Deborah F. Tate

Evaluation of an internet-based physical activity intervention: A preliminary investigation

The Internet has the potential for delivering innovative, interactive physical activity (PA) interventions to large numbers of people. This study was designed to test the efficacy of an Internet intervention that consisted of a Web site plus 12 weekly e-mail tip sheets, compared with a waiting list control group. The Internet intervention was theory based and emphasized clear, graphical presentation of PA information. Sixty-five (30 intervention and 35 control) sedentary adult employees of several large hospitals (9 men and 56 women) were randomly assigned to 1 of the 2 study arms. Of the 65 participants, 57 completed the 1-month follow-up, and 52 completed the 3-month follow-up. At both 1 and 3 months, those in the intervention group were significantly more likely to have progressed in stage of motivational readiness for PA than participants in the control group: 1 month, χ2(1, N=52) = 4.05, p > .05; 3 months, χ2(1, N = 52) = 6.45, p > .01. We hypothesized that at 1 and 3 months, the intervention group would exhibit significant increases relative to the control group on the number of minutes of moderate activity. At the 1-month assessment, the intervention group did exhibit significant increases, relative to the control group in moderate minutes, F(1, 54) = 5.79, p > .05; however, at the 3-month assessment this difference was no longer significant. In addition, secondary analyses were conducted to examine total number of minutes of walking reported. At 1 month, the intervention group did exhibit significant increases, relative to the control group, in walking minutes, F(1, 54) = 12.1, p > .001. At the 3-month assessment, amount of time spent in walking activity continued to be significantly higher for the intervention group compared with the control group, F(1, 48) = 5.2, p > .05. These findings show that a theoretically based PA Web site and weekly e-mail tip sheets can have a short-term impact on PA motivation and behavior both at 1 and 3 months. As Internet access increases, and as bandwith and other technical attributes of this medium improve, Web site delivered health behavior interventions will become increasingly useful in public health promotion.

Replacing caloric beverages with water or diet beverages for weight loss in adults: main results of the Choose Healthy Options Consciously Everyday (CHOICE) randomized clinical trial

Background: Replacement of caloric beverages with noncaloric beverages may be a simple strategy for promoting modest weight reduction; however, the effectiveness of this strategy is not known. Objective: We compared the replacement of caloric beverages with water or diet beverages (DBs) as a method of weight loss over 6 mo in adults and attention controls (ACs). Design: Overweight and obese adults [n = 318; BMI (in kg/m2): 36.3 ± 5.9; 84% female; age (mean ± SD): 42 ± 10.7 y; 54% black] substituted noncaloric beverages (water or DBs) for caloric beverages (≥200 kcal/d) or made dietary changes of their choosing (AC) for 6 mo. Results: In an intent-to-treat analysis, a significant reduction in weight and waist circumference and an improvement in systolic blood pressure were observed from 0 to 6 mo. Mean (±SEM) weight losses at 6 mo were −2.5 ± 0.45% in the DB group, −2.03 ± 0.40% in the Water group, and −1.76 ± 0.35% in the AC group; there were no significant differences between groups. The chance of achieving a 5% weight loss at 6 mo was greater in the DB group than in the AC group (OR: 2.29; 95% CI: 1.05, 5.01; P = 0.04). A significant reduction in fasting glucose at 6 mo (P = 0.019) and improved hydration at 3 (P = 0.0017) and 6 (P = 0.049) mo was observed in the Water group relative to the AC group. In a combined analysis, participants assigned to beverage replacement were 2 times as likely to have achieved a 5% weight loss (OR: 2.07; 95% CI: 1.02, 4.22; P = 0.04) than were the AC participants. Conclusions: Replacement of caloric beverages with noncaloric beverages as a weight-loss strategy resulted in average weight losses of 2% to 2.5%. This strategy could have public health significance and is a simple, straightforward message. This trial was registered at clinicaltrials.gov as NCT01017783.

