About

Linda M. Collins is a Professor of Global Public Health in the Department of Social and Behavioral Sciences at NYU School of Global Public Health, with a secondary appointment in the Department of Biostatistics. Her research focuses on the development, dissemination, and application of the multiphase optimization strategy (MOST), a framework aimed at enhancing the effectiveness, efficiency, economy, and scalability of behavioral, biobehavioral, and social-structural interventions. Collins has collaborated on research applying MOST in areas such as smoking cessation, prevention of excessive drinking and risky sexual behavior in college students, and HIV services. Her work has been funded by prominent agencies including the National Institute on Drug Abuse, the National Institute on Alcohol Abuse and Alcoholism, and the National Science Foundation. Collins has delivered over 150 presentations worldwide on MOST and has published in journals across behavioral science, quantitative methodology, medicine, and engineering. She has held tenured faculty positions at the University of Southern California and Penn State University, where she was a Distinguished Professor and Director of The Methodology Center. Her contributions have been recognized through numerous awards and honors, including fellowships in major psychological and behavioral societies, and she has received awards such as the Fulbright Specialist and the Society for Prevention Research President’s Award.

Research topics

• Medicine
• Psychology
• Internal medicine
• Psychiatry
• Political Science
• Clinical psychology
• Nursing
• Gerontology
• Sociology
• Physical therapy
• Computer Science
• Social psychology
• Environmental health
• Geography
• Surgery
• Engineering
• Statistics
• Management science
• Mathematics
• Data science

Selected publications

• Purpose-driven approaches to age estimation in Australian flying-foxes (Pteropus)

  Wildlife Research · 2025-03-05 · 5 citations

  articleOpen access

  Aging is a ubiquitous component of the life history and biological function of all species. In wildlife studies, estimates of age are critical in order to understand how a species’ ecology, biology and behaviour vary in parallel with its life-history events. Longitudinal studies that track individuals as they age are limited in fruit bats, as recapture is difficult for vagile species with nomadic lifestyles. Most studies estimate age by the broad categorisation of individuals with similar biological characteristics or morphometrics into age classes (e.g. sub-adult and adult). In this review, we systematically compile and compare the age classifications used across a range of studies on Australian flying-foxes (Pteropus). We discuss the associated challenges of those classifications and identify current knowledge gaps. The terminology, methodology and explanations behind age classifications were inconsistent across reviewed studies, demonstrating that age classifications are highly subjective – particularly when identifying reproductively immature individuals. Downstream analyses and cross-disciplinary data use are likely to be compromised as a result. Further known-aged studies of flying-foxes would assist in clarifying variations of key parameters among non-adult individuals. We also encourage greater consistency in age classification and reporting, ensuring that classifications are well defined and biologically sound.

  PublisherOA PDFDOI

• Integrating implementation science and intervention optimization

  Implementation Science · 2025-10-03 · 3 citations

  articleOpen access

  BACKGROUND: Implementation scientists increasingly recognize the value of multiple strategies to improve the adoption, fidelity, and scale up of an evidence-based intervention (EBI). However, with this recognition comes the need for alternative and innovative methods to ensure that the package of implementation strategies work well within constraints imposed by the need for affordability, scalability, and/or efficiency. The aim of this article is to illustrate that this can be accomplished by integrating principles of intervention optimization into implementation science. METHOD: We use a hypothetical example to illustrate the application of the multiphase optimization strategy (MOST) to develop and optimize a package of implementation strategies designed to improve clinic-level adoption of an EBI for smoking cessation. RESULTS: We describe the steps an investigative team would take using MOST for an implementation science study. For each of the three phases of MOST (preparation, optimization, and evaluation), we describe the selection, optimization, and evaluation of four candidate implementation strategies (e.g., training, treatment guide, workflow redesign, and supervision). We provide practical considerations and discuss key methodological points. CONCLUSION: Our intention in this methodological article is to inspire implementation scientists to integrate principles of intervention optimization in their studies, and to encourage the continued advancement of this integration.

