Publications

Allison M, Jensky N, Marshall SJ, Bertoni A. Cushman, M. Sedentary behavior is associated with adiposity-associated inflammation: the multi-ethnic study of atherosclerosis. Am J Prev Med 2012;42(1).

Carlson JA, Sallis JF, Ramirez ER, Patrick K, Norman GJ. Physical activity and dietary behavior change in internet-based weight loss interventions: comparing two multiple-behavior change indices. Prev Med. (in press).

Carlson JA, Sallis JF, Wagner N, Calfas KJ, Patrick K, Groesz LM, Norman, GJ. Brief physical activity-related psychosocial measures: reliability and construct validity. J Phys Act Health. (in press)

Millstein RA, Strobel J, Kerr J, Sallis JF, Norman GJ, Durant N, Harris, S, Saelens, B. Home, school, and neighborhood environmental factors and youth physical activity. Pediatr Exerc Sci. (in press).

Roesch, SC, Norman, GJ, Merz, E, Sallis, JF, Patrick, K. Longitudinal measurement invariance of psychosocial measures in physical activity research: An application to adolescent data. J Appl Soc Psychol. (in press).

Rosenberg DE, Kerr J, Norman GJ, Patrick K, Calfas KJ, Sallis JF. Promoting walking among older adults living in retirement communities. J Aging Phys Act. (in press).

Carlson, JJ, Eisenmann, JC, Norman, GJ, Ortiz, KA, Young, PC. Dietary fiber and nutrient density are inversely associated with the metabolic syndrome in U.S. adolescents. J Am Dietetic Assoc 2011;111:688–95.

Fowler JH, Settle JE, Christakis NA. Correlated genotypes in friendship networks, Proc Natl Acad Sci 2011;108(5):1993–1997. PMCID: 3033315.

Hill L, Baird S, Rybar J, Patrick K, Coimbra R.  Road safe seniors:  screening for age-related driving disorders in inpatient and outpatient settings. J Safety Res 2011;42(3):165-9.

Huang JS, Gottschalk M, Norman GJ, Calfas KJ, Sallis JF, Patrick K. Compliance with behavioral guidelines for diet, physical activity and sedentary behaviors is related to insulin resistance among overweight and obese youth. BMC Research Notes 2011;4:29. doi:10.1186/1756-0500-4-29.

Linke, SE, Gallo, L, Norman, GJ. Attrition and adherence rates of sustained vs. intermittent exercise interventions. Ann Behav Med 2011;42:197–209.

Maniccia DM, Davison KK, Marshall SJ, Manganello JA, Dennison BA. A meta-analysis of interventions that target children's screen time for reduction. Pediatrics 2011;128(1):e193-210.

Marshall SJ, Ramirez E. Reducing sedentary behavior: a new paradigm for physical activity promotion. Am J Lifestyle Med 2011;5: 518–30. DOI: 10.1177/1559827610395487.

Patrick, K, Calfas, KJ, Norman, GJ, Zabinski, MF, Sallis, JF, Rock, CL, Dillon, LW. Dietary and physical activity outcomes in a twelve-month web-based intervention for overweight men. Ann Behav Med 2011;42:391–401.

Patrick K, Wolszon L, Basen-Engquist K, et al., “CYberinfrastructure for COmparative effectiveness REsearch (CYCORE): improving data from cancer clinical trials,” J Transl Behav Med 2011;1(1):83–88, (10.1007/s13142-010-0005-z).

Ramirez ER, Norman GJ, Rosenberg D, Kerr J, Saelens BE, Durant N, Sallis JF. Adolescent screen time and rules to limit screen time in the home. J Adol Health 2011;48:379–85.

Rosenquist JN, Fowler JH, Christakis NA. Social network determinants of depression. Mol Psychiatry 2011;16(3):273–81.

Salmon J, Tremblay MS, Marshall SJ, Hume C. Health risks, correlates, and interventions to reduce sedentary behavior in young people. Am J Prev Med 2011;41(2), 197–206.

Baird S, Hill L, Rybar J, Patrick K, Coimbra R.  Age-related driving disorders: screening in hospitals and outpatients settings. Geriatr Gerontol Int 2010;10(4):288-94. doi: 10.1111/j.1447-0594.2010.00622.x.

Christakis NA, Fowler JH. Social network sensors for early detection of contagious outbreaks. PLoS One 2010;5(9):e12948. PMCID: 2939797

Farcas C, Farcas E, Krueger I. Requirements for service composition in ultra-large scale software-intensive systems. In Choppy C, Sokolsky O (eds), Foundations of computer software: future trends and techniques for development, 15th Monterey Workshop 2008, Budapest, Hungary, September 24-26, 2008. Revised selected papers, Berlin, Heidelberg: Springer, 2010:93-115.

Fowler JH, Christakis NA. Cooperative behavior cascades in human social networks. Proc Natl Acad Sci 2010;107(12):5334–8. PMCID: 2851803

Kelada A, Hill L, Lindsay S, Slymen D, Fortlage D, Coimbra R.  The U.S.-Mexico Border: A time trend analysis of border crossing injuries. Am J Prev Med 2010;40(3):548-50.

