2024 Annual Meeting & Scientific Sessions Pre-Conference Courses

All courses will be held on Wednesday, March 13, 2024, and are 2 hours in length.

Course fees are as follows:
Full/Associate/Emeritus Members: $100
Student/Trainee or Transitional Members: $50
Non-Members: $150

8:30 - 10:30 a.m.

Course 1: A How-to Guide for Defining, Measuring, and Alleviating Social Isolation and Loneliness in the Context of Older Adulthood

Social isolation is the objective lack of contact with other people. Loneliness is a related but distinct construct that refers to the subjective feelings of dissatisfaction with the quality of one’s social relationships or lack thereof. Each has been linked with a range of negative physical and mental health outcomes. Specifically, socially isolated individuals have a 29% increased mortality rate, compared to non-socially isolated individuals. Loneliness predicts poorer depression outcomes, anxiety, lower levels of physical activity, increase in work inefficiency, and suicidal ideation. Studying social isolation and loneliness in the context of older adulthood is of particular importance, as nearly one-fourth of older adults are considered socially isolated. This preconference course moves behavioral science upstream to promote education on social isolation and loneliness, as well as a comprehensive discussion on theoretical and methodological approaches to defining, measuring, and alleviating social isolation and loneliness both in the context of older adulthood and in the population more generally. Identifying risk for and conducting prevention toward the cause of negative outcomes has the added benefit of decreasing the likelihood of a cascade of mutually reinforcing, negative psychosocial, clinical or physical issues that arise from social isolation or loneliness. Given the complexity and cost of treating these negative health outcomes once they have developed, a risk-oriented preventative approach is more effective and efficient, while also greatly lessening human suffering. This course consists of a broad set of didactics on the distinction between the two constructs, definitions, evidence-based predictors and correlates, as well as an overview of measurement and interventions to reduce social isolation and loneliness in various populations, including older adults. Our team will prepare an interactive exercise in which attendees highlight the ways in which social isolation and loneliness may be relevant for the populations they treat clinically or research. Our course will combine experience and expertise from a social/health psychologist researcher and a geriatrician, and features a unique and valuable contribution on social isolation and loneliness in the current federal landscape.

Course 2: A Simple Introduction to Complex Survey Data Analysis

Behavioral scientists frequently analyze complex sample survey data (e.g., BRFSS, NHANES, NHIS, HINTS) for public health surveillance, evaluating policies/interventions, and identifying health disparities. These datasets typically sample a population using stratification, clustering, and unequal probability of selection. Appropriate statistical procedures are needed to account for these design features and failing to do so can yield biased estimates, incorrect standard errors, and increase the likelihood of committing a type I error. This pre-conference workshop will introduce participants to the basics of analyzing complex survey data, with an emphasis on common analytic mistakes related to variance estimation and sub-population analyses. In addition, the workshop will review the Preferred Reporting Items for Complex Sample Survey Analysis (PRICSSA), a new checklist for researchers publishing analyses of complex survey data. Lastly, attendees will practice analyzing complex survey data and reproduce results from selected published papers.

SBM student and transitional member attendees of this course may be reimbursed 100% of the course fee and other attendees may be reimbursed 75% of the course fee, pending grant underwriting from the National Institutes of Health Office of Disease Prevention.

Course 3: Demystifying Outcome Assessment: How to Select and Administer Participant-Reported Outcome Measures for Your Study

