Translational Research of the Acute Effects of Negative Emotions on Vascular Endothelial Health: Findings From a Randomized Controlled Study.

BACKGROUND: Provoked anger is associated with an increased risk of cardiovascular disease events. The underlying mechanism linking provoked anger as well as other core negative emotions including anxiety and sadness to cardiovascular disease remain unknown. The study objective was to examine the acute effects of provoked anger, and secondarily, anxiety and sadness on endothelial cell health. METHODS AND RESULTS: Apparently healthy adult participants (n=280) were randomized to an 8-minute anger recall task, a depressed mood recall task, an anxiety recall task, or an emotionally neutral condition. Pre-/post-assessments of endothelial health including endothelium-dependent vasodilation (reactive hyperemia index), circulating endothelial cell-derived microparticles (CD62E+, CD31+/CD42-, and CD31+/Annexin V+) and circulating bone marrow-derived endothelial progenitor cells (CD34+/CD133+/kinase insert domain receptor+ endothelial progenitor cells and CD34+/kinase insert domain receptor+ endothelial progenitor cells) were measured. There was a group×time interaction for the anger versus neutral condition on the change in reactive hyperemia index score from baseline to 40 minutes (P=0.007) with a mean±SD change in reactive hyperemia index score of 0.20±0.67 and 0.50±0.60 in the anger and neutral conditions, respectively. For the change in reactive hyperemia index score, the anxiety versus neutral condition group by time interaction approached but did not reach statistical significance (P=0.054), and the sadness versus neutral condition group by time interaction was not statistically significant (P=0.160). There were no consistent statistically significant group×time interactions for the anger, anxiety, and sadness versus neutral condition on endothelial cell-derived microparticles and endothelial progenitor cells from baseline to 40 minutes. CONCLUSIONS: In this randomized controlled experimental study, a brief provocation of anger adversely affected endothelial cell health by impairing endothelium-dependent vasodilation.

Diabetes and Multiple Long-term Conditions: A Review of Our Current Global Health Challenge.

Use of effective treatments and management programs is leading to longer survival of people with diabetes. This, in combination with obesity, is thus contributing to a rise in people living with more than one condition, known as multiple long-term conditions (MLTC or multimorbidity). MLTC is defined as the presence of two or more long-term conditions, with possible combinations of physical, infectious, or mental health conditions, where no one condition is considered as the index. These include a range of conditions such as cardiovascular diseases, cancer, chronic kidney disease, arthritis, depression, dementia, and severe mental health illnesses. MLTC has major implications for the individual such as poor quality of life, worse health outcomes, fragmented care, polypharmacy, poor treatment adherence, mortality, and a significant impact on health care services. MLTC is a challenge, where interventions for prevention and management are lacking a robust evidence base. The key research directions for diabetes and MLTC from a global perspective include system delivery and care coordination, lifestyle interventions and therapeutic interventions.

The effect of a multi-component behavior change technique intervention on medication adherence among individuals on primary prevention statin therapy: a dose-finding protocol.

BACKGROUND: In the USA, the primary cause of death and morbidity continues to be cardiovascular disease (CVD). Numerous trials have shown that statin medication reduces the likelihood of CVD events; it is a cornerstone of CVD prevention. However, studies have also indicated that up to 60% of the estimated 26.8 million Americans prescribed primary prevention statin treatment are nonadherent during the first year. Multi-component behavioral change technique (BCT) therapies have shown moderate promise in improving medication adherence as well as other positive health behaviors (such as physical activity). However, no research has looked at the duration of multi-component BCT intervention needed to result in a clinically significant improvement in statin adherence behaviors. This study aims to determine the necessary dose of a multi-component BCT intervention (defined as duration in weeks) to promote adherence to statin medication among those on primary prevention statin treatment by utilizing the modified time-to-event continuous reassessment method (TiTE-CRM). METHODS AND DESIGN: The study will utilize the modified TiTE-CRM in 42 participants, recruited in 14 cohorts of 3 participants each. The goal of this analysis is to identify the minimum effective dose (MED) of a multi-behavior change technique (BCT) intervention required to increase adherence to statins by 20% between baseline and follow-up periods. Using the TiTE-CRM method, the dose of the behavior intervention in weeks will be assigned to each cohort based on the performance of the prior cohort. At the end of the study, the intervention dose that has been found to be associated with a 20% increase in statin adherence among 80% of participants assigned to that dose will be identified as the MED. DISCUSSION: If successful, the current trial will provide additional guidance to researchers and clinicians seeking to increase statin medication adherence using a BCT intervention by identifying the dose (i.e., the duration) of an intervention required to meaningfully increase adherence. TRIAL REGISTRATION: ClinicalTrials.gov NCT05273736. Registered on March 10, 2022. https://www. CLINICALTRIALS: gov/ct2/show/NCT05273736.

Which measures of perceived vulnerability predict protective intentions-and when?

Assessing perceived vulnerability to a health threat is essential to understanding how people conceptualize their risk, and to predicting how likely they are to engage in protective behaviors. However, there is limited consensus about which of many measures of perceived vulnerability predict behavior best. We tested whether the ability of different measures to predict protective intentions varies as a function of the type of information people learn about their risk. Online participants (N = 909) read information about a novel respiratory disease before answering measures of perceived vulnerability and vaccination intentions. Type-of-risk information was varied across three between-participant groups. Participants learned either: (1) only information about their comparative standing on the primary risk factors (comparative-only), (2) their comparative standing as well as the base-rate of the disease in the population (+ base-rate), or (3) their comparative standing as well as more specific estimates of their absolute risk (+ absolute-chart). Experiential and affective measures of perceived vulnerability predicted protective intentions well regardless of how participants learned about their risk, while the predictive ability of deliberative numeric and comparative measures varied based on the type of risk information provided. These results broaden the generalizability of key prior findings (i.e., some prior findings about which measures predict best may apply no matter how people learn about their risk), but the results also reveal boundary conditions and critical points of distinction for determining how to best assess perceived vulnerability.

Testing Behavior Change Techniques to Increase Physical Activity in Middle-Aged and Older Adults: Protocol for a Randomized Personalized Trial Series.

BACKGROUND: Being physically active is critical to successful aging, but most middle-aged and older adults do not move enough. Research has shown that even small increases in activity can have a significant impact on risk reduction and improve quality of life. Some behavior change techniques (BCTs) can increase activity, but prior studies on their effectiveness have primarily tested them in between-subjects trials and in aggregate. These design approaches, while robust, fail to identify those BCTs most influential for a given individual. In contrast, a personalized, or N-of-1, trial design can assess a person's response to each specific intervention. OBJECTIVE: This study is designed to test the feasibility, acceptability, and preliminary effectiveness of a remotely delivered personalized behavioral intervention to increase low-intensity physical activity (ie, walking) in adults aged 45 to 75 years. METHODS: The intervention will be administered over 10 weeks, starting with a 2-week baseline period followed by 4 BCTs (goal-setting, self-monitoring, feedback, and action planning) delivered one at a time, each for 2 weeks. In total, 60 participants will be randomized post baseline to 1 of 24 intervention sequences. Physical activity will be continuously measured by a wearable activity tracker, and intervention components and outcome measures will be delivered and collected by email, SMS text messages, and surveys. The effect of the overall intervention on step counts relative to baseline will be examined using generalized linear mixed models with an autoregressive model that accounts for possible autocorrelation and linear trends for daily steps across time. Participant satisfaction with the study components and attitudes and opinions toward personalized trials will be measured at the intervention's conclusion. RESULTS: Pooled change in daily step count will be reported between baseline and individual BCTs and baseline versus overall intervention. Self-efficacy scores will be compared between baseline and individual BCTs and between baseline and the overall intervention. Mean and SD will be reported for survey measures (participant satisfaction with study components and attitudes and opinions toward personalized trials). CONCLUSIONS: Assessing the feasibility and acceptability of delivering a personalized, remote physical activity intervention for middle-aged and older adults will inform what steps will be needed to scale up to a fully powered and within-subjects experimental design remotely. Examining the effect of each BCT in isolation will allow for their unique impact to be assessed and support design of future behavioral interventions. In using a personalized trial design, the heterogeneity of individual responses for each BCT can be quantified and inform later National Institutes of Health stages of intervention development trials. TRIAL REGISTRATION: clinicaltrials.gov NCT04967313; https://clinicaltrials.gov/ct2/show/NCT04967313. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/43418.

Protocol of a feasibility study of a virtual personalized (N-of-1) trial for increasing low-intensity physical activity in older adults via habit formation.

