Quality of life among colorectal cancer survivors participating in a pilot randomized controlled trial of a web-based dietary intervention with text messages.

PURPOSE: We aimed to estimate the effect of a 12-week web-based dietary intervention with text messages on quality of life (QoL) among colorectal cancer (CRC) survivors. METHODS: Between 2017 and 2018, 50 CRC survivors were randomized (1:1) to receive a 12-week web-based dietary intervention with daily text messages or wait-list control. Health-related QoL was assessed using the European Organization for the Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Core 30 (QLQ-C30) and colorectal quality of life module (QLQ-CR29) at baseline, 12, and 24 weeks. Within- and between-group mean changes in health-related QoL with 95% confidence intervals (CI) were calculated for both arms. RESULTS: Compared to the controls, participants receiving the intervention had an improvement in emotional functioning (mean change: 14.3; 95% CI: 3.0, 25.6) at 12 weeks and social functioning (mean change: 13.8; 95% CI: 2.1, 25.5) at 24 weeks. A decrease of fatigue from baseline was also observed in the intervention arm (mean change: - 9.1; 95% CI: - 17.1, - 1.1) at 24 weeks. No other changes in QoL scores were associated with the intervention. CONCLUSION: CRC survivors randomized to receive a web-based dietary intervention with text messages experienced higher emotional and social functioning. Further study with a larger population may be warranted. TRIAL REGISTRATION: clinicaltrials.gov, NCT02965521. Registered 16 November 2016, https://clinicaltrials.gov/ct2/keydates/NCT02965521.

Mechanisms of an App-Based Physical Activity Intervention and Maintenance in Community-Dwelling Women: Mediation Analyses of a Randomized Controlled Trial.

BACKGROUND: Understanding the mechanism of interventions that increase physical activity (PA) is critical to developing robust intervention strategies. AIMS: This study aims to examine the mediation effects of hypothesized changes in self-efficacy, social support, and barriers on daily changes in accelerometer-measured steps and the duration of moderate to vigorous PA over 3-month intervention and 6-month maintenance periods with a mobile phone-based PA education program. METHODS: Data were analyzed for a total of 210 physically inactive women who were randomized. The mean (SD) age was 52.4 (11.0) years. The framework of Baron and Kenny and the Sobel test were used to evaluate the proportion of the treatment effect explained by mediation factors. RESULTS: Postintervention PA changes were mediated by a reduction in self-efficacy and barriers and an increase in social support from friends during the intervention and maintenance periods (P ≤ .05). However, social support from family was significant only during the intervention, but not the maintenance (P = .90). Barriers to PA had the largest mediation effect on the intervention, explaining 13% to 16% of the 3-month intervention effect and 14% to 19% of the 6-month maintenance effect on daily steps and duration of moderate to vigorous PA minutes (P ≤ .05). CONCLUSIONS: Incorporating strategies for overcoming PA barriers and promoting social support for PA is important for the design of interventions for physically inactive women. However, a reduction in self-efficacy was observed in the intervention group at 3 and 9 months as compared with the control group. This unexpected finding requires further investigation.

Behavioral Analytics for Myopic Agents.

Many multi-agent systems have a single coordinator providing incentives to a large number of agents. Two challenges faced by the coordinator are a finite budget from which to allocate incentives, and an initial lack of knowledge about the utility function of the agents. Here, we present a behavioral analytics approach for solving the coordinator's problem when the agents make decisions by maximizing utility functions that depend on prior system states, inputs, and other parameters that are initially unknown. Our behavioral analytics framework involves three steps: first, we develop a model that describes the decision-making process of an agent; second, we use data to estimate the model parameters for each agent and predict their future decisions; and third, we use these predictions to optimize a set of incentives that will be provided to each agent. The framework and approaches we propose in this paper can then adapt incentives as new information is collected. Furthermore, we prove that the incentives computed by this approach are asymptotically optimal with respect to a loss function that describes the coordinator's objective. We optimize incentives with a decomposition scheme, where each sub-problem solves the coordinator's problem for a single agent, and the master problem is a pure integer program. We conclude with a simulation study to evaluate the effectiveness of our approach for designing a personalized weight loss program. The results show that our approach maintains efficacy of the program while reducing its costs by up to 60%, while adaptive heuristics provide substantially less savings.