Selecting the right participant-reported outcome (PRO) measure for a health research study is a critical design decision. Researchers need to consider well-known measurement properties like validity and reliability, but also lesser well-known properties like diversity of the validation sample and the measure’s sensitivity to change. The primary objective of this pre-conference course is to assist researchers in making these decisions through didactic and interactive activities. We will share lessons learned from our own experiences selecting, implementing, and analyzing PROs in cancer research and facilitate an opportunity for attendees to apply these lessons to their own research. In the first hour, content expert facilitators will provide guidance on (1) confirming psychometric validation in the target population, (2) the benefits and drawbacks of selecting a general population versus disease-specific measure, (3) the pros and cons of selecting an established PRO versus creating a PRO tailored to the study objectives, and (4) essential properties of the PRO based on its planned use in hypothesis testing (e.g., meaningful change, between group differences). These didactic lessons will be interspersed with real-world examples from the facilitators’ experiences selecting, administering, and analyzing PROs in cancer research. We will conclude the didactic lesson with a discussion of the methods researchers can use to administer PROs (e.g., technology-mediated platforms, paper and pencil methods). In the second hour, the participants will break into small groups, each moderated by a facilitator. In advance of the workshop, participants will be asked to bring a research study idea or proposal. During the small groups, participants will introduce their study objective, and some of the key considerations they have in selecting a PRO. The group members and facilitator will provide initial feedback, and all participants will work to incorporate the feedback and information learned during the didactic lessons. Each participant will then provide an updated plan for PRO measure selection and administration. At the course conclusion, the full group will reconvene to discuss lessons learned, answer remaining questions, and provide take home materials. In addition to the small group activity, attendee participation will be facilitated through pre-course question solicitation, polling for knowledge testing, and question and answer sessions through didactic lessons.

Course 4: Design of a Dual Randomized Trial in a Type 2 Hybrid Effectiveness-Implementation Study

The objective of this workshop is to provide a step-by-step guide to designing a Dual Randomized Controlled Trial (DRCT). DRCTs are type 2 hybrid effectiveness-implementation studies that include two randomized trials: one testing implementation strategies and one testing an intervention. This study design offers efficiency by providing rigorous investigation of both implementation strategies and the intervention in one study. Nevertheless, our literature review has shown that type 2 studies that successfully use this design are rare. We believe that the low usage is related to the complexities encountered when attempting to apply the design as it involves much more than simply adding an outcome. This workshop will enable attendees to construct a well-designed type 2 hybrid DRCT in their own area of behavioral and implementation research. We will provide a step-by-step guide to designing a DRCT using a paradigm we have constructed that breaks down the components of the study design. We make a clear distinction between the dual strands that test the implementation strategy versus the intervention, and a minimum of three randomized arms is advocated. We suggest an active treatment arm that includes both the implementation strategy and intervention that are hypothesized to be superior. We suggest two comparison/control arms: one to test the implementation strategy and the second to test the intervention. Further, we recommend selection criteria for the two control arms that place emphasis on maximizing the utility of the study design to advance public health practice. After describing the design features of the DRCT, we will guide the audience through an example DRCT study and discuss different options for exposures and study arms. Following that preparation, attendees will receive support designing a DRCT in their area of research. This workshop will give both implementation scientists and those who are not familiar with implementation science a better understanding of the DRCT design and encouragement to use it. Our hope is that investigators will be encouraged to use the DRCT design to advance research that can improve health and reduce health disparities.

Course 5: Infusing Social Determinants of Health into Behavioral Medicine: From Research and Clinical Practice to Policy

