobacco dependence interventions: a brief negotiation interview; 6 weeks of nicotine replacement therapy with the first dose delivered in the ED; active referral to a telephone quitline; and enrollment in SmokefreeTXT, a free short-messaging service program. Study data were analyzed with a novel mixed methods approach to assess clinical efficacy, cost-effectiveness, and qualitative participant feedback. The primary endpoint was tobacco abstinence at 3 months, verified by exhaled carbon monoxide using a Bedfont Micro+ Smokerlyzer. Results: Between February 2017 and May 2019, we enrolled 1,056 adult smokers visiting the ED. Odd ratios (95% confidence intervals) from the primary analysis of biochemically confirmed abstinence rates at 3 months for each intervention, versus control, were: brief negotiation interview, 1.8 (1.1, 2.8); nicotine replacement therapy, 2.1 (1.3, 3.2); quitline, 1.4 (0.9, 2.2); SmokefreeTXT, 1.1 (0.7, 1.7). There were no statistically significant interactions among components. Economic and qualitative analyses are in progress. Conclusion: The brief negotiation interview and nicotine replacement therapy were efficacious. This study is the first to identify components of ED-initiated tobacco dependence treatment that are individually effective. Future work will address the scalability of the brief negotiation interview and nicotine replacement therapy by offering provider-delivered brief negotiation interviews and nicotine replacement therapy prescriptions.System identification modeling of a smoking cessation intervention
Timms, K. P., Rivera, D. E., Collins, L., & Piper, M. E. (n.d.). (PART 1).Publication year
2012Page(s)
786-791AbstractThis paper examines the use of system identification to describe time-varying phenomena in a smoking cessation intervention. The analysis is facilitated by the availability of intensive longitudinal data that enables the application of system identification techniques. Two model structures are considered; one involves the concept of statistical mediation, while the other describes a feedback mechanism. In fitting these models to intensive longitudinal data from a University of Wisconsin clinical trial that studied bupropion and counseling as smoking cessation aids, we focus on the relationship between craving and smoking. Here, we find craving features inverse response and smoking behavior features a dramatic reduction on the quit date, followed by a resumption in smoking. Analyzing the resulting models, we find that they differ in how they describe smoking resumption, and the case is made that the feedback mechanism more appropriately describes the relationship between craving and smoking.The acquisition and maintenance of safer sexual behaviors among injection drug users
Posner, S. F., Collins, L., Longshore, D., & Anglin, M. D. (n.d.).Publication year
1996Journal title
Substance Use and MisuseVolume
31Issue
14Page(s)
1995-2015AbstractThe current research tests stage-sequential models of safer sexual behavior using a new method for data analysis called Latent Transition Analysis (LTA). Results are presented from data collected on 359 injection drug users participating in a seroconversion study conducted by the UCLA Drug Abuse Research Center. We identified a six-stage model that adequately represented the data. Results indicate that respondents moved back and forth among high, medium, and low risk stages. This finding highlights the need for continual, sustained interventions to help maintain safer sex and drug using behaviors in highrisk groups.The effect of the timing and spacing of observations in longitudinal studies of tobacco and other drug use : Temporal design considerations
Collins, L., & Graham, J. W. (n.d.).Publication year
2002Journal title
Drug and alcohol dependenceVolume
68Issue
SUPPL.Page(s)
85-96AbstractThis article explores the impact of the temporal design, i.e. the sampling of times of measurement, on the statistical and substantive conclusions drawn from longitudinal biomedical and social science research. It is shown that for a study of a given duration, if observations are spaced too far apart the resulting data can support misleading conclusions, whereas if observations are spaced relatively close together, a much more veridical picture of the process of interest is provided. The application of these ideas in several areas is discussed, including correlation and regression analysis where a variable measured at one time is used to predict a variable measured at a later time; growth curve analyses; and analyses involving stage-sequential processes. We argue that longitudinal designs should relate the choice of timing and spacing of observations in longitudinal studies to characteristics of the processes being measured. In addition, consideration of the possible effects of measurement design on results of statistical analyses may aid in their interpretation. New approaches involving intensive data collection with much shorter measurement intervals, such as Ecological Momentary Assessment, are promising, but are costly and are not suitable for every research question. More information is needed to help guide researchers in their choice of temporal design.The Longitudinal Guttman Simplex : A New Methodology for Measurement of Dynamic Constructs in Longitudinal Panel Studies
Collins, L., Cliff, N., & Dent, C. W. (n.d.).Publication year
1988Journal title
Applied Psychological MeasurementVolume
12Issue
3Page(s)
217-230AbstractTraditional psychometric procedures can be inade quate for the measurement of dynamic constructs in longitudinal panel studies. This paper introduces an al ternative based on the longitudinal Guttman simplex (LGS) model, a measurement model developed espe cially for dynamic constructs measured longitudinally. The LGS is a model of cumulative, unitary develop ment. It is cumulative in the sense that as persons ac quire new skills (or abilities, or opinions), earlier ob tained skills are retained; it is unitary in the sense that all persons progress through a sequence of skills in the same skill order. CL, a consistency index that gives the researcher a measure of the extent to which the LGS model axioms are obeyed in a given dataset, is introduced. By making use of this consistency index, the researcher can develop scales uniquely sensitive to cumulative, unitary development. LGSCLUS, an explor atory procedure to find longitudinal Guttman scales in empirical datasets, is described. An artificial data study is reported, the purpose of which was to test the performance of LGSCLUS under controlled conditions. The artificial data study showed that, in general, LGSCLUS recovers longitudinal Guttman scales with a high degree of accuracy. There remains a need for measurement procedures for dynamic constructs exhib iting types of development other than cumulative and unitary. Index terms: Dynamic constructs, Gutt man simplex, Longitudinal panel studies, Mathemati cal models, Measurement theory, Scaling, Three-set data.The measurement of dynamic latent variables in longitudinal aging research : Quantifying adult development