Kerr J, Norman GJ, Adams MA, Ryan S, Frank L, Sallis JF, Calfas KJ, Patrick K. Do neighborhood environments moderate the effect of physical activity lifestyle interventions in adults? Health Place 2010;16(5):903–8.

Marshall SJ, Gyi D. Evidence of health risks from occupational sitting; where do we stand? Am J Prev Med 2010;39(4):389–91.

McQueen A, Vernon SW, Rothman AJ, Norman GJ, Myers RE, Tilley BC. Examining the role of perceived susceptibility on colorectal cancer screening intention and behavior. Ann Behav Med 2010;40:205–17.

Norman GJ, Adams MA, Kerr J, Ryan S, Frank LD, Roesch SC. A latent profile analysis of neighborhood recreation environments in relation to adolescent physical activity, sedentary time, and obesity. J Public Health Manag Practice 2010;16,:411–9.

Norman, GJ, Carlson, JA, Sallis, JF, Wagner, N, Calfas, KJ, Patrick, K. Reliability and validity of brief psychosocial measures related to dietary behaviors. Int J Behav Nutr Phys Act 2010;7:56. doi:10.1186/1479-5868-7-56.

Roesch SC, Norman GJ, Villodas F, Sallis JF, Patrick K. Intervention-mediated effects for adult physical activity: A latent growth curve analysis. Soc Sci Med 2010;71:494-501.

Rosenberg DE, Norman GJ, Wagner N, Patrick K, Calfas KJ, Sallis JF. Reliability and validity of the sedentary behavior questionnaire (SBQ) for adults. J Phys Act Health 2010;7:697–705.

Rosenquist JN, Murabito J, Fowler JH, Christakis NA. The spread of alcohol consumption behavior in a large social network. Ann Intern Med 2010;152(7):426–33. PMID: 20368648

Rosenberg DE, Sallis JF, Kerr J, Maher J, Norman GJ, Durant N, Harris SK, Saelens BE. Brief scales to assess physical activity and sedentary equipment in the home. Int J Behav Nutr Phys Act 2010;7:1-11.

Rosenberg DE, Depp CA, Vahia IV, Reichstadt J, Palmer BW, Kerr J, Norman GJ, Jeste DV. Exergames for subsyndromal depression in older adults: a pilot study of a novel intervention. Am J Psychiatry 2010;18:221-6.Rovniak LS, Sallis JF,

Saelens BE, Frank LD, Marshall SJ, Norman GJ, Conway TF, Cain KL, Hovell, MF. Adults' physical activity patterns across life domains: Cluster analysis with replication. Health Psychol 2010;29(5):496–505.

Sallis JF, Kerr J, Carlson JA, Norman GJ, Saelens BE, Durant N, Ainsworth BE. Evaluating a brief self-report measure of neighborhood environments for physical activity research and surveillance: physical activity neighborhood environment scale (PANES). J Phys Act Health 2010;7:533–40.

Adams MA, Caparosa S, Thompson S, Norman GJ. Translating physical activity recommendations for overweight adolescents to steps per day. Am J Prev Med 2009;37:137-40.

Adams MA, Caparosa S, Thompson S, Norman GJ. Translating physical activity recommendations for overweight adolescents to steps per day. Am J Prev Med 2009;37:137–40.

Adams MA. Marshall SJ, Dillon L, Caparosa S, Ramirez E, Phillips J, Norman GJ. A theory-based framework for evaluating exergames as persuasive technology. In Proceedings of the 4th Annual International Persuasive Technology. Association for Computing Machinery Press, 2009. doi.acm.org/10.1145/1541948.1542006.

Adams MA, Ryan S, Kerr J, Sallis JF, Frank L, Patrick K, Norman GJ. Validation of the neighborhood environment walkability scale (NEWS) items using geographic information systems. J Phys Act Health 2009;6(suppl 1):S113-23.

Adams MA, Norman GJ, Hovell MF, Sallis JF, Patrick K. Reconceptualizing decisional balance in an adolescent sun protection intervention: mediating effects and theoretical interpretations. Health Psychol 2009;28(2):217-25.Objective: The Transtheoretical model (TTM) integrates principles of operant learning, such as stimulus control and reinforcement, and psychological factors, such as decisional balance. Understanding interrelationships between decisions, behavior, and consequences from multiple-theoretical perspectives can advance theory and inform development of more effective interventions.
Method: This analysis examined the mediating effects of a special case of the decisional balance construct in which the pros of competing behaviors (i.e., sun protection vs. exposure) were measured rather than the pros and cons of the same behavior. Participants included 819 adolescents (10 to 16 years old, 53.5% girls, 58.4% White) randomized to a 24-month expert system intervention (SunSmart) or a physical activity and nutrition comparison group.
Main Outcome Measures: Self-report measures included sun protection behaviors, pros for protection, and pros for exposure. Mediation analysis using latent growth curve models found both the treatment-to-mediator and mediator-to-behavior paths significant for decisional balance, producing an indirect effect of .323 (p < .01) and good model fit (CFI = .973, RMSEA = .055).
Results: Multiple strategies for conceptualizing and measuring decisional balance appear to be valid. Results are interpreted from the TTM and operant perspectives.