Social determinants of health (SDoH) strongly influence inequities in health behaviors and outcomes. Thus, addressing SDoH is critical to achieving health equity. Yet, rarely does behavioral medicine training provide the necessary tools and techniques to adequately understand and address SDoH. Supplemental or ad hoc training is needed to ensure an SDoH perspective is incorporated in research design and evaluation, clinical practice, and policy efforts. Aligned with the 2024 SBM annual meeting theme (“Moving Behavioral Science Upstream”), this course is designed to facilitate the adaptation of upstream behavioral medicine strategies by enhancing perspectives and skills in SDoH. The course is intended for a wide audience (e.g., students/trainees, researchers, clinicians, practitioners) and aims to strengthen SDoH knowledge and awareness of SDoH resources. At the start of the course, SDoH experts will provide a didactic overview of SDoH as related to health behavior and outcomes, including theoretical frameworks and foundation, followed by examples of the application of SDoH in research, clinical practice, and health policy. A research-focused presentation will provide participants with resources for finding data and measurement tools on SDoH across the socio-ecological spectrum and will highlight how behavioral health intervention trials have been used to address SDoH. Next, a clinical practice-focused presentation will discuss best practices for tracking and addressing SDoH in patient populations, the use of SDoH screeners in clinical settings, and implementation of SDoH in clinical care and medical education. Finally, a policy-focused presentation will describe how SDoH data can inform policy, opportunities to address SDoH in policymaking and advocacy, and the unintended consequences of policies on SDoH. In the second part of the course, participants will be grouped by interest area, identified before the course via a brief survey. Small group dialogue will be facilitated by SDoH experts, who will mentor participants on strategies for incorporating SDoH in their own work. Participants will share a current SDoH-related challenge, opportunities they have to work with SDoH, and identify barriers and facilitators to addressing SDoH at their institution. Participants will identify actionable steps for incorporating a SDoH perspective into their work. The course will end with a large-group discussion and identification of additional strategies and resources.

Course 6: Motivational Interviewing: Partnering Together for Health Behavior Change

In order for clinicians to effectively partner with people to promote health behavior change, recognition of the multifactorial influences on change is critical. Motivational interviewing (MI) is an empirically-supported intervention for guiding health behavior change that emphasizes non-judgmental and collaborative interactions in order to support changes a person wants to make. The foundation of MI involves honoring autonomy and demonstrating appreciation of a person’s values, strengths, and barriers to making a behavioral change. This workshop will provide an overview of MI for health behavior change as well as practical applications to clinical work for practitioners from various specialty areas. Content will include education about the spirit of MI, which includes working together in partnership, acceptance of the person’s current behaviors, compassionate intention to give priority to the well-being of the person, and empowerment to make choices a person desires. Additionally, participants will learn about common tasks of MI as well as practical core skills to utilize in the course of clinical practice. The workshop will consist of didactics, discussion of case studies, practice of MI skills, and constructive feedback for participants. Aligned with the conference theme, this workshop will provide practical real-world examples of how MI is an evidence-based approach to partner with patients for health behavior change.

11 a.m. - 1 p.m.

Course 8: An A to Z and not just “K:” Considerations for Applying the Multiphase Optimization Strategy in Your Career Development Award

Interest in optimizing and improving the uptake of multicomponent interventions has skyrocketed in recent years, particularly among early career scientists. One framework for doing so is the multiphase optimization strategy (MOST). MOST is an innovative, iterative 3-phase framework that emphasizes careful management of research resources and ongoing improvement of a new or existing intervention. The ultimate goal of MOST is to identify an intervention that is not only effective, but also efficient, affordable, and scalable. While the engineering-inspired MOST is not new to behavioral and biobehavioral sciences, it is not standard in most scientific training, and many early career investigators struggle to successfully apply the framework in their grant submissions. MOST has the potential to set early career scientists up for success by guiding pilot work to scalable intervention development, optimization, and evaluation in a strategic and economic fashion. But how does one actually apply the MOST framework in a career development award application? This course is designed for attendees who are considering, actively planning, or preparing to conduct an optimization career development project. We will provide a brief overview of MOST using the phases of MOST (i.e., preparation, optimization, and evaluation) to frame the substantive elements of the course. A substantial amount of time will be devoted to the discussion of building and incorporating MOST in the writing of the candidate background, training plan, and research strategy sections of career development awards. We will cover practical skills, strategies, and tools for building mentorship teams, identifying training opportunities, and developing effective conceptual models. We will discuss optimization design considerations from the preparation through evaluation phases in the context of career development awards, highlighting issues around timeline, optimization criteria, randomization and management of experimental conditions, and analysis of data. Finally, we will discuss incorporating feedback and MOST-related grantsmanship. Throughout the session, we will share the practicalities and challenges of career development awards and MOST phase-specific activities with case exemplars from our presenters who currently have or have completed career development awards with optimization trials. Ample time will be allotted for open discussion and problem-solving followed by small groups led by the presenters for more individualized feedback. Attendees will be given a handout with the PowerPoint slides and a list of articles containing additional information.

