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As the prevalence of childhood obesity in the United States rises, opportunities for children to be physically active become more vital. One opportunity for physical activity involves children walking to and from school. However, children that live in areas with a pedestrian-unfriendly built environment and a low degree of walkability are less likely to be physically active and more likely to be overweight. The purpose of this study was to study walking routes from schools in low-income neighborhoods in Southwestern United States to a local community center. Walking routes from the three study schools (South Mountain High School, Percy Julian Middle School, and Rose Linda Elementary School) were determined by distance, popularity, and the presence of a major thoroughfare. Segments and intersections, which formed the routes, were randomly selected from each school's buffer region. The walking routes as a whole, along with the segments and intersections, were audited and scored using built environment assessments tools: MAPS, PEQI and Walkability Checklist. These scores were utilized to develop interactive mapping tools to visualize the quality of the routes, segments and intersections and identify areas for improvement. Results showed that the routes from Percy Julian to the Kroc Center were, overall, rated higher than routes from the other two schools. The highest scoring route, from the seven routes studied, was route 2 from Percy Julian to the Kroc Center along Broadway Road. South Mountain High School was overall the worst starting point for walking to the Kroc Center as those three walking routes were graded as the least walkable. Possible areas for improvement include installing traffic calming features along major thoroughfares and reducing the perceived risk to pedestrian safety by beautifying the community by planting greenery. Future directions include studying the built environment in South Phoenix communities that surround the Kroc Center.
ContributorsZeien, Justin Lee (Author) / Buman, Matthew (Thesis director) / Hekler, Eric (Committee member) / Fellows, Brian (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Previous research has found improvements in motor and cognitive measures following Assisted Cycle Therapy (AC) in adolescence with Down syndrome (DS). Our study investigated whether we would find improvements in older adults with DS on measures of leisure physical activity (GLTEQ) and sleep, which are early indicators of Alzheimer's disease (AD) in persons with Down syndrome. This study consisted of eight participants with Down syndrome between 31 and 51 years old that cycled for 30 minutes 3 x/week for eight weeks either at their voluntary cycling rate (VC) or approximately 35% faster with the help of a mechanical motor (AC). We predicted that, based on pilot data (Gomez, 2015), GLTEQ would either maintain or improve after AC, but would decrease after VC and would stay the same after NC. We predicted that the sleep score may improve after both VC or AC or it may improve more after VC than AC based on pilot data related to leisure activity. Our results were consistent with our prediction that GLTEQ will either maintain or improve after AC but will decrease after VC. Our results were not consistent with our prediction that sleep may improve after both VC or AC or it may improve more after VC than AC, possibly because we did not pre-screen for sleep disorders. Future research should focus on recruiting more participants and using both objective and subjective measures of sleep and physical activity to improve the efficacy of the study.
ContributorsParker, Lucas Maury (Author) / Ringenbach, Shannon (Thesis director) / Buman, Matthew (Committee member) / Holzapfel, Simon (Committee member) / School of Social and Behavioral Sciences (Contributor) / School of Nutrition and Health Promotion (Contributor) / College of Public Service and Community Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Translating research has been a goal of the Department of Health and Human Services since 1999. Through two years of iteration and interview with our community members, we have collected insights into the barriers to accomplishing this goal. Liberating Science is a think-tank of researchers and scientists who seek to create a more transparent process to accelerate innovation starting with behavioral health research.
ContributorsRaghani, Pooja Sioux (Author) / Hekler, Eric (Thesis director) / Buman, Matthew (Committee member) / Pruthi, Virgilia Kaur (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Biomedical Informatics Program (Contributor)
Created2014-05
Description
Over the last decade, the ability to track daily activity through step counting devices has undergone major changes. Advanced technologies have brought about new step counting devices and new form factors. The validity of these new devices is not fully known. The purpose of this study was to validate and compare the step counting accuracy of commercially available hip- and wrist-worn accelerometers. A total of 185 participants (18-64 years of age) were analyzed for this study, with the sample composed nearly evenly of each gender (53.5% female) and BMI classification (33% overweight, 31.9% obese). Each participant wore five devices including hip-worn Omron HJ-112 and Fitbit One, and wrist-worn Fitbit Flex, Nike Fuelband, and Jawbone UP. A range of activities (some constant among all participants, some randomly assigned) were then used to accumulate steps including walking on a hard surface for 400m, treadmill walking/running at 2mph, 3mph, and ≥5mph, walking up five flights of stairs, and walking down five flights of stairs. To validate the accuracy of each device, steps were also counted by direct observation. Results showed high concordance with directly observed steps for all devices (intraclass correlation coefficient range: 0.86 to 0.99), with hip-worn devices more accurate than wrist-worn devices. Absolute percent error values were lower among hip-worn devices and at faster walking/running speeds. Nike Fuelband consistently was the worst performing of all test devices. These results are important because as pedometers become more complex, it is important that they remain accurate throughout a variety of activities. Future directions for this research are to explore the validity of these devices in free-living settings and among younger and older populations.