Christakis NA, Fowler JH. Connected: The surprising power of our social networks and how they shape our lives. Little Brown, 2009.

Fowler JH, Dawes CT, Christakis NA. Model of genetic variation in human social networks, Proc Natl Acad Sci 2009;106(6):1720–4. PMCID: 2644104.

Hill L, Mueller MR, Roussos S, Hovell M, Fontanesi J. Opportunities for the use of shared decision making tools in primary care. Fam Med 2009;41(5):350-5.

Huang JS, Sallis J, Patrick K. The role of primary care in promoting children's physical activity. Br J Sports Med 2009;43(1):19-21.Regular physical activity enhances health during childhood and adolescence and is important in setting the stage for participation in physical activity across the lifespan. Physician-patient interactions during childhood and adolescence provide important opportunities for clinicians to influence physical activity behaviours. This article reviews current physical activity recommendations for youth and the wide range of health benefits provided to youth from engaging in regular physical activity. It also outlines a practical counselling model, the 5As approach, that can guide clinical counselling for physical activity, and reviews how an increasingly important model of practice organisation, the Care Model, can be used to promote physical activity in children and adolescents. Family, social and environmental influences on child and adolescent physical activity are also addressed.

Patrick K, Raab F, Adams MA, Dillon L, Zabinski MF, Rock CL, Griswold WG, Norman, GJ. A text message-based intervention for weight loss: A pilot study. J Med Informatics Res 2009;11:1–9.

Roesch SC, Norman GJ, Adams MA, Kerr J, Sallis JF, Ryan S, Calfas KJ, Patrick K. Latent growth curve modeling of adolescent physical activity: testing parallel process and mediation models. J Health Psychol 2009;14(2):313-25.Data from a randomized clinical trial were used to examine the extent to which a health promotion intervention affected changes in psychosocial constructs and if so whether these in turn explained changes in physical activity (PA). PA and psychosocial data on 878 adolescents (ages 11-15) recruited through primary care providers (age M = 12.7 years, SD = 1.3; 58% white non-Hispanic) were measured at baseline, six and 12 months. Parallel process latent growth curve analyses found positive relationships between the growth trajectories of behavior change strategies, self-efficacy, family support, peer support and the growth trajectory of PA. However, mediation analyses did not reveal statistically significant intervention-mediated effects.

Rosenberg DE, Ding D, Sallis JS, Kerr J, Norman GJ, Durant N, Harris SK, Saelens BE. Neighborhood environment walkability scale for youth (NEWS-Y): Reliability and relationship with physical activity. Prev Med 2009;49:213–8.

Rosenberg D, Kerr J, Sallis JF, Patrick K, Moore DJ, King A. Feasibility and outcomes of a multilevel place-based walking intervention for seniors: a pilot study. Health Place 2009;15(1):173-9.This pilot study tested the feasibility and acceptability of a novel multilevel walking intervention for older adults in a continuing care retirement community (CCRC). The intervention included site-specific walking route maps, pedometers, and individualized goal setting. Pedometers were worn for self-monitoring and for the primary outcome (steps per day). Surveys at pre- and post-intervention assessed daily activities, benefits, barriers, route use, quality of life, and satisfaction. Steps per day were very low at baseline and increased significantly at post-test. The findings indicate that a multilevel site-specific intervention is feasible and acceptable for increasing steps among seniors living in a CCRC.

Sallis JF, Linton LS, Kraft MK, Cutter CL, Kerr J, Weitzel J, Wilson A, Spoon C, Harrison ID, Cervero R, Patrick K, Schmid TL, Pratt M. The Active Living Research program: six years of grantmaking. Am J Prev Med 2009;36(2 S):S10-21.Changes in policies and built environments are advocated as part of efforts to increase physical activity, but in 2001 the knowledge base to inform these changes was limited. The Robert Wood Johnson Foundation addressed this deficit by initiating Active Living Research (ALR). The mission of ALR was to stimulate and support research that could guide the improvement of environments, policies, and practices to promote active living. The program's goals were to (1) build the evidence base about environmental and policy factors related to physical activity, (2) build the capacity of researchers in multiple fields to collaborate, and (3) inform and facilitate policy change. To build the evidence base, 121 grants were supported with $12.5 million. Efforts were made to support new investigators, fund investigators from numerous disciplines, and increase the demographic diversity of researchers. Activities to build capacity to conduct collaborative research included annual conferences, journal supplements, seminars for multiple disciplines, and the posting of environmental measures. Coordination with Active Living Leadership was a primary means of communicating research to policymakers. Other activities to facilitate the application of research included research summaries written for nonresearchers, collaborations with Active Living by Design, several components of the website (www.activelivingresearch.org), and using policy relevance as a funding criterion. Two independent evaluations were accomplished, and they concluded that ALR made progress on all three goals. ALR has been renewed through 2012. The new mission is to use a $15.4 million research budget to contribute to reversing the childhood obesity epidemic, especially among youth in the highest-risk groups.

Christakis NA, Fowler JH. The collective dynamics of smoking in a large social network. N Engl J Med 2008;358(21):2249–58. PMCID: 2822344.

