Implementation Research at NHLBI: Methodological and Design Challenges and Lessons Learned from the DECIPHeR Initiative.

NHLBI funded seven projects as part of the Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR) Initiative. They were expected to collaborate with community partners to (1) employ validated theoretical or conceptual implementation research frameworks, (2) include implementation research study designs, (3) include implementation measures as primary outcomes, and (4) inform our understanding of mediators and mechanisms of action of the implementation strategy. Several projects focused on late-stage implementation strategies that optimally and sustainably delivered two or more evidence-based multilevel interventions to reduce or eliminate cardiovascular and/or pulmonary health disparities and to improve population health in high-burden communities. Projects that were successful in the three-year planning phase transitioned to a 4-year execution phase. NHLBI formed a Technical Assistance Workgroup during the planning phase to help awardees refine study aims, strengthen research designs, detail analytic plans, and to use valid sample size methods. This paper highlights methodological and study design challenges encountered during this process. Important lessons learned included (1) the need for greater emphasis on implementation outcomes, (2) the need to clearly distinguish between intervention and implementation strategies in the protocol, (3) the need to address clustering due to randomization of groups or clusters, (4) the need to address the cross-classification that results when intervention agents work across multiple units of randomization in the same arm, (5) the need to accommodate time-varying intervention effects in stepped-wedge designs, and (6) the need for data-based estimates of the parameters required for sample size estimation.

Deciphering Disparities: The NHLBI Program on Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR).

Despite several ambitious national health initiatives to eliminate health disparities, spanning more than 4 decades, health disparities remain pervasive in the United States. In an attempt to bend the curve in disparities elimination, the National Heart, Lung, and Blood Institute (NHLBI) issued a funding opportunity on Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR) in March 2019. Seven implementation research centers and 1 research coordinating center were funded in September 2020 to plan, develop, and test effective implementation strategies for eliminating disparities in heart and lung disease risk. In the 16 articles presented in this issue of Ethnicity & Disease, the DECIPHeR Alliance investigators and their NHLBI program staff address the work accomplished in the first phase of this biphasic research endeavor. Included in the collection are an article on important lessons learned during technical assistance sessions designed to ensure scientific rigor in clinical study designs, and 2 examples of clinical study process articles. Several articles show the diversity of clinical and public health settings addressed including schools, faith-based settings, federally qualified health centers, and other safety net clinics. All strategies for eliminating disparities tackle a cardiovascular or pulmonary disease and related risk factors. In an additional article, NHLBI program staff address expectations in phase 2 of the DECIPHeR program, strategies to ensure feasibility of scaling and spreading promising strategies identified, and opportunities for translating the DECIPHeR research model to other chronic diseases for the elimination of related health disparities.

New NIH Primary and Secondary Prevention Research During 2012-2019.

INTRODUCTION: This manuscript characterizes primary and secondary prevention research in humans and related methods research funded by NIH in 2012‒2019. METHODS: The NIH Office of Disease Prevention updated its prevention research taxonomy in 2019‒2020 and applied it to a sample of 14,523 new extramural projects awarded in 2012-2019. All projects were coded manually for rationale, exposures, outcomes, population focus, study design, and type of prevention research. All results are based on that manual coding. RESULTS: Taxonomy updates resulted in a slight increase, from an average of 16.7% to 17.6%, in the proportion of prevention research awards for 2012‒2017; there was a further increase to 20.7% in 2019. Most of the leading risk factors for death and disability in the U.S. were observed as an exposure or outcome in <5% of prevention research projects in 2019 (e.g., diet, 3.7%; tobacco, 3.9%; blood pressure, 2.8%; obesity, 4.4%). Analysis of existing data became more common (from 36% to 46.5%), whereas randomized interventions became less common (from 20.5% to 12.3%). Randomized interventions addressing a leading risk factor in a minority health or health disparities population were uncommon. CONCLUSIONS: The number of new NIH awards classified as prevention research increased to 20.7% in 2019. New projects continued to focus on observational studies and secondary data analysis in 2018 and 2019. Additional research is needed to develop and test new interventions or develop methods for the dissemination of existing interventions, which address the leading risk factors, particularly in minority health and health disparities populations.

Assessment of Prevention Research Measuring Leading Risk Factors and Causes of Mortality and Disability Supported by the US National Institutes of Health.

Importance: No studies to date have examined support by the National Institutes of Health (NIH) for primary and secondary prevention research in humans and related methods research that measures the leading risk factors or causes of death or disability as outcomes or exposures. Objective: To characterize NIH support for such research. Design and Setting: This serial cross-sectional study randomly sampled NIH grants and cooperative agreements funded during fiscal years 2012 through 2017. For awards with multiple subprojects, each was treated as a separate project. Study characteristics, outcomes, and exposures were coded from October 2015 through February 2019. Analyses weighted to reflect the sampling scheme were completed in March through June 2019. Using 2017 data from the Centers for Disease Control and Prevention and 2016 data from the Global Burden of Disease project, the leading risk factors and causes of death and disability in the United States were identified. Main Outcomes and Measures: The main outcome was the percentage of the NIH prevention research portfolio measuring a leading risk factor or cause of death or disability as an outcome or exposure. Results: A total of 11 082 research projects were coded. Only 25.9% (95% CI, 24.0%-27.8%) of prevention research projects measured a leading cause of death as an outcome or exposure, although these leading causes were associated with 74.0% of US mortality. Only 34.0% (95% CI, 32.2%-35.9%) measured a leading risk factor for death, although these risk factors were associated with 57.3% of mortality. Only 31.4% (95% CI, 29.6%-33.3%) measured a leading risk factor for disability-adjusted life-years lost, although these risk factors were associated with 42.1% of disability-adjusted life-years lost. Relatively few projects included a randomized clinical trial (24.6%; 95% CI, 22.5%-26.9%) or involved more than 1 leading cause (3.3%; 95% CI, 2.6%-4.1%) or risk factor (8.8%; 95% CI, 7.9%-9.8%). Conclusions and Relevance: In this cross-sectional study, the leading risk factors and causes of death and disability were underrepresented in the NIH prevention research portfolio relative to their burden. Because so much is already known about these risk factors and causes, and because randomized interventions play such a vital role in the development of clinical and public health guidelines, it appears that greater attention should be given to develop and test interventions that address these risk factors and causes, addressing multiple risk factors or causes when possible.

The Importance of Evaluating Health Disparities Research.

Health disparity populations are socially disadvantaged, and the multiple levels of discrimination they often experience mean that their characteristics and attributes differ from those of the mainstream. Programs and policies targeted at reducing health disparities or improving minority health must consider these differences. Despite the importance of evaluating health disparities research to produce high-quality data that can guide decision-making, it is not yet a customary practice. Although health disparities evaluations incorporate the same scientific methods as all evaluations, they have unique components such as population characteristics, sociocultural context, and the lack of health disparity common indicators and metrics that must be considered in every phase of the research. This article describes evaluation strategies grouped into 3 components: formative (needs assessments and process), design and methodology (multilevel designs used in real-world settings), and summative (outcomes, impacts, and cost). Each section will describe the standards for each component, discuss the unique health disparity aspects, and provide strategies from the National Institute on Minority Health and Health Disparities Metrics and Measures Visioning Workshop (April 2016) to advance the evaluation of health disparities research.

NIH Primary and Secondary Prevention Research in Humans During 2012-2017.

INTRODUCTION: This paper provides the first detailed analysis of the NIH prevention research portfolio for primary and secondary prevention research in humans and related methods research. METHODS: The Office of Disease Prevention developed a taxonomy of 128 topics and applied it to 11,082 projects representing 91.7% of all new projects and 84.1% of all dollars used for new projects awarded using grant and cooperative agreement activity codes that supported research in fiscal years 2012-2017. Projects were coded in 2016-2018 and analyzed in 2018. RESULTS: Only 16.7% of projects and 22.6% of dollars were used for primary and secondary prevention research in humans or related methods research. Most of the leading risk factors for death and disability in the U.S. were selected as an outcome in <5% of the projects. Many more projects included an observational study, or an analysis of existing data, than a randomized intervention. These patterns were consistent over time. CONCLUSIONS: The appropriate level of support for primary and secondary prevention research in humans from NIH will differ by field and stage of research. The estimates reported here may be overestimates, as credit was given for a project even if only a portion of that project addressed prevention research. Given that 74% of the variability in county-level life expectancy across the U.S. is explained by established risk factors, it seems appropriate to devote additional resources to developing and testing interventions to address those risk factors.

A Machine Learning Approach to Identify NIH-Funded Applied Prevention Research.

INTRODUCTION: To fulfill its mission, the NIH Office of Disease Prevention systematically monitors NIH investments in applied prevention research. Specifically, the Office focuses on research in humans involving primary and secondary prevention, and prevention-related methods. Currently, the NIH uses the Research, Condition, and Disease Categorization system to report agency funding in prevention research. However, this system defines prevention research broadly to include primary and secondary prevention, studies on prevention methods, and basic and preclinical studies for prevention. A new methodology was needed to quantify NIH funding in applied prevention research. METHODS: A novel machine learning approach was developed and evaluated for its ability to characterize NIH-funded applied prevention research during fiscal years 2012-2015. The sensitivity, specificity, positive predictive value, accuracy, and F1 score of the machine learning method; the Research, Condition, and Disease Categorization system; and a combined approach were estimated. Analyses were completed during June-August 2017. RESULTS: Because the machine learning method was trained to recognize applied prevention research, it more accurately identified applied prevention grants (F1 = 72.7%) than the Research, Condition, and Disease Categorization system (F1 = 54.4%) and a combined approach (F1 = 63.5%) with p<0.001. CONCLUSIONS: This analysis demonstrated the use of machine learning as an efficient method to classify NIH-funded research grants in disease prevention.

An evaluation of constrained randomization for the design and analysis of group-randomized trials with binary outcomes.

Group-randomized trials are randomized studies that allocate intact groups of individuals to different comparison arms. A frequent practical limitation to adopting such research designs is that only a limited number of groups may be available, and therefore, simple randomization is unable to adequately balance multiple group-level covariates between arms. Therefore, covariate-based constrained randomization was proposed as an allocation technique to achieve balance. Constrained randomization involves generating a large number of possible allocation schemes, calculating a balance score that assesses covariate imbalance, limiting the randomization space to a prespecified percentage of candidate allocations, and randomly selecting one scheme to implement. When the outcome is binary, a number of statistical issues arise regarding the potential advantages of such designs in making inference. In particular, properties found for continuous outcomes may not directly apply, and additional variations on statistical tests are available. Motivated by two recent trials, we conduct a series of Monte Carlo simulations to evaluate the statistical properties of model-based and randomization-based tests under both simple and constrained randomization designs, with varying degrees of analysis-based covariate adjustment. Our results indicate that constrained randomization improves the power of the linearization F-test, the KC-corrected GEE t-test (Kauermann and Carroll, 2001, Journal of the American Statistical Association 96, 1387-1396), and two permutation tests when the prognostic group-level variables are controlled for in the analysis and the size of randomization space is reasonably small. We also demonstrate that constrained randomization reduces power loss from redundant analysis-based adjustment for non-prognostic covariates. Design considerations such as the choice of the balance metric and the size of randomization space are discussed.

Effectiveness of Two Community Health Worker Models of Tobacco Dependence Treatment Among Community Residents of Ohio Appalachia.

INTRODUCTION: Community health workers (CHW) may be effective in the delivery of tobacco dependence treatment with underserved groups. This study evaluated two evidence-based CHW models of treatment. It was hypothesized that smokers assigned to a CHW face-to-face condition would have higher abstinence at 12-month posttreatment than smokers enrolled in CHW referral to a state-sponsored quitline condition. Intrapersonal and treatment-related factors associated with abstinence at 12 months were determined. METHODS: A group-randomized trial was conducted with residents of 12 Ohio Appalachian counties with counties (n = 6) randomized to either a CHW face-to-face (F2F) or CHW quitline (QL) condition. Both conditions included behavioral counseling and free nicotine replacement therapy for 8 weeks. Follow-up data were collected at 3-, 6-, and 12-month posttreatment. Biochemically validated abstinence at 12 months served as the primary outcome. RESULTS: Seven hundred and seven participants were enrolled (n = 353 CHWF2F; n = 354 CHWQL). Baseline sample characteristics did not differ by condition. Using an intent-to-treat analysis (85.4% retention at 12 months), 13.3% of CHWF2F participants were abstinent at 12 months, compared to 10.7% of CHWQL members (OR = 1.28; 95% confidence interval [CI] = 0.810, 2.014; p = .292). No differences in abstinence were noted at 3 or 6 months by condition. Age, marital status, and baseline levels of cigarette consumption, depressive symptoms, and self-efficacy for quitting in positive settings were associated with abstinence, as was counseling dose during treatment. CONCLUSIONS: This research adds to the body of science evaluating the effectiveness of CHW models of tobacco dependence treatment. Both approaches may offer promise in low-resource settings and underserved regions. IMPLICATIONS: This 12-county community-based group-randomized trial in Ohio Appalachia adds to the body of science evaluating the effectiveness of CHW models of tobacco dependence treatment. Both CHW approaches may offer promise in low-resource settings and underserved regions. These findings are useful to national, state, and local tobacco control agencies, as they expand delivery of preventive health care services postadoption of the Affordable Care Act in the United States.

