Browsing by Author "Adams, Marc A"
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- ItemAn adaptive physical activity intervention for overweight adults: a randomized controlled trial.(2013-12-18) Adams, Marc A; Sallis, James F; Norman, Gregory J; Hovell, Melbourne F; Hekler, Eric B; Perata, ElyseBACKGROUND Physical activity PA interventions typically include components or doses that are static across participants Adaptive interventions are dynamic components or doses change in response to short term variations in participant s performance Emerging theory and technologies make adaptive goal setting and feedback interventions feasible OBJECTIVE To test an adaptive intervention for PA based on Operant and Behavior Economic principles and a percentile based algorithm The adaptive intervention was hypothesized to result in greater increases in steps per day than the static intervention METHODS Participants N 20 were randomized to one of two 6 month treatments 1 static intervention SI or 2 adaptive intervention AI Inactive overweight adults 85 women M 36 9 9 2 years 35 non white in both groups received a pedometer email and text message communication brief health information and biweekly motivational prompts The AI group received daily step goals that adjusted up and down based on the percentile rank algorithm and micro incentives for goal attainment This algorithm adjusted goals based on a moving window an approach that responded to each individual s performance and ensured goals were always challenging but within participants abilities The SI group received a static 10 000 steps day goal with incentives linked to uploading the pedometer s data RESULTS A random effects repeated measures model accounted for 180 repeated measures and autocorrelation After adjusting for covariates the treatment phase showed greater steps day relative to the baseline phase pUnder 001 and a group by study phase interaction was observed p 017 The SI group increased by 1 598 steps day on average between baseline and treatment while the AI group increased by 2 728 steps day on average between baseline and treatment a significant between group difference of 1 130 steps day Cohen s d 74 CONCLUSIONS The adaptive intervention outperformed the static intervention for increasing PA The adaptive goal and feedback algorithm is a behavior change technology that could be incorporated into mHealth technologies and scaled to reach large populations TRIAL REGISTRATION ClinicalTrials gov NCT01793064
- ItemFruit and vegetable intake and eating behaviors mediate the effect of a randomized text-message based weight loss program.(2013-01-08) Norman, Gregory J; Kolodziejczyk, Julia K; Adams, Marc A; Patrick, Kevin; Marshall, Simon JINTRODUCTION We hypothesized that fruit vegetable intake and eating behaviors mediate the relationship between experimental condition and weight loss in a randomized trial evaluating a text message based weight loss program METHODS Overweight obese individuals from San Diego CA N 52 with complete data were randomly assigned in 2007 into one of two groups for four months 1 the intervention group that received 2 5 weight management text messages p day 2 the usual care comparison group Three 24 hour recalls assessed fruit vegetable intake change and the eating behavior inventory EBI measured change in eating behaviors Regression path models tested intervention mediation RESULTS Direct effects of the intervention were found for change in body weight b 3 84 R 2 0 074 fruit vegetable intake b 2 00 R 2 0 083 and EBI scores b 7 15 R 2 0 229 ps Under 0 05 The treatment group to weight change path was not statistically significant b 0 673 R 2 0 208 when fruit vegetable intake change and EBI score change were specified as intervention mediators in the model The total indirect effect was 3 17 lb indicating that the indirect paths explained 82 6 of the total effect on weight change DISCUSSION Fruit vegetable intake and eating behaviors mediated the intervention s effect on weight change The findings suggest that sending text messages that promote healthy eating strategies resulted in moderate short term weight loss
- ItemA Markov Approach for Increasing Precision in the Assessment of Data-Intensive Behavioral Interventions.(0000-00-00) Berardi, Vincent; Carretero-González, Ricardo; Bellettiere, John; Adams, Marc A; Hughes, Suzanne; Hovell, MelbourneHealth interventions using real time sensing technology are characterized by intensive longitudinal data which has the potential to enable nuanced evaluations of individuals responses to treatment Existing analytic tools were not developed to capitalize on this opportunity as they typically focus on first order findings such as changes in the level and or slope of outcome variables over different intervention phases This paper introduces an exploratory Markov based empirical transition method that offers a more comprehensive assessment of behavioral responses when intensive longitudinal data are available The procedure projects a univariate time series into discrete states and empirically determines the probability of transitioning from one state to another State transition probabilities are summarized separately in phase specific transition matrices Comparing transition matrices illuminates intricate quantifiable differences in behavior between intervention phases Statistical significance is estimated via bootstrapping techniques This paper introduces the methodology via three case studies from a secondhand smoke reduction trial utilizing real time air particle sensors Analysis enabled the identification of complex phenomena such as avoidance and escape behavior in response to punitive contingencies for tobacco use Additionally the largest changes in behavior dynamics were associated with the introduction of behavioral feedback The Markov approach s ability to elucidate subtle behavioral details has not typically been feasible with standard methodologies mainly due to historical limitations associated with infrequent repeated measures These results suggest that the evaluation of intervention effects in data intensive single case designs can be enhanced providing rich information that can ultimately be used to develop interventions uniquely tailored to specific individuals