Background: Personalized interventions that can be delivered remotely are needed to increase physical activity (PA) in older adults to reduce risk of CV disease and mortality. Prior research indicates that Behavioral Change Techniques (BCTs) (e.g., goal setting, self-monitoring, behavioral repetition) can instill a habit for increasing daily walking. However, past interventions relied on between-subject randomized clinical trials, which can only only be informative about response of the hypothetical average person. Personalized trial designs can identify the benefits of an intervention for a specific individual although extended periods are required for collecting frequent measurements within-subject. Advances in remote, virtual technologies (e.g., text messaging, activity trackers), integrated with automatic platforms, can meet these requirements because they capacitate delivery of BCT interventions, and collection of data during daily life without personal contact. This Stage I-b trial is designed test whether a virtual, personalized intervention is feasible and acceptable to older adults, can elicit participant adherence and exhibit preliminary evidence for efficacy. Methods: A series of up to 60 single-arm, personalized trials, involving no personal contact, will recruit adults, 45-75 years of age, to wear an activity tracker during a 2-week baseline and a 10-week intervention. Five BCT prompts to execute a walking plan will be delivered on a daily basis during the intervention phase. Participants will rate satisfaction with personalized trial components and whether automaticity of the walking plan can be achieved. Step-counts, adherence to the walking plan and self-monitoring of step-count will also be recorded.

Activation Versus Change as a Principle Underlying Intervention Strategies to Promote Health Behaviors.

BACKGROUND AND PURPOSE: Interventions are effective in promoting health behavior change to the extent that (a) intervention strategies modify targets (i.e., mechanisms of action), and (b) modifying targets leads to changes in behavior. To complement taxonomies that characterize the variety of strategies used in behavioral interventions, we outline a new principle that specifies how strategies modify targets and thereby promote behavior change. We distinguish two dimensions of targets-value (positive vs. negative) and accessibility (activation level)-and show that intervention strategies operate either by altering the value of what people think, feel, or want (target change) or by heightening the accessibility of behavior-related thoughts, feelings, and goals (target activation). METHODS AND RESULTS: We review strategies designed to promote target activation and find that nudges, cue-reminders, goal priming, the question-behavior effect, and if-then planning are each effective in generating health behavior change, and that their effectiveness accrues from heightened accessibility of relevant targets. We also identify several other strategies that may operate, at least in part, via target activation (e.g., self-monitoring, message framing, anticipated regret inductions, and habits). CONCLUSIONS: The Activation Vs. Change Principle (AVCP) offers a theoretically grounded and parsimonious means of distinguishing among intervention strategies. By focusing on how strategies modify targets, the AVCP can aid interventionists in deciding which intervention strategies to deploy and how to combine different strategies in behavioral trials. We outline a research agenda that could serve to further enhance the design and delivery of interventions to promote target activation.

Series of virtual light therapy interventions for fatigue: a feasibility pilot study protocol for a series of personalised (N-of-1) trials.

INTRODUCTION: Fatigue is one of the most commonly recorded patient symptoms that can result in deficits in aspects of psychomotor functioning, cognition, work performance and mood. Research shows that bright light and dim light therapy may be an efficacious way to reduce symptoms of fatigue. Still, the feasibility, scalability, individual treatment effects and adverse event heterogeneity of these treatments are unknown. METHODS AND ANALYSIS: The current study evaluates the feasibility, acceptability and effectiveness of a series of personalised (N-of-1) interventions for virtual delivery of bright light therapy and dim light therapy versus usual care treatment for fatigue in 60 participants. We hypothesise that this study will provide valuable information about implementing virtual, N-of-1 randomised controlled trials (RCTs) for fatigue. It will also offer results about determining participants' ratings of usability and satisfaction with the virtual, personalised intervention delivery system; evaluating participants' improvement of fatigue symptoms; and, in the long term, identify ways to integrate N-of-1 light therapy trials into patient care. ETHICS AND DISSEMINATION: This trial was approved by the Northwell Health Institutional Review Board. The trial results will be published in a peer-reviewed journal. All publications resulting from this series of personalised trials will follow the Consolidated Standards of Reporting Trials extension for N-of-1 trials CENT 2015 reporting guidelines. REGISTRATION DETAILS: This trial is registered in www. CLINICALTRIALS: gov (number NCT04707846). TRIAL REGISTRATION NUMBER: NCT04707846.

Emerging approaches to multiple chronic condition assessment.

