Browsing by Author "Bennett, Gary G"

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Self-monitoring of dietary intake is a valuable component of behavioral weight loss treatment but engagement in self-monitoring declines quickly, resulting in suboptimal treatment outcomes. This dissertation examined a novel weight loss intervention that aims to lessen the decline in self-monitoring engagement by building mastery, self-efficacy, and self-regulatory skills—key constructs of behavior change—prior to self-monitoring diet. GoalTracker was a randomized controlled trial among 105 adults with overweight or obesity comparing three standalone 12-week weight loss interventions: (1) a Simultaneous arm with concurrent self-monitoring of weight and diet each day, along with weekly lessons, action plans, and tailored feedback via email; (2) a Sequential arm with the same components but that tracked only weight through week 4, then added diet tracking; and (3) an App-Only arm that only tracked diet, and did not receive additional behavior change components. All groups used the commercial app MyFitnessPal for self-monitoring and received a tailored calorie goal and a goal to lose 5% of initial weight by 12 weeks. Paper one examined the impact of the intervention on weight change and self-monitoring engagement (Aims 1-3) and found significant weight loss and engagement for all treatment arms, with no differences between arms. Paper two examined the relation between consistent self-monitoring and weight loss (Aim 4), revealing that consistent trackers lost significantly more weight than others. Lastly, paper three examined whether early weight loss predicts future engagement and weight loss success (Aim 5), which was supported. Regardless of the order in which diet is tracked, using tailored goals and a commercial app can produce clinically significant weight loss. Consistent self-monitoring and early weight loss should be emphasized. Standalone digital health treatments may be a viable option for those looking for a lower intensity approach.

Background: Hypertension is a primary risk factor for cardiovascular disease. Studies have shown that hypertension may have a more severe effect on cardiovascular disease outcomes among women. To mitigate this risk of hypertension in women, evidence supports that the DASH (Dietary Approaches to Stop Hypertension) diet as an effective treatment. Despite decades of evidence supporting the efficacy of the DASH diet to treat hypertension, compliance to DASH remains consistently low across all populations. However, given the importance of self-monitoring for producing behavior change, innovative efforts that utilize this strategy are needed to improve adoption of DASH on a population level. Methods: This thesis is a secondary analysis of 3-month digital health intervention (DASH Cloud) to improve adoption of DASH among high risk women conducted in Durham, NC at Duke University. Participants (N= 59) were allocated into the DASH Cloud arm (N= 30), or the attention control arm (N = 29). Both groups received publicly available booklets about the DASH diet and were asked to self-monitor their diet using a commercially available diet tracking app. Only the intervention arm received personalized feedback about their compliance to the DASH diet and skills training videos via text message. The goal of this study was to understand patterns and predictors of self-monitoring via the diet tracking app. Results: Overall, the median proportion of self-monitoring engagement was 76%. By treatment arm, the median proportion of engagement in the DASH Cloud arm and attention control arm was 68% and 85%, respectively. Significant predictors of self-monitoring include those who had 100% engagement during the first two weeks and first month of the study, had marital support, lower BMI, at least a college degree, insurance, a negative perception of their food environment, were somewhat comfortable with using apps and less likely to use an app to track medication adherence. Conclusion: This study provided evidence that self-monitoring of diet is high within the context of an intervention aimed at using digital health to promote compliance to the DASH diet among high risk women. The strongest predictor of self-monitoring engagement was early engagement. This suggests that interventions aiming to improve rates of self-monitoring an improve uptake of DASH using diet tracking apps should aim to improve early engagement to achieve success overall. However, given the small sample size of the study, future studies should include a larger population to describe patterns of self-monitoring and ascertain other predictors of engagement.

Objectives: To inform the cultural translation of a US behavioral intervention (iOTA) for the Chinese population.

Methods: We conducted a systematic literature review, counseling Chinese collaborators' experiences, and conducted key informant interviews. 38 overweight/obese participants (BMI≥24) were recruited in Peking University Health Science Center and Peking University Third Hospital for the key informant interview. Only 20 (52.6%) participants (12 female, 8 male) who came to the face-to-face interview and complete the 20-minute survey were selected for data analysis. The interviews contained questions about weight loss history, weight related concerns and barriers during weight loss process, general lifestyles, and also inquiries of comments and acceptance for each iOTA goal and intervention approach.

Results: Physical activity and dieting are the primary options for weight loss. Health and lack of perseverance are the biggest weight loss concern and barrier. After tailoring by literature review, all of the tailored iOTA goal and intervention approaches had more than 80% acceptance except "Red meat no more than 1 time per week" with only 60% acceptance. 20% people found difficulty attending all of the 4 group sessions.