An assessment of US microbiome research.

Genome-enabled technologies have supported a dramatic increase in our ability to study microbial communities in environments and hosts. Taking stock of previously funded microbiome research can help to identify common themes, under-represented areas and research priorities to consider moving forward. To assess the status of US microbiome research, a team of government scientists conducted an analysis of federally funded microbiome research. Microbiomes were defined as host-, ecosystem- or habitat-associated communities of microorganisms, and microbiome research was defined as those studies that emphasize community-level analyses using 'omics technologies. Single pathogen, single strain and culture-based studies were not included, except symbiosis studies that served as models for more complex communities. Fourteen governmental organizations participated in the data call. The analysis examined three broad research themes, eight environments and eight microbial categories. Human microbiome research was larger than any other environment studied, and the basic biology research theme accounted for half of the total research activities. Computational biology and bioinformatics, reference databases and biorepositories, standardized protocols and high-throughput tools were commonly identified needs. Longitudinal and functional studies and interdisciplinary research were also identified as needs. This study has implications for the funding of future microbiome research, not only in the United States but beyond.

Enhancing Coordination Among the U.S. Preventive Services Task Force, Agency for Healthcare Research and Quality, and National Institutes of Health.

This paper focuses on the relationships among the U.S. Preventive Services Task Force (USPSTF); Agency for Healthcare Research and Quality (AHRQ); and NIH. After a brief description of the Task Force, AHRQ, NIH, and an example of how they interact, we describe the steps that have been taken recently by NIH to enhance their coordination. We also discuss several challenges that remain and consider potential remedies that NIH, AHRQ, and investigators can take to provide the USPSTF with the data it needs to make recommendations, particularly those pertaining to behavioral interventions.

Identifying state-level policy and provision domains for physical education and physical activity in high school.

BACKGROUND: It is important to quickly and efficiently identify policies that are effective at changing behavior; therefore, we must be able to quantify and evaluate the effect of those policies and of changes to those policies. The purpose of this study was to develop state-level physical education (PE) and physical activity (PA) policy domain scores at the high-school level. Policy domain scores were developed with a focus on measuring policy change. METHODS: Exploratory factor analysis was used to group items from the state-level School Health Policies and Programs Study (SHPPS) into policy domains. Items that related to PA or PE at the High School level were identified from the 7 SHPPS health program surveys. Data from 2000 and 2006 were used in the factor analysis. RESULTS: From the 98 items identified, 17 policy domains were extracted. Average policy domain change scores were positive for 12 policy domains, with the largest increases for "Discouraging PA as Punishment", "Collaboration", and "Staff Development Opportunities". On average, states increased scores in 4.94 ± 2.76 policy domains, decreased in 3.53 ± 2.03, and had no change in 7.69 ± 2.09 policy domains. Significant correlations were found between several policy domain scores. CONCLUSIONS: Quantifying policy change and its impact is integral to the policy making and revision process. Our results build on previous research offering a way to examine changes in state-level policies related to PE and PA of high-school students and the faculty and staff who serve them. This work provides methods for combining state-level policies relevant to PE or PA in youth for studies of their impact.

Developing a research agenda for cardiovascular disease prevention in high-risk rural communities.

The National Institutes of Health convened a workshop to engage researchers and practitioners in dialogue on research issues viewed as either unique or of particular relevance to rural areas, key content areas needed to inform policy and practice in rural settings, and ways rural contexts may influence study design, implementation, assessment of outcomes, and dissemination. Our purpose was to develop a research agenda to address the disproportionate burden of cardiovascular disease (CVD) and related risk factors among populations living in rural areas. Complementary presentations used theoretical and methodological principles to describe research and practice examples from rural settings. Participants created a comprehensive CVD research agenda that identified themes and challenges, and provided 21 recommendations to guide research, practice, and programs in rural areas.

State policies targeting junk food in schools: racial/ethnic differences in the effect of policy change on soda consumption.