ContributorsKramer, Cody Lee (Author) / Buman, Matthew (Thesis director) / Hoffner, Kristin (Committee member) / Marshall, Simon (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2014-05
Description
Human activity recognition is the task of identifying a person’s movement from sensors in a wearable device, such as a smartphone, smartwatch, or a medical-grade device. A great method for this task is machine learning, which is the study of algorithms that learn and improve on their own with the help of massive amounts of useful data. These classification models can accurately classify activities with the time-series data from accelerometers and gyroscopes. A significant way to improve the accuracy of these machine learning models is preprocessing the data, essentially augmenting data to make the identification of each activity, or class, easier for the model. <br/>On this topic, this paper explains the design of SigNorm, a new web application which lets users conveniently transform time-series data and view the effects of those transformations in a code-free, browser-based user interface. The second and final section explains my take on a human activity recognition problem, which involves comparing a preprocessed dataset to an un-augmented one, and comparing the differences in accuracy using a one-dimensional convolutional neural network to make classifications.
ContributorsLi, Vincent (Author) / Turaga, Pavan (Thesis director) / Buman, Matthew (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Introduction: There is currently a lack of industry-wide gold standardization in accelerometer study
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
ContributorsMartin, Logan Rhett (Author) / Buman, Matthew (Thesis director) / Toledo, Meynard John (Committee member) / Kurka, Jonathan (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
This thesis paper examines the effects of increased standing and light physical activity in the workplace on postprandial glucose. Sedentary behavior is detrimental to our health, affecting metabolic risk factors. An easy way to implement change is by decreasing sedentary time in workplaces where sitting is common, such as office workspaces. To consider how postprandial glucose is affected by decreasing sedentary time, participants ate a standardized meal for lunch and were asked to decrease their sitting time by replacing it with standing and light physical activity.
ContributorsChilders, Autumn Skye (Author) / Buman, Matthew (Thesis director) / Sears, Dorothy (Committee member) / Hasanaj, Kristina (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
The purpose of this study was to examine the overall maintenance of behavior during the 12 to 24 month period of the Stand&Move@Work study and the impact of implementation factors (i.e., facilitators, advocate activity, and the amount of strategies used) on behavior change. The design of the study was a cluster randomized trial which was facilitated by researchers for the first 12 months of the study. The primary aim of the study was to examine the maintenance of behavior change (i.e., sitting time) at the 12 month and 24 month marks using objectively measured sedentary behavior (activPAL micro). The secondary aim of the study was to examine the impact of implementation factors (i.e., facilitators, advocate activity, and the amount of strategies used) on behavior change during the 12 through 24 months maintenance period. Participants (N=630) included full-time, caucasian, middle-aged office workers. For the primary aim, descriptive means were used to cluster for observations within-persons and were adjusted for age, gender, race, job-type, and ordering effects.. For the secondary aim, descriptive means adjusted for workplace culture and environment were computed. At the 24 month mark, participants spent 280.67 ± 87.67 min/8hr workday sitting and 161.94 ± 85.87 min/8hr workday standing. The top performing worksites displayed reductions in sitting time which largely translated into standing time by about 30 minutes per 8 hour workday at 24 months. Feasibility findings indicated that implementation strategies do not show differences between the top 25% and bottom 25% performing worksites. This study provides insight to implementation strategies for interventions in the workplace.
ContributorsTong, Alyssa Taylor (Author) / Buman, Matthew (Thesis director) / Larouche, Miranda (Committee member) / Estabrooks, Paul (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Cardiovascular disease attributed to about 800,000 deaths per year and is the leading cause of all-cause mortality in the U.S. Previous studies indicate that reducing sedentary time or increasing physical activity (PA) can independently reduce cardiometabolic risk (CMR). Further, studies have shown that higher levels of moderate-to-vigorous PA can attenuate the negative effects of sedentary behavior on CMR.
In this study, we evaluated the association between sedentary time, light-intensity PA (LPA), and moderate-vigorous PA (MVPA) and CMR biomarkers (high density lipoprotein level, low density lipoprotein level, triglycerides, fasting glucose, total cholesterol, blood pressure, and body mass index). Additionally, we examined if the detrimental association between sedentary time and CMR biomarkers is partially or fully attenuated by MVPA. Baseline objective physical activity and cardiometabolic risk data from a two-arm-cluster randomized trial (Stand&Move@work) were used in this study. Multilevel models clustered by worksite evaluated the fixed effects and interaction between MVPA and sedentary time on CMR. Data from 630 sedentary working adults (from 24 worksites) were included in the analysis. The sample was mainly middle aged (44.6±11.2) females (74%) with race distributions as follows; 70.5% white, 13.8% hispanic, 4.1% black, 5.1% asian, and 2.1% other. Our study showed detrimental trends consistent with previous studies between sedentary behavior and cardiometabolic outcomes including HDL, LDL, and total cholesterol. MVPA demonstrated beneficial associations with lipoproteins including HDL, LDL, total cholesterol, and triglycerides. We observed that high levels of MVPA may be able to partially attenuate the negative effects of highly sedentary behavior on fasting glucose, total cholesterol, and LDL levels. Overall, sedentary behavior indicated deleterious associations with cardiometabolic outcomes. Future directions for this study could examine a more at-risk population or a highly active population for further assessment of CMR biomarkers and the effects of behavior.