Course 9: Best Practices for Conducting Efficient Systematic Reviews: An Example from Physical Activity Research

The science of synthesizing a body of research to determine the state of the evidence is rapidly emerging as an important strategy for identifying research gaps and informing policies and practice. Despite this important area of inquiry, there are few training opportunities to develop an understanding of systematic reviews. The wide array of review types (e.g., scoping, narrative, meta-analysis) all follow a common research process. This workshop will lay out the steps for developing a research question, deciding on the most appropriate type of review, identifying search terms, completing the search, extracting data and synthesizing the results to arrive at meaningful conclusions. In this workshop, experts will discuss systematic review methodology and illustrate some of the methods used to complete a systematic review examining the state of the science of physical activity research within the Society of Behavioral Medicine. Presenter 1 will describe the process of registering reviews in PROSPERO, identifying databases, selecting keywords, and compiling articles. They will also describe how artificial intelligence (AI) is evolving in a way that may better support this process. Presenter 2 will talk about defining your PICOD (i.e., population, intervention, comparison, outcome, and design) research question, and leveraging team science to respond to the need for an interdisciplinary perspective in the review process. Presenter 3 will discuss electronic tools for conducting a systematic review and provide concrete examples about how to use one of these tools (i.e., Covidence). Presenter 4 will discuss the types of reviews, evaluating the quality of articles in your review, building an evidence table, and choosing your data synthesis methods. Presenters 5 and 6 will provide insights about the importance of reliability in coding, processes for coming to consensus, and the iterative nature of data extraction. Attendees will use a flow chart and matching activity to practice matching types of data synthesis methods with types of reviews. In each presentation, experiential learning, personal narratives, and research challenges and solutions will be integrated into a set of individual and group exercises. Attendees will receive a short reading and worksheet in advance to help prepare them for the workshop.

Course 10: Collaborative Research Excellence: A Workshop on Academic-Industry Research Operations

This hands-on workshop is geared toward early and mid-career professionals who are currently working on or aim to develop academic industry collaborations (AIC). The overall goal is to help attendees build knowledge, skills, and confidence around research operations in this unique context. Over the course of the workshop, the presenters will lead participants through practical considerations for initiating, conducting, and disseminating AIC research based on their own experiences with AICs and best practice from the Research Operations (ReOps) community. Proven checklists and processes will be used as starting points to illustrate the steps involved in research operationalization, with a focus on understanding each partner’s goals, constraints, and points of view throughout the research process.. Over the course of the workshop, additional perspectives and insights – from both the facilitators’ and the participants’ unique experiences – will be added to a shared digital mural board. The workshop will work through ReOps’ Eight Pillars of Research Operations in the context of AIC: Environment, Scope, People, Organizational Context, Recruitment and Administration, Data and Knowledge Management, Governance, and Tools and Infrastructure. The main exercise in this workshop is a case study designed to generate conversation and idea sharing among participants rather than promote a particular point of view or determine a single set of solutions. Through the case study exercise, participants will apply knowledge gained through the interactive lecture portion of the workshop. Participants will pair up and represent either industry or academia to collaborate on research operationalization in the context of a specific example. Attendees may choose to focus on an AIC they seek to optimize (whether planned for the future or a current collaboration), or can work through a real world AIC example provided by the presenters. The presenters will shift between groups to facilitate discussions and support ideation. Toward the end of the session, pairs will have the option to share their experience and output through the digital mural board and discuss amongst the group. We welcome attendees to bring in their own ideas of an AIC they would like to pursue or an existing partnership they want to optimize, but this is not required.

