The Impact of Monetary Incentives on Delay Discounting Within a Year-Long Physical Activity Intervention.

BACKGROUND: Delay discounting is the depreciation in a reward's perceived value as a function of the time until receipt. Monetary incentive programs that provide rewards contingent on meeting daily physical activity (PA) goals may change participants' delay discounting preferences. PURPOSE: Determine if monetary incentives provided in close temporal proximity to meeting PA goals changed delay discounting, and if such changes mediated intervention effects. METHODS: Inactive adults (n = 512) wore accelerometers during a 12-month intervention where they received proximal monetary incentives for meeting daily moderate-to-vigorous PA (MVPA) goals or delayed incentives for study participation. Delay discount rate and average MVPA were assessed at baseline, end of intervention, and a 24-month follow-up. Using structural equation modeling, we tested effects of proximal versus delayed rewards on delay discounting and whether any changes mediated intervention effects on MVPA. PA self-efficacy was also evaluated as a potential mediator, and both self-efficacy and delay discounting were assessed as potential moderators of intervention effects. RESULTS: Proximal rewards significantly increased participants' delay discounting (ß = 0.238, confidence interval [CI]: -0.078, 0.380), indicating greater sensitivity to reinforcement timing. This change did not mediate incentive-associated increases in MVPA at the end of the 12-month intervention (ß = -0.016, CI: -0.053, 0.019) or at a 24-month follow-up (ß = -0.020, CI: -0.059, 0.018). Moderation effects were not found. CONCLUSIONS: Incentive-induced increases in delay discounting did not deleteriously impact MVPA. This finding may help assuage concerns about using monetary incentives for PA promotion, but further research regarding the consequences of changes in delay discounting is warranted.

This study examined the effects of providing proximal monetary incentives for meeting daily exercise goals on people's tendency to value immediate versus delayed rewards. Inactive adults (n = 512) participated in a year-long program where they wore an accelerometer each day and received either (i) small monetary rewards in close temporal proximity to instances of meeting daily exercise goals or (ii) larger rewards at 2-month intervals for ongoing participation. Those receiving proximal incentives showed an increased preference for immediate rewards, yet this reported change did not compromise long-term physical activity gains. In a comparison analysis, we found that proximal monetary incentives were not associated with changes in exercise self-efficacy. Overall, the findings suggest that monetary incentives for exercise do not negatively impact people's activity levels, though more research is needed to fully understand the implications of changes in reward timing preferences.

The moderating impact of neighborhood walkability on mHealth interventions to increase moderate to vigorous physical activity for insufficiently active adults in a randomized trial.

BACKGROUND: Ecological models suggest that interventions targeting specific behaviors are most effective when supported by the environment. This study prospectively examined the interactions between neighborhood walkability and an mHealth intervention in a large-scale, adequately powered trial to increase moderate-to-vigorous physical activity (MVPA). METHODS: Healthy, insufficiently active adults (N = 512) were recruited purposefully from census block groups ranked on walkability (high/low) and socioeconomic status (SES, high/low). Participants were block-randomized in groups of four to WalkIT Arizona, a 12-month, 2 × 2 factorial trial evaluating adaptive versus static goal setting and immediate versus delayed financial reinforcement delivered via text messages. Participants wore ActiGraph GT9X accelerometers daily for one year. After recruitment, a walkability index was calculated uniquely for every participant using a 500-m street network buffer. Generalized linear mixed-effects hurdle models tested for interactions between walkability, intervention components, and phase (baseline vs. intervention) on: (1) likelihood of any (versus no) MVPA and (2) daily MVPA minutes, after adjusting for accelerometer wear time, neighborhood SES, and calendar month. Neighborhood walkability was probed at 5th, 25th, 50th, 75th, and 95th percentiles to explore the full range of effects. RESULTS: Adaptive goal setting was more effective in increasing the likelihood of any MVPA and daily MVPA minutes, especially in lower walkable neighborhoods, while the magnitude of intervention effect declined as walkability increased. Immediate reinforcement showed a greater increase in any and daily MVPA compared to delayed reinforcement, especially relatively greater in higher walkable neighborhoods. CONCLUSIONS: Results partially supported the synergy hypotheses between neighborhood walkability and PA interventions and suggest the potential of tailoring interventions to individuals' neighborhood characteristics. TRIAL REGISTRATION: Preregistered at clinicaltrials.gov (NCT02717663).