OBJECTIVES: We estimated the association between state policy changes and adolescent soda consumption and body mass index (BMI) percentile, overall and by race/ethnicity. METHODS: We obtained data on whether states required or recommended that schools prohibit junk food in vending machines, snack bars, concession stands, and parties from the 2000 and 2006 School Health Policies and Programs Study. We used linear mixed models to estimate the association between 2000-2006 policy changes and 2007 soda consumption and BMI percentile, as reported by 90 730 students in 33 states and the District of Columbia in the Youth Risk Behavior Survey, and to test for racial/ethnic differences in the associations. RESULTS: Policy changes targeting concession stands were associated with 0.09 fewer servings of soda per day among students (95% confidence interval [CI] = -0.17, -0.01); the association was more pronounced among non-Hispanic Blacks (0.19 fewer servings per day). Policy changes targeting parties were associated with 0.07 fewer servings per day (95% CI = -0.13, 0.00). Policy changes were not associated with BMI percentile in any group. CONCLUSIONS: State policies targeting junk food in schools may reduce racial/ethnic disparities in adolescent soda consumption, but their impact appears to be too weak to reduce adolescent BMI percentile.

Tobacco use by male prisoners under an indoor smoking ban.

INTRODUCTION: Most correctional facilities have implemented tobacco restrictions in an effort to reduce costs and improve prisoner health, but little has been done to evaluate the impact of these policy changes. Patterns of tobacco use among prisoners were explored to determine the impact of incarceration in a facility with an indoor smoking ban on tobacco use behaviors. METHODS: Recently incarcerated male inmates (n = 200) were surveyed about their tobacco use prior to and during incarceration. RESULTS: Tobacco use was prevalent prior to arrest (77.5%) and increased during incarceration (81.0%). Though the number of cigarette smokers increased during imprisonment, per-capita cigarette consumption declined by 7.1 cigarettes/day (p < .001). Despite widespread tobacco use, most participants recognized that smoking is a cause of lung cancer (96.0%) and heart disease (75.4%) and that it can be addicting (97.5%). Most tobacco users (70.0%) reported a desire to quit, with 63.0% saying they intended to try quitting in the next year. CONCLUSIONS: Indoor smoking bans do not promote cessation in prisons but may reduce the amount of tobacco consumed. Though smoking is commonplace in prisons, most prisoners recognize the risks involved and wish to quit. This creates an ideal setting for intervention. Evidence-based cessation assistance should be made freely available to all incarcerated smokers.

The Memphis Girls' health Enrichment Multi-site Studies (GEMS): an evaluation of the efficacy of a 2-year obesity prevention program in African American girls.

OBJECTIVE: To determine the efficacy of a 2-year obesity prevention program in African American girls. DESIGN: Memphis GEMS (Girls' health Enrichment Multi-site Studies) was a controlled trial in which girls were randomly assigned to an obesity prevention program or alternative intervention. SETTING: Local community centers and YWCAs (Young Women's Christian Associations) in Memphis, Tennessee. PARTICIPANTS: Girls aged 8 to 10 years (N = 303) who were identified by a parent or guardian as African American and who had a body mass index (BMI) at or higher than the 25th percentile for age or 1 parent with a BMI of 25 or higher. INTERVENTIONS: Group behavioral counseling to promote healthy eating and increased physical activity (obesity prevention program) or self-esteem and social efficacy (alternative intervention). MAIN OUTCOME MEASURE: The BMI at 2 years. RESULTS: The BMI increased in all girls with no treatment effect (obesity prevention minus alternative intervention) at 2 years (mean, 0.09; 95% confidence interval [CI], -0.40 to 0.58). Two-year treatment effects in the expected direction were observed for servings per day of sweetened beverages (mean, -0.19; 95% CI, -0.39 to 0.09), water (mean, 0.21; 95% CI, 0.03 to 0.40), and vegetables (mean, 0.15; 95% CI,-0.02 to 0.30), but there were no effects on physical activity. Post hoc analyses suggested a treatment effect in younger girls (P for interaction = .08). The mean BMI difference at 2 years was -2.41 (95% CI, -4.83 to 0.02) in girls initially aged 8 years and -1.02 (95% CI, -2.31 to 0.27) in those initially aged 10 years. CONCLUSIONS: The lack of significant BMI change at 2 years indicates that this intervention alone is insufficient for obesity prevention. Effectiveness may require more explicit behavior change goals and a stronger physical activity component as well as supportive changes in environmental contexts.