Collins, L. (n.d.).Publication year
1991Journal title
Experimental Aging ResearchVolume
17Issue
1Page(s)
13-20AbstractDynamic latent variables involve systematic intraindividual change over time. Although it seems natural to apply traditional measurement theory to dynamic latent variables, in fact this is often inappropriate. Traditional measurement theory is based on the idea of static latent variables and offers little guidance to the researcher who wishes to measure a dynamic latent variable with a high degree of accuracy and validity. It is the contention of this article that measurement of a dynamic latent variable must start from a clearly defined substantive theory about human development. Two approaches that take this perspective are presented: the longitudinal Guttman simplex (LGS), a measurement model for dynamic latent variables undergoing irreversible cumulative, unitary development; and latent transition analysis (LTA), a more general latent class measurement model.The Measurement of Dynamic Latent Variables in Longitudinal Aging Research : Quantifying Adult Development
Collins, L. (n.d.).Publication year
1990Journal title
GerodontologyVolume
9Issue
4Page(s)
127-134AbstractDynamic latent variables involve systematic intraindividual change over time. Although it seems natural to apply traditional measurement theory to dynamic latent variables, in fact this is often inappropriate. Traditional measurement theory is based on the idea of static latent variables and offers little guidance to the researcher who wishes to measure a dynamic latent variable with a high degree of accuracy and validity. It is the contention of this article that measurement of a dynamic latent variable must start from a clearly defined substantive theory about human development. Two approaches that take this perspective are presented; the longitudinal Guttman simplex (LGS), a measurement model for dynamic latent variables undergoing irreversible cumulative, unitary development; and latent transition analysis (LTA), a more general latent class measurement model.The Microrandomized Trial for Developing Digital Interventions : Experimental Design and Data Analysis Considerations
Qian, T., Walton, A. E., Collins, L., Klasnja, P., Lanza, S. T., Nahum-Shani, I., Rabbi, M., Russell, M. A., Walton, M. A., Yoo, H., & Murphy, S. A. (n.d.).Publication year
2022Journal title
Psychological MethodsAbstractJust-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that use frequent opportunities for the intervention to be adapted-weekly, daily, or even many times a day. The microrandomized trial (MRT) has emerged for use in informing the construction of JITAIs. MRTs can be used to address research questions about whether and under what circumstances JITAI components are effective, with the ultimate objective of developing effective and efficient JITAI. The purpose of this article is to clarify why, when, and how to use MRTs; to highlight elements that must be considered when designing and implementing an MRT; and to review primary and secondary analyses methods for MRTs. We briefly review key elements of JITAIs and discuss a variety of considerations that go into planning and designing an MRT. We provide a definition of causal excursion effects suitable for use in primary and secondary analyses of MRT data to inform JITAI development. We review the weighted and centered least-squares (WCLS) estimator which provides consistent causal excursion effect estimators from MRT data. We describe how the WCLS estimator along with associated test statistics can be obtained using standard statistical software such as R (R Core Team, 2019). Throughout we illustrate the MRT design and analyses using the HeartSteps MRT, for developing a JITAI to increase physical activity among sedentary individuals. We supplement the HeartSteps MRT with two other MRTs, SARA and BariFit, each of which highlights different research questions that can be addressed using the MRT and experimental design considerations that might arise. (PsycInfo Database Record (c) 2022 APA, all rights reserved).The Multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART). New Methods for More Potent eHealth Interventions
Collins, L., Murphy, S. A., & Strecher, V. (n.d.).Publication year
2007Journal title
American journal of preventive medicineVolume
32Issue
5 SUPPL.Page(s)
S112-S118AbstractAbstract: In this article two new methods for building and evaluating eHealth interventions are described. The first is the Multiphase Optimization Strategy (MOST). It consists of a screening phase, in which intervention components are efficiently identified for inclusion in an intervention or for rejection, based on their performance; a refining phase, in which the selected components are fine tuned and issues such as optimal levels of each component are investigated; and a confirming phase, in which the optimized intervention, consisting of the selected components delivered at optimal levels, is evaluated in a standard randomized controlled trial. The second is the Sequential Multiple Assignment Randomized Trial (SMART), which is an innovative research design especially suited for building time-varying adaptive interventions. A SMART trial can be used to identify the best tailoring variables and decision rules for an adaptive intervention empirically. Both the MOST and SMART approaches use randomized experimentation to enable valid inferences. When properly implemented, these approaches will lead to the development of more potent eHealth interventions.