Quality of life of colorectal cancer survivors participating in a pilot randomized controlled trial of physical activity trackers and daily text messages.

PURPOSE: There are over 1.3 million colorectal cancer (CRC) survivors in the USA, many of whom report lower health-related quality of life (HRQoL) years after treatment. This study aimed to explore the effect of digital health tools on HRQoL in CRC survivors. METHODS: We conducted a two-arm, randomized controlled trial of 42 subjects who had completed treatment for CRC. Participants in the intervention arm received a Fitbit Flex™ and daily text messages for 12 weeks. HRQoL was assessed as a secondary endpoint in both arms at enrollment and 12 weeks using the Medical Outcomes Study Short Form Survey (SF-36) and the Functional Assessment of Cancer Therapy-Colorectal (FACT-C). Survey score changes from enrollment to 12 weeks were compared between the two arms using independent t tests, and scores at enrollment and 12 weeks were compared using paired t tests. RESULTS: An increase in the FACT-C functional well-being subscale was observed in individuals in the intervention arm pre- to post-intervention (median difference, 2; interquartile range (IQR), 1, 4; P = .02). Although the between-group comparison was not statistically significant, no change in the functional well-being subscale was observed in the control arm (median difference, 0; IQR, 1, 1; P = .71). No other measures of HRQoL appeared to differ within arm across time points or between arms. CONCLUSION: A 12-week digital physical activity intervention may improve functional well-being among CRC survivors. Larger randomized studies are needed to determine if digital health tools improve functional well-being among CRC survivors and if this improvement can be sustained over time. TRIAL REGISTRATION: NCT02966054; registration date, November 17, 2016.

Slower upper extremity function in older adults with hyperkyphosis negatively impacts the 6-min walk test.

BACKGROUND: Approximately 30% to 40% of older adults have hyperkyphosis, defined as excessive curvature of the thoracic spine. Hyperkyphosis is associated with increased morbidity and mortality. This study aimed to determine whether hyperkyphosis (Cobb's angle) and upper extremity tasks were independently associated with the 6-min walk test (6MWT) in community-dwelling older adults with hyperkyphosis. METHODS: In this cross-sectional study, we studied 71 women and 28 men aged 60-87 from the study of hyperkyphosis, exercise, and function trial (SHEAF) who had kyphosis, 3 timed upper extremity tasks and the 6MWT assessed at their baseline visit. We used standing lateral spine radiographs and a standardized protocol for thoracic kyphosis (T4-T12) to measure Cobb angle of kyphosis. In addition, 3 activity of daily living (ADL) extremity tests (putting on and removing a laboratory coat, picking up a penny from the floor, and lifting a 7-lb. book to a shelf) were used. RESULTS: The mean ± SD age was 70.1 ± 6.1 years. The mean ± SD Cobb angle of kyphosis was 57.4 ± 12.5 degrees. On average ± SD, the participants walked 504.8 ± 84.2 m in 6 min and took 2.4 ± 2.2 prescription medications. The mean ± SD height was 164.7 ± 8.5 cm, weight was 68.7 ± 13.1 kg, and BMI was 25.2 ± 4.0 kg/m2. Multivariate regression revealed that age, height, upper extremity book lift task, and the number of prescribed medications were significant predictors of performance on the 6MWT (p < 0.05). CONCLUSIONS: While kyphosis was not associated with the 6MWT, timed tests of upper extremity function indicated that upper body dynamics can affect walking performance. In addition, sociodemographic factors and the number of prescribed medications were significant contributing factors to the 6MWT in older adults with mild to moderate hyperkyphosis. These results illustrate multifactorial influences on physical performance and the need for an integrated and targeted approach in helping older hyperkyphotic adults maintain healthy physical functioning as they age.

Perceived Risk of Heart Attack and Type 2 Diabetes in Hispanic Adults With Overweight and Obesity.

