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BackgroundThe COVID-19 pandemic has had a widespread impact on attendance in biomedical research and health care visits. ObjectiveThis study aimed to identify when and how American adults might feel comfortable about resuming in-person research and health care visits. MethodsCross-sectional questionnaire data were collected from 135 adults (age: median 48 years; women: n=113, 83.7%; White participants: n=92, 68.2%) who were engaged in health-related research. ResultsMore than half of the respondents (65/122, 53.3%) felt that the COVID-19 pandemic positively affected their desire to participate in research. Although 73.6% (95/129) of respondents also indicated a willingness to attend in-person health care visits while Centers for Disease Control and Prevention (CDC) guidelines are implemented, 85.8% (109/127) indicated a willingness to attend in-person, outdoor visits, and 92.2% (118/128) reported a willingness to attend drive-through visits (with CDC guidelines implemented during both visit types). Videoconferencing was the most preferred format for intervention visits; however, adults over the age of 65 years preferred this format less than younger adults (P=.001). ConclusionsResearchers and clinicians should continue to provide opportunities for continuing the conduction of remote-based interventions while enforcing CDC guidelines during in-person visits.

BackgroundTechnology-mediated obesity treatments are commonly affected by poor long-term adherence. Supportive Accountability Theory suggests that the provision of social support and oversight toward goals may help to maintain adherence in technology-mediated treatments. However, no tool exists to measure the construct of supportive accountability. ObjectiveThis study aimed to develop and psychometrically validate a supportive accountability measure (SAM) by examining its performance in technology-mediated obesity treatment. MethodsSecondary data analyses were conducted in 2 obesity treatment studies to validate the SAM (20 items). Study 1 examined reliability, criterion validity, and construct validity using an exploratory factor analysis in individuals seeking obesity treatment. Study 2 examined the construct validity of SAM in technology-mediated interventions involving different self-monitoring tools and varying amounts of phone-based interventionist support. Participants received traditional self-monitoring tools (standard, in-home self-monitoring scale [SC group]), newer, technology-based self-monitoring tools (TECH group), or these newer technology tools plus additional phone-based support (TECH+PHONE group). Given that the TECH+PHONE group involves more interventionist support, we hypothesized that this group would have greater supportive accountability than the other 2 arms. ResultsIn Study 1 (n=353), the SAM showed strong reliability (Cronbach α=.92). A factor analysis revealed a 3-factor solution (representing Support for Healthy Eating Habits, Support for Exercise Habits, and Perceptions of Accountability) that explained 69% of the variance. Convergent validity was established using items from the motivation for weight loss scale, specifically the social regulation subscale (r=0.33; P

The visibility of female role models in science is vital for engaging and retaining women in scientific fields. In this study, we analyse four senior secondary science courses delivered across the states and territories in Australia: Biology, Chemistry, Environmental Science, and Physics. We compared male and female representation within the science courses by examining the mentions of male and female scientists along with the context of their inclusions in the syllabuses. We find a clear gender bias with only one unique mention of a female scientist. We also find a clear Eurocentric focus and narrow representation of scientists. This bias will contribute to the continuing low engagement of women in scientific fields. We outline possible solutions to address this issue, including the accreditation of scientific discoveries to include female scientists and explicit discussion of structural barriers preventing the participation and progression of women in science, technology, engineering, and mathematics (STEM).

ObjectiveTo characterize vaping behavior and nicotine intake during ad libitum e-cigarette access.MethodsThirteen adult e-cigarette users had 90 minutes of videotaped ad libitum access to their usual e-cigarette. Plasma nicotine was measured before and every 15 minutes after the first puff; subjective effects were measured before and after the session.ResultsAverage puff duration and interpuff interval were 3.5±1.4 seconds (±SD) and 118±141 seconds, respectively. 12% of puffs were unclustered puffs while 43%, 28%, and 17% were clustered in groups of 2-5, 6-10, and >10 puffs, respectively. On average, 4.0±3.3 mg of nicotine was inhaled; the maximum plasma nicotine concentration (Cmax) was 12.8±8.5 ng/mL. Among the 8 tank users, number of puffs was positively correlated with amount of nicotine inhaled, Cmax, and area under the plasma nicotine concentration-time curve (AUC0→90min) while interpuff interval was negatively correlated with Cmax and AUC0→90.ConclusionVaping patterns differ from cigarette smoking. Plasma nicotine levels were consistent with intermittent dosing of nicotine from e-cigarettes compared to the more bolus dosing from cigarettes. Differences in delivery patterns and peak levels of nicotine achieved could influence the addictiveness of e-cigarettes compared to conventional cigarettes.