Conclusion: iOTA principle is largely accepted by Chinese population with proper cultural modification focusing on health concerns, perseverance, special eating habit, and social stress.

Keywords: Weight-loss, interventions, iOTA, cultural translation, key informant interview

Weight bias internalization is considered a chronic discriminatory stressor and a threat to health. Weight bias internalization has known associations with health-depleting behaviors (i.e., disordered eating, social isolation) and avoidance of health-promoting behaviors (i.e., physical activity, adherence to healthcare guidelines). Despite the numerous deleterious health effects of weight bias internalization, relatively few efficacious interventions have been identified for this critical treatment target. Self-compassion training presents itself as a potential intervention, though has not been rigorously tested in those with elevated internalized weight bias. Ruby was a two-arm randomized control designed to reduce internalized weight bias. Ruby tested the efficacy of a 4-week digitally-delivered self-compassion intervention compared to wait list control. Participants in the intervention group received daily text messages which included psychoeducation videos, writing prompts, and guided mindfulness audio files to facilitate daily mindful self-compassion practices ranging from 4-21 minutes per day. The main outcome of this trial was the 4-week reduction in weight bias internalization as measured by the Weight Bias Internalization Scale, compared to wait list control. Trial outcomes were analyzed using linear mixed models and one-way analysis of covariance models using an intent-to-treat framework. Ruby participants were 121 adults with elevated internalized weight bias (i.e., WBIS score > 4.0) and a body mass index over 30 kg/m2. Participants in the intervention demonstrated greater reductions in weight bias internalization compared to the wait list control (Net difference: -0.84, CI: -1.21 to -0.48, p < .0001). Participants in the intervention demonstrated similar reductions in secondary outcomes, including weight self-stigma, weight-related experiential avoidance, and fear of self-compassion (p’s < .05). Additionally, they reported increases in self-compassion, mindfulness, body appreciation, intuitive eating, and physical activity. Mediation analyses suggest that reductions in weight bias internalization are likely partially driven by increases in self-compassion. Ruby was the first digital standalone self-compassion based intervention targeting weight bias internalization. Results suggest that a brief mindful self-compassion intervention can meaningfully reduce internalized weight bias over 4 weeks. Additionally, a mindful self-compassion intervention can reduce several other secondary outcomes related to internalized weight bias. Due to its standalone digital delivery, Ruby may be a highly-scalable treatment for internalized weight bias that can be delivered on its own or combined with other treatments. Ruby is poised to expand a burgeoning body of literature related to psychological intervention for internalized weight bias.

Background: Online communities may be an effective, convenient, and relatively inexpensive intervention platform for individuals seeking assistance with weight management. Recent research suggests that these communities may be as effective as in-person treatments for weight management; however, very little is known about the characteristics that predict weight loss amongst those using an online community. Methods: Within a social-cognitive framework, we sought to identify the psychosocial characteristics that are associated with successful weight management for users of MyFitnessPal, a popular online community for weight management. We recruited participants who were new to the online community and asked them to complete 2 surveys (one at baseline and one 3 months later) that assessed various psychosocial constructs as well as self-reported height and weight. Results: Participants in our sample reported losing, on average, 4.55 kg during the 3-month time period. We found that engaging in weight control behaviors (e.g., monitoring food intake, weighing oneself, etc.) fully mediated the relationship between several of our variables of interest (i.e., baseline self-efficacy and perceived social support within the community) and weight loss. We also found that participants who expected to lose more weight at baseline were significantly more likely to have lost more weight at follow-up. Conclusions: On average, participants in our study lost a clinically meaningful amount of weight. Predictors of weight loss within this community included perceived support within the community (mediated by weight control behaviors), baseline self-efficacy (mediated by weight control behaviors), and baseline outcome expectations. Results of this study can ultimately serve to inform the design of future eHealth interventions for weight management.

Understanding how engagement in mobile health (mHealth) weight loss interventions relates to weight change may help develop effective intervention strategies.

This study aims to examine the (1) patterns of participant engagement overall and with key intervention components within each intervention arm in the Cell Phone Intervention For You (CITY) trial; (2) associations of engagement with weight change; and (3) participant characteristics related to engagement.

The CITY trial tested two 24-month weight loss interventions. One was delivered with a smartphone app (cell phone) containing 24 components (weight tracking, etc) and included prompting by the app in predetermined frequency and forms. The other was delivered by a coach via monthly calls (personal coaching) supplemented with limited app components (18 overall) and without any prompting by the app. Engagement was assessed by calculating the percentage of days each app component was used and the frequency of use. Engagement was also examined across 4 weight change categories: gained (≥2%), stable (±2%), mild loss (≥2% to <5%), and greater loss (≥5%).

