Intraday relations between physical activity and energy intake among behavioral weight loss participants.

OBJECTIVE: Weight loss results from a negative energy balance, when energy intake (EI) is less than energy expended, e.g., from physical activity (PA). However, PA may impact energy balance beyond energy expenditure alone, through indirect effects on eating behavior. Yet, no research has examined if engaging in PA-a central component of most weight loss programs-is associated with same-day EI among individuals with overweight/obesity pursuing weight loss. METHOD: Adults (N = 101) with overweight/obesity in a weight loss program were prescribed a reduced-calorie diet and PA regimen (250 min of moderate-to-vigorous PA at midtreatment). For 3 weeks at midtreatment, PA and EI were measured via an accelerometer and self-monitoring app, respectively. Multilevel models examined within-person relations between PA and EI preceding PA ("pre-PA"), acutely following PA ("acute post-PA," the 2 hr following PA), in the time following the acute post-PA period ("remaining time in day"), and across entire PA days ("full-day"), relative to non-PA matched time periods. RESULTS: EI was higher in the pre-PA and acute post-PA periods. There were no reliable differences in EI during the remaining time in day nor across the full-day on PA days versus within-subject matched non-PA days. There also was insufficient evidence to suggest EI pre-PA, post-PA, or across entire PA days, relative to non-PA matched time periods, was associated with percent weight change. CONCLUSIONS: Findings suggest that engaging in PA was associated with different within-person EI patterns compared to non-PA days, though there was little evidence to support that these patterns relate to weight change. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Application of machine learning to discover interactions predictive of dietary lapses.

The purpose of this study it to build a machine learning model to predict dietary lapses with comparable accuracy, sensitivity, and specificity to previous literature while recovering predictor interactions. The sample for the current study consisted of merged data from two separate studies of individuals with obesity/overweight (total N = 87). Participants completed six ecological momentary assessment surveys per day where they were asked about 16 risk factors of lapse and if they had lapsed from their dietary prescriptions since the previous survey. Alcohol consumption and self-efficacy were the most prevalent in the top 10 stable interactions. Alcohol consumption decreased the protective effect of self-efficacy, motivation, and planning. Higher planning predicted higher risk for lapse only when consuming alcohol. Low motivation, hunger, cravings, and lack of healthy food availability increased the protective effect of self-efficacy. Higher self-efficacy increased risk effect of positive mood and having recently eaten a meal on lapse. For individuals with lower levels of self-efficacy, planning increased the risk of lapse. Alcohol intake and self-efficacy interact with several variables to predict dietary lapses, and these interactions should be targeted in just-in-time adaptive interventions that deliver interventions for lapses.

The role of everyday activities on likelihood of dietary lapse: an ecological momentary assessment study.

Developing a more nuanced understanding of factors predicting risk of dietary lapse (i.e., instances of non-adherence to a reduced calorie diet) is important, because dietary lapses contribute to suboptimal weight outcomes. The study investigated, for the first time, how various everyday activities affected likelihood of dietary lapses at two timescales-both in-the-moment, and in the hours after engaging in an activity. Participants (N = 107) with overweight/obesity in a behavioral weight loss program completed ecological momentary assessment surveys on dietary adherence and daily activities for 3 weeks at mid-treatment. Generalized estimating equations revealed that socializing predicted greater concurrent lapse risk, while work/school, doing chores, cooking, or practicing a spiritual activity/prayer/meditation were associated with reduced lapse risk. In terms of subsequent effects, cooking and indoor hobbies were associated with greater lapse risk in the next few hours, whereas spiritual activity/meditation was associated with reduced risk. Certain activities may have affected concurrent and subsequent lapse risk due to: their influence on the presence of tempting food, the compatibility of engaging in the activity and eating simultaneously, and the reward reaped from the activity (potentially reducing desire for food-related reward). Findings speak to the importance of attending to the timescale of relationships between activities and lapses, which has clinical implications for providing nuanced and optimally timed interventions for overweight/obesity.

Momentary predictors of dietary lapse from a mobile health weight loss intervention.

Identifying factors that influence risk of dietary lapses (i.e., instances of dietary non-adherence) is important because lapses contribute to suboptimal weight loss outcomes. Existing research examining lapse risk factors has had methodological limitations, including retrospective recall biases, subjective operationalizations of lapse, and has investigated lapses among participants in gold-standard behavioral weight loss programs (which are not accessible to most Americans). The current study will address these limitations by being the first to prospectively assess several risk factors of lapse (objectively operationalized) in the context of a commercial mobile health (mHealth) intervention, a highly popular and accessible method of weight loss. N = 159 adults with overweight or obesity enrolled in an mHealth commercial weight loss program completed ecological momentary assessments (EMAs) of 15 risk factors and lapses (defined as exceeding a point target for a meal/snack) over a 2-week period. N = 9 participants were excluded due to low EMA compliance, resulting in a sample of N = 150. Dietary lapses were predicted by momentary increases in urges to deviate from one's eating plan (b = .55, p < .001), cravings (b = .55, p < .001), alcohol consumption (b = .51, p < .001), and tiredness (b = .19, p < .001), and decreases in confidence related to meeting dietary goals (b = -.21, p < .001) and planning food intake (b = -.15, p < .001). This study was among the first to identify prospective predictors of lapse in the context of a commercial mHealth weight loss program. Findings can inform mHealth weight loss programs, including just-in-time interventions that measure these risk factors, calculate when risk of lapse is high, and deliver momentary interventions to prevent lapses.

Real-time fluctuations in mindful awareness, willingness, and values clarity, and their associations with craving and dietary lapse among those seeking weight loss.

BACKGROUND: Mindful awareness, willingness and values clarity have been examined as protective factors across a wide range of problems, including overweight/obesity. However, these variables have almost exclusively been examined at the trait-level. It is possible that these variables also fluctuate within individuals in daily life, and that these intraindividual fluctuations may in turn be related to food craving and dietary lapse. The current study used ecological momentary assessment (EMA) to examine the extent to which momentary mindful awareness, willingness, and values clarity varied within-person, and were associated with craving and likelihood of dietary lapse among weight-loss seeking individuals with overweight/obesity prior to starting a weight loss program. We also examined the extent to which craving was associated with dietary lapse. METHODS: Adults with overweight/obesity (N = 126) completed one week of EMA prior to enrolling in a randomized controlled trial of behavioral weight loss treatments. They responded to EMA questions assessing dietary lapses, craving, mindful awareness, willingness, and values clarity six-times per day. RESULTS: Mindful awareness, willingness, and values clarity demonstrated substantial within-person variability, and higher within-person mindful awareness, willingness, and values clarity were concurrently (but not prospectively) associated with lower craving and likelihood of dietary lapse. Higher craving was concurrently (but not prospectively) associated with higher likelihood of dietary lapse. Between-person, higher mindful awareness, willingness, and values clarity were associated with lower craving and likelihood of dietary lapse, and higher craving was associated with greater frequency of dietary lapses. CONCLUSION: Mindful awareness, willingness, and values clarity vary substantially at the daily level, and may be important mechanisms to target to reduce craving and dietary lapses in the daily lives of individuals with overweight/obesity.

Comparing ecological momentary assessment to sensor-based approaches in predicting dietary lapse.

Ecological momentary assessment (EMA; brief self-report surveys) of dietary lapse risk factors (e.g., cravings) has shown promise in predicting and preventing dietary lapse (nonadherence to a dietary prescription), which can improve weight loss interventions. Passive sensors also can measure lapse risk factors and may offer advantages over EMA (e.g., objective, automatic, semicontinuous data collection), but currently can measure only a few lapse predictors, a notable limitation. This study preliminarily compared the burden and accuracy of commercially available sensors versus established EMA in lapse prediction. N = 23 adults with overweight/obesity completed a 6-week commercial app-based weight loss program. Participants wore a Fitbit, enabled GPS tracking, completed EMA, and reported on EMA and sensor burden poststudy via a 5-point Likert scale. Sensed risk factors were physical activity and sleep (accelerometer), geolocation (GPS), and time, from which 233 features (measurable characteristics of sensor signals) were extracted. EMA measured 19 risk factors, lapse, and categorized GPS into meaningful geolocations. Two supervised binary classification models (LASSO) were created: the sensor model predicted lapse with 63% sensitivity (true prediction rate of lapse) and 60% specificity (true prediction rate of non-lapse) and EMA model with 59% sensitivity and 72% specificity. EMA model accuracy was higher, but self-reported EMA burden (M = 2.96, SD = 1.02) also was higher (M = 1.50, SD = 0.94). EMA model accuracy was superior, but EMA burden was higher than sensor burden. Findings highlight the promise of sensors in contributing to lapse prediction, and future research may use EMA, sensors, or both depending on prioritization of accuracy versus participant burden.

Attentional bias to diabetes cues mediates disease management improvements in a pilot randomized controlled trial for adolescents with type 1 diabetes.

For type 1 diabetes management, the role of attentional bias remains unclear. This secondary analysis examined type 1 diabetes attentional bias and adolescent type 1 diabetes management prior to and during a cognitive and behavioral intervention. Youth with type 1 diabetes and above target glycemic control were assigned to intervention or usual care control. Participants completed baseline and follow-up type 1 diabetes Stroop tasks, HbA1c tests, and blood glucose meter downloads. Intervention was associated with greater reductions in type 1 diabetes attentional bias than control, and these reductions partially mediated the effect of treatment on diabetes management behaviors. Type 1 diabetes attentional bias is a potential target to improve type 1 diabetes management.

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.

Momentary changes in heart rate variability can detect risk for emotional eating episodes.

Emotion dysregulation is a known risk factor for a variety of maladaptive eating behaviors, including emotional eating (Crockett, Myhre, & Rokke, 2015; Lavender et al., 2015). New passive sensing technologies offer the prospect of detecting emotion dysregulation in real-time through measurement of heart rate variability (HRV), a transdiagnostic bio-signal of emotion regulation, which may in turn signal risk of engaging in a maladaptive eating behavior. In the current study, our primary aim was to test the hypothesis that momentary changes in HRV can be used to detect risk of experiencing an emotional eating episode in an ecologically valid setting using a wrist worn sensor with acceptable classification accuracy. Participants were 21 adults with clinically significant emotional eating behaviors. Participants wore the Empatica E4 wrist-sensor and tracked all emotional eating episodes using ecological momentary assessment for four weeks. Time and frequency domain features of HRV were extracted in the 30-min period preceding emotional eating episodes and control cases (defined as the 30 min prior to an EMA survey that did not contain an emotional eating episode). Support vector machine (SVM) learning models were implemented using time domain and frequency domain features. SVM models using frequency domain features achieved the highest classification accuracy (77.99%), sensitivity (78.75%), and specificity (75.00%), consistent with standards deemed acceptable for the prediction of event-level health behavior. SVM models using time domain features still performed above chance, though were less accurate at classifying episodes (accuracy 63.48%, sensitivity 62.68%, and specificity 70.00%) and did not meet acceptable classification accuracy. Wearable sensors that assess HRV show promise as a tool for capturing risk of engaging in emotional eating episodes.

Is physical activity a risk or protective factor for subsequent dietary lapses among behavioral weight loss participants?

OBJECTIVE: Dietary lapses drive weight loss failure, and specific factors influence risk of lapse. Physical activity (PA) may be one such risk factor, though whether PA increases or decreases appetite, and thus risk of lapse, is unclear. In fact, most studies examining the relation between PA and energy intake are limited by use of laboratory-based settings, intensive PA manipulations, and healthy-weight samples. This study aimed to maximize ecological validity by examining the extent to which free-living PA of various intensities prospectively predicts same-day dietary lapses among individuals enrolled in a weight loss program. METHOD: Participants were 130 adults with overweight/obesity in a behavioral weight loss treatment instructed to follow a PA and dietary prescription. At midtreatment, moderate-to-vigorous PA (MVPA) and light PA were measured using hip-worn Actigraph GT3X+ accelerometers (Actigraph, Pensacola, FL). Lapses were assessed using ecological momentary assessment. Within-subject total PA (b = -0.012, SE = 0.005, p = .01) and light PA (b = -0.014, SE = 0.006, p = .01) negatively predicted lapse. MVPA followed the same pattern, but the effect was not statistically significant (b = -0.013, SE = 0.009, p = .12). CONCLUSION: This study was the first to investigate if objectively measured PA prospectively predicts lapse from a weight loss program. Results suggested that for every additional 10 min of total PA one engaged in, the risk of lapse decreased by 1%. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Randomized controlled trial of OnTrack, a just-in-time adaptive intervention designed to enhance weight loss.

Individual instances of nonadherence to reduced calorie dietary prescriptions, that is, dietary lapses, represent a key challenge for weight management. Just-in-time adaptive interventions (JITAIs), which collect and analyze data in real time to deliver tailored interventions during moments of need, may be well suited to promote weight loss by preventing dietary lapses. We developed OnTrack (OT), a smartphone application (app) that collects data on lapses and triggers of lapse, uses a continuously improving machine learning model to predict lapse risk, and delivers tailored interventions when risk is elevated. The current study evaluated the efficacy of OT against an active control in facilitating weight loss. Participants (N = 181) with overweight/obesity (MBMI = 34.32; 85.1% female; 73.5% White) were randomized to receive either the WW (formerly Weight Watchers) Beyond the Scale (BTS) digital program alone or WW plus OnTrack (WW + OT) for 10 weeks. In an unplanned, natural experiment, the WW program changed mid-way through the trial from BTS to a more flexible one, Freestyle (FS). A general linear model revealed a treatment condition × diet plan interaction (F[1, 173] = 9.68, p = .002) such that OT demonstrated greater efficacy only among those receiving BTS (weight loss MWW + OT = 4.7%, standard error [SE] = .55 versus MWW = 2.6%, SE = .80). Compared to FS, BTS WW + OT participants also reported considerably higher satisfaction with the intervention, engagement was higher, and algorithm accuracy was superior. Overall, results offer qualified support for OT and generally for machine learning-powered JITAIs that facilitate weight loss by predicting and preventing dietary lapses.

Does executive function moderate the relation between momentary affective and physical states and subsequent dietary lapse? An EMA investigation.

The study explored whether baseline individual differences in executive function (EF) affect the relation between elevations in internal states and subsequent likelihood of lapsing from a dietary prescription. Participants were 189 adults with overweight/obesity in a behavioral weight loss treatment who completed a neuropsychological EF task at intake and a 2-week EMA protocol measuring internal states and dietary lapses at start of treatment. Generalized estimating equations found relations between momentary elevations in tiredness (b = .06, p = .01) and deprivation (b = .06, p = .047) and subsequent likelihood of lapsing were more robust for participants with lower EF, whereas the relation between momentary elevations in boredom and subsequent likelihood of lapsing (b = .04, p = .03) was more robust for participants with higher EF. Results provide support for EF impacting the relation between elevations in internal states and likelihood of dietary lapse, informing the development of personalized behavioral weight loss treatments.

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.

Executive function and somatic problems in adolescents with above target glycemic control.

Adolescents with type 1 diabetes may be at elevated risk for somatic problems. This study used cross-sectional, baseline data from an intervention to examine if problems with executive function (EF) were associated with greater somatic problems independent of poor adherence and disease severity in adolescents with type 1 diabetes and above target glycemic control. In addition, it examined whether certain types of EF skills, that is, metacognitive and behavior regulation, accounted for variance in somatic problems. Ninety-three adolescents completed a glycated hemoglobin (HbA1c) blood test and parents completed adherence, somatic problems, and EF questionnaires, which measured metacognitive, behavior regulation, and global EF. Greater somatic problems had significant bivariate associations with greater global (r = 0.42, P < 0.01), metacognitive (r = 0.43, P < 0.01), and behavior regulation EF problems (r = 0.31, P < 0.01), worse adherence (r = -0.39, P < 0.01), and poorer metabolic control (r = 0.26, P < 0.05). However, when adherence, metabolic control, and EF subscales were examined together in the same model, only greater global EF problems (b = 0.15, P < 0.01) and metacognitive EF problems (b = 0.16, P < 0.01) were independently associated with greater somatic problems; behavior regulation EF problems were not independently associated with greater somatic problems when controlling for adherence. Metacognitive EF problems may predict somatic problems in adolescents with above target glycemic control above and beyond physical symptoms related to disease management, underscoring the importance of proper assessment and treatment of these distinct somatic problems.

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.