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Behavioral weight loss programs often prescribe physical activity (PA) goals in terms of minutes/week of moderate-to-vigorous PA (MVPA) and steps/day. However, the impact of meeting each type of goal prescription on weight loss is unclear, particularly in digitally-based (eHealth/mHealth) programs. This secondary analysis of a randomized trial examined the effects of meeting steps-based and minutes-based goals on weight loss in an eHealth behavioral weight control program.Adults in the control arm received a 6-month online behavioral weight loss intervention with prescribed weekly goals for daily steps and minutes of MVPA. The number of weeks steps-based and minutes-based goals were met (≥100% and ≥75% thresholds) based on self-reported PA were examined as predictors of 6-month weight loss among those providing weight outcomes (Participants (BMI 35.6 kg/mGreater attainment of PA goals prescribed as steps and minutes of MVPA independently contribute to similar weight loss outcomes in a 6-month online behavioral weight loss intervention. Future research should determine whether promoting adherence to combined steps-based and minutes-based goals produces better weight loss than utilizing either goal alone and identify strategies that improve adherence.

Objective There is a high prevalence of obesity in people with asthma, and obesity is associated with poorly controlled asthma. Significant weight loss might improve asthma control: the purpose of this study was to investigate patient characteristics and factors that might affect implementation of a weight loss and/or roflumilast intervention, to target both obesity and asthma. Methods A cross‐sectional study of people with obesity and poorly controlled asthma performed at 13 sites across the United States. Results One hundred and two people participated in this study. Median BMI was 37 (IQR 35–42). The majority, 55%, were African American and 76% were female. Fifty two percent had very poorly controlled asthma. Most participants were quite sedentary (70% reported being inactive or participating only in light‐intensity activities according to the Stanford Brief Activity Survey). Participants reported significant impairments related to physical function on the Impact of Weight on Quality of Life‐Lite questionnaire (median score 67 [IQR 41–84]). Thirty‐five percent of participants reported mild, and 2 % moderate, depressive symptoms as assessed by the Patient Health Questionnaire‐9. Conclusions Poorly controlled asthma and obesity often affect minority populations and are associated with significant impairments in health related to physical function and low levels of physical activity that might complicate efforts to lose weight. Interventions targeted at poorly controlled asthma associated with obesity in the United States need to address factors complicating health in underserved communities, such as increasing opportunities for physical activity, while also managing activity limitations related to the combination of asthma and obesity.

Physical activity (PA) goal adherence is consistently associated with greater weight loss during behavioral obesity treatment, and early weight loss response predicts future weight loss success. However, it remains unclear which behaviors during the initial weeks of treatment distinguish responders from nonresponders and might be effective targets for improving treatment outcomes. To characterize subgroups with distinct patterns of PA goal adherence during the initial 2 months of an online, group-based weight control program and determine associations between these patterns and 6-month weight loss. Participants received an online behavioral obesity intervention with PA goals and daily self-monitoring. Weekly adherence to step goals and moderate-to-vigorous PA (MVPA) minute goals based on self-monitoring records were examined using latent class analysis. Body weight was objectively measured at 0, 2, and 6 months. Participants (N = 212; 91.5% female, 31.6% race/ethnic minority, mean body mass index: 35.8 ± 5.9 kg/m2) clustered into three subgroups based on early goal attainment: "Both PA Goals," "MVPA Goals Only," and "Neither PA Goal." The "Both PA Goals" class had significantly greater 6-month weight loss (estimated mean weight loss [95% CI]: -9.4% [7.4 to 11.5]) compared to the "MVPA Goals Only" (-4.8% [3.4 to 6.1]) and "Neither PA Goal" classes (-2.5% [1.4 to 3.6]). Individuals meeting both PA goals early in treatment achieve greater weight losses than those meeting MVPA but not step goals, pointing to the need to explore factors associated with nonadherence to each of the PA goals to better understand these potential targets for treatment refinement and adaptive interventions.This study is the first to characterize subgroups of individuals engaged in a behavioral weight control program with distinct patterns of early physical activity (PA) goal attainment. These early PA patterns emerged as a novel factor associated with subsequent weight loss and provide an important lens to view early treatment engagement. The greatest weight losses were seen in the subgroup likely to meet program goals for both weekly minutes of moderate-to-vigorous PA and daily steps. Understanding the factors associated with PA goal attainment during the initial 2 months of a behavioral weight control program may provide insights that will allow early identification of likely treatment success and detect individuals at risk for reduced weight losses, which could signal individuals for whom additional or different support may then be directed to increase weight loss success.

Summary Objective Internet delivery of behavioural weight control interventions offers potential for broad geographic reach and accessibility, but weight losses online fall short of those produced with the same programme delivered in‐person. This pilot study examined feasibility and preliminary efficacy of a video‐based platform for delivering weekly chat as part of a 6‐month, 24‐session online group behavioural weight control programme compared with the established text‐based format, which has produced the best online weight losses to date. Method Women with obesity (N = 32) were randomized to either (a) weekly video group chat sessions and provided with a cellular‐enabled scale (Video) or (b) Text‐based weekly chat sessions and given a digital scale (Text) and followed for 6 months to determine weight loss and treatment engagement. Results Women randomized to the ideo condition lost more weight than those in the Text condition (−5.0 ± 6.0% vs. −3.0 ± 4.1%, respectively) at 6 months, although the difference was not statistically significant. However, women in the Video condition had significantly greater treatment engagement, with greater self‐monitoring and website utilization than those in the Text condition. Conclusions Videoconference delivery of group‐based online weight control accompanied by a cellular‐connected scale may promote greater treatment engagement and weight loss than text‐based chat. A larger, adequately powered study is warranted to determine which elements drive these enhanced treatment outcomes.

Obesity and overweight are key contributors to chronic disease and pose a large public health challenge, with approximately 74% of American men classified as overweight or obese (Flegal et al., 2012). In the United States in 2008, the medical costs associated with obesity reached $147 billion, and annual estimated medical costs are currently $1500 higher for individuals with obesity (Finkelstein et al., 2009). In 2013, approximately $2.4 billion was spent on weight loss services provided by over 29,000 companies, and 85% of consumers of the services were women (IBISWorld, 2013). Men who are overweight or obese are generally recognized as a hard to involve, yet high-risk group for obesity-related chronic disease treatment (Morgan et al., 2011a; Young et al., 2012). A variety of studies have demonstrated that men are less likely to perceive themselves as overweight, and therefore are less likely to attempt weight loss or participate in a weight loss program (Andersson and Rossner, 1997; Brown et al., 2015; Collins et al., 2011; Lemon et al., 2009; Morgan et al., 2011a; Young et al., 2012). In a systematic review of weight loss interventions conducted online, notably

OBJECTIVE Dietary self-monitoring is consistently related to both short- and long-term weight loss. The purpose of this study was to quantify the time spent and the daily frequency of self-monitoring necessary for weight-loss success. METHODS Participants in a 24-week, online, behavioral weight-control intervention recorded daily dietary intake using a Web-based dietary analysis program. Time spent self-monitoring and frequency of dietary journal page access were captured. Weight loss (kilograms) and the proportion of participants losing ≥ 5% and ≥ 10% of baseline weight were assessed at 6 months. RESULTS Participants (n = 142; BMI 35.8 kg/m2 ; 90.8% female; 23.2% African American) spent an average of 23.2 minutes per day self-monitoring in month 1 and 14.6 minutes in month 6. For those still recording any minutes self-monitoring by month 6 (65.5%), there were no significant differences in time spent based on weight loss; however, those losing either ≥ 5% or ≥ 10% logged in to the journal Web page significantly more times per day (1.6 vs. 2.4, P

BACKGROUND Standard behavioral weight loss interventions often set uniform physical activity (PA) goals and promote PA self-monitoring; however, adherence remains a challenge, and recommendations may not accommodate all individuals. Identifying patterns of PA goal attainment and self-monitoring behavior will offer a deeper understanding of how individuals adhere to different types of commonly prescribed PA recommendations (ie, minutes of moderate-to-vigorous physical activity [MVPA] and daily steps) and guide future recommendations for improved intervention effectiveness. OBJECTIVE This study examined weekly patterns of adherence to step-based and minute-based PA goals and self-monitoring behavior during a 6-month online behavioral weight loss intervention. METHODS Participants were prescribed weekly PA goals for steps (7000-10,000 steps/day) and minutes of MVPA (50-200 minutes/week) as part of a lifestyle program. Goals gradually increased during the initial 2 months, followed by 4 months of fixed goals. PA was self-reported daily on the study website. For each week, participants were categorized as adherent if they self-monitored their PA and met the program PA goal, suboptimally adherent if they self-monitored but did not meet the program goal, or nonadherent if they did not self-monitor. The probability of transitioning into a less adherent status was examined using multinomial logistic regression. RESULTS Participants (N=212) were predominantly middle-aged females with obesity, and 67 (31.6%) self-identified as a racial/ethnic minority. Initially, 73 (34.4%) participants were categorized as adherent to step-based goals, with 110 [51.9%] suboptimally adherent and 29 [13.7%] nonadherent, and there was a high probability of either remaining suboptimally adherent from week to week or transitioning to a nonadherent status. However, 149 (70.3%) participants started out adherent to minute-based goals (34 [16%] suboptimally adherent and 29 [13.7%] nonadherent), with suboptimally adherent seen as the most variable status. During the graded goal phase, participants were more likely to transition to a less adherent status for minute-based goals (odds ratio [OR] 1.39, 95% CI 1.31-1.48) compared to step-based goals (OR 1.24, 95% CI 1.17-1.30); however, no differences were seen during the fixed goal phase (minute-based goals: OR 1.06, 95% CI 1.05-1.08; step-based goals: OR 1.07, 95% CI 1.05-1.08). CONCLUSIONS States of vulnerability to poor PA adherence can emerge rapidly and early in obesity treatment. There is a window of opportunity within the initial 2 months to bring more people toward adherent behavior, especially those who fail to meet the prescribed goals but engage in self-monitoring. Although this study describes the probability of adhering to step- and minute-based targets, it will be prudent to determine how individual characteristics and contextual states relate to these behavioral patterns, which can inform how best to adapt interventions. CLINICALTRIAL ClinicalTrials.gov NCT02688621; https://clinicaltrials.gov/ct2/show/NCT02688621

BACKGROUND: Weight loss might improve asthma control in people with obesity. However, people with asthma might have particular challenges losing weight and the amount of weight loss needed to improve asthma control is not clear. OBJECTIVES: To pilot test an online weight loss intervention and to estimate the impact of weight loss on asthma control. METHODS: We performed a 6-month, single-arm, futility trial of an online weight loss intervention at two centers. To reject the assumption of futility, 9 or more participants had to lose at least 5% of their body weight. We also assessed the association between weight loss (5% or more) and asthma outcomes. RESULTS: Forty-three participants (85% women) started the weight loss intervention; median and interquartile range (IQR) for BMI was 40.3 kg/m(2) (34.7, 46.8), and 14 (12, 17) for Asthma Control Test score. At 6 months, 10 participants (23%, 95%CI 12%, 39%) lost at least 5% of their initial weight. Weight loss of at least 5% was associated with a clinically and statistically significant improvements in their Asthma Control Test (median [IQR] increase of 3 [1 7], p< 0.05), Marks Asthma Quality of Life Score (−9.5 [ −18, −3], p=0.008), and their general health-related quality of life score (RAND-36) improved by 9.4 [ 2.8, 22.5], p=0.014). CONCLUSION: An online weight loss intervention has potential to meet FDA guidance for product evaluation (at least 5% weight loss in 35% of people) for obesity, and is associated with a clinically significant improvement in asthma control, quality of life, and overall health-related quality of life.

Americans are cooking fewer meals at home and eating more convenience foods prepared elsewhere. Cooking at home is associated with higher quality diets, while a reduction in cooking may be associated with increases in obesity and risk factors for chronic disease. The aims of this study were to examine cooking as an intervention for weight control in overweight and obese adults, and whether such an intervention increases participants&rsquo, food agency and diet quality. Overweight and obese adults were randomized into one of two intervention conditions: active or demonstration. Both conditions received the same 24-week behavioral weight loss intervention, and bi-weekly cooking classes. The active condition prepared a weekly meal during a hands-on lesson, while the demonstration condition observed a chef prepare the same meal. The active condition lost significantly more weight at six months compared with the demonstration condition (7.3% vs. 4.5%). Both conditions saw significant improvements in food agency scores and Healthy Eating Index scores, though no significant differences were noted between groups. The addition of active cooking to a weight management intervention may improve weight loss outcomes, though benefits in diet quality and cooking behaviors may also be seen with the addition of a demonstration-only cooking intervention.