BACKGROUND: Individuals with a greater perceived risk of heart attack or type 2 diabetes tend to adopt recommended lifestyle changes to minimize their risks. Despite the rapidly growing Hispanic population in the United States, data regarding their perceived risks are lacking. OBJECTIVE: This study aimed to examine the perceived risk of suffering a heart attack and/or developing type 2 diabetes and to explore the factors associated with these risk perceptions in Hispanic adults with overweight/obesity. METHODS: We analyzed 69 Hispanic adults with overweight/obesity who participated in the screening/baseline visit for the Adelgaza study, a weight loss and diabetes prevention trial, using descriptive statistics and logistic regressions. Heart attack or type 2 diabetes risk perception was assessed using a single-item questionnaire. RESULTS: The mean (SD) values for age and body mass index (BMI) were 43.8 (11.2) years and 31.7 (4.5) kg/m 2 , respectively. Of all participants, 46.4% perceived a low risk for heart attack and 29.0% perceived a low risk for developing type 2 diabetes in their lifetime, whereas only 11.6% reported both risk perceptions. Older age, lower BMI, and longer walking duration (minutes) per day were significantly associated with a lower perceived risk of heart attack ( P < .05). Having no family history of heart attack, lower BMI, and lower fat intake were significant predictors of a lower diabetes-risk perception ( P < .05). CONCLUSIONS: Hispanic adults with overweight/obesity seem to underestimate their risks of heart attack and type 2 diabetes.

Factors associated with the 6-minute walk test performance in older adults with hyperkyphosis.

Age-related hyperkyphosis is associated with adverse health outcomes, such as falls, fractures, and mortality. However, few studies investigated the relationship between the severity of hyperkyphosis and physical endurance in older adults. This study examined whether a degree of hyperkyphosis curvature was independently associated with the 6-minute walk test (6MWT) distance. We analyzed the baseline data of 112 older adults aged 60-92 enrolled in the Specialized Center of Research (SCOR) Kyphosis trial. The majority of the sample had at least a college degree and were white. On average, participants walked 503.9 (SD 82.3) meters in 6 minutes. Multivariate regression results showed that the degree of hyperkyphosis curvature was not independently associated with the 6MWT distance, but taller height, lighter weight, and less prescription medication were significant predictors of better performance on the 6MWT distance. Validation of the study findings in a large, diverse older adult population is warranted.

A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss.

BACKGROUND: This systematic review aimed to evaluate AI chatbot characteristics, functions, and core conversational capacities and investigate whether AI chatbot interventions were effective in changing physical activity, healthy eating, weight management behaviors, and other related health outcomes. METHODS: In collaboration with a medical librarian, six electronic bibliographic databases (PubMed, EMBASE, ACM Digital Library, Web of Science, PsycINFO, and IEEE) were searched to identify relevant studies. Only randomized controlled trials or quasi-experimental studies were included. Studies were screened by two independent reviewers, and any discrepancy was resolved by a third reviewer. The National Institutes of Health quality assessment tools were used to assess risk of bias in individual studies. We applied the AI Chatbot Behavior Change Model to characterize components of chatbot interventions, including chatbot characteristics, persuasive and relational capacity, and evaluation of outcomes. RESULTS: The database search retrieved 1692 citations, and 9 studies met the inclusion criteria. Of the 9 studies, 4 were randomized controlled trials and 5 were quasi-experimental studies. Five out of the seven studies suggest chatbot interventions are promising strategies in increasing physical activity. In contrast, the number of studies focusing on changing diet and weight status was limited. Outcome assessments, however, were reported inconsistently across the studies. Eighty-nine and thirty-three percent of the studies specified a name and gender (i.e., woman) of the chatbot, respectively. Over half (56%) of the studies used a constrained chatbot (i.e., rule-based), while the remaining studies used unconstrained chatbots that resemble human-to-human communication. CONCLUSION: Chatbots may improve physical activity, but we were not able to make definitive conclusions regarding the efficacy of chatbot interventions on physical activity, diet, and weight management/loss. Application of AI chatbots is an emerging field of research in lifestyle modification programs and is expected to grow exponentially. Thus, standardization of designing and reporting chatbot interventions is warranted in the near future. SYSTEMATIC REVIEW REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO): CRD42020216761 .

Secondary analysis of change in physical function after exercise intervention in older adults with hyperkyphosis and low physical function.