- ItemRationale and design of Smart Walk: A randomized controlled pilot trial of a smartphone-delivered physical activity and cardiometabolic risk reduction intervention for African American women.(0000-00-00) Joseph, Rodney P; Ainsworth, Barbara E; Vega-López, Sonia; Adams, Marc A; Hollingshead, Kevin; Hooker, Steven P; Todd, Michael; Gaesser, Glenn A; Keller, ColleenBACKGROUND African American AA women perform low levels of physical activity PA and are disproportionally burdened by cardiometabolic disease conditions when compared to White women and the U S population as a whole These disparities emphasize the need for innovative and effective interventions to increase PA and reduce cardiometabolic disease risk among AA women Recent evidence suggests that mobile health mHealth interventions have the potential to increase PA and reduce cardiometabolic disease risk factors Few studies have examined the efficacy of mHealth PA interventions among racial ethnic minorities including AA women This represents a missed opportunity given the reported success of technology delivered PA interventions in predominately White populations and the high use of technology among AA women OBJECTIVE To describe the design theoretical rationale and cultural relevance of Smart Walk a culturally sensitive smartphone delivered PA intervention for AA women DESIGN AND METHODS Smart Walk is an 8 month randomized controlled pilot trial designed to increase PA and reduce cardiometabolic disease risk among AA women Sixty physically inactive AA women with obesity will be assigned to receive either a culturally relevant intervention designed to increase PA by targeting leisure time household chore task related and occupational PA or a culturally relevant wellness attention matched control condition Outcomes will be assessed at baseline 4 months and 8 months and include feasibility and acceptability of the PA intervention and evaluation of effects on PA and cardiometabolic risk factors SUMMARY Smart Walk represents a culturally relevant theory based approach to promote PA and reduce cardiometabolic disease risk in AA women
- ItemA text message-based intervention for weight loss: randomized controlled trial.(2009-01-14) Patrick, Kevin; Raab, Fred; Adams, Marc A; Dillon, Lindsay; Zabinski, Marian; Rock, Cheryl L; Griswold, William G; Norman, Gregory JBACKGROUND To our knowledge no studies have evaluated whether weight loss can be promoted in overweight adults through the use of an intervention that is largely based on daily SMS Short Message Service text and MMS Multimedia Message Service small picture messages transmitted via mobile phones OBJECTIVE This paper describes the development and evaluation of a text message based intervention designed to help individuals lose or maintain weight over 4 months METHODS The study was a randomized controlled trial with participants being exposed to one of the following two conditions lasting 16 weeks 1 receipt of monthly printed materials about weight control 2 an intervention that included personalized SMS and MMS messages sent two to five times daily printed materials and brief monthly phone calls from a health counselor The primary outcome was weight at the end of the intervention A mixed model repeated measures analysis compared the effect of the intervention group to the comparison group on weight status over the 4 month intervention period Analysis of covariance ANCOVA models examined weight change between baseline and 4 months after adjusting for baseline weight sex and age RESULTS A total of 75 overweight men and women were randomized into one of the two groups and 65 signed the consent form completed the baseline questionnaire and were included in the analysis At the end of 4 months the intervention group n 33 lost more weight than the comparison group 1 97 kg difference 95 CI 0 34 to 3 60 kg P 02 after adjusting for sex and age Intervention participants adjusted average weight loss was 2 88 kg 3 16 At the end of the study 22 of 24 92 intervention participants stated that they would recommend the intervention for weight control to friends and family CONCLUSIONS Text messages might prove to be a productive channel of communication to promote behaviors that support weight loss in overweight adults
- ItemTutorial for Using Control Systems Engineering to Optimize Adaptive Mobile Health Interventions.(0000-00-00) Hekler, Eric B; Rivera, Daniel E; Martin, Cesar A; Phatak, Sayali S; Freigoun, Mohammad T; Korinek, Elizabeth; Klasnja, Predrag; Adams, Marc A; Buman, Matthew PBACKGROUND Adaptive behavioral interventions are individualized interventions that vary support based on a person s evolving needs Digital technologies enable these adaptive interventions to function at scale Adaptive interventions show great promise for producing better results compared with static interventions related to health outcomes Our central thesis is that adaptive interventions are more likely to succeed at helping individuals meet and maintain behavioral targets if its elements can be iteratively improved via data driven testing ie optimization Control systems engineering is a discipline focused on decision making in systems that change over time and has a wealth of methods that could be useful for optimizing adaptive interventions OBJECTIVE The purpose of this paper was to provide an introductory tutorial on when and what to do when using control systems engineering for designing and optimizing adaptive mobile health mHealth behavioral interventions OVERVIEW We start with a review of the need for optimization building on the multiphase optimization strategy MOST We then provide an overview of control systems engineering followed by attributes of problems that are well matched to control engineering Key steps in the development and optimization of an adaptive intervention from a control engineering perspective are then summarized with a focus on why what and when to do subtasks in each step IMPLICATIONS Control engineering offers exciting opportunities for optimizing individualization and adaptation elements of adaptive interventions Arguably the time is now for control systems engineers and behavioral and health scientists to partner to advance interventions that can be individualized adaptive and scalable This tutorial should aid in creating the bridge between these communities