  PublisherOA PDFDOI

• Optimizing Self-Monitoring in a Digital Weight Loss Intervention (Spark): Protocol for a Factorial Randomized Trial

  JMIR Research Protocols · 2025-09-23

  articleOpen access

  BACKGROUND: Self-monitoring is a vital component of behavioral obesity treatment. It often involves tracking dietary intake, physical activity, and body weight. However, the optimal combination of self-monitoring strategies that maximizes weight loss is unknown. To address this gap, we leverage a framework called the multiphase optimization strategy, which facilitates the identification of an intervention's "active ingredients" that promote weight loss and its "inactive ingredients" that have little impact, thus adding unnecessary patient effort and time demands. OBJECTIVE: This study aims to examine the unique and combined weight loss effects of 3 popular self-monitoring strategies (tracking dietary intake, steps, and body weight). METHODS: Spark was an optimization-randomized clinical trial that used a 2 × 2 × 2 full factorial design with 8 experimental conditions. Participants, US adults with overweight or obesity (N=176), were randomized to receive 0-3 self-monitoring strategies in a 6-month fully digital weight loss intervention. For each assigned strategy, participants were instructed to self-monitor daily via commercially available digital tools (a mobile app, wearable activity tracker, and smart scale) and received a corresponding goal (eg, a daily calorie goal) and weekly automated feedback. All participants received core intervention components, including weekly lessons and action plans informed by Social Cognitive Theory, to promote healthy eating and physical activity. Assessments occurred at baseline and at 1, 3, and 6 months. Weight was assessed objectively via a smart scale. The primary aim is to test the main effects of the 3 self-monitoring components and their interactions on weight change from baseline to 6 months. Secondary outcomes include change in BMI, caloric intake, diet quality, physical activity, and health-related quality of life, as well as 1- and 3-month weight change and the relation between self-monitoring engagement and weight change. Patterns of engagement will be operationalized as the percentage of days of self-monitoring during the 6-month intervention. Moderators of weight loss success will be explored to understand whether certain subgroups of individuals benefit more from specific self-monitoring strategies. We also conducted a separate embedded experiment to test the impact of a self-directed web-based orientation session on 6-month trial retention. After the intervention, semistructured qualitative interviews were conducted with a subset of participants to elucidate factors that impact engagement and its link to weight loss. RESULTS: Recruitment occurred from September 2023 to November 2024. Data collection was completed in June 2025. Data analysis is ongoing. CONCLUSIONS: This trial will provide evidence as to which self-monitoring strategies are the "active ingredients" in a fully digital weight loss intervention and begin to explore which subgroups may do best with which strategies. These results have potential for public health impact by maximizing weight loss while minimizing patient burden. TRIAL REGISTRATION: ClinicalTrials.gov NCT05249465, https://clinicaltrials.gov/study/NCT05249465. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/75629.

  PublisherDOI

• A Brief Engagement Intervention Adapted for Racial and Ethnic Minority Young Adults in Mental Health Services: Protocol for a Pilot Optimization Trial