Demark-Wahnefried W, Rock CL, Patrick K, Byers T. Lifestyle interventions to reduce cancer risk and improve outcomes. Am Fam Physician 2008;77(11):1573-8.There are more than one half million cancer deaths in the United States each year, and one third of these deaths are attributed to suboptimal diet and physical activity practices. Maintaining a healthy weight, staying physically active throughout life, and consuming a healthy diet can substantially reduce the lifetime risk of developing cancer, as well as influence overall health and survival after a cancer diagnosis. The American Cancer Society's Nutrition and Physical Activity Guidelines serve as a source document for communication, policy, and community strategies to improve dietary and physical activity patterns among Americans. In 2006, they published updated guidelines for the primary prevention of cancer and guidelines for improving outcomes among cancer survivors through tertiary prevention. These two sets of guidelines have similar recommendations, including: achievement and maintenance of a healthy weight; regular physical activity of at least 30 minutes per day and at least five days per week; a plant-based diet high in fruits, vegetables, and whole grains and low in saturated fats and red meats; and moderate alcohol consumption, if at all. Physicians are encouraged to find teachable moments to impart appropriate nutrition, physical activity, and weight management guidance to their patients, and to support policies and programs that can improve these factors in the community to reduce cancer risk and improve outcomes after cancer.

Demchak B, Ermagan V, Farcas C, Farcas E, Krüger IH, Menarini M. Rich services: addressing challenges of ultra-large-scale software-intensive systems. In Proceedings of the ICSE 2nd International Workshop on Ultra-Large-Scale Software-Intensive Systems (ULSSIS 2008), Leipzig, Germany. New York: ACM, May 2008:29–32

Fowler JH, Christakis NA. The dynamic spread of happiness in a large social network. Br Med J 2008;337:a2338. PMCID: 2600606.

Fowler JH, Christakis NA. Estimating peer effects on health in social networks. J Health Econ 2008;27(5):1400–5.

Fowler JH, Schreiber D. Biology, politics, and the emerging science of human nature. Science 2008;322(5903):912–4. PMID: 18988845

Kerr J, Patrick K, Norman G, Stein MB, Calfas K, Zabinski M, Robinson A. Randomized control trial of a behavioral intervention for overweight women: impact on depressive symptoms. Depress Anxiety 2008;25(7):555-8.Phone and Internet-based interventions can improve the management of depression in primary care, and interventions using these communication channels are increasingly used to improve behaviors such as diet and physical activity. Increased physical activity has been shown to improve depressive symptoms, but to date there are no reports of the effects of a phone and Internet diet and exercise intervention on symptoms of depression in patients seen in primary care. This study assessed depressive symptoms in 401 participants in a randomized control trial of a 12-month primary care, phone and Internet-based behavioral intervention for overweight women. A one-way analysis of variance examining the mean change in Center for Epidemiological Studies Depression (CESD) score from baseline to 12 months, controlling for age, education, marital status, and employment showed that those receiving the intervention significantly decreased their CESD scores (P=.03) more than those receiving standard care. Although the intervention did not target depressed individuals or present material relating to mood management, those with probable depression (27% of the whole sample) showed clinically important improvements-a mean five-point change on the CESD short form. Participants who engaged more readily with the intervention were more likely to reduce their depression scores. A 1-year primary care based phone and Internet diet and exercise intervention can improve depressive symptoms in overweight women. Given the promise of phone and Internet-based interventions to improve both depression and lifestyle-related behaviors, and given that such interventions could extend the reach of primary care to many individuals at relatively low cost, these results suggest the need for further research, including the effects of additional mood management components.

Kerr J, Norman GJ, Sallis JF, Patrick K. Exercise AIDS, neighborhood safety, and physical activity in adolescents and parents. Med Sci Sports Exerc 2008;40(7):1244 -8.Purpose: To investigate the relationships among exercise aids available at home, physical activity, and perceived neighborhood safety.
Methods: Physical activity was assessed using the 7-d recall interview for adolescents (n = 878) and the International Physical Activity Questionnaire for parents (n = 853). Parents reported exercise aids such as fitness equipment, running shoes, and dogs in their household using a 16-item checklist and perceptions of neighborhood safety using the Neighborhood Environment Walkability Scale. Physical activity scores were dichotomized to represent meeting weekly guidelines for children (300 min) and adults (150 min). Logistic regression analyses investigated the interaction between exercise equipment and neighborhood safety in relation to the two physical activity outcomes, controlling for participant demographics.
Results: The number of home-use (OR = 1.27) and outdoor-use (OR = 1.24) exercise aids was significantly related to physical activity in adolescent girls but not boys. An interaction effect indicated that the relationship between home-use exercise equipment and physical activity levels was specific for girls in neighborhoods perceived as less-safe (OR = 4.40), rather than those perceived as safe (OR = 1.07, P < 0.01). In the parent sample, home-use (OR = 1.24) and outdoor use (OR = 1.16) exercise aids were significantly related to physical activity levels. An interaction between outdoor exercise aids and safety indicated that the effect was specific to parents who lived in neighborhoods perceived as safe (OR = 2.43) compared to those perceived as less-safe (OR = 0.91, P < 0.01).
Conclusion: Girls living in neighborhoods their parents perceive to be less-safe may benefit from having exercise equipment they can use in the home. Parents living in neighborhoods perceived to be safe may benefit from having exercise aids that they can use outside.

Lindamer LA, McKibbin C, Norman GJ, Jordan L, Harrison K, Abeyesinhe S, Patrick K. Assessment of physical activity in middle-aged and older adults with schizophrenia. Schizophr Res 2008;104(1-3):294-301.Background: Regular physical activity (PA) decreases morbidity in the general population; yet, information about the amount and effects of PA in persons with schizophrenia is scant. To develop interventions to increase PA and to assess its potential benefits in this group, accurate measurement of PA is needed. The purpose of this study was to characterize PA and determine the test-retest reliability and concurrent validity of the Yale Physical Activity Scale (YPAS), a self-report measure, in persons with schizophrenia.
Methods: PA was assessed with the YPAS, a scale of motivational readiness for PA, and accelerometry in middle-aged and older persons with a diagnosis of schizophrenia (n=54) and in a comparison group with no known psychiatric diagnosis (n=27).
Results: On the YPAS measures, persons with schizophrenia reported on average 11 h per week of PA, whereas the non-psychiatric comparison group reported about 32 h per week. Only about 30% of schizophrenia subjects were classified as being regularly active relative to 62% of the comparison group on PA motivational stages of readiness. On the accelerometry measures, the schizophrenia group had lower levels of light activity than the comparison group, but there were no differences in moderate and vigorous activity or sedentary behavior. Only in the comparison group were there significant associations between YPAS and accelerometer variables. Several YPAS scores demonstrated high test-retest reliability in both groups, and concurrent validity was supported between the YPAS and PA motivational stages of readiness.
Conclusions: We found that the YPAS is a reliable measure of PA in schizophrenia for some indices. Although the YPAS demonstrated concurrent validity with other self-report measures, it did not demonstrate concurrent validity when compared to PA measured by accelerometry in persons with schizophrenia. Use of multiple measures, both subjective and objective, is recommended when assessing PA in schizophrenia.

Patrick K, Griswold WG, Raab F, Intille SS. Health and the mobile phone. Am J Prev Med. 2008;35(2):177-81.

Robinson AH, Norman GJ, Sallis JF, Calfas KJ, Rock CL, Patrick K. Validating stage of change measures for physical activity and dietary behaviors for overweight women. Int J Obes (Lond). 2008;32(7):1137-44.Objective: To investigate the construct, concurrent and predictive validity of stage of change measures for physical activity (PA), and intakes of fruit and vegetables (FVs), dietary fiber (FB) and dietary fat (DF) among a sample of overweight women.
Design: Subjects were 401 women (mean age=41, s.d.=8.7 years; mean body mass index=32.35, s.d.=4.6) recruited to participate in a 12-month weight loss intervention trial. Concurrent validity tests included (1) self-report of current behavior, (2) decisional balance (for example, pros and cons of behavior change), (3) self-efficacy, (4) the MTI Actigraph accelerometer (for the PA staging measure), and (5) a food-frequency questionnaire (for all dietary staging measures). Predictive validity was assessed through tests of the relationship between the baseline stage of change measures and their corresponding behavior 1-year later.
Results: Coefficient alpha-tests of internal consistency exceeded 0.70 on the majority of scales. Concurrent validity tests indicated strong validity evidence for three staging measures and little validity for the DF staging measure (eta(2) range, 0.02-0.18). All staging algorithms demonstrated predictive validity (eta(2) range, 0.04-0.126).
Conclusion: Staging measures can determine motivational readiness for overweight women, contribute to the standardization of stage of change assessment and facilitate cross-study comparisons.

Arrott M, Demchak B, Ermagan V, Farcas C, Farcas E, Krüger IH, Menarini M. Rich services: the integration piece of the SOA puzzle. In Proceedings of the 2007 ICWS, IEEE, July 2007:176–83.

Broy M, Krüger IH, Meisinger M. A formal model of service. ACM Transactions on Software Engineering and Methodology (TOSEM) 2007;16(1):5.Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. N Engl J Med 2007;357(4):370–9. PMID: 17652652

Demchak B, Farcas C, Farcas E, Krüger IH. The treasure map for rich services. In Proceedings of the 2007 IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, NV. IEEE, August 2007:400–5.

Hagler AS, Norman GJ, Zabinski MF, Sallis JF, Calfas KJ, Patrick K. Psychosocial correlates of dietary intake among overweight and obese men. Am J Health Behav 2007;31(1):3-12.Objectives: To investigate the relationship between theoretically based psychosocial constructs and dietary components among overweight men.
Methods: Participants were 441 men (BMI M = 34.2). Psychosocial constructs included self-efficacy, decisional balance, social support, and behavior change strategies. Dietary components were fat, fiber, and fruit and vegetable intake.
Results: All significant findings were in the expected direction. Multiple regression models indicated that the psychosocial factors accounted for the most variance in vegetable intake (R(2)=.13) and the least variance in fat (R(2)=.05).
Conclusions: Theoretically based psychosocial constructs were related to overweight men's dietary intake and have potential for use in tailored behavior-change interventions.