Data from 122 cell phone and 120 personal coaching participants were analyzed. Use of the app was the highest during month 1 for both arms; thereafter, use dropped substantially and continuously until the study end. During the first 6 months, the mean percentage of days that any app component was used was higher for the cell phone arm (74.2%, SD 20.1) than for the personal coaching arm (48.9%, SD 22.4). The cell phone arm used the apps an average of 5.3 times/day (SD 3.1), whereas the personal coaching participants used them 1.7 times/day (SD 1.2). Similarly, the former self-weighed more than the latter (57.1% days, SD 23.7 vs 32.9% days, SD 23.3). Furthermore, the percentage of days any app component was used, number of app uses per day, and percentage of days self-weighed all showed significant differences across the 4 weight categories for both arms. Pearson correlation showed a negative association between weight change and the percentage of days any app component was used (cell phone: r=−.213; personal coaching: r=−.319), number of apps use per day (cell phone: r=−.264; personal coaching: r=−.308), and percentage of days self-weighed (cell phone: r=−.297; personal coaching: r=−.354). None of the characteristics examined, including age, gender, race, education, income, energy expenditure, diet quality, and hypertension status, appeared to be related to engagement.

Engagement in CITY intervention was associated with weight loss during the first 6 months. Nevertheless, engagement dropped substantially early on for most intervention components. Prompting may be helpful initially. More flexible and less intrusive prompting strategies may be needed during different stages of an intervention to increase or sustain engagement. Future studies should explore the motivations for engagement and nonengagement to determine meaningful levels of engagement required for effective intervention.

ClinicalTrials.gov NCT01092364; https://clinicaltrials.gov/ct2/show/NCT01092364 (Archived by WebCite at http://www.webcitation.org/72V8A4e5X)

Background

Objective

Methods

Results

Conclusions

Trial registration

Background

Methods

Discussion

Trials registration

Introduction

Methods

Results

Conclusions

Digital health interventions are widely considered a highly promising solution to issues with access to evidence-based care. However, digital health interventions are limited by lower rates of engagement than are typically seen in traditional, face-to-face interventions. Despite the importance of engagement for intervention efficacy, engagement is rarely a primary outcome in intervention studies, and few studies have empirically tested intervention changes to improve engagement. Hazel was a two-arm, randomized controlled exploratory study designed to investigate the impact of intervention design on engagement as a primary outcome. We conducted a trial of a mental health intervention, based on the Unified Protocol, delivered entirely online. Participants were randomized to complete the 12-week intervention self-guided (the unsupported arm) or with 4 weeks of therapist support (the supported arm). We sought to measure engagement as comprehensively as possible and therefore collected numerous self-report, behavioral, and objective measures of multiple facets of engagement, including how participants felt about the intervention, how they used the intervention technology, and how their behavior changed over the course of the intervention. We collected engagement outcomes at baseline, weekly during the intervention, and immediately following completion of the intervention. We hypothesized that a low dose of therapist support would improve engagement and subsequent mental health outcomes while being more scalable and feasible to implement than offering therapist support during all intervention weeks. The aims of this small, exploratory study were to learn more about patterns of engagement with the intervention and identify issues with the current intervention and trial design. We used descriptive statistics and visualizations to understand and describe trends in the data rather than p-value significance testing, in line with best practices for pilot studies. We recruited 23 North Carolina-based adults with clinically elevated depression and/or anxiety symptoms. Overall, the intervention and trial design appeared acceptable to participants. Participants in both arms had relatively positive attitudes toward the intervention at all time points, and there was no evidence that the response burden of our outcome measures was too high. However, several of our measures showed little variation between participants or over time. Our findings provides guidance for future studies to select alternative measures and/or to administer some engagement measures less frequently. This represents a meaningful step forward for the field of engagement research, as prior to this study, there was almost no empirical guidance on how to select measures of engagement or how frequently to administer them. We observed a substantial drop in engagement for participants in the supported arm when video sessions began, contrary to our expectations that video sessions would improve engagement. Notably, video sessions began partway through the intervention and participants were blinded to condition until the onset of these sessions; changes to blinding and/or timing of video sessions might improve engagement. At the same time, those participants in the supported arm who did engage in video sessions (n=4) completed more of each weekly lesson than participants in the unsupported arm, indicating that there is evidence that therapist support can increase engagement. Secondary outcomes were sample diversity and depression and anxiety symptom change. Our sample was comparably diverse to other digital health studies in terms of race and socioeconomic status, and we overrecruited LGBTQ+-identified participants. Despite finding little evidence of changes in behavior or the theoretical mechanisms underlying the intervention, the majority of participants showed improvement in their symptoms.

Background

Methods

Results

Conclusions

Trial registration