Background Knee extensor muscle performance is reduced after lower extremity trauma and orthopedic surgical interventions. At-home use of neuromuscular electrical stimulation (NMES) may improve functional recovery, but adherence to at-home interventions is low. Greater benefits from NMES may be realized with closer monitoring of adherence to at-home prescriptions and more frequent patient-provider interactions. Objective This study aimed to develop a cyber-physical system to monitor at-home adherence to NMES prescription and facilitate patient-provider communications to improve adherence in near real time. Methods The RehabTracker cyber-physical system was developed to accomplish this goal and comprises four components: (1) hardware modifications to a commercially available NMES therapy device to monitor device use and provide Bluetooth functionality; (2) an iPhone Operating System–based mobile health (mHealth) app that enables patient-provider communications in near real time; (3) a clinician portal to allow oversight of patient adherence with device use; and (4) a back-end server to store data, enable adherence analysis, and send automated push notifications to the patient. These four elements were designed to be fully compliant with the Health Insurance Portability and Accountability Act. The system underwent formative testing in a cohort of patients following anterior cruciate ligament rupture (n=7) to begin to assess face validity. Results Compared with the NMES device software–tracked device use, the RehabTracker system recorded 83% (40/48) of the rehabilitation sessions, with 100% (32/32) of all sessions logged by the system in 4 out of 7 patients. In patients for whom tracking of automated push notifications was enabled, 100% (29/29) of the push notifications sent by the back-end server were received by the patient. Process, hardware, and software issues contributing to these inaccuracies are detailed. Conclusions RehabTracker represents a promising mHealth app for tracking and improving adherence with at-home NMES rehabilitation programs and warrants further refinement and testing.

Purpose The purpose of this paper is to explore commonalities and differences between projects and processes, and between project management (PjM) and process management (PcM), with a view to challenge this dichotomic typology, clarify the gray areas in between and propose better ways to classify and manage different endeavors. Design/methodology/approach The research compares different tools and techniques used in both fields, explores the respective literatures and uses various examples to bring out similarities and differences. Findings The current paradigms engender a number of organizational endeavors, which are actually complex processes being managed as projects, using the PjM body of knowledge. Because each instantiation takes a somewhat different form, it is treated as a one-of-a-kind undertaking; whereby many of the opportunities for learning and continuous improvement associated with PcM are lost. A reframing and typology is proposed to clarify the central notions involved. Research limitations/implications The proposed model has not been tested empirically and the authors could not agree on all aspects of the paper, though existing differences are more about degrees, nuances and wording than about the basic findings of the paper. Practical implications The research makes the case that two research and practice communities that are evolving independently have much to gain by adopting a unified model and integrating their respective bodies of knowledge. Practitioners would thus access resources that are better adapted to the management challenges they are facing and gain a sustainable source of strategic advantage. Originality/value The paper challenges long-established paradigms between two distinct research streams. A new typology and classification criteria are proposed.

Little is known about the impact of the relationship built between interventionists and their participants on weight loss. Our objective is to determine whether stronger early (i.e., 4 weeks) participant-interventionist bond is associated with significantly greater weight loss success and treatment adherence. Three hundred and ninety-eight participants received an online group behavioral weight control program over 18 months. Weight was measured objectively at baseline and at 6 and 18 months. At 4 weeks, participants completed the Working Alliance Inventory (WAI) bonding subscale, which measures the collaborative bond with the interventionist. Adherence (i.e., session attendance and online self-monitoring diary completion) was recorded by the interventionists. Participant-interventionist bond at 4 weeks was significantly associated with weight loss at 6 months (t(322) = −2.14, p = .03) but not at 18 months (t(290) = 0.53, p = .60). The model indicated that participant-interventionist bond at 4 weeks was a significant predictor of adherence at 6 months (b = .063, standard error [SE] = .30, p = .04), and 6 month adherence was a significant predictor of weight loss at 6 months (b = −.594, SE = .049, p < .0001). The indirect effect of the WAI-Bond subscale was significant (b = −.037, p = .03, 95% confidence interval: −.074, −.002) and accounted for 54% of the total effect of participant-interventionist bond on weight loss. However, the total weight loss explained by WAI-Bond subscale was small (0.04 kg). Participant-interventionist bond between participant and interventionist is an early predictor of treatment adherence and weight loss success at 6 months; however, the degree of weight loss explained by participant-interventionist bond is small and was not maintained at 18 months.