Cardiometabolic Risk Factors Among Insufficiently Active African American Women With Obesity: Baseline Findings From Smart Walk.

BACKGROUND: Low moderate-to-vigorous physical activity (MVPA) levels and obesity are associated with increased cardiometabolic disease risk. OBJECTIVE: The aim of this study was to describe MVPA and cardiometabolic risk characteristics of insufficiently active African American women with obesity (N = 60) enrolled in a culturally tailored MVPA intervention. METHODS: We assessed accelerometer-measured and self-reported MVPA, blood pressure, serum lipid profiles, cardiorespiratory fitness (VO 2 peak), and aortic pulse wave velocity. RESULTS: Participants (mean age, 38.4; mean body mass index, 40.6 kg/m 2 ) averaged 15 min/d of accelerometer-measured MVPA and 30 min/wk of self-reported MVPA. Systolic and diastolic blood pressure levels were elevated (135.4 and 84.0 mm Hg, respectively). With the exception of low-density lipoprotein cholesterol (121.4 mg/dL) and high-density lipoprotein cholesterol (47.6 mg/dL), lipid profiles were within reference ranges. Compared with normative reference values, average VO 2 peak was low (18.7 mL/kg/min), and pulse wave velocity was high (7.4 m/s). CONCLUSIONS: Our sample of insufficiently active African American women with obesity was at an elevated risk for cardiometabolic disease.

Burstiness and Stochasticity in the Malleability of Physical Activity.

This study examined whether patterns of self-organization in physical activity (PA) predicted long-term success in a yearlong PA intervention. Increased moderate to vigorous PA (MVPA) was targeted in insufficiently active adults (N = 512) via goal setting and financial reinforcement. The degree to which inverse power law distributions, which are reflective of self-organization, summarized (a) daily MVPA and (b) time elapsed between meeting daily goals (goal attainment interresponse times) was calculated. Goal attainment interresponse times were also used to calculate burstiness, the degree to which meeting daily goals clustered in time. Inverse power laws accurately summarized interresponse times, but not daily MVPA. For participants with higher levels of MVPA early in the study, burstiness in reaching goals was associated with long-term resistance to intervention, while stochasticity in meeting goals predicted receptiveness to intervention. These results suggest that burstiness may measure self-organizing resistance to change, while PA stochasticity could be a precondition for behavioral malleability.

Built Environment, Physical Activity, and Obesity: Findings from the International Physical Activity and Environment Network (IPEN) Adult Study.

Creating more physical activity-supportive built environments is recommended by the World Health Organization for controlling noncommunicable diseases. The IPEN (International Physical Activity and Environment Network) Adult Study was undertaken to provide international evidence on associations of built environments with physical activity and weight status in 12 countries on 5 continents (n > 14,000). This article presents reanalyzed data from eight primary papers to identify patterns of findings across studies. Neighborhood environment attributes, whether measured objectively or by self-report, were strongly related to all physical activity outcomes (accelerometer-assessed total physical activity, reported walking for transport and leisure) and meaningfully related to overweight/obesity. Multivariable indexes of built environment variables were more strongly related to most outcomes than were single-environment variables. Designing activity-supportive built environments should be a higher international health priority. Results provide evidence in support of global initiatives to increase physical activity and control noncommunicable diseases while achieving sustainable development goals.

Delay Discount Rate Moderates a Physical Activity Intervention Testing Immediate Rewards.

Financial incentives can increase physical activity (PA), but differences in the immediacy of reward delivery and individual differences in delay discount rates (i.e., higher discount values associated with less tolerance for delayed rewards) may explain differential responding. The current study tested whether delay discount rate moderated the relative effectiveness of immediate financial rewards on increasing daily PA. Inactive, overweight adults (ages 18-60, N = 96) were randomized to receive either smaller, immediate goal-contingent rewards or larger, delayed rewards for participation. Delay discount rates were derived for those who completed the Monetary Choice Questionnaire (N = 85). Linear mixed models tested interactions between discount rate and intervention arm on changes in mean daily Fitbit-measured steps from baseline to intervention phases, and rates of change during the intervention phase. Across all groups, participants increased by 2258 steps/day on average from baseline to intervention and declined by 9 steps/day across the 4-month intervention phase. The mean increase in daily steps was greater for immediate reward-arm participants across all discount rates. Descriptive exploration of reward effects by delay discount rate suggested that the magnitude of reward effects decreased at higher discount rates. During the 4-month intervention phase, rates of decline in daily steps were similar in both reward arms, but declines became more pronounced at higher discount rates. Overall, intervention efficacy decreased with less tolerance for delays. The importance of financial reward immediacy for increasing PA appears to increase with greater delay discount rates.

Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions.

Mobile health (mHealth) technologies are contributing to the increasing relevance of control engineering principles in understanding and improving health behaviors, such as physical activity. Social Cognitive Theory (SCT), one of the most influential theories of health behavior, has been used as the conceptual basis for behavioral interventions for smoking cessation, weight management, and other health-related outcomes. This paper presents a control-oriented dynamical systems model of SCT based on fluid analogies that can be used in system identification and control design problems relevant to the design and analysis of intensively adaptive interventions. Following model development, a series of simulation scenarios illustrating the basic workings of the model are presented. The model's usefulness is demonstrated in the solution of two important practical problems: 1) semiphysical model estimation from data gathered in a physical activity intervention (the MILES study) and 2) as a means for discerning the range of "ambitious but doable" daily step goals in a closed-loop behavioral intervention aimed at sedentary adults. The model is the basis for ongoing experimental validation efforts, and should encourage additional research in applying control engineering technologies to the social and behavioral sciences.

Do associations of sex, age and education with transport and leisure-time physical activity differ across 17 cities in 12 countries?

BACKGROUND: Leisure-time and transport activity domains are studied most often because they are considered more amenable to intervention, but to date evidence on these domains is limited. The aim of the present study was to examine patterns of socio-demographic correlates of adults' leisure-time and transport physical activity and how these associations varied across 17 cities in 12 countries. METHODS: Participants (N = 13,745) aged 18-66 years in the IPEN Adult study and with complete data on socio-demographic and self-reported physical activity characteristics were included. Participants reported frequency and duration of leisure-time and transport activities in the last 7 days using the self-administered International Physical Activity Questionnaire-Long Form. Six physical activity outcomes were examined in relation with age, education, and sex, and analyses explored variations by city and curvilinear associations. RESULTS: Sex had the most consistent results, with five of six physical activity outcomes showing females were less active than males. Age had the most complex associations with self-report transport and leisure-time physical activity. Compared to older people, younger adults were less likely to engage in transport physical activity, but among those who did, younger people were likely to engage in more active minutes. Curvilinear associations were found between age and all three leisure-time physical activity outcomes, with the youngest and the oldest being more active. Positive associations with education were found for leisure-time physical activity only. There were significant interactions of city with sex and education for multiple physical activity outcomes. CONCLUSIONS: Although socio-demographic correlates of physical activity are widely studied, the present results provide new information. City-specific findings suggest there will be value in conducting more detailed case studies. The curvilinear associations of age with leisure-time physical activity as well as significant interactions of leisure-time activity with sex and education should be further investigated. The findings of lower leisure-time physical activity among females as well as people with low education suggest that greater and continued efforts in physical activity policies and programs tailored to these high-risk groups are needed internationally.

Associations of built environment and proximity of food outlets with weight status: Analysis from 14 cities in 10 countries.

The study aimed to examine associations of neighborhood built environments and proximity of food outlets (BE measures) with body weight status using pooled data from an international study (IPEN Adult). Objective BE measures were calculated using geographic information systems for 10,008 participants (4463 male, 45%) aged 16-66 years in 14 cities. Participants self-reported proximity to three types of food outlets. Outcomes were body mass index (BMI) and overweight/obesity status. Male and female weight status associations with BE measures were estimated by generalized additive mixed models. Proportion (95% CI) of overweight (BMI 25 to <30) ranged from 16.6% (13.1, 19.8) to 41.1% (37.3, 44.7), and obesity (BMI ≥ 30) from 2.9% (1.3, 4.4) to 31.3% (27.7, 34.7), with Hong Kong being the lowest and Cuernavaca, Mexico highest for both proportions. Results differed by sex. Greater street intersection density, public transport density and perceived proximity to restaurants (males) were associated with lower odds of overweight/obesity (BMI ≥ 25). Proximity to public transport stops (females) was associated with higher odds of overweight/obesity. Composite BE measures were more strongly related to BMI and overweight/obesity status than single variables among men but not women. One standard deviation improvement in the composite measures of BE was associated with small reductions of 0.1-0.5% in BMI but meaningful reductions of 2.5-5.3% in the odds of overweight/obesity. Effects were linear and generalizable across cities. Neighborhoods designed to support public transport, with food outlets within walking distance, may contribute to global obesity control.