  JMIR Research Protocols · 2025-05-05

  articleOpen access

  Background Young adults from racial and ethnic minority (REM) groups are at greater risk of disengaging from vital mental health services than their majority group peers. Emerging research suggests developmentally tailored interventions that enable personalized exploration of cultural and structural contexts; encourage trust in relationships with service providers; enhance hope for recovery; and increase self-efficacy to adhere to treatment can improve engagement among underserved REM young adults with mental health disorders. Objective Just Do You is a brief young adult treatment engagement intervention. Although Just Do You showed evidence of efficacy with medium effect sizes in a previous clinical trial, not all participants benefited, and some of the proposed mediators were not changed. Grounded in the multiphase optimization strategy (MOST), we propose to improve the provision and effects of Just Do You by testing a set of new candidate intervention components that complement the original Just Do You program. This can potentially enhance its effects on engagement and mental health service use for REM young adults. Methods A total of 3 new candidate behavioral intervention components and their putative mediators were designed in collaboration with REM young adults and other key informants. The new candidate components and their mechanisms of action are (1) cultural identity (perceived cultural competency), (2) future self (hope), and (3) understanding environments (self-efficacy). A pilot optimization randomized controlled trial will be conducted in an outpatient mental health setting with REM participants aged 18-34 years (N=80). The candidate components will be tested in a 23-factorial design where all participants will receive Just Do You and be randomly assigned to one of 8 experimental conditions, each composed of a unique combination of candidate components. We will assess the new components’ acceptability and feasibility, and explore preliminary evidence of their effects on the primary outcome (engagement in mental health care) and mediators at a 3-month follow-up assessment. Results The study began recruitment in December 2024 and is planned to continue through December 2026. Final study completion is planned for March 2027. The results will be disseminated via professional and scientific publications, presentations, and social media, as well as to members of the participant community. Conclusions Findings from this study will supply critical deployment-focused evidence to inform a future randomized controlled trial as the next step in this program of research. We ultimately aim to create an effective, efficient, and scalable intervention to improve engagement and mental health outcomes among REM young adults. Trial Registration ClinicalTrials.gov NCT06508450; https://clinicaltrials.gov/study/NCT06508450 International Registered Report Identifier (IRRID) DERR1-10.2196/68885

  PublisherDOI

• Addressing racial inequities: a systematic review of intervention programs for Black/African American children with autism spectrum disorder and attention-deficit hyperactivity disorder (2019–2024)

  Pediatric Medicine · 2025-08-01 · 2 citations

  article
  PublisherDOI

• Optimizing Interventions for Equitability: Some Initial Ideas

  Prevention Science · 2024-01-31 · 9 citations

  articleOpen accessSenior author

  Interventions (including behavioral, biobehavioral, biomedical, and social-structural interventions) hold tremendous potential not only to improve public health overall but also to reduce health disparities and promote health equity. In this study, we introduce one way in which interventions can be optimized for health equity in a principled fashion using the multiphase optimization strategy (MOST). Specifically, we define intervention equitability as the extent to which the health benefits provided by an intervention are distributed evenly versus concentrated among those who are already advantaged, and we suggest that, if intervention equitability is acknowledged to be a priority, then equitability should be a key criterion that is balanced with other criteria (effectiveness overall, as well as affordability, scalability, and/or efficiency) in intervention optimization. Using a hypothetical case study and simulated data, we show how MOST can be applied to achieve a strategic balance that incorporates equitability. We also show how the composition of an optimized intervention can differ when equitability is considered versus when it is not. We conclude with a vision for next steps to build on this initial foray into optimizing interventions for equitability.

  PublisherOA PDFDOI

• Cancer Precision-Prevention trial of Metformin in adults with Li Fraumeni syndrome (MILI) undergoing yearly MRI surveillance: a randomised controlled trial protocol