Course 11: Sci Comm Studio

The Public Education Committee (PEC) leads the Society of Behavioral Medicine’s (SBM) science communication (SciComm) efforts through their flagship SciComm toolkit. The toolkit was first developed through an organization-wide strategic priority in response to the SBM membership’s growing SciComm interest. While many members passively learn about SciComm strategies and products, many are hesitant to take the first leap to develop content, delaying SciComm engagement or halting it altogether. Led by members of SBM’s PEC with over a decade of SciComm experience, the purpose of the proposed pre-conference workshop is to offer attendees exposure to numerous forms of SciComm as well as applied SciComm training in two areas of their choosing. First, attendees will hear brief presentations on how to create SciComm content (e.g., infographics, op-eds). Attendees will be instructed to come to the workshop with a particular work product in mind; a research publication, policy brief, or technical report are ideal. Next, attendees will choose two mini studios within the pre-conference workshop in which an expert will lead them through the development of two SciComm work products. Mini studio areas will include: (1) op-eds; (2) infographics and graphical abstracts; (3) reporting back to community members; (4) press interviews, social media, and communicating with a press office, reporter, or podcast host; and (5) writing SBM Healthy Living articles. Mini studios will combine coaching and instruction with active, guided working time alongside the SciComm experts. Attendees will leave with drafts of two SciComm products ready for further iteration with their research teams or dissemination. Sample products include: (1) an op-ed; (2) infographic aimed at fellow scientists, practitioners, study participants, or the lay public; (3) a study results document that researchers can provide to participants following data collection completion or a newsletter detailing interim results and study progress; (4) a social media thread or video explaining study results; (5) sample responses for common press interview questions; and (6) a Healthy Living article or blog post. Finally, the workshop will conclude with strategies for a SciComm dissemination plan that engages collaborators across multiple platforms and maximizes reach. This workshop meets the Annual Meeting’s governing priority of moving behavioral medicine upstream by helping members use their rigorous science to reach broader communities where they can impact meaningful change and ultimately influence health on population and individual levels.

Course 12: Utilizing Publicly Available Datasets: Developing and Analyzing a Theory-Driven Project

The primary goal of this preconference course is to demonstrate and teach the key skills required for developing and conducting a theory-driven project based on large publicly available datasets. The secondary aim of the preconference is to create connections between preconference attendees. We deliberately focus on the conference theme, Moving Behavioral Science Upstream as a call to come together to exchange ideas and educate each other on new methods to examine the factors that impact our behavior and health. Utilizing publicly available datasets can be valuable as the large sample size of these data sets help researchers and clinicians develop robust predictive and preventive models of factors and processes involved in health decision-making. However, there are challenges and misconceptions associated with using large datasets effectively. The preconference will provide the following education and skills for developing and conducting a theory driven project utilizing large publicly available datasets:

Advantages/disadvantages
Incorporating theory
Selecting a publicly available dataset
Variable selection
Weighing data
Data Integration (e.g., insurance)
Methodological considerations (e.g., biases, sampling issues)
Computational Resources (e.g., R, SAS, STATA)
Provide a resource with publicly available datasets/details on obtaining access

1:30 - 3:30 p.m.

Course 13: Adaptive Interventions: Innovations in Intervention and Experimental Design

Among the challenges faced by scientists is how to design and implement interventions to achieve the greatest societal benefit. Adaptive interventions are intervention delivery frameworks that guide how dynamic information about a person should be used in practice to decide whether and how to intervene. The goal is to deliver the right type of intervention, at the right time, while minimizing the delivery of unnecessary treatment. For example, an adaptive intervention for promoting physical activity might start with a minimal intervention including a wearable device to monitor and provide feedback about physical activity. Then, physical activity adherence data from the wearable device are used monthly to decide whether to continue or step up with coaching calls. A mobile intervention to support smoking cessation, might collect data about the person’s stress every minute via wearable devices and use this data to decide whether or not to deliver a mobile-based message to promote tobacco abstinence. Advances in digital technologies, such as electronic health records, mobile devices, and wearable sensors, have created unprecedented opportunities to adapt interventions on different timescales (e.g., slow—every few months or weeks; and fast—every day, every few hours, or at the scale of minutes) and at multiple levels (e.g., at the patient level, the clinic level, and the health system level). Recent years have seen explosive growth in research to develop adaptive interventions across various domains of health. This growth was powered by the rapid development of experimental designs that enable investigators to answer important scientific questions about how to optimize (i.e., systematically develop effective and resource-efficient) various types of adaptive interventions. These novel designs, which were developed by our team, include the sequential multiple assignment randomized trial (SMART), the micro-randomized trial (MRT), the hybrid experimental design (HED) and the multilevel SMART. This course will provide an introduction to recent methodological advances for optimizing adaptive interventions. Specifically, we will introduce novel types of adaptive interventions that vary in terms of the timescale and level at which data is used to decide whether and how to intervene. We will also discuss new experimental designs for optimizing each type of adaptive intervention, including the SMART, MRT, HED and the multilevel SMART.