Huang JS, Norman GJ, Zabinski MF, Calfas KJ, Patrick K. Body image and self-esteem among adolescents undergoing an intervention targeting dietary and physical activity behaviors. J Adolesc Health 2007;40(3):245-51.Purpose: To determine the effect of a one-year intervention targeting physical activity, sedentary, and diet behaviors among adolescents on self-reported body image and self-esteem. Health promotion interventions can lead to awareness of health risk and subsequent adoption of beneficial changes in behavior. However, it is possible that interventions targeting behaviors associated with childhood obesity may also increase the likelihood of unhealthy eating and physical activity obsessions and behaviors.
Methods: Body image and self-esteem were assessed for adolescents participating in the PACE+ study, a randomized controlled trial of a 1-year behavioral intervention targeting physical activity, sedentary, and dietary behaviors. The Body Dissatisfaction subscale of the Eating Disorder Inventory and Rosenberg Self-Esteem scale were used to assess body image and self-esteem, respectively, and measurements were performed at baseline, and at 6 and 12 months. Demographic characteristics and weight status of participants were also ascertained. Analysis of responses was performed via both between-group and within-group repeated measure analyses.
Results: There were 657 adolescents who completed all measurements. Body image differences were found for age, gender, and weight status at baseline, whereas self-esteem differences were demonstrated for gender, ethnicity, and weight status. There were no intervention effects on body image or self-esteem for either girls or boys. Self-esteem and body satisfaction did not worsen as a result of participating in the PACE+ intervention for either boys or girls whether or not they lost or maintained their weight or gained weight. Girls assigned to the PACE intervention who experienced weight reduction or weight maintenance at either 6 or 12 months reported improvements in body image satisfaction (p = .02) over time compared with subjects who had experienced weight gain during the 12-month study period.
Conclusions: Adverse effects on body satisfaction and self-esteem were not observed among adolescents undergoing this behavioral intervention. These results suggest that a behavioral intervention directed at improving physical activity and diet habits may be safely undertaken by adolescents, including those who are overweight and at risk for overweight, without adverse psychological consequences. Inclusion of specific elements in the intervention that directly addressed body image and self-esteem issues may have reduced the risk for negative psychological effects.

Norman GJ, Adams MA, Calfas KJ, Covin J, Sallis JF, Rossi JS, Redding CA, Cella J, Patrick K. A randomized trial of a multicomponent intervention for adolescent sun protection behaviors. Arch Pediatr Adolesc Med 2007;161(2):146-52.Objective: To evaluate a multicomponent primary care-based intervention to increase sun protection behaviors among adolescents. Excessive sun exposure in childhood increases the lifetime risk of melanomas and other forms of skin cancer. Interventions to improve sun protection behaviors in childhood have been based primarily in school and community settings, with little attention to the role of primary care physicians.
Design: A 2-year randomized controlled trial.
Setting: Primary care physician offices and participant homes.
Participants: Eight hundred nineteen adolescents aged 11 to 15 years. INTERVENTIONS: At the study onset and the 12-month follow-up, the adolescents engaged in an office-based expert system assessment of sun protection behaviors followed by brief stage-based counseling from the primary care provider. Participants also received up to 6 expert system-generated feedback reports, a brief printed manual, and periodic mailed tip sheets. Participants randomized to the comparison condition received a physical activity and nutrition intervention.
Main Outcome Measure: A self-reported composite measure of sun protection behavior.
Results: A random-effects repeated-measures model indicated a greater adoption of sun protection behaviors over time in the intervention group compared with the control group. The intervention effect corresponded to between-group differences at 24 months in avoiding the sun and limiting exposure during midday hours and using sunscreen with a sun protection factor of at least 15. Secondary analysis indicated that, by 24 months, more adolescents in the intervention group had moved to the action or the maintenance stage of change than those in the control group (25.1% vs 14.9%; odds ratio, 1.74; 95% confidence interval, 1.13-2.68). Sun protection behavior was also found to be positively associated with the completion of more intervention sessions (P = .002).
Conclusion: Primary care counseling coupled with a minimal-intensity expert system intervention can improve adolescents' sun protection behaviors.

Rosenberg DE, Norman GJ, Sallis JF, Calfas KJ, Patrick K. Covariation of adolescent physical activity and dietary behaviors over 12 months. J Adolesc Health 2007;41(5):472-8.Purpose: This study examined covariation among changes in dietary, physical activity, and sedentary behaviors over 12 months among adolescents participating in a health behavior intervention. Evidence of covariation among behaviors would suggest multi-behavior interventions could have synergistic effects.
Methods: Prospective analyses were conducted with baseline and 12-month assessments from a randomized controlled trial to promote improved diet, physical activity, and sedentary behaviors (experimental condition) or SUN protection behaviors (comparison condition). Participants were adolescent girls and boys (N = 878) aged 11-15 years on entry. The main outcomes were: diet, based on multiple 24-hour recalls (total fat, grams of fiber, servings of fruit and vegetables, total calories); average daily energy expenditure (kcals/kg) based on 7-day physical activity recall interviews; daily minutes of moderate-vigorous physical activity minutes from accelerometery; and self-reported daily hours of sedentary behavior.
Results: Covariation was found between fat and calories (r = .16), fiber and calories (r = .53), fiber and fruit/vegetables (r = .53), calories and fruit/vegetables (r = .34), and fruit and vegetables and sedentary behavior (r = -.12) for the total sample (all p values < .01). The pattern of findings was similar for most subgroups defined by gender and study condition.
Conclusions: The strongest covariation was observed for diet variables that are inherently related (calories and fat, fiber, and fruit/vegetables). Little covariation was detected within or between other diet, physical activity and sedentary behavior domains suggesting that interventions to improve these behaviors in adolescents need to include specific program components for each target behavior of interest.