A growing body of research has focused on the utility of adaptive intervention models for promoting long-term weight loss maintenance; however, evaluation of these interventions often requires customized smartphone applications. Building such an app from scratch can be resource-intensive. To support a novel clinical trial of an adaptive intervention for weight loss maintenance, we developed a companion app, MyTrack+, to pair with a main commercial app, FatSecret (FS), leveraging a user-centered design process for rapid prototyping and reducing software engineering efforts. MyTrack+ seamlessly integrates data from FS and the BodyTrace smart scale, enabling participants to log and self-monitor their health data, while also incorporating customized questionnaires and timestamps to enhance data collection for the trial. We iteratively refined the app by first developing initial mockups and incorporating feedback from a usability study with 17 university students. We further improved the app based on an in-the-wild pilot study with 33 participants in the target population, emphasizing acceptance, simplicity, customization options, and dual app usage. Our work highlights the potential of using an iterative human-centered design process to build a companion app that complements a commercial app for rapid prototyping, reducing costs, and enabling efficient research progress. [ABSTRACT FROM AUTHOR]

This is a review of Margaret Wheatley's Who Do You Choose To Be? (2nd Edition). [ABSTRACT FROM AUTHOR]

Background: For individuals who are eligible but unlikely to join comprehensive weight loss programs, a low burden self‐weighing intervention may be a more acceptable approach to weight management. Methods: This was a single‐arm feasibility trial of a 12‐month self‐weighing intervention. Participants were healthcare patients with a BMI ≥25 kg/m2 with a weight‐related comorbidity or a BMI >30 kg/m2 who reported lack of interest in joining a comprehensive weight loss program, or did not enroll in a comprehensive program after being provided program information. In the self‐weighing intervention, participants were asked to weigh themselves daily on a cellular connected scale and were sent text messages every other week with tailored weight change feedback, including messages encouraging use of comprehensive programs if weight gain occurred. Results: Of 86 eligible patients, 39 enrolled (45.3%) in the self‐weighing intervention. Self‐weighing occurred on average 4.6 days/week (SD = 1.4). At 12 months, 12 participants (30.8%) lost ≥3% baseline weight, 11 (28.2%) experienced weight stability (±3% baseline), 6 (15.4%) gained ≥3% of baseline weight, and 10 (25.6%) did not have available weight data to evaluate. Three participants reported joining a weight loss program during the intervention (7.7%). Participants reported high intervention satisfaction in quantitative ratings (4.1 of 5), and qualitative interviews identified areas of satisfaction (e.g., timing and content of text messages) and areas for improvement (e.g., increasing personalization of text messages). Conclusion: A low‐burden self‐weighing intervention can reach adults with overweight/obesity who would be unlikely to engage in comprehensive weight loss programs; the efficacy of this intervention for preventing weight gain should be further evaluated in a randomized trial. [ABSTRACT FROM AUTHOR]

Rate of nicotine metabolism has been identified as an important factor influencing nicotine intake and can be estimated using the nicotine metabolite ratio (NMR), a validated biomarker of CYP2A6 enzyme activity. Individuals who metabolize nicotine faster (higher NMR) may alter their smoking behavior to titrate their nicotine intake in order to maintain similar levels of nicotine in the body compared to slower nicotine metabolizers. There are known racial differences in the rate of nicotine metabolism with African Americans on average having a slower rate of nicotine metabolism compared to Whites. The goal of this study was to determine if there are racial differences in the relationship between rate of nicotine metabolism and measures of nicotine intake assessed using multiple biomarkers of nicotine and tobacco smoke exposure. Using secondary analyses of the screening data collected in a recently completed clinical trial, treatment-seeking African American and White daily smokers (10 or more cigarettes per day) were grouped into NMR quartiles so that the races could be compared at the same NMR, even though the distribution of NMR within race differed. The results indicated that rate of nicotine metabolism was a more important factor influencing nicotine intake in White smokers. Specifically, Whites were more likely to titrate their nicotine intake based on the rate at which they metabolize nicotine. However, this relationship was not found in African Americans. Overall there was a greater step-down, linear type relationship between NMR groups and cotinine or cotinine/cigarette in African Americans, which is consistent with the idea that differences in blood cotinine levels between the African American NMR groups were primarily due to differences in CYP2A6 enzyme activity without titration of nicotine intake among faster nicotine metabolizers.

BackgroundAfrican American (AA) smokers experience greater tobacco-related disease burden than Whites, despite smoking fewer cigarettes per day (CPD). Understanding factors that influence daily nicotine intake in AA smokers is an important step toward decreasing tobacco-related health disparities. One factor of interest is smoking topography, or the study of puffing behavior.Aims(i) to create a model using puff characteristics, nicotine dependence, and nicotine metabolism to predict daily nicotine exposure, and (ii) to compare puff characteristics and nicotine intake from two cigarettes smoked at different times to ensure the reliability of the puff characteristics included in our model.MethodsSixty AA smokers smoked their preferred brand of cigarette at two time points through a topography device. Plasma nicotine, expired CO, and changes in subjective measures were measured before and after each cigarette. Total nicotine equivalents (TNE) was measured from 24-hour urine collected during ad libitum smoking.ResultsIn a model predicting daily nicotine exposure, total puff volume, CPD, sex, and menthol status were significant predictors (R(2) = 0.44, P < 0.001). Total puff volume was significantly greater and inter-puff intervals were significantly shorter after ad lib smoking compared with the first cigarette of the day, but puffing behaviors for both cigarettes were highly correlated (r range = 0.69-0.89, P < 0.001) within-subjects.ConclusionThis is the first study, to our knowledge, to show that puff characteristics of individual cigarettes are predictive of daily nicotine intake.ImpactThese findings enhance our understanding of the relationship between smoking behavior and nicotine intake in AA smokers. Cancer Epidemiol Biomarkers Prev; 25(6); 936-43. ©2016 AACR.

Research has suggested that there may be a bidirectional association between stress and physical activity; however, much of this work has been conducted in athletes or adults with normal weight. The current study investigated the bidirectional association between stress and physical activity in adults with overweight and obesity. For a full year, during and after a 12-week, Internet-based weight loss program, 74 participants (BMI = 31.2 kg/m.sup.2) were asked to report stress and minutes of physical activity each week. An increase in stress was associated with less physical activity during the same week and predicted fewer minutes of physical activity the following week. Finally, each 1 h increase in physical activity on a given week was associated with a small decrease in stress ratings the following week. Results confirmed the bidirectional association between stress and physical activity in a sample of adults with overweight/obesity, and supported results highlighting stress as a barrier to physical activity. Future studies should investigate whether adding intervention components to decrease stress or to reinforce physical activity can improve physical activity engagement in this population., Author(s): Andrea N. Brockmann [sup.1] , Kathryn M. Ross [sup.1] Author Affiliations: (1) grid.15276.37, 0000 0004 1936 8091, Department of Clinical and Health Psychology, College of Public Health and Health [...]

IntroductionThe Food and Drug Administration has the authority to regulate tobacco product constituents, including nicotine, to promote public health. Reducing the nicotine content in cigarettes may lead to lower levels of addiction. Smokers however may compensate by smoking more cigarettes and/or smoking more intensely. The objective of this study was to test whether individual differences in the level of nicotine dependence (as measured by the Fagerstrom Test of Cigarette Dependence [FTCD]) and/or the rate of nicotine metabolism influence smoking behavior and exposure to tobacco toxicants when smokers are switched to reduced nicotine content cigarettes (RNC).MethodsData from 51 participants from a previously published clinical trial of RNC were analyzed. Nicotine content of cigarettes was progressively reduced over 6 months and measures of smoking behavior, as well as nicotine metabolites and tobacco smoke toxicant exposure, CYP2A6 and nicotinic CHRNA5-A3-B4 (rs1051730) genotype were measured.ResultsHigher baseline FTCD predicted smoking more cigarettes per day (CPD), higher cotinine and smoke toxicant levels while smoking RNC throughout the study, with no interaction by RNC level. Time to first cigarette (TFC) was associated with differences in compensation. TFC within 10 min was associated with a greater increase in CPD compared to TFC greater than 10 min. Neither rate of nicotine metabolism, nor CYP2A6 or nicotinic receptor genotype, had an effect on the outcome variables of interest.ConclusionsFTCD is associated with overall exposure to nicotine and other constituents of tobacco smoke, while a short TFC is associated with an increased compensatory response after switching to RNC.

Objective: Greater self‐monitoring of caloric intake and weight has been associated with success at both initial weight loss and long‐term maintenance. Given the existence of wide variability in weight loss outcomes and the key role of self‐monitoring within behavioral weight management interventions, this study examined individual variability in associations between self‐monitoring and weight change and whether demographic factors could predict who may best benefit from self‐monitoring. Methods: Participants were 72 adults with overweight or obesity (mean ± SD, age = 50.6 ± 10.3; body mass index = 31.2 ± 4.5 kg/m2; 71%Female; 83%White) enrolled in a 12‐week weight loss program followed by a 40‐week observational maintenance period. Participants were encouraged to self‐monitor caloric intake and weight daily and to report these data via a study website each week. Multilevel mixed models were used to estimate week‐to‐week associations between self‐monitoring and weight change, by individual and linear regressions and ANOVAs were used to explore demographic differences in these associations. Results: Most participants (68%) demonstrated statistically significant negative associations between self‐monitoring of either caloric intake or weight and weight change. Of these, 76% benefited from self‐monitoring both caloric intake and weight, 18% from self‐monitoring caloric intake only, and 6% from self‐weighing only. The magnitude of associations between self‐monitoring and weight change did not significantly differ by age, gender, race/ethnicity, education, or income, all ps > 0.05. Conclusions: Differences in the effectiveness of self‐monitoring for weight loss were not observed by demographic characteristics. Future research should examine if other factors may predict the effectiveness of self‐monitoring. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to develop a predictive algorithm of "high‐risk" periods for weight regain after weight loss. Methods: Longitudinal mixed‐effects models and random forest regression were used to select predictors and develop an algorithm to predict weight regain on a week‐to‐week basis, using weekly questionnaire and self‐monitoring data (including daily e‐scale data) collected over 40 weeks from 46 adults who lost ≥5% of baseline weight during an initial 12‐week intervention (Study 1). The algorithm was evaluated in 22 adults who completed the same Study 1 intervention but lost <5% of baseline weight and in 30 adults recruited for a separate 30‐week study (Study 2). Results: The final algorithm retained the frequency of self‐monitoring caloric intake and weight plus self‐report ratings of hunger and the importance of weight‐management goals compared with competing life demands. In the initial training data set, the algorithm predicted weight regain the following week with a sensitivity of 75.6% and a specificity of 45.8%; performance was similar (sensitivity: 81%–82%, specificity: 30%–33%) in testing data sets. Conclusions: Weight regain can be predicted on a proximal, week‐to‐week level. Future work should investigate the clinical utility of adaptive interventions for weight‐loss maintenance and develop more sophisticated predictive models of weight regain. [ABSTRACT FROM AUTHOR]

Research has suggested that memories of mood, emotions, and behaviors are not purely unbiased retrieval, but more similar to reconstructions based on current opinions, positive or negative experiences associated with the memory, and how a person believes they would have felt, thought, or acted. We investigated this memory bias in 66 adult participants with overweight/obesity who rated their mood, emotions, and behaviors during a 12-week, Internet-based behavioral weight loss program and later recalled these ratings at Month 3 (immediate post-test) and Month 12 (follow-up). At Month 3, participants recalled the intervention more positively than reported previously, p = .010, but reported remembering the intervention more negatively at the Month 12 follow-up, p = .004. Memory bias was associated with initial weight loss and regain, ps < .05, such that participants who lost more weight at Month 3 remembered their mood, emotions, and behaviors during intervention more positively, and those who regained more weight at Month 12, more negatively. Future research should investigate whether this bias is associated with willingness to re-engage with intervention., Author(s): Kathryn M. Ross [sup.1] , Rena R. Wing [sup.2] Author Affiliations: (1) Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 0000 [...]

Obesity is a prevalent health care issue associated with disability, premature morality, and high costs. Behavioral weight management interventions lead to clinically significant weight losses in overweight and obese individuals; however, many individuals are not able to participate in these face-to-face treatments due to limited access, cost, and/or time constraints. Technological advances such as widespread access to the Internet, increased use of smartphones, and newer behavioral self-monitoring tools have resulted in the development of a variety of eHealth weight management programs. In the present paper, a summary of the most current literature is provided along with potential solutions to methodological challenges (e.g., high attrition, minimal participant racial/ethnic diversity, heterogeneity of technology delivery modes). Dissemination and policy implications will be highlighted as future directions for the field of eHealth weight management., Author(s): Andrea T. Kozak [sup.1] , Joanna Buscemi [sup.2] , Misty A. W. Hawkins [sup.3] , Monica L. Wang [sup.4] , Jessica Y. Breland [sup.5] [sup.6] , Kathryn M. Ross [...]

It is not known whether individuals successful at long term weight loss maintenance differ in chronotype (i.e., being a 'morning' or 'evening' person) or sleep habits compared to those who are overweight and obese. We compared Morningness-Eveningness Questionnaire (MEQ) and Pittsburgh Sleep Quality Index scores of 690 National Weight Control Registry (NWCR) members (73 % female, 93 % white, age = 51.7 ± 12.5, BMI = 26.4 ± 5.1) to 75 enrollees in two behavioral weight loss interventions (INT; 77 % female, 88 % white, age = 55.7 ± 10.4, BMI = 36.2 ± 4.7). Controlling for age, MEQ scores were higher in NWCR than INT, p = .004, such that more NWCR than INT were morning-types and fewer were evening types, p = .014. Further, NWCR participants reported better sleep quality, longer sleep duration, and shorter latency to sleep onset compared to INT, ps < .05, and fewer NWCR participants reported, Author(s): Kathryn M. Ross[sup.1] , J. Graham Thomas[sup.1] , Rena R. Wing[sup.1] Author Affiliations: (1) Weight Control & Diabetes Research Center, Department of Psychiatry and Human Behavior, Alpert Medical School [...]