Course 14: Applications of the ORBIT Model: Case Studies in the Design and Preliminary Testing of Health-Related Behavioral Interventions

This course will provide investigators whose research involves the design and testing of health-related behavioral interventions an opportunity to (1) better understand the defining features and appropriate study designs and methods in the ORBIT model, a framework for developing, refining and testing behavioral treatments for chronic diseases; (2) learn about issues that are critical to application of the model, including how to define “clinical” vs. “statistical” significance in the process of developing a behavioral intervention; and (3) apply knowledge about relevant designs, methodologies and funding opportunities for early-phase behavioral intervention research to obtain funding for and publish their own behavioral treatment development projects. The speakers will begin by providing a brief overview of the ORBIT model, followed by presentations on topics important to an advanced understanding and appropriate use of the ORBIT model. These include: (1) role of the ORBIT model in designing and refining complex interventions that reach beyond the individual to incorporate concepts such as health equity, community engagement, and multiple levels of influence; (2) understanding the concept of clinical significance and how it is operationalized within a program of behavioral intervention development; and (3) the value and appropriate use of proof-of-concept studies in designing behavioral interventions. Case studies will be provided throughout the session to illustrate the concepts being discussed and how a deep understanding of these topics can enhance a program of intervention development using the ORBIT model. The presenters will describe their own experiences in designing behavioral intervention development studies, bringing these “lessons learned” to bear in providing guidance to course attendees to help them design their own behavioral intervention development projects. The speakers will also walk participants through specific examples of successful grant applications and publications that have used the ORBIT model and provide advice and tips for maximizing success in grant submissions and publications that utilize this model. Participants will be asked to submit in advance a synopsis of a behavioral intervention development project they have or are considering submitting for funding, and/or specific questions they may have regarding the ORBIT model and the process of behavioral intervention development. The information and questions they submit will help to shape the presentations and discussions and will provide opportunities for presenters to follow-up with individual participants during the meeting or afterwards to address their questions and needs in the area of behavioral intervention development and preliminary testing.

Course 16: How to Build and Strengthen Community Engaged Research and Infrastructure in the Office of Community Outreach and Engagement

Although cancer survivorship has dramatically improved in the last decade, inequities in morbidity and mortality among marginalized populations have grown. These inequities can be attributed to structural, societal, and institutional factors. To address these inequities in cancer-related outcomes, community engagement is now a key part of the requirements for the 72 National Cancer Institute designated comprehensive cancer centers and included in the metrics for scoring. Community Engagement occurs on a continuum (Key et al., 2019; NIH, 2011) and remains an integral part of community-engaged and community-based participatory research (Wallerstein et al., 2020). Engaging communities experiencing inequities in cancer incidence, morbidity, and mortality to evaluate and address the factors contributing to poorer cancer-related outcomes is important but challenging. The proposed workshop will focus on presenting novel and successful approaches to engaging the community to address cancer-related inequities. Participants will hear from leading scholars in the country who are at the helm of Community Engagement at some of the nation’s top cancer centers via a panel discussion. This will be followed by a break -out session wherein the participants will discuss challenges within their own institutions and gain from panelists’ experience. We will then will focus on working to address internal inequities (infrastructure) and how researchers, directors, stakeholders can collaborate to reduce health inequities (upstream) through policy and other proactive ways via debriefing session. We will conclude this pre-conference session with dissemination of resources/practical guides to initiate and sustain community engaged research.