Older adults experience a higher prevalence of multiple chronic conditions (MCCs). Establishing the presence and pattern of MCCs in individuals or populations is important for healthcare delivery, research, and policy. This report describes four emerging approaches and discusses their potential applications for enhancing assessment, treatment, and policy for the aging population. The National Institutes of Health convened a 2-day panel workshop of experts in 2018. Four emerging models were identified by the panel, including classification and regression tree (CART), qualifying comorbidity sets (QCS), the multimorbidity index (MMI), and the application of omics to network medicine. Future research into models of multiple chronic condition assessment may improve understanding of the epidemiology, diagnosis, and treatment of older persons.

Personalized (N-of-1) Trials for Patient-Centered Treatments of Multimorbidity.

Treatment of patients who suffer from concurrent health conditions is not well served by (1) evidence-based clinical guidelines that mainly specify treatment of single conditions and (2) conventional randomized controlled trials (RCTs) that identify treatments as safe and effective on average. Clinical decision-making based on the average patient effect may be inappropriate for treatment of those with multimorbidity who experience burdens and obstacles that may be unique to their personal situation. We describe how the personalized (N-of-1) trials can be integrated with an automatic platform and virtual/remote technologies to improve patient-centered care for those living with multimorbidity. To illustrate, we present a hypothetical clinical scenario-survivors of both coronavirus disease 2019 (COVID-19) and cancer who chronically suffer from sleeplessness and fatigue. Then, we will describe how the four standard phases of conventional RCT development can be modified for personalized trials and applied to the multimorbidity clinical scenario, outline how personalized trials can be adapted and extended to compare the benefits of personalized trials versus between-subject trial design, and explain how personalized trials can address special problems associated with multimorbidity for which conventional trials are poorly suited.

Introducing Data Sciences to N-of-1 Designs, Statistics, Use-Cases, the Future, and the Moniker 'N-of-1' Trial.

This article, an introduction to HDSR's "Personalized (N-of-1) Trials: Methods, Applications, and Impact" special issue, describes the rationale for a primer of the methods, data types and management, designs, and use cases for personalized (N-of-1) trials. It explains that the design and implementation of personalized (N-of-1) trials is only useful if patients volunteer for research involving them and actively participate in clinical services that use them. However, 'N-of-1 trials' may be an inadequate name to enact such patient engagement. The authors briefly review what patients have reported about the 'N-of-1' label and propose a more consumer-friendly moniker for this type of research and clinical approach to improve evidence-based science.

Now is the time to assess the effects of open science practiceswith randomized control trials.

We issue a call for the design and conduct of experimental trials to test the effects of researchers' adoption of Open Science (OS) research practices. OS emerged to address lapses in the transparency, quality, integrity, and reproducibility of research by proposing that investigators institute practices, such as preregistering study hypotheses, procedures, and statistical analyses, before launching their research. These practices have been greeted with enthusiasm by some parts of the scientific community, but empirical evidence of their effects relies mainly on observational studies; furthermore, questions remain about the time and effort required by these practices and their ultimate benefit to science. To assess the outcomes of OS research practices, we propose they be viewed as behavioral interventions for scientists and tested in randomized controlled trials (RCTs), to identify potential benefits and (unintended) harms. As this is a call to action rather than an action plan per se, we sketch out four potential trial designs to encourage further deliberation and planning. Experimental tests to document the outcomes of OS practices can provide evidence to optimize how scientists, funders, policymakers, and institutions utilize these strategies to advance scientific practice. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Measuring Multimorbidity: Selecting the Right Instrument for the Purpose and the Data Source.

BACKGROUND: Adults have a higher prevalence of multimorbidity-or having multiple chronic health conditions-than having a single condition in isolation. Researchers, health care providers, and health policymakers find it challenging to decide upon the most appropriate assessment tool from the many available multimorbidity measures. OBJECTIVE: The objective of this study was to describe a broad range of instruments and data sources available to assess multimorbidity and offer guidance about selecting appropriate measures. DESIGN: Instruments were reviewed and guidance developed during a special expert workshop sponsored by the National Institutes of Health on September 25-26, 2018. RESULTS: Workshop participants identified 4 common purposes for multimorbidity measurement as well as the advantages and disadvantages of 5 major data sources: medical records/clinical assessments, administrative claims, public health surveys, patient reports, and electronic health records. Participants surveyed 15 instruments and 2 public health data systems and described characteristics of the measures, validity, and other features that inform tool selection. Guidance on instrument selection includes recommendations to match the purpose of multimorbidity measurement to the measurement approach and instrument, review available data sources, and consider contextual and other related constructs to enhance the overall measurement of multimorbidity. CONCLUSIONS: The accuracy of multimorbidity measurement can be enhanced with appropriate measurement selection, combining data sources and special considerations for fully capturing multimorbidity burden in underrepresented racial/ethnic populations, children, individuals with multiple Adverse Childhood Events and older adults experiencing functional limitations, and other geriatric syndromes. The increased availability of comprehensive electronic health record systems offers new opportunities not available through other data sources.