A Markov approach for increasing precision in the assessment of data-intensive behavioral interventions.

Health 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.

Modeling individual differences: A case study of the application of system identification for personalizing a physical activity intervention.

BACKGROUND: Control systems engineering methods, particularly, system identification (system ID), offer an idiographic (i.e., person-specific) approach to develop dynamic models of physical activity (PA) that can be used to personalize interventions in a systematic, scalable way. The purpose of this work is to: (1) apply system ID to develop individual dynamical models of PA (steps/day measured using Fitbit Zip) in the context of a goal setting and positive reinforcement intervention informed by Social Cognitive Theory; and (2) compare insights on potential tailoring variables (i.e., predictors expected to influence steps and thus moderate the suggested step goal and points for goal achievement) selected using the idiographic models to those selected via a nomothetic (i.e., aggregated across individuals) approach. METHOD: A personalized goal setting and positive reinforcement intervention was deployed for 14 weeks. Baseline PA measured in weeks 1-2 was used to inform personalized daily step goals delivered in weeks 3-14. Goals and expected reward points (granted upon goal achievement) were pseudo-randomly assigned using techniques from system ID, with goals ranging from their baseline median steps/day up to 2.5× baseline median steps/day, and points ranging from 100 to 500 (i.e., $0.20-$1.00). Participants completed a series of daily self-report measures. Auto Regressive with eXogenous Input (ARX) modeling and multilevel modeling (MLM) were used as the idiographic and nomothetic approaches, respectively. RESULTS: Participants (N = 20, mean age = 47.25 ±â€¯6.16 years, 90% female) were insufficiently active, overweight (mean BMI = 33.79 ±â€¯6.82 kg/m2) adults. Results from ARX modeling suggest that individuals differ in the factors (e.g., perceived stress, weekday/weekend) that influence their observed steps/day. In contrast, the nomothetic model from MLM suggested that goals and weekday/weekend were the key variables that were predictive of steps. Assuming the ARX models are more personalized, the obtained nomothetic model would have led to the identification of the same predictors for 5 of the 20 participants, suggesting a mismatch of plausible tailoring variables to use for 75% of the sample. CONCLUSION: The idiographic approach revealed person-specific predictors beyond traditional MLM analyses and unpacked the inherent complexity of PA; namely that people are different and context matters. System ID provides a feasible approach to develop personalized dynamical models of PA and inform person-specific tailoring variable selection for use in adaptive behavioral interventions.

Adaptive step goals and rewards: a longitudinal growth model of daily steps for a smartphone-based walking intervention.

Adaptive interventions are an emerging class of behavioral interventions that allow for individualized tailoring of intervention components over time to a person's evolving needs. The purpose of this study was to evaluate an adaptive step goal + reward intervention, grounded in Social Cognitive Theory delivered via a smartphone application (Just Walk), using a mixed modeling approach. Participants (N = 20) were overweight (mean BMI = 33.8 ± 6.82 kg/m2), sedentary adults (90% female) interested in participating in a 14-week walking intervention. All participants received a Fitbit Zip that automatically synced with Just Walk to track daily steps. Step goals and expected points were delivered through the app every morning and were designed using a pseudo-random multisine algorithm that was a function of each participant's median baseline steps. Self-report measures were also collected each morning and evening via daily surveys administered through the app. The linear mixed effects model showed that, on average, participants significantly increased their daily steps by 2650 (t = 8.25, p < 0.01) from baseline to intervention completion. A non-linear model with a quadratic time variable indicated an inflection point for increasing steps near the midpoint of the intervention and this effect was significant (t2 = -247, t = -5.01, p < 0.001). An adaptive step goal + rewards intervention using a smartphone app appears to be a feasible approach for increasing walking behavior in overweight adults. App satisfaction was high and participants enjoyed receiving variable goals each day. Future mHealth studies should consider the use of adaptive step goals + rewards in conjunction with other intervention components for increasing physical activity.