Course 17: Promotion and Tenure: Creating Goals and Demystifying the Process

Promotion and tenure are major academic career milestones, but candidates are often required to put themselves forward to gain these achievements. However, many do not self-nominate even when they may be qualified, especially women and members of minoritized groups. While structural barriers exist, the process can also be opaque and there may be a lack of guidance. Not moving through the promotion and tenure process has individual implications (i.e. pay, prestige) as well as implications for mentorship and science as a whole. This workshop is designed to help junior and mid-career faculty at a variety of institutions understand the common components of promotion and tenure (P&T) applications, learn about how to assemble commonly-required documents, and evaluate progress towards P&T milestones both independently and with mentorship. During the workshop, a diverse group of panelists from a variety of institutions (e.g. R1 university, academic medical center, smaller teaching-focused university) will provide an inside view into their experiences in the P&T process, including developing their candidate statement. Panelists will also include members of faculty development/promotion and tenure committees to share tips and common pitfalls in compiling materials. Attendees will be asked to bring their own P&T requirements and breakout sessions will focus on self-assessments. Panelists will also discuss how to identify appropriate letter-writers and attendees will brainstorm potential candidates within small groups. Questions and examples will be solicited from attendees prior to the workshop, and attendees will have ample opportunity throughout the workshop and during roundtables with experts to ask questions and discuss key issues related to these important career milestones.

Course 18: Timing and Inferences with Intensive Longitudinal Data

Researchers employ studies using intensive longitudinal data (ILD), such as wearable sensor data, ecological momentary assessments, and daily diaries, to investigate within-person processes both within and across days. ILD studies provide unique insights into within-person processes under ecologically valid conditions that can inform causal inferences and the development of just-in-time adaptive interventions. However, when designing ILD studies, researchers need to make careful decisions about the frequency (i.e., how often) and timing (i.e., when) of measurements, as well how to define a ‘day’, because these features impact interpretation of study results, causal inferences, and the predictive value of ILD. This workshop will guide participants on how often and when to measure constructs of interest in ILD studies and consider the implications of these design decisions on interpreting the results. Recommendations will be informed by the extensive experience of the presenters in designing, implementing, and interpreting the results of ILD studies across different populations and a variety of psychosocial constructs (e.g., affect, stress) and health behaviors (e.g., physical activity, alcohol use). Part 1 of the workshop, “Considerations for designing the frequency and timing of measurements in ILD studies”, will discuss the issues that need to be considered when deciding how often (e.g., one per day, every two hours) and when (e.g., morning, during physical activity, after eating) constructs are measured in ecological momentary assessment (EMA) and daily diary studies. We will discuss design issues, including differences in variability across individuals and constructs, the purpose of the assessment, concerns about recall biases/saliency/missing information, and participant needs. Part 2 of the workshop, “Considerations for interpreting results based on measurement frequency and timing in ILD studies,” will discuss the different approaches to defining a ‘day’ (e.g., traditional 24-hour calendar day versus a person-centric day based on sleep-wake cycle) and their influence on the interpretation of within-person processes both within- and across days. We will also discuss how the timing of assessments and temporal lags influence causal inferences and the predictive value of ILD measures within a day or a discrete event (e.g., physical activity or drinking bout). Throughout this interactive workshop, we will provide practical, applied examples from existing studies and discuss the pros and cons of each approach. The workshop will include multiple breakout sessions for participants to discuss their own examples and experiences and to debate the merits of different approaches. The goal of the workshop is to provide actionable knowledge for attendees looking to conduct highly impactful ILD studies with designs that support clear predictive inferences.

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