BACKGROUND: Hyperkyphosis is common in older adults and associated with low physical function and reduced health related quality of life (HrQol). Improved kyphosis has been previously established in kyphosis-targeted interventions in randomized controlled trials in older adults with hyperkyphosis; however, evidence for improved physical function is conflicting. Few studies have investigated change in physical function after a targeted kyphosis intervention in older adults with low physical function. The primary aim in this descriptive study was to explore change in physical function after a progressive high-intensity 3-month targeted kyphosis exercise and posture training intervention in older adults with low physical function and hyperkyphosis. Secondary aims were to explore change in HrQol, spinal strength and spinal curvature, and adherence and safety of the intervention. METHODS: In this secondary analysis of the Specialized Center of Research (SCOR) Kyphosis randomized trial, 101 community dwelling older men and women with hyperkyphosis who completed the intervention were divided into a low function group (LFG) and high function group (HFG). Baseline characteristics were compared between LFG and HFG. Physical function, HrQol, spinal strength and spinal curvature (kyphosis and lordosis) pre/post intervention change scores were explored within and between groups. Adherence and adverse events were examined in the LFG and HFG. RESULTS: Twenty-six (26%) older adults were LFG, mean Short Phyiscal Performance Battery (SPPB) 9.62 (SD = 1.17) points. At baseline, the LFG was older than HFG (p = 0.005), experienced more pain, (p = 0.060), had worse physical function and HrQol (p ≤ 0.001), and comparable kyphosis (p = 0.640). SPPB changed 0.62 (95% CI: - 0.20 to 1.44) points in the LFG and - 0.04 (95%CI: - 0.28 to 0.19) points in the HFG, p = 0.020. Gait speed changed 0.04 (95% CI: - 0.02 to 0.10) m/s in the LFG. Kyphosis improved equally in both groups. Adherence to the intervention was 83% in the LFG and 79% in the HFG. There were no adverse events in either group. CONCLUSIONS: Older adults with low physical function and hyperkyphosis may improve physical function after a kyphosis targeted intervention. Older adults with low physical function may safely participate in targeted high-intensity kyphosis exercise and posture training. This observation needs to be confirmed in larger adequately powered studies. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT01766674 .

Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint.

BACKGROUND: Chatbots empowered by artificial intelligence (AI) can increasingly engage in natural conversations and build relationships with users. Applying AI chatbots to lifestyle modification programs is one of the promising areas to develop cost-effective and feasible behavior interventions to promote physical activity and a healthy diet. OBJECTIVE: The purposes of this perspective paper are to present a brief literature review of chatbot use in promoting physical activity and a healthy diet, describe the AI chatbot behavior change model our research team developed based on extensive interdisciplinary research, and discuss ethical principles and considerations. METHODS: We conducted a preliminary search of studies reporting chatbots for improving physical activity and/or diet in four databases in July 2020. We summarized the characteristics of the chatbot studies and reviewed recent developments in human-AI communication research and innovations in natural language processing. Based on the identified gaps and opportunities, as well as our own clinical and research experience and findings, we propose an AI chatbot behavior change model. RESULTS: Our review found a lack of understanding around theoretical guidance and practical recommendations on designing AI chatbots for lifestyle modification programs. The proposed AI chatbot behavior change model consists of the following four components to provide such guidance: (1) designing chatbot characteristics and understanding user background; (2) building relational capacity; (3) building persuasive conversational capacity; and (4) evaluating mechanisms and outcomes. The rationale and evidence supporting the design and evaluation choices for this model are presented in this paper. CONCLUSIONS: As AI chatbots become increasingly integrated into various digital communications, our proposed theoretical framework is the first step to conceptualize the scope of utilization in health behavior change domains and to synthesize all possible dimensions of chatbot features to inform intervention design and evaluation. There is a need for more interdisciplinary work to continue developing AI techniques to improve a chatbot's relational and persuasive capacities to change physical activity and diet behaviors with strong ethical principles.

Self-monitoring and reminder text messages to increase physical activity in colorectal cancer survivors (Smart Pace): a pilot randomized controlled trial.

