Impulsivity and affect reactivity prospectively predict disordered eating attitudes in adolescents: a 6-year longitudinal study.

Eating disorders (EDs) are associated with significant psychological and physical comorbidities, and adolescence is a particularly high-risk time for the development of EDs. Impulsivity (i.e., acting with little conscious judgment or forethought) and affect reactivity (i.e., changes in negative affect in response to a stressor) are hypothesized to contribute to the development of binge/purge ED pathology. The current study is the first to examine the prospective relationships between impulsivity and affect reactivity as predictors of the development of ED attitudes in adolescents over time. Two hundred six adolescents participated in a longitudinal study examining the development of psychopathology. ED attitudes were assessed via the College Eating Disorders Screen annually for 6 years. Baseline impulsivity and affect reactivity were also assessed. Affect reactivity, impulsivity, and their interaction were examined as baseline predictors of changes in ED attitudes over time using latent growth modeling. Results of latent growth modeling indicated that ED attitudes increased over time. The interaction between impulsivity and affect reactivity significantly predicted the slope of ED attitudes, such that the relationship between impulsivity and ED attitudes was strongest for those with elevated levels of affect reactivity. Findings suggest that greater levels of affect reactivity and impulsivity are key risk factors for the development of ED attitudes in adolescents. Subsequent research should examine the relation between affect reactivity and impulsivity in predicting objectively measured ED behaviors, in addition to ED attitudes. Further investigation may implicate affect reactivity and impulsivity as important targets for early intervention to prevent onset of ED symptoms in adolescents.

Developing an Acceptance-Based Behavioral Weight Loss Treatment for Individuals With Binge Eating Pathology: A Preliminary Proof of Concept Study and Clinical Case Series.

Binge eating (BE; i.e., the consumption of a large amount of food in a discrete time period, accompanied by a sense of loss of control) is highly comorbid with overweight or obesity and is the primary symptom of binge eating disorder (BED). Current gold-standard treatment for BED (i.e., CBT) does not produce meaningful weight loss, thus failing to address a critical treatment target. This article describes the development of a novel acceptance-based behavioral treatment (ABBT) for individuals with clinically significant BE desiring to reduce BE symptoms and achieve concurrent weight loss. We discuss the development and structure of the novel treatment approach, and describe the test of a proof of concept version of the treatment in a clinical case series of four individuals. In the context of each clinical case description, we present initial acceptability of the treatment and challenges faced in treatment development and delivery. Finally, we discuss future research directions for the treatment, which could improve BE symptoms and weight loss outcomes for individuals with BE pathology.

Promising technological innovations in cognitive training to treat eating-related behavior.

One potential reason for the suboptimal outcomes of treatments targeting appetitive behavior, such as eating and alcohol consumption, is that they do not target the implicit cognitive processes that may be driving these behaviors. Two groups of related neurocognitive processes that are robustly associated with dysregulated eating and drinking are attention bias (AB; selective attention to specific stimuli) and executive function (EF; a set of cognitive control processes such as inhibitory control, working memory, set shifting, that govern goal-directed behaviors). An increasing body of work suggests that EF and AB training programs improve regulation of appetitive behaviors, especially if trainings are frequent and sustained. However, several key challenges, such as adherence to the trainings in the long term, and overall potency of the training, remain. The current manuscript describes five technological innovations that have the potential to address difficulties related to the effectiveness and feasibility of EF and AB trainings: (1) deployment of training in the home, (2) training via smartphone, (3) gamification, (4) virtual reality, and (5) personalization. The drawbacks of these innovations, as well as areas for future research, are also discussed. The above-mentioned innovations are likely to be instrumental in the future empirical work to develop and evaluate effective EF and AB trainings for appetitive behaviors.

Return of the JITAI: Applying a Just-in-Time Adaptive Intervention Framework to the Development of m-Health Solutions for Addictive Behaviors.

PURPOSE: Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possible to prevent lapses before they occur by using m-Health solutions to deliver interventions in real-time. METHOD: Just-in-time adaptive intervention (JITAI) is an intervention design framework that could be delivered via mobile app to facilitate in-the-moment monitoring of triggers for lapsing, and deliver personalized coping strategies to the user to prevent lapses from occurring. An organized framework is key for successful development of a JITAI. RESULTS: Nahum-Shani and colleagues (2014) set forth six core elements of a JITAI and guidelines for designing each: distal outcomes, proximal outcomes, tailoring variables, decision points, decision rules, and intervention options. The primary aim of this paper is to illustrate the use of this framework as it pertains to developing a JITAI that targets lapse behavior among individuals following a weight control diet. CONCLUSION: We will detail our approach to various decision points during the development phases, report on preