Selection of and Response to Physical Activity-Based Social Comparisons in a Digital Environment: Series of Daily Assessment Studies.

BACKGROUND: Innovative approaches are needed to understand barriers to and facilitators of physical activity among insufficiently active adults. Although social comparison processes (ie, self-evaluations relative to others) are often used to motivate physical activity in digital environments, user preferences and responses to comparison information are poorly understood. OBJECTIVE: We used an iterative approach to better understand users' selection of comparison targets, how they interacted with their selected targets, and how they responded to these targets. METHODS: Across 3 studies, different samples of insufficiently active college students used the Fitbit system (Fitbit LLC) to track their steps per day as well as a separate, adaptive web platform each day for 7 to 9 days (N=112). The adaptive platform was designed with different layouts for each study; each allowed participants to select their preferred comparison target from various sets of options, view the desired amount of information about their selected target, and rate their physical activity motivation before and after viewing information about their selected target. Targets were presented as achieving physical activity at various levels below and above their own, which were accessed via the Fitbit system each day. We examined the types of comparison target selections, time spent viewing and number of elements viewed for each type of target, and day-level associations between comparison selections and physical activity outcomes (motivation and behavior). RESULTS: Study 1 (n=5) demonstrated that the new web platform could be used as intended and that participants' interactions with the platform (ie, the type of target selected, the time spent viewing the selected target's profile, and the number of profile elements viewed) varied across the days. Studies 2 (n=53) and 3 (n=54) replicated these findings; in both studies, age was positively associated with time spent viewing the selected target's profile and the number of profile elements viewed. Across all studies, upward targets (who had more steps per day than the participant) were selected more often than downward targets (who had fewer steps per day than the participant), although only a subset of either type of target selection was associated with benefits for physical activity motivation or behavior. CONCLUSIONS: Capturing physical activity-based social comparison preferences is feasible in an adaptive digital environment, and day-to-day differences in preferences for social comparison targets are associated with day-to-day changes in physical activity motivation and behavior. Findings show that participants only sometimes focus on the comparison opportunities that support their physical activity motivation or behavior, which helps explain previous, equivocal findings regarding the benefits of physical activity-based comparisons. Additional investigation of day-level determinants of comparison selections and responses is needed to fully understand how best to harness comparison processes in digital tools to promote physical activity.

Self-report versus clinical interview: Discordance among measures of binge eating in a weight-loss seeking sample.

PURPOSE: Obese, behavioral weight-loss (BWL) seeking individuals may be prone to over-reporting binge-eating (BE). However, many studies rely on self-reported measures of BE in this population, which may be inaccurate. As such, this is the first-ever study to examine the concordance rates among one self-reported and one clinician- administered measure of BE in a BWL-seeking sample with overweight/obesity. METHODS: At baseline of a BWL trial, participants (N = 94) completed two measures of BE: The Eating Disorders Examination Questionnaire (EDE-Q) and the interview-based Eating Disorder Examination (EDE, Overeating section). RESULTS: Cohen's kappa detected poor agreement between measures (κ < 0). A paired samples t-test detected large, significant differences in OBE frequency across the EDE-Q and EDE, p < 0.001. The self-reported EDE-Q detected a significantly greater frequency of OBEs compared to the EDE (MEDE-Q = 0.73, SD = 1.29 vs. MEDE = 0.06, SD = 0.34). The EDE-Q detected that approximately 50% of participants have experienced OBEs, while the EDE detected that only 5% of participants have experienced OBEs. The frequency of OBEs detected by the EDE-Q was statistically greater than the frequency of OBEs detected by the EDE, p < 0.001. DISCUSSION: Results suggest poor agreement between one self-reported measure and the "gold-standard," clinician-administered measure of BE in a BWL-seeking sample with overweight/obesity. The EDE-Q exhibited high sensitivity but low-to-moderate specificity of OBEs, with the number of false positives (41) outweighing that of true positives (4). Studies measuring BE in this population should consider relying solely on assessor-administered measures, as this sample may require clinical guidance or clarification on the definition and features of BE. LEVEL OF EVIDENCE: Level V, cross-sectional, descriptive study.

Gender differences in the effect of gamification on weight loss during a daily, neurocognitive training program.

A major contributor to the obesity epidemic is the overconsumption of high-calorie foods, which is partly governed by inhibitory control, that is, the ability to override pre-prepotent impulses and drives. Computerized inhibitory control trainings (ICTs) have demonstrated qualified success at affecting real-world health behaviors, and at improving weight loss, particularly when repeated frequently over an extended duration. It has been proposed that gamification (i.e., incorporating game-like elements such as a storyline, sounds, graphics, and rewards) might enhance participant interest and thus training compliance. Previous findings from a mostly female sample did support this hypothesis; however, it might be expected that the effects of gamification differ by gender such that men, who appear more motivated by gaming elements, stand to benefit more from gamification. The present study evaluated whether gender moderated the effect of a gamified ICT on weight loss. Seventy-six overweight individuals received a no-sugar-added dietary prescription and were randomized to 42 daily and 2 weekly ICTs focused on sweet foods that were either gamified or nongamified. Results supported the hypothesis that gamification elements had a positive effect on weight loss for men and not women (p = .03). However, mechanistic hypotheses for the moderating effect (in terms of enjoyment, compliance, and improvements in inhibitory control) were generally not supported (p's > .20). These results suggest that gamification of ICTs may boost weight loss outcomes for men and not women, but further research is needed to determine the specific mechanisms driving this effect and to arrive at gamification elements that enhance effects for both men and women.

Computerized neurocognitive training for improving dietary health and facilitating weight loss.

Nearly 70% of Americans are overweight, in large part because of overconsumption of high-calorie foods such as sweets. Reducing sweets is difficult because powerful drives toward reward overwhelm inhibitory control (i.e., the ability to withhold a prepotent response) capacities. Computerized inhibitory control trainings (ICTs) have shown positive outcomes, but impact on real-world health behavior has been variable, potentially because of limitations inherent in existing paradigms, e.g., low in frequency, intrinsic enjoyment, personalization, and ability to adapt to increasing ability. The present study aimed to assess the feasibility, acceptability, and efficacy of a gamified and non-gamified, daily, personalized, and adaptive ICT designed to facilitate weight loss by targeting consumption of sweets. Participants (N = 106) were randomized to one of four conditions in a 2 (gamified vs. non-gamified) by 2 (ICT vs. sham) factorial design. Participants were prescribed a no-added-sugar diet and completed 42 daily, at-home trainings, followed by two weekly booster trainings. Results indicated that the ICTs were feasible and acceptable. Surprisingly, compliance to the 44 trainings was excellent (88.8%) and equivalent across both gamified and non-gamified conditions. As hypothesized, the impact of ICT on weight loss was moderated by implicit preference for sweet foods [F(1,95) = 6.17, p = .02] such that only those with higher-than-average implicit preference benefited (8-week weight losses for ICT were 3.1% vs. 2.2% for sham). A marginally significant effect was observed for gamification to reduce the impact of ICT. Implications of findings for continued development of ICTs to impact health behavior are discussed.

Long-Term Follow-up of the Mind Your Health Project: Acceptance-Based versus Standard Behavioral Treatment for Obesity.