A Social Media-Based Physical Activity Intervention A Randomized Controlled Trial

BACKGROUND Online social networks, such as Facebook™, have extensive reach, and they use technology that could enhance social support, an established determinant of physical activity. This combination of reach and functionality makes online social networks a promising intervention platform for increasing physical activity. PURPOSE To test the efficacy of a physical activity intervention that combined education, physical activity monitoring, and online social networking to increase social support for physical activity compared to an education-only control. DESIGN RCT. Students (n=134) were randomized to two groups: education-only controls receiving access to a physical activity-focused website (n=67) and intervention participants receiving access to the same website with physical activity self-monitoring and enrollment in a Facebook group (n=67). Recruitment and data collection occurred in 2010 and 2011; data analyses were performed in 2011. SETTING/PARTICIPANTS Female undergraduate students at a large southeastern public university. INTERVENTION Intervention participants were encouraged through e-mails, website instructions, and moderator communications to solicit and provide social support related to increasing physical activity through a physical activity-themed Facebook group. Participants received access to a dedicated website with educational materials and a physical activity self-monitoring tool. MAIN OUTCOME MEASURES The primary outcome was perceived social support for physical activity; secondary outcomes included self-reported physical activity. RESULTS Participants experienced increases in social support and physical activity over time but there were no differences in perceived social support or physical activity between groups over time. Facebook participants posted 259 times to the group. Two thirds (66%) of intervention participants completing a post-study survey indicated that they would recommend the program to friends. CONCLUSIONS Use of an online social networking group plus self-monitoring did not produce greater perceptions of social support or physical activity as compared to education-only controls. Given their promising features and potential reach, efforts to further understand how online social networks can be used in health promotion should be pursued. TRIAL REGISTRATION This study is registered at clinicaltrials.govNCT01421758.

Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association

The adoption and maintenance of physical activity are critical foci for blood glucose management and overall health in individuals with diabetes and prediabetes. Recommendations and precautions vary depending on individual characteristics and health status. In this Position Statement, we provide a clinically oriented review and evidence-based recommendations regarding physical activity and exercise in people with type 1 diabetes, type 2 diabetes, gestational diabetes mellitus, and prediabetes. Physical activity includes all movement that increases energy use, whereas exercise is planned, structured physical activity. Exercise improves blood glucose control in type 2 diabetes, reduces cardiovascular risk factors, contributes to weight loss, and improves well-being (1,2). Regular exercise may prevent or delay type 2 diabetes development (3). Regular exercise also has considerable health benefits for people with type 1 diabetes (e.g., improved cardiovascular fitness, muscle strength, insulin sensitivity, etc.) (4). The challenges related to blood glucose management vary with diabetes type, activity type, and presence of diabetes-related complications (5,6). Physical activity and exercise recommendations, therefore, should be tailored to meet the specific needs of each individual. Physical activity recommendations and precautions may vary by diabetes type. The primary types of diabetes are type 1 and type 2. Type 1 diabetes (5%–10% of cases) results from cellular-mediated autoimmune destruction of the pancreatic β-cells, producing insulin deficiency (7). Although it can occur at any age, β-cell destruction rates vary, typically occurring more rapidly in youth than in adults. Type 2 diabetes (90%–95% of cases) results from a progressive loss of insulin secretion, usually also with insulin resistance. Gestational diabetes mellitus occurs during pregnancy, with screening typically occurring at 24–28 weeks of gestation in pregnant women not previously known to have diabetes. Prediabetes is diagnosed when blood glucose levels are above the normal range but not high enough to be classified as …

Tweets, Apps, and Pods: Results of the 6-Month Mobile Pounds Off Digitally (Mobile POD) Randomized Weight-Loss Intervention Among Adults