BACKGROUND: Over 1.3 million people live with colorectal cancer in the United States. Physical activity is associated with lower risk of colorectal cancer recurrence and mortality. Interventions are needed to increase physical activity in colorectal cancer survivors. METHODS: We conducted a 2-arm non-blinded pilot randomized controlled trial at the University of California, San Francisco among 42 individuals who had completed curative-intent treatment for colorectal cancer to determine the feasibility and acceptability of a 12-week (84 days) physical activity intervention using a Fitbit Flex™ and daily text messages. Participants were randomized 1:1 to receive the intervention with print educational materials or print educational materials alone. We explored the impact of the intervention versus usual care on physical activity using ActiGraph GT3X+ accelerometers pre-/post-intervention. RESULTS: We screened 406 individuals and randomized 42 to intervention (n = 21) or control (n = 21) groups. During the 12-week study, the intervention arm wore their Fitbits a median of 74 days [88% of days in study period, interquartile range: 23-83 days] and responded to a median of 34 (out of 46) text messages that asked for a reply (interquartile range: 13-38 text messages). Among the 16 intervention participants who completed the feedback survey, the majority (88%) reported that the intervention motivated them to exercise and that they were satisfied with their experience. No statistically significant difference in change in moderate-to-vigorous physical activity was found from baseline to 12 weeks between arms. CONCLUSION: A 12-week physical activity intervention with a Fitbit and text messages was feasible and acceptable among colorectal cancer patients after curative treatment. Larger studies are needed to determine whether the intervention increases physical activity. TRIAL REGISTRATION: Clinicaltrials.gov Identifier NCT02966054 . Registered 17 November 2016, retrospectively registered.

Applying machine learning to predict future adherence to physical activity programs.

BACKGROUND: Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction models using objectively measured physical activity data in the Mobile Phone-Based Physical Activity Education program (mPED) trial. To the best of our knowledge, this is the first to apply Machine Learning methods to predict exercise relapse using accelerometer-recorded physical activity data. METHODS: We use logistic regression and support vector machine methods to design two versions of a Discontinuation Prediction Score (DiPS), which uses objectively measured past data (e.g., steps and goal achievement) to provide a numerical quantity indicating the likelihood of exercise relapse in the upcoming week. The respective prediction accuracy of these two versions of DiPS are compared, and then numerical simulation is performed to explore the potential of using DiPS to selectively allocate financial incentives to participants to encourage them to increase physical activity. RESULTS: we had access to a physical activity trial data that were continuously collected every 60 sec every day for 9 months in 210 participants. By using the first 15 weeks of data as training and test on weeks 16-30, we show that both versions of DiPS have a test AUC of 0.9 with high sensitivity and specificity in predicting the probability of exercise adherence. Simulation results assuming different intervention regimes suggest the potential benefit of using DiPS as a score to allocate resources in physical activity intervention programs in reducing costs over other allocation schemes. CONCLUSIONS: DiPS is capable of making accurate and robust predictions for future weeks. The most predictive features are steps and physical activity intensity. Furthermore, the use of DiPS scores can be a promising approach to determine when or if to provide just-in-time messages and step goal adjustments to improve compliance. Further studies on the use of DiPS in the design of physical activity promotion programs are warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT01280812 Registered on January 21, 2011.

Does having a buddy help women with young children increase physical activity? Lessons learned from a pilot study.

A 12-week pilot controlled trial of a physical activity (PA) buddy program was designed for women with young children. Conducted in January 2015 through March 2016, 49 women (mean age = 36.4 ± 4.8 years) were randomized to one of two groups. Both conditions received an in-person session, weekly step goals based on their baseline number of steps, an accelerometer, and its mobile app. Only women assigned to the intervention group brought their buddies and exercised together at least once per week. Buddies also received an accelerometer and its mobile app. Among 47 women who completed the study, we found no significant difference between groups in changes in the mean number of daily steps for the prior week (p = 0.56). When women were categorized into three groups based on change in buddies' PA, those with inactive buddies had significantly less change in number of steps than those with an active buddy and those in the control group (p < 0.018). Those with an active buddy also had higher friend social support scores for PA than the other two groups (p = 0.05). Thus, to improve PA, creating a social environment in which women associate with active individuals may be necessary.

Behavioral Modeling in Weight Loss Interventions.

Designing systems with human agents is difficult because it often requires models that characterize agents' responses to changes in the system's states and inputs. An example of this scenario occurs when designing treatments for obesity. While weight loss interventions through increasing physical activity and modifying diet have found success in reducing individuals' weight, such programs are difficult to maintain over long periods of time due to lack of patient adherence. A promising approach to increase adherence is through the personalization of treatments to each patient. In this paper, we make a contribution towards treatment personalization by developing a framework for predictive modeling using utility functions that depend upon both time-varying system states and motivational states evolving according to some modeled process corresponding to qualitative social science models of behavior change. Computing the predictive model requires solving a bilevel program, which we reformulate as a mixed-integer linear program (MILP). This reformulation provides the first (to our knowledge) formulation for Bayesian inference that uses empirical histograms as prior distributions. We study the predictive ability of our framework using a data set from a weight loss intervention, and our predictive model is validated by comparison to standard machine learning approaches. We conclude by describing how our predictive model could be used for optimization, unlike standard machine learning approaches which cannot.