Tutorial for Using Control Systems Engineering to Optimize Adaptive Mobile Health Interventions.

BACKGROUND: 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.

Physical activity in relation to urban environments in 14 cities worldwide: a cross-sectional study.

BACKGROUND: Physical inactivity is a global pandemic responsible for over 5 million deaths annually through its effects on multiple non-communicable diseases. We aimed to document how objectively measured attributes of the urban environment are related to objectively measured physical activity, in an international sample of adults. METHODS: We based our analyses on the International Physical activity and Environment Network (IPEN) adult study, which was a coordinated, international, cross-sectional study. Participants were sampled from neighbourhoods with varied levels of walkability and socioeconomic status. The present analyses of data from the IPEN adult study included 6822 adults aged 18-66 years from 14 cities in ten countries on five continents. Indicators of walkability, public transport access, and park access were assessed in 1·0 km and 0·5 km street network buffers around each participant's residential address with geographic information systems. Mean daily minutes of moderate-to-vigorous-intensity physical activity were measured with 4-7 days of accelerometer monitoring. Associations between environmental attributes and physical activity were estimated using generalised additive mixed models with gamma variance and logarithmic link functions. RESULTS: Four of six environmental attributes were significantly, positively, and linearly related to physical activity in the single variable models: net residential density (exp[b] 1·006 [95% CI 1·003-1·009]; p=0·001), intersection density (1·069 [1·011-1·130]; p=0·019), public transport density (1·037 [1·018-1·056]; p=0·0007), and number of parks (1·146 [1·033-1·272]; p=0·010). Mixed land use and distance to nearest public transport point were not related to physical activity. The difference in physical activity between participants living in the most and least activity-friendly neighbourhoods ranged from 68 min/week to 89 min/week, which represents 45-59% of the 150 min/week recommended by guidelines. INTERPRETATION: Design of urban environments has the potential to contribute substantially to physical activity. Similarity of findings across cities suggests the promise of engaging urban planning, transportation, and parks sectors in efforts to reduce the health burden of the global physical inactivity pandemic. FUNDING: Funding for coordination of the IPEN adult study, including the present analysis, was provided by the National Cancer Institute of National Institutes of Health (CA127296) with studies in each country funded by different sources.

Do associations between objectively-assessed physical activity and neighbourhood environment attributes vary by time of the day and day of the week? IPEN adult study.

BACKGROUND: To more accurately quantify the potential impact of the neighbourhood environment on adults' physical activity (PA), it is important to compare environment-PA associations between periods of the day or week when adults are more versus less likely to be in their neighbourhood and utilise its PA resources. We examined whether, among adults from 10 countries, associations between objectively-assessed neighbourhood environment attributes and moderate-to-vigorous physical activity (MVPA) varied by time of the day and day of the week. The secondary aim was to examine whether such associations varied by employment status, gender and city. METHODS: This cross-sectional study included 6,712 adults from 14 cities across 10 countries with ≥1 day of valid accelerometer-assessed MVPA and complete information on socio-demographic and objectively-assessed environmental characteristics within 0.5 and 1 km street-network buffers around the home. Accelerometer measures (MVPA min/h) were created for six time periods from early morning until late evening/night, for weekdays and weekend days separately. Associations were estimated using generalized additive mixed models. RESULTS: Time of the day, day of week, gender and employment status were significant moderators of environment-MVPA associations. Land use mix was positively associated with MVPA in women who were employed and in men irrespective of their employment status. The positive associations between MVPA and net residential density, intersection density and land use mix were stronger in the mornings of weekdays and the afternoon/evening periods of both weekdays and weekend days. Associations between number of parks and MVPA were stronger in the mornings and afternoon/evenings irrespective of day of the week. Public transport density showed consistent positive associations with MVPA during weekends, while stronger effects on weekdays were observed in the morning and early evenings. CONCLUSIONS: This study suggests that space and time constraints in adults' daily activities are important factors that determine the impact of neighbourhood attributes on PA. Consideration of time-specific associations is important to better characterise the magnitude of the effects of the neighbourhood environment on PA. Future research will need to examine the contribution of built environment characteristics of areas surrounding other types of daily life centres (e.g., workplaces) to explaining adults' PA at specific times of the day.