Sanchez A, Norman GJ, Sallis JF, Calfas KJ, Cella J, Patrick K. Patterns and correlates of physical activity and nutrition behaviors in adolescents. Am J Prev Med 2007;32(2):124-30.Background: Knowledge of the prevalence, clustering, and correlates of multiple adolescent health behaviors can inform the design of health promotion interventions.
Methods: A cross-sectional design was used to assess 878 adolescents aged 11 to 15 years (53.6% girls, 58% non-Hispanic white) recruited in primary care clinics in 2001-2002. Adolescent physical activity (assessed with accelerometers), television viewing time (reported), percent calories from fat, and servings of fruits and vegetables (assessed with multiple 24-hour recalls) were dichotomized into meeting or not meeting national guidelines. Parent health behaviors were assessed with self-reported measures. Analyses were conducted in 2006.
Results: Fifty-five percent of adolescents did not meet the physical activity guideline, and 30% exceeded 2 hours daily of television viewing time, with boys more active and less sedentary than girls (p <0.01). The majority of the adolescents did not meet dietary guidelines. Nearly 80% had multiple risk behaviors and only 2% met all four guidelines. The number of risk behaviors was associated with being older and being at risk for overweight or being overweight, for boys and girls (p <0.05). Two parent health behaviors-history of smoking and failure to meet the fruits and vegetables guideline-were significantly associated with a higher number of risk behaviors for girls (p <0.05).
Conclusions: Eight of ten adolescents in this sample failed to meet guidelines for two or more diet, physical activity, and sedentary risk behaviors. Some parent health behaviors, along with the adolescent's weight status and age, were associated with a higher number of adolescent health risk behaviors.

Zabinski M, Norman G, Sallis J, Calfas K, Patrick K. Patterns of sedentary behavior among adolescents. Health Psychol 2007;31(1):3-12.Objective: Reducing certain sedentary behaviors (e.g., watching television, using a computer) can be an effective weight loss strategy for youth. Knowledge about whether behaviors cluster together could inform interventions.
Study Design: Estimates of time spent in 6 sedentary behaviors (watching television, talking on the telephone, using a computer, listening to music, doing homework, reading) were cluster analyzed for a sample of 878 adolescents (52% girls, mean age = 12.7 years, 58% Caucasian).
Main Outcome Measures: The clusters were based on the sedentary behaviors listed above and compared on environmental variables (e.g., household rules), psychosocial variables (e.g., self-efficacy, enjoyment), and health behaviors (e.g., physical activity, diet).
Results: Four clusters emerged: low sedentary, medium sedentary, selective high sedentary, and high sedentary. Analyses revealed significant cluster differences for gender (p < .002), age (p < .002), body mass index (p < .001), physical activity (p < .01), and fiber intake (p < .01).
Conclusions: Results suggest a limited number of distinct sedentary behavior patterns. Further study is needed to determine how interventions may use cluster membership to target segments of the adolescent population.

Hagler AS, Calfas KJ, Norman GJ, Sallis JF, Patrick K. Construct validity of physical activity and sedentary behaviors staging measures for adolescents. Ann Behav Med 2006;31(2):186-93.

Norman G, Nutter S, Ryan S, Sallis J, Calfas K, Patrick K. Community design and access to recreational facilities as correlates of adolescent physical activity and body mass index. 2006 J Phy Act Health S113-23.

Patrick K, Calfas KJ, Norman GJ, Zabinski MF, Sallis JF, Rupp J, Covin J, Cella J. Randomized controlled trial of a primary care and home based intervention for physical activity and nutrition behaviors: PACE+ for adolescents. Arch Pediatr Adolesc Med 2006;160:128-36.

Zabinski MF, Daly T, Norman GJ, Rupp JW, Calfas KJ, Sallis JF, Patrick K. Psychosocial correlates of fruit, vegetable, and dietary fat intake among adolescent boys and girls. J Am Diet Assoc. 2006;106(6):814-21.

Lenert L, Norman G, Mailhot M, Patrick K; A framework for health behavior protocols and their linkage to behavior theory. J Biomed Inform 2005;38(4):270-80.

Norman GJ, Schmid BA, Sallis JF, Calfas KJ, Patrick K. Psychosocial and environmental correlates of adolescent sedentary behaviors. Pediatrics 2005;116(4):908-16.

Patrick K, Intille S, Zabinski M: An ecological framework for cancer communication: Implications for research. J Med Internet Res 2005;7(3):e2

Norman G, Vaughn A, Roesch S, Sallis J, Calfas K, Patrick K: Development of decisional balance and self-efficacy measures for adolescent sedentary habits. Psychol Health 2004;19(5):561-75.