National Institutes of Health Advancing Multimorbidity Research.

BACKGROUND: Multimorbidity, the co-occurrence of 2 or more chronic diseases, is more common than having a single chronic disease, especially among persons age 65 years and older. The routine measurement of multimorbidity can facilitate a better understanding of potential causes and interactions and promote more effective treatment and improved outcomes. OBJECTIVES: To present a multimorbidity research framework and identify gaps in the research literature related to multimorbidity. DESIGN: In preparation for an expert panel workshop convened in September 2018, planning committee members reviewed the literature and developed a guiding framework that informed the selection of topics and speakers. RESULTS: The framework, grounded in a patient-centered approach, incorporates the concept of concordant and discordant comorbidity, and includes potential causes, interactions, and outcomes. This work informed workshop presentations and discussion related to identifying and selecting the best available multimorbidity instruments and determining future research needs. CONCLUSIONS: Multimorbidity research can be advanced by addressing gaps in study design and target populations, and by increasing attention to universal outcome measurement.

The influence of multi-morbidities on colorectal cancer screening recommendations and completion.

PURPOSE: Patients' chronic disease burden can influence the likelihood that providers will recommend cancer screening and that patients will participate in it. Using data from the STOP CRC pragmatic study, we examined associations between chronic disease burden and colorectal cancer screening recommendation and use. METHODS: Participating STOP CRC clinics (n = 26) received either usual care or training to implement a mailed fecal immunochemical test (FIT) outreach program. Selected clinic patients (n = 60,187 patients) were aged 50-74 and overdue for colorectal cancer screening. We used logistic regression to examine the associations between FIT recommendations and completion and patients' chronic disease burden, calculated using the Charlson Comorbidity Index and the Chronic Illness and Disability Payment System. RESULTS: For each index, FIT recommendation odds were 8-9% higher among individuals with minimal chronic disease burden and 13-23% lower among individuals with high chronic disease burden (inverted U-shaped association). Among adults who were ordered a FIT, FIT completion odds were 20% lower for individuals with any, versus no, chronic condition and diminished with increasing disease burden (inverse linear association). CONCLUSIONS: Analysis showed an inverted U-shaped association between patients' chronic disease burden and providers' recommendation of a FIT and an inverse linear association between patients' chronic disease burden and FIT completion. ClinicalTrials.gov registration: NCT01742065.

Temporal and social comparative self-assessments of physical health in young, middle-aged, and young-old adults in the MIDUS study.

This study examined temporal and social comparisons of physical health status. Participants in two waves of the MIDUS cohort ranging in age from young adult to young-old (N = 2,408) rated current, past, and future physical health, as well as peer health. Past health was generally rated as better than current health (particularly among young adults). Young adults expected better future health; young-old adults expected declining health. All groups recalled their health as better than they reported a decade earlier. Middle-aged and young-old respondents expected more decline than they reported ten years later; young adults' ratings were consistent. The two older groups believed they were healthier than same-age peers, whereas younger respondents believed they were less healthy (though as healthy as the other age groups). The nature and trajectories of temporal and social comparisons of physical health across the lifespan suggest the need to examine their consequences for health behaviors.

Social Comparison Features in Physical Activity Promotion Apps: Scoping Meta-Review.