Neighborhood built environment and socio-economic status in relation to multiple health outcomes in adolescents.

The study aim was to examine associations of neighborhood built environment and neighborhood socio-economic status (SES) with multiple physical activity (PA) behaviors, sedentary time, and obesity indicators among adolescents. Cross-sectional study of 325 adolescents aged 14-18years recruited from schools in Valencia, Spain. Participants' home neighborhoods were classified according to walkability and SES levels. Walkability was defined as an index of three built environment characteristics (i.e., residential density, land use mix, and street connectivity) based on geographic information system data. Moderate-vigorous PA (MVPA) and sedentary time were assessed using accelerometers. Active commuting to school, leisure-time PA, and time in specific sedentary activities were evaluated by questionnaire. Objectively measured weight and height were used to calculate body mass index, and percent body fat was analyzed by bioelectrical impedance. Data were collected in 2013-15. Mixed model regression analyses were performed. Analyses showed an SES-by-walkability interaction for MVPA on weekends. MVPA was highest in high-SES/high-walkable neighborhoods. Another SES-by-walkability interaction was found for sedentary minutes per weekend day. The lowest average sedentary minutes were found in high-SES/high-walkable areas. Neighborhood SES was positively related to participation in sports teams/PA classes and, negatively to time spent in sedentary behaviors. Adolescents living in lower-SES neighborhoods spent more time watching TV and had more obesity and body fat. Present findings strengthen the rationale for targeting neighborhood built and SES environments as health promotion interventions for adolescents.

Online versus in-person comparison of Microscale Audit of Pedestrian Streetscapes (MAPS) assessments: reliability of alternate methods.

BACKGROUND: An online version of the Microscale Audit of Pedestrian Streetscapes (Abbreviated) tool was adapted to virtually audit built environment features supportive of physical activity. The current study assessed inter-rater reliability of MAPS Online between in-person raters and online raters unfamiliar with the regions. METHODS: In-person and online audits were conducted for a total of 120 quarter-mile routes (60 per site) in Phoenix, AZ and San Diego, CA. Routes in each city included 40 residential origins stratified by walkability and SES, and 20 commercial centers. In-person audits were conducted by raters residing in their region. Online audits were conducted by raters in the alternate location using Google Maps (Aerial and Street View) images. The MAPS Abbreviated Online tool consisted of four sections: overall route, street segments, crossings and cul-de-sacs. Items within each section were grouped into subscales, and inter-rater reliability (ICCs) was assessed for subscales at multiple levels of aggregation. RESULTS: Online and in-person audits showed excellent agreement for overall positive microscale (ICC = 0.86, 95% CI [0.80, 0.90]) and grand scores (ICC = 0.93, 95% CI [0.89, 0.95]). Substantial to near-perfect agreement was found for 21 of 30 (70%) subscales, valence, and subsection scores, with ICCs ranging from 0.62, 95% CI [0.50, 0.72] to 0.95, 95% CI [0.93, 0.97]. Lowest agreement was found for the aesthetics and social characteristics scores, with ICCs ranging from 0.07, 95% CI [-0.12, 0.24] to 0.27, 95% CI [0.10, 0.43]. CONCLUSIONS: Results support use of the MAPS Abbreviated Online tool to reliably assess microscale neighborhood features that support physical activity and may be used by raters residing in different geographic regions and unfamiliar with the audit areas.

International comparison of observation-specific spatial buffers: maximizing the ability to estimate physical activity.

BACKGROUND: Advancements in geographic information systems over the past two decades have increased the specificity by which an individual's neighborhood environment may be spatially defined for physical activity and health research. This study investigated how different types of street network buffering methods compared in measuring a set of commonly used built environment measures (BEMs) and tested their performance on associations with physical activity outcomes. METHODS: An internationally-developed set of objective BEMs using three different spatial buffering techniques were used to evaluate the relative differences in resulting explanatory power on self-reported physical activity outcomes. BEMs were developed in five countries using 'sausage,' 'detailed-trimmed,' and 'detailed,' network buffers at a distance of 1 km around participant household addresses (n = 5883). RESULTS: BEM values were significantly different (p < 0.05) for 96% of sausage versus detailed-trimmed buffer comparisons and 89% of sausage versus detailed network buffer comparisons. Results showed that BEM coefficients in physical activity models did not differ significantly across buffering methods, and in most cases BEM associations with physical activity outcomes had the same level of statistical significance across buffer types. However, BEM coefficients differed in significance for 9% of the sausage versus detailed models, which may warrant further investigation. CONCLUSIONS: Results of this study inform the selection of spatial buffering methods to estimate physical activity outcomes using an internationally consistent set of BEMs. Using three different network-based buffering methods, the findings indicate significant variation among BEM values, however associations with physical activity outcomes were similar across each buffering technique. The study advances knowledge by presenting consistently assessed relationships between three different network buffer types and utilitarian travel, sedentary behavior, and leisure-oriented physical activity outcomes.