  Trials · 2024-02-03 · 14 citations

  articleOpen access

  BACKGROUND: Li-Fraumeni syndrome (LFS) is a rare autosomal dominant disease caused by inherited or de novo germline pathogenic variants in TP53. Individuals with LFS have a 70-100% lifetime risk of developing cancer. The current standard of care involves annual surveillance with whole-body and brain MRI (WB-MRI) and clinical review; however, there are no chemoprevention agents licensed for individuals with LFS. Preclinical studies in LFS murine models show that the anti-diabetic drug metformin is chemopreventive and, in a pilot intervention trial, short-term use of metformin was well-tolerated in adults with LFS. However, metformin's mechanism of anticancer activity in this context is unclear. METHODS: Metformin in adults with Li-Fraumeni syndrome (MILI) is a Precision-Prevention phase II open-labelled unblinded randomised clinical trial in which 224 adults aged ≥ 16 years with LFS are randomised 1:1 to oral metformin (up to 2 mg daily) plus annual MRI surveillance or annual MRI surveillance alone for up to 5 years. The primary endpoint is to compare cumulative cancer-free survival up to 5 years (60 months) from randomisation between the intervention (metformin) and control (no metformin) arms. Secondary endpoints include a comparison of cumulative tumour-free survival at 5 years, overall survival at 5 years and clinical characteristics of emerging cancers between trial arms. Safety, toxicity and acceptability of metformin; impact of metformin on quality of life; and impact of baseline lifestyle risk factors on cancer incidence will be assessed. Exploratory end-points will evaluate the mechanism of action of metformin as a cancer preventative, identify biomarkers of response or carcinogenesis and assess WB-MRI performance as a diagnostic tool for detecting cancers in participants with LFS by assessing yield and diagnostic accuracy of WB-MRI. DISCUSSION: Alongside a parallel MILI study being conducted by collaborators at the National Cancer Institute (NCI), MILI is the first prevention trial to be conducted in this high-risk group. The MILI study provides a unique opportunity to evaluate the efficacy of metformin as a chemopreventive alongside exploring its mechanism of anticancer action and the biological process of mutated P53-driven tumourigenesis. TRIAL REGISTRATION: ISRCTN16699730. Registered on 28 November 2022. URL: https://www.isrctn.com/ EudraCT/CTIS number 2022-000165-41.

  PublisherOA PDFDOI

• 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

  Translational Behavioral Medicine · 2024-05-25 · 4 citations

  articleOpen access

  Advances 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.

  PublisherOA PDFDOI

• Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology

  Annual Review of Clinical Psychology · 2024-02-05 · 53 citations

  reviewOpen access1st authorCorresponding

  To build a coherent knowledge base about what psychological intervention strategies work, develop interventions that have positive societal impact, and maintain and increase this impact over time, it is necessary to replace the classical treatment package research paradigm. The multiphase optimization strategy (MOST) is an alternative paradigm that integrates ideas from behavioral science, engineering, implementation science, economics, and decision science. MOST enables optimization of interventions to strategically balance effectiveness, affordability, scalability, and efficiency. In this review we provide an overview of MOST, discuss several experimental designs that can be used in intervention optimization, consider how the investigator can use experimental results to select components for inclusion in the optimized intervention, discuss the application of MOST in implementation science, and list future issues in this rapidly evolving field. We highlight the feasibility of adopting this new research paradigm as well as its potential to hasten the progress of psychological intervention science.

  PublisherDOI

• Empirical Development of a Behavioral Intervention for African American/Black and Latino Persons with Unsuppressed HIV Viral Load Levels: An Application of the Multiphase Optimization Strategy (MOST) Using Cost-Effectiveness as an Optimization Objective

  AIDS and Behavior · 2024-04-25 · 3 citations

  articleOpen access
  PublisherOA PDFDOI

Recent grants

• NIH Grant R23DA003673

  NIH · $60k · 1986

• Reinvigorating HIV Prevention and Care for People Who Use Drugs: Accelerating Progress and Sustaining Gains in the Midst of Societal Disruption

  NIH · $31.7M · 1998–2028

• NIH Grant P50CA143188

  NIH · $3.0M · 2014

• NIH Grant R21DA024266

  NIH · $1.1M · 2013

• NIH Grant R01DA004111

  NIH · $726k · 1996

Frequent coauthors

• William B. Hansen

  27 shared

• Jessica W. Cook

  William S. Middleton Memorial Veterans Hospital

  27 shared

• Megan E. Piper

  26 shared

• John W. Graham

  24 shared

• Marya Gwadz

  New York University

  23 shared

• Robert Freeman

  23 shared

• Stephanie T. Lanza

  Pennsylvania State University

  23 shared

• C. Anderson Johnson

  Vanderbilt University Medical Center

  21 shared

Awards & honors

• Fulbright Specialist, National University of Ireland Galway…
• Pauline Schmitt Russell Distinguished Career Award, Pennsylv…
• Evan G. and Helen G. Pattishall Outstanding Research Achieve…
• President’s Award, Society for Prevention Research (2004)
• Faculty Scholar Medal for the Social and Behavioral Sciences…