Background Previous interventions have shown promising results using theory-based podcasts to deliver a behavioral weight-loss intervention. Objective The objective of our study was to examine whether a combination of podcasting, mobile support communication, and mobile diet monitoring can assist people in weight loss. Methods In this 6-month, minimal contact intervention, overweight (n = 96, body mass index 32.6 kg/m2) adults were recruited through television advertisements and email listservs and randomly assigned to Podcast-only or Podcast+Mobile groups. Both groups received 2 podcasts per week for 3 months and 2 minipodcasts per week for months 3–6. In addition to the podcasts, the Podcast+Mobile group was also instructed to use a diet and physical activity monitoring application (app) on their mobile device and to interact with study counselors and other participants on Twitter. Results Weight loss did not differ by group at 6 months: mean –2.7% (SD 5.6%) Podcast+Mobile, n = 47; mean –2.7% (SD 5.1%) Podcast, n = 49; P = .98. Days/week of reported diet monitoring did not differ between Podcast+Mobile (mean 2.3, SD 1.9 days/week) and Podcast groups (mean 1.9, SD 1.7 days/week; P = .28) but method of monitoring did differ. Podcast+Mobile participants were 3.5 times more likely than the Podcast group to use an app to monitor diet (P = .01), whereas the majority of Podcast participants reported using the Web (14/41, 34%) or paper (12/41, 29%). There were more downloads per episode in the Podcast+Mobile group (1.4/person) than in the Podcast group (1.1/person; P < .001). The number of podcasts participants reported downloading over the 6-month period was significantly moderately correlated with weight loss in both the Podcast+Mobile (r = –.46, P = .001) and the Podcast (r = –.53, P < .001) groups. Podcast+Mobile participants felt more user control at 3 months (P = .02), but not at 6 months, and there was a trend (P = .06) toward greater elaboration among Podcast+Mobile participants. There were significant differences in reported source of social support between groups. More Podcast participants relied on friends (11/40, 28% vs 4/40, 10%; P = .045) whereas Podcast+Mobile participants relied on online sources (10/40, 25% vs 0/40; P = .001). Conclusions Results confirm and extend previous findings showing a minimally intensive weight-loss intervention can be delivered via podcast, but prompting and mobile communication via Twitter and monitoring app without feedback did not enhance weight loss. Trial Registration Clinicaltrials.gov NCT01139255; http://clinicaltrials.gov/ct2/show/NCT01139255 (Archived by WebCite at http://www.webcitation.org/625OjhiDy)

Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program.

OBJECTIVE Self-monitoring of physical activity (PA) and diet are key components of behavioral weight loss programs. The purpose of this study was to assess the relationship between diet (mobile app, website, or paper journal) and PA (mobile app vs no mobile app) self-monitoring and dietary and PA behaviors. MATERIALS AND METHODS This study is a post hoc analysis of a 6-month randomized weight loss trial among 96 overweight men and women (body mass index (BMI) 25-45 kg/m(2)) conducted from 2010 to 2011. Participants in both randomized groups were collapsed and categorized by their chosen self-monitoring method for diet and PA. All participants received a behavioral weight loss intervention delivered via podcast and were encouraged to self-monitor dietary intake and PA. RESULTS Adjusting for randomized group and demographics, PA app users self-monitored exercise more frequently over the 6-month study (2.6±0.5 days/week) and reported greater intentional PA (196.4±45.9 kcal/day) than non-app users (1.2±0.5 days/week PA self-monitoring, p<0.01; 100.9±45.1 kcal/day intentional PA, p=0.02). PA app users also had a significantly lower BMI at 6 months (31.5±0.5 kg/m(2)) than non-users (32.5±0.5 kg/m(2); p=0.02). Frequency of self-monitoring did not differ by diet self-monitoring method (p=0.63); however, app users consumed less energy (1437±188 kcal/day) than paper journal users (2049±175 kcal/day; p=0.01) at 6 months. BMI did not differ among the three diet monitoring methods (p=0.20). CONCLUSIONS These findings point to potential benefits of mobile monitoring methods during behavioral weight loss trials. Future studies should examine ways to predict which self-monitoring method works best for an individual to increase adherence.

The role of adherence in mediating the relationship between depression and health outcomes.

Depression has been linked to poor health outcome in a number of studies; however, the mechanism underlying this relationship has received little attention. This paper explores the possibility that adherence mediates the relationship between depression and outcome. Principal findings regarding the relationship between depression, adherence, and outcome are reviewed. The data suggest that depression is related, at least moderately, to poorer adherence to a variety of treatment components. The relationship between adherence and outcome is more difficult to establish. In addition, current data, albeit limited, do not support the hypothesis that adherence mediates the relationship between depression and outcome. An alternative model in which adherence precedes and influences both mood state and health outcome is discussed. Finally, possible explanations for these relationships are explored and suggestions for future research provided.

The efficacy of a technology-based system in a short-term behavioral weight loss intervention

Objective: The objective was to examine the efficacy of adding a technology‐based program to an in‐person, behavioral weight loss intervention.

A pilot study testing the effect of different levels of financial incentives on weight loss among overweight employees

Objective: To test the ability of two levels of modest financial incentives to encourage weight loss among overweight employees. Methods: This study used a randomized design with measurements at baseline, 3, and 6 months and two levels of financial incentives (

Maintaining large weight losses: the role of behavioral and psychological factors.

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