OBJECTIVE: In the Mind Your Health Trial, acceptance-based behavioral treatment (ABT) for obesity outperformed standard behavioral treatment (SBT) at posttreatment. This trial compared effects over 2 years of follow-up. METHODS: Participants with overweight or obesity (n = 190) were randomized to 25 sessions of SBT or ABT over 1 year and assessed at months 12 (i.e., posttreatment), 24 (1 year posttreatment), and 36 (2 years posttreatment). RESULTS: Weight-loss differences previously observed at 12 months attenuated by follow-up, though a large difference was observed in the proportion of treatment completers who maintained 10% weight loss at 36 months (SBT = 17.1% vs. ABT = 31.6%; P = 0.04; intent-to-treat: SBT = 14.4% vs. ABT = 25.0%; P = 0.07). The amount of regain between posttreatment and follow-up did not differ between groups. ABT produced higher quality of life at 24 and 36 months. Autonomous motivation and psychological acceptance of food-related urges mediated the effect of condition on weight. No moderator effects were identified. CONCLUSIONS: Overall, results suggest that infusing SBT for weight loss with acceptance-based strategies enhances weight loss initially, but these effects fade in the years following the withdrawal of treatment. Even so, those receiving ABT were about twice as likely to maintain 10% weight loss at 36 months, and they reported considerably higher quality of life.

Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?

Behavioral weight loss (WL) trials show that, on average, participants regain lost weight unless provided long-term, intensive-and thus costly-intervention. Optimization solutions have shown mixed success. The artificial intelligence principle of "reinforcement learning" (RL) offers a new and more sophisticated form of optimization in which the intensity of each individual's intervention is continuously adjusted depending on patterns of response. In this pilot, we evaluated the feasibility and acceptability of a RL-based WL intervention, and whether optimization would achieve equivalent benefit at a reduced cost compared to a non-optimized intensive intervention. Participants (n = 52) completed a 1-month, group-based in-person behavioral WL intervention and then (in Phase II) were randomly assigned to receive 3 months of twice-weekly remote interventions that were non-optimized (NO; 10-min phone calls) or optimized (a combination of phone calls, text exchanges, and automated messages selected by an algorithm). The Individually-Optimized (IO) and Group-Optimized (GO) algorithms selected interventions based on past performance of each intervention for each participant, and for each group member that fit into a fixed amount of time (e.g., 1 h), respectively. Results indicated that the system was feasible to deploy and acceptable to participants and coaches. As hypothesized, we were able to achieve equivalent Phase II weight losses (NO = 4.42%, IO = 4.56%, GO = 4.39%) at roughly one-third the cost (1.73 and 1.77 coaching hours/participant for IO and GO, versus 4.38 for NO), indicating strong promise for a RL system approach to weight loss and maintenance.

A multimodal investigation of impulsivity as a moderator of the relation between momentary elevations in negative internal states and subsequent dietary lapses.

Suboptimal outcomes from behavioral weight loss (BWL) treatments are partially attributable to accumulated instances of non-adherence to dietary prescriptions (i.e., dietary lapses). Results identifying negative internal triggers for dietary lapses are inconsistent, potentially due to individual differences that impact how individuals respond to cues. Impulsivity is one factor that likely influences reactivity to internal states. We examined three dimensions of impulsivity (delay discounting, inhibitory control, and negative urgency) as moderators of the relation between affective and physical states and subsequent dietary lapses at the beginning of BWL. Overweight/obese adults (n = 189) completed behavioral and self-reported measures of impulsivity at baseline of BWL and an ecological momentary assessment (EMA) protocol across the first two weeks of treatment to report on affective/physical states and instances of dietary lapses. Results indicated that baseline negative urgency, but not delay discounting or inhibitory control, was positively associated with overall lapse risk. Moderation analyses indicated that poorer inhibitory control strengthened the relation between momentary increases in stress and subsequent dietary lapse, and higher negative urgency strengthened the relation between increases in loneliness and dietary lapse. Negative urgency also moderated the impact of momentary hunger on subsequent dietary lapse risk in an unexpected direction, such that higher negative urgency weakened the relation between hunger and subsequent lapse. Results lend partial and tentative support for the moderating role of impulsivity on the relation between internal states and lapse likelihood. With replication, the development and testing of personalized treatment components based on baseline impulsivity level may be warranted.