Mediators affecting girls' levels of physical activity outside of school: findings from the trial of activity in adolescent girls.

BACKGROUND: Providing after school activities is a community level approach for reducing the decline in physical activity of girls as they reach early adolescence. PURPOSE: The purpose of this study was to examine psychosocial, environmental, and behavioral factors as potential mediators of after school physical activity in adolescent girls. METHODS: We assessed objectively measured levels of physical activity occurring outside of school and potential predictors and mediators of activity in girls participating in the Trial of Activity in Adolescent Girls (TAAG). RESULTS: We found that the TAAG intervention had a statistically significant and positive effect on out of school activity in the 2006 cohort. Self-efficacy, friends' social support, total social support, and difficulty getting to and from community activities mediated the level of moderate to vigorous physical activity in girls. CONCLUSIONS: Parents, communities, and schools should provide and enhance opportunities outside of the school day for adolescents to be active. Reducing transportation barriers and enlisting social support appear to be key.

Promoting physical activity in middle school girls: Trial of Activity for Adolescent Girls.

BACKGROUND: Physical activity is important for weight control and good health; however, activity levels decline in the adolescent years, particularly in girls. DESIGN: Group randomized controlled trial. SETTING/PARTICIPANTS: Middle school girls with English-speaking skills and no conditions to prevent participation in physical activity in 36 schools in six geographically diverse areas of the United States. Random, cross-sectional samples were drawn within schools: 6th graders in 2003 (n=1721) and 8th graders in 2005 (n=3504) and 2006 (n=3502). INTERVENTION: A 2-year study-directed intervention (fall 2003 to spring 2005) targeted schools, community agencies, and girls to increase opportunities, support, and incentives for increased physical activity. Components included programs linking schools and community agencies, physical education, health education, and social marketing. A third-year intervention used school and community personnel to direct intervention activities. MAIN OUTCOME MEASURES: The primary outcome, daily MET-weighted minutes of moderate-to-vigorous physical activity (MET-weighted MVPA), was assessed using accelerometry. Percent body fat was assessed using anthropometry. RESULTS: After the staff-directed intervention (pre-stated primary outcome), there were no differences (mean= -0.4, 95% CI= -8.2 to 7.4) in adjusted MET-weighted MVPA between 8th-grade girls in schools assigned to intervention or control. Following the Program Champion-directed intervention, girls in intervention schools were more physically active than girls in control schools (mean difference 10.9 MET-weighted minutes of MVPA, 95% CI=0.52-21.2). This difference is about 1.6 minutes of daily MVPA or 80 kcal per week. There were no differences in fitness or percent body fat at either 8th-grade timepoint. CONCLUSION: A school-based, community-linked intervention modestly improved physical activity in girls.

Physical activities in adolescent girls: variability in energy expenditure.

BACKGROUND: Understanding interindividual variability of energy expended in common activities is important for determining precise estimates of energy expenditure in surveillance studies and clinical trials. The purpose of this study was to describe the variability in energy expenditure for selected physical activities among adolescent girls. METHODS: Seventy-four adolescent girls (aged 13 to 14 years) participated in this cross-sectional investigation. Data were collected in 2001 and analyzed in 2004. Energy expenditure was measured by indirect calorimetry for ten activities and during a submaximal cycle ergometer test, which was used to estimate cardiorespiratory fitness. Variability in energy expended for the various activities was expressed by standard deviation, coefficient of variation, and range for three different energy expenditure variables: relative VO2 (milliliters per kilogram per minute), absolute VO2 (liters per minute(-1)), and calculated metabolic rate (kilojoules per minute). RESULTS: Depending on the expression of energy expenditure, coefficients of variation ranged from a low of 13.2% for climbing stairs to a high of 38.4% for playing a computer game. Some lower-intensity activities were associated with greater variability in energy expenditure. Bicycling showed consistently higher coefficients of variation across expressions of energy expenditure (29.1%, 37.7%, and 33.5% for relative VO2, absolute VO2, and calculated metabolic rate, respectively). CONCLUSIONS: Energy expenditure for common activities is highly variable in adolescent girls. The coefficient of variation was higher in some activities of lower intensity, regardless of energy expenditure expression. This variance may influence the evaluation of physical activity interventions, particularly with regard to issues such as a prescribed dose of activity and the statistical power to detect change.