BACKGROUND: Smartphone apps promoting physical activity (PA) are abundant, but few produce substantial and sustained behavior change. Although many PA apps purport to induce users to compare themselves with others (by invoking social comparison processes), improvements in PA and other health behaviors are inconsistent. Existing literature suggests that social comparison may motivate PA for some people under some circumstances. However, 2 aspects of work that apply social comparison theory to PA apps remain unclear: (1) how comparison processes have been operationalized or harnessed in existing PA apps and (2) whether incorporating sources of variability in response to comparison have been used to tailor comparison features of apps, which could improve their effectiveness for promoting PA. OBJECTIVE: The aim of this meta-review was to summarize existing systematic, quantitative, and narrative reviews of behavior change techniques in PA apps, with an emphasis on social comparison features, to examine how social comparison is operationalized and implemented. METHODS: We searched PubMed, Web of Science, and PsycINFO for reviews of PA smartphone apps. Of the 3743 initial articles returned, 26 reviews met the inclusion criteria. Two independent raters extracted the data from these reviews, including the definition of social comparison used to categorize app features, the percentage of apps categorized as inducing comparison, specific features intended to induce comparison, and any mention of tailoring comparison features. For reference, these data were also extracted for related processes (such as behavioral modeling, norm referencing, and social networking). RESULTS: Of the included review articles, 31% (8/26) categorized app features as prompting social comparison. The majority of these employed Abraham and Michie's earliest definition of comparison, which differs from versions in later iterations of the same taxonomy. Very few reviews specified what dimension users were expected to compare (eg, steps, physical fitness) or which features of the apps were used to induce comparison (eg, leaderboards, message boards). No review referenced tailoring of comparison features. In contrast, 54% (14/26) reviews categorized features for prompting behavioral modeling and 31% (8/26) referenced tailoring app features for users' personal goals or preferences. CONCLUSIONS: The heterogeneity across reviews of PA apps and the absence of relevant information (eg, about dimensions or features relevant for comparison) create confusion about how to best harness social comparison to increase PA and its effectiveness in future research. No evidence was found that important findings from the broader social comparison literature (eg, that people have differing preferences for and responses to social comparison information) have been incorporated in the design of existing PA apps. Greater integration of the mobile health (mHealth) and social comparison literatures may improve the effectiveness of PA apps, thereby increasing the public health impact of these mHealth tools. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-https://osf.io/nh4td/.

Bridging Behavioral Science with Cancer Prevention and Control: Contributions of an NCI Working Group (2009-2019).

Human behavior plays a central role in cancer-related morbidity and mortality. Much behavior is, in turn, attributable to several core biological, cognitive, emotional, motivational, and interpersonal processes. Understanding the systematic and interactive impact of these processes can inform efforts to address cancer-relevant outcomes such as tobacco use, reliance on cancer misinformation, engagement in genetic testing, adherence to treatment, and acceptance of palliative care. Here, we review efforts of the NCI-supported Cognitive, Affective, and Social Processes in Health Research working group. Since 2009, this group has endeavored to advance the integration of basic behavioral science with cancer prevention and control by addressing topics such as the degree to which behavioral interventions alter cognitions underlying behavior, how technological innovations might facilitate behavioral measurement and intervention in areas such as smoking cessation, whether decision science principles might be applied to genetic testing decisions, how the cognitive effects of chemotherapy impair self-regulation, and the extent to which emotional factors drive palliative care decisions. The group has initiated numerous activities to build capacity for research in these areas including state-of-the-science meetings, written syntheses, conference symposia, and training workshops. We conclude with reflections about future needs as well as how to sustain such integrative efforts.

Measuring Cigarette Smoking Risk Perceptions.

Risk perception is an important construct in many health behavior theories. Smoking risk perceptions are thoughts and feelings about the harms associated with cigarette smoking. Wide variation in the terminology, definition, and assessment of this construct makes it difficult to draw conclusions about the associations of risk perceptions with smoking behaviors. To understand optimal methods of assessing adults' cigarette smoking risk perceptions (among both smokers and nonsmokers), we reviewed best practices from the tobacco control literature, and where gaps were identified, we looked more broadly to the research on risk perceptions in other health domains. Based on this review, we suggest assessments of risk perceptions (1) about multiple smoking-related health harms, (2) about harms over a specific timeframe, and (3) for the person affected by the harm. For the measurement of perceived likelihood in particular (ie, the perceived chance of harm from smoking based largely on deliberative thought), we suggest including (4) unconditional and conditional items (stipulating smoking behavior) and (5) absolute and comparative items and including (6) comparisons to specific populations through (7) direct and indirect assessments. We also suggest including (8) experiential (ostensibly automatic, somatic perceptions of vulnerability to a harm) and affective (emotional reactions to a potential harm) risk perception items. We also offer suggestions for (9) response options and (10) the assessment of risk perception at multiple time points. Researchers can use this resource to inform the selection, use, and future development of smoking risk perception measures. IMPLICATIONS: Incorporating the measurement suggestions for cigarette smoking risk perceptions that are presented will help researchers select items most appropriate for their research questions and will contribute to greater consistency in the assessment of smoking risk perceptions among adults.