Spousal influence on physical activity in physically inactive pregnant women: A cross-sectional study.

Regular physical activity (PA) is recommended during pregnancy, but the prevalence of pregnant women who met the recommended level for PA is very low. In this descriptive study, we examined the association between spousal characteristics (belief, knowledge, social support, and PA level) and pregnant women's PA level in 18 couples living in the San Francisco Bay Area. Among other spousal characteristics, only spousal PA level was a significant predictor of pregnant women's PA level regardless of whether it was unadjusted or adjusted by spouses' age and body index mass (p = .01). Our finding shows a need to develop strategies to incorporate spousal support for PA.

New insights into discrepancies between self-reported and accelerometer-measured moderate to vigorous physical activity among women - the mPED trial.

BACKGROUND: The aims of this report were 1) to describe the duration of moderate to vigorous physical activity (MVPA) and the proportion of participants meeting the recommended criterion of at least 150 min of MVPA per week as measured by the 7 Day Physical Activity Recall Questionnaire (7D-PAR) and accelerometer among women who were enrolled in the mPED trial; 2) to assess the level of agreement of the two measures using a Bland-Altman plot; and 3) to describe the positive and negative predictive values (PPV and NPV, respectively) of meeting the guidelines by calculating the percentage of women meeting the physical activity recommendation by the 7D-PAR who also met this recommendation based on data from the accelerometer. METHODS: Baseline data on duration of MVPA from the mPED trial were analyzed for 215 women. Among the women who met the recommended criterion by the 7D-PAR (self-report), we calculated the proportion of individuals who also met it by the accelerometer (objective measure). A Bland Altman Plot was used to assess concordance between the two measures. RESULTS: The mean age was 52.4 (±11.2) years; 54.4 % were white; and 48.8 % were single or divorced. While median MVPA was 160 min/week by the 7D-PAR, it was only 24 min/week in the accelerometer. A total of 117 women met the 150-min criterion by the 7D-PAR. Of these, only 18 also met the criterion by the objective measure (PPV 15.4 %, 95 % CI 9.4-23.2 %). Among the 98 women who did not meet the criterion by the 7D-PAR, none met it by the accelerometer (NPV 100 %). A Bland Altman plot showed the mean difference of +145 min between the two measures with a 95 % limit of agreement at + 471 to -181 min. CONCLUSIONS: The large discrepancy between the self-reported and objective measures of MVPA meeting the 150-min criterion suggests that self-reported physical activity measures should be used with caution in intervention studies. While our data suggest that self-report could be used to identify a physically inactive sample, it would be likely to over-estimate the proportions of women who become active in one or both arms of trials of interventions promoting MVPA. TRIAL REGISTRATION: ClinicalTrials.gov NCT01280812.

mHealth Physical Activity Intervention: A Randomized Pilot Study in Physically Inactive Pregnant Women.

INTRODUCTION: Physical inactivity is prevalent in pregnant women, and innovative strategies to promote physical activity are strongly needed. The purpose of the study was to test a 12-week mobile health (mHealth) physical activity intervention for feasibility and potential efficacy. METHODS: Participants were recruited between December 2012 and February 2014 using diverse recruitment methods. Thirty pregnant women between 10 and 20 weeks of gestation were randomized to an intervention (mobile phone app plus Fitbit) or a control (Fitbit) group. Both conditions targeted gradual increases in physical activity. The mHealth intervention included daily messages and a mobile phone activity diary with automated feedback and self-monitoring systems. RESULTS: On monthly average, 4 women were screened for initial eligibility by telephone and 2.5 were randomized. Intervention participants had a 1096 ± 1898 step increase in daily steps compared to an increase of 259 ± 1604 steps in control participants at 12 weeks. The change between groups in weekly mean steps per day during the 12-week study period was not statistically significant (p = 0.38). The intervention group reported lower perceived barrier to being active, lack of energy, than the control group at 12-week visit (p = 0.02). The rates of responding to daily messages and using the daily diary through the mobile app declined during the 12 week study period. DISCUSSION: It was difficult to recruit and randomize inactive women who wanted to increase physical activity during pregnancy. Pregnant women who were motivated to increase physical activity might find using mobile technologies in assessing and promoting PA acceptable. Possible reasons for the non-significant treatment effect of the mHealth intervention on physical activity are discussed. Public awareness of safety and benefits of physical activity during pregnancy should be promoted. Clinicaltrials.Gov Identifier NCT01461707.

MicroRNAs associated with exercise and diet: a systematic review.

MicroRNAs are posttranscriptional regulators of gene expression. MicroRNAs reflect individual biologic adaptation to exposures in the environment. As such, measurement of circulating microRNAs presents an opportunity to evaluate biologic changes associated with behavioral interventions (i.e., exercise, diet) for weight loss. The aim of this study was to perform a systematic review of the literature to summarize what is known about circulating microRNAs associated with exercise, diet, and weight loss. We performed a systematic review of three scientific databases. We included studies reporting on circulating microRNAs associated with exercise, diet, and weight loss in humans. Of 1,219 studies identified in our comprehensive database search, 14 were selected for inclusion. Twelve reported on microRNAs associated with exercise, and two reported on microRNAs associated with diet and weight loss. The majority of studies used a quasiexperimental, cross-sectional design. There were numerous differences in the type and intensity of exercise and dietary interventions, the biologic source of microRNAs, and the methodological approaches used quantitate microRNAs. Data from several studies support an association between circulating microRNAs and exercise. The evidence for an association between circulating microRNAs and diet is weaker because of a small number of studies. Additional research is needed to validate previous observations using methodologically rigorous approaches to microRNA quantitation to determine the specific circulating microRNA signatures associated with behavioral approaches to weight loss. Future directions include longitudinal studies to determine if circulating microRNAs are predictive of response to behavioral interventions.

Factors Associated with Underestimation of Weight Status among Caucasian, Latino, Filipino, and Korean Americans--DiLH Survey.

OBJECTIVE: To describe weight misperception and to examine the influence of sociodemographic factors on underestimation of weight status in Caucasian, Latino, Filipino, and Korean Americans. DESIGN: Data from 886 non-pregnant adults who participated in a cross-sectional survey administered in English, Spanish, and Korean were analyzed. The actual weight status derived from the participants' body mass index (BMI) categories and their perceived weight status were compared. A multiple logistic regression model was used to explore if underestimation of weight status was associated with ethnicity, sex, and education level. RESULTS: Caucasians, Latinos, Filipinos, and Koreans represented 19.4%, 26.8%, 27.4%, and 26.4%, respectively, of the total sample of 886. Overall, two in three participants correctly perceived their weight status, but 42% of Latinos underestimated their weight status and 22% of Koreans overestimated their weight status. Latino ethnicity, male, and low education (high school) were related to greater underestimation of weight status (P < .05). In contrast, Korean ethnicity was related to less underestimation of weight status (P < .05). CONCLUSIONS: Misperception of weight status should be counted in any efforts to develop a weight management intervention for Latino and Korean Americans.

Randomized controlled trial lifestyle interventions for Asian Americans: a systematic review.

OBJECTIVE: Asian Americans are the fastest-growing race in the United States. However, they are largely underrepresented in health research, particularly in lifestyle interventions. A systematic review was conducted to analyze the characteristics and quality of lifestyle intervention literature promoting changes in physical activity (PA), diet, and/or weight management targeting Asian Americans. METHOD: A systematic electronic database search identified randomized controlled clinical trials (RCTs), involving lifestyle interventions for Asian Americans, published from 1995 to 2013 conducted in the US. Data extraction was conducted from August through December 2013. RESULTS: Seven RCTs met the review criteria. Cross-study comparisons were difficult due to diversity in: RCT intervention designs, cultural appropriateness, outcome measures, sample size, and race/ethnic groups. Overall, risk of bias and cultural appropriateness scores were moderate to low. Five out of seven RCTs showed significant between group differences for PA, diet, and weight. In general, sample sizes were small or lacked sufficient power to fully analyze intervention efficacy. CONCLUSION: Evidence of the efficacy for lifestyle interventions among Asian Americans was mixed. Recommendations include: more rigorous RCT designs, more objective measures, larger Asian American sample sizes, culturally appropriate interventions, individual tailoring, maintenance phase with support, and providing education and modeling of lifestyle behaviors.