Patrick K, Norman GJ, Calfas KJ, Sallis JF, Zabinski MF, Rupp J, Cella J. Diet, physical activity, and sedentary behaviors as risk factors for overweight in adolescence. Arch Pediatr Adolesc Med 2004;158(4):385-90.

Doshi A, Patrick K, Sallis J, Calfas K: Evaluation of physical activity websites for use of behavior change theories. Ann Behav Med 2003;25(2):105-11.

Fleming R, Patrick K: Osteoporosis prevention: Pediatricians knowledge, attitudes and counseling practices. Prev Med 2002;34:411-21.

Calfas KJ, Sallis JF, Zabinski MF, Wilfley DE, Rupp J, Prochaska JJ, Thompson S, Pratt M, Patrick K. Preliminary evaluation of a multi-component program for nutrition and physical activity change in primary care: PACE+ for adults. Prev Med 2002;34:153-61.

Saelens BE, Sallis JF, Wilfley DE, Patrick K, Cella JA, Buchta R. Behavioral weight control for overweight adolescents initiated in primary care. Obes Res 2002;10(1):22-32.

Patrick K, Sallis JF, Prochaska JJ, Lydston DD, Calfas KJ, Zabinski MF, Wilfley DE, Saelens BE, Brown DR. A multicomponent program for nutrition and physical activity change in primary care: PACE+ for adolescents. Arch Pediatr Adolesc Med 2001;155(8):940-6.

Calfas KJ, Zabinski MF, Rupp J. Practical nutrition assessment in primary care settings: a review. Am J Prev Med 2000;18(4):289-99.

Prochaska JJ, Zabinski MF, Calfas KJ, Sallis JF, Patrick K. PACE+: Interactive communication technology for behavior change in clinical settings. Am J Prev Med 2000;9(2):127-31.

Sallis JF, Patrick K, Calfas KJ. Counseling patients/clients about physical activity and nutrition. Weight Control Digest 1999;9(5):843, 846-50.

Sallis JF, Patrick K, Calfas KJ, Zabinski MF, Prochaska JJ, Thompson S, Rupp J, Wilfley DE, Lydston DD, Long BJ. A multi-media behavior change program for nutrition and physical activity in primary care: PACE+ for adults. Homeostasis 1999;39(5):196-202.

Simons-Morton DG, Calfas KJ, Oldenburg B, Burton NW. Effects of interventions in health care settings or physical activity or cardiorespiratory fitness. Am J Prev Med 1998;15(4):413-30.

Calfas KJ, Sallis JF, Oldenburg B, Ffrench M. Mediators of change in physical activity following an intervention in primary care: PACE. Prev Med 1997;26:297-304.

Calfas KJ, Long BJ, Sallis JF, Wooten WJ, Pratt M, Patrick K. A controlled trial of physician counseling to promote the adoption of physical activity. Prev Med 1996;25:225-33.

Long BJ, Calfas KJ, Wooten W, Sallis JF, Patrick K, Goldstein M, Marcus BH, Schwenk TL, Chenoweth J, Carter R, Torres T, Palinkas LA, Heath G. A multisite field test of the acceptability of physical activity counseling in primary care: Project PACE. Am J Prev Med 1996;12(2):73-81.

Patrick K, Calfas KJ, Sallis JF, Long BJ. Basic principles of physical activity counseling: Project PACE. In: Thomas RJ, ed. The heart and exercise: a practical guide for the clinician. New York: Igaku-Shoin, 1996.

Patrick K, Sallis JF, Long BJ, Calfas KJ, Wooten WJ, Heath G. A new tool for encouraging activity: Project PACE. Phys Sportsmed 1994;22(11);45-55.

Pender NJ, Sallis JF, Long BJ, Calfas KJ. Health care provider counseling to promote physical activity. In Dishman RK, ed. Exercise adherence (2nd ed.) Human Kinetics, 1994.Changes in policies and built environments are advocated as part of efforts to increase physical activity, but in 2001 the knowledge base to inform these changes was limited. The Robert Wood Johnson Foundation addressed this deficit by initiating Active Living Research (ALR). The mission of ALR was to stimulate and support research that could guide the improvement of environments, policies, and practices to promote active living. The program's goals were to (1) build the evidence base about environmental and policy factors related to physical activity, (2) build the capacity of researchers in multiple fields to collaborate, and (3) inform and facilitate policy change. To build the evidence base, 121 grants were supported with $12.5 million. Efforts were made to support new investigators, fund investigators from numerous disciplines, and increase the demographic diversity of researchers. Activities to build capacity to conduct collaborative research included annual conferences, journal supplements, seminars for multiple disciplines, and the posting of environmental measures. Coordination with Active Living Leadership was a primary means of communicating research to policymakers. Other activities to facilitate the application of research included research summaries written for nonresearchers, collaborations with Active Living by Design, several components of the website (www.activelivingresearch.org), and using policy relevance as a funding criterion. Two independent evaluations were accomplished, and they concluded that ALR made progress on all three goals. ALR has been renewed through 2012. The new mission is to use a $15.4 million research budget to contribute to reversing the childhood obesity epidemic, especially among youth in the highest-risk groups.