Adaptive goal setting and financial incentives: a 2 × 2 factorial randomized controlled trial to increase adults' physical activity.

BACKGROUND: Emerging interventions that rely on and harness variability in behavior to adapt to individual performance over time may outperform interventions that prescribe static goals (e.g., 10,000 steps/day). The purpose of this factorial trial was to compare adaptive vs. static goal setting and immediate vs. delayed, non-contingent financial rewards for increasing free-living physical activity (PA). METHODS: A 4-month 2 × 2 factorial randomized controlled trial tested main effects for goal setting (adaptive vs. static goals) and rewards (immediate vs. delayed) and interactions between factors to increase steps/day as measured by a Fitbit Zip. Moderate-to-vigorous PA (MVPA) minutes/day was examined as a secondary outcome. RESULTS: Participants (N = 96) were mainly female (77%), aged 41 ± 9.5 years, and all were insufficiently active and overweight/obese (mean BMI = 34.1 ± 6.2). Participants across all groups increased by 2389 steps/day on average from baseline to intervention phase (p < .001). Participants receiving static goals showed a stronger increase in steps per day from baseline phase to intervention phase (2630 steps/day) than those receiving adaptive goals (2149 steps/day; difference = 482 steps/day, p = .095). Participants receiving immediate rewards showed stronger improvement (2762 step/day increase) from baseline to intervention phase than those receiving delayed rewards (2016 steps/day increase; difference = 746 steps/day, p = .009). However, the adaptive goals group showed a slower decrease in steps/day from the beginning of the intervention phase to the end of the intervention phase (i.e. less than half the rate) compared to the static goals group (-7.7 steps vs. -18.3 steps each day; difference = 10.7 steps/day, p < .001) resulting in better improvements for the adaptive goals group by study end. Rate of change over the intervention phase did not differ between reward groups. Significant goal phase x goal setting x reward interactions were observed. CONCLUSIONS: Adaptive goals outperformed static goals (i.e., 10,000 steps) over a 4-month period. Small immediate rewards outperformed larger, delayed rewards. Adaptive goals with either immediate or delayed rewards should be preferred for promoting PA. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02053259 registered prospectively on January 31, 2014.

Reliability between online raters with varying familiarities of a region: Microscale Audit of Pedestrian Streetscapes (MAPS).

Background: To test inter-rater reliability of the online Microscale Audit of Pedestrian Streetscapes (MAPS) tool between raters with varying familiarities of Phoenix, Arizona. Methods: The online MAPS tool, based on the MAPS in-field audit tool and scoring system, was used for audits. Sixty route pairs, 141 segment pairs, and 92 crossing pairs in Phoenix were included. Each route, segment or crossing was audited by two independent raters: one rater in Phoenix and the other in San Diego, California, respectively. Item, subscale scores, and total scores reliability analyses were computed using Kappa or intra-class correlation coefficient (ICC). Results: The route overall score had substantial reliability (ICC: 0.832). Of the route subscale and overall scores, sixteen out of twenty had moderate to substantial reliability (ICC: 0.616-0.906), and the four subscales had fair reliability (ICC: 0.409-0.563). Sixteen out of twenty scores in segment and crossing sections demonstrated fair to substantial reliability (ICC: 0.448-0.897), and the remaining four had slight reliability (ICC: 0.348-0.364). Conclusions: Most of the online MAPS items, subscales, and overall scores demonstrated fair to substantial reliability between raters with varied familiarities of the Phoenix area. Results support use of online MAPS to measure microscale elements of the built environment by raters unfamiliar with a region.