In this study, we evaluated the association between sedentary time, light-intensity PA (LPA), and moderate-vigorous PA (MVPA) and CMR biomarkers (high density lipoprotein level, low density lipoprotein level, triglycerides, fasting glucose, total cholesterol, blood pressure, and body mass index). Additionally, we examined if the detrimental association between sedentary time and CMR biomarkers is partially or fully attenuated by MVPA. Baseline objective physical activity and cardiometabolic risk data from a two-arm-cluster randomized trial (Stand&Move@work) were used in this study. Multilevel models clustered by worksite evaluated the fixed effects and interaction between MVPA and sedentary time on CMR. Data from 630 sedentary working adults (from 24 worksites) were included in the analysis. The sample was mainly middle aged (44.6±11.2) females (74%) with race distributions as follows; 70.5% white, 13.8% hispanic, 4.1% black, 5.1% asian, and 2.1% other. Our study showed detrimental trends consistent with previous studies between sedentary behavior and cardiometabolic outcomes including HDL, LDL, and total cholesterol. MVPA demonstrated beneficial associations with lipoproteins including HDL, LDL, total cholesterol, and triglycerides. We observed that high levels of MVPA may be able to partially attenuate the negative effects of highly sedentary behavior on fasting glucose, total cholesterol, and LDL levels. Overall, sedentary behavior indicated deleterious associations with cardiometabolic outcomes. Future directions for this study could examine a more at-risk population or a highly active population for further assessment of CMR biomarkers and the effects of behavior.
ContributorsMeyer, Emily Camille (Author) / Buman, Matthew (Thesis director) / Toledo, Meynard (Committee member) / Pereira, Mark (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
While type 2 diabetes (T2D) rates have soared, the number of Americans classified as ‘prediabetic’ has also increased. Despite this, current preventative approaches are costly and often not without undue side-effects. Instead, behavioral lifestyle approaches hold promise in reducing conversion rates of T2D as the latest treatment option that could mitigate and transform disease management. However, present interventions do not possess the scope necessary for implementation in a realistic, scalable way that can target the large at-risk population.
The application (app) “BeWell24” mitigates this diabetes risk through targeting sleep, physical activity, sedentary behavior, and diet, and is being delivered through mHealth technology to attenuate the higher-risk of the prediabetic Veteran population. In order for full scale dissemination, this thesis examines a provider perspective of the ‘Post-intervention interview guide’, performed with a Phoenix Veterans Affairs Health Care System (PVAHCS) provider. It then suggests revisions to the interview guide based on the provider’s interview and existing literature. This thesis also emphasizes the rationale behind these proposed changes to be organized in line with the iPARIHS framework (integrated Promoting Action on Research Implementation in Health Services).
Overall, the provider responded positively to BeWell24 and the ‘Post-intervention interview guide’, with constructive suggestions for each question in the interview guide. The main theme of the provider’s answers and comments were to prioritize efficiency and preserve standard clinical flow. A revised interview guide is provided, which prospectively presents as a more brief and focused interview organized by the iPARIHS framework. This revised interview guide could aid in the clarity of provider responses, specifically for the prospective interviews of the ongoing larger BeWell24 study and future studies.
The application (app) “BeWell24” mitigates this diabetes risk through targeting sleep, physical activity, sedentary behavior, and diet, and is being delivered through mHealth technology to attenuate the higher-risk of the prediabetic Veteran population. In order for full scale dissemination, this thesis examines a provider perspective of the ‘Post-intervention interview guide’, performed with a Phoenix Veterans Affairs Health Care System (PVAHCS) provider. It then suggests revisions to the interview guide based on the provider’s interview and existing literature. This thesis also emphasizes the rationale behind these proposed changes to be organized in line with the iPARIHS framework (integrated Promoting Action on Research Implementation in Health Services).
Overall, the provider responded positively to BeWell24 and the ‘Post-intervention interview guide’, with constructive suggestions for each question in the interview guide. The main theme of the provider’s answers and comments were to prioritize efficiency and preserve standard clinical flow. A revised interview guide is provided, which prospectively presents as a more brief and focused interview organized by the iPARIHS framework. This revised interview guide could aid in the clarity of provider responses, specifically for the prospective interviews of the ongoing larger BeWell24 study and future studies.
ContributorsWojtas, Abby Ann (Author) / Buman, Matthew (Thesis director) / Larouche, Miranda (Committee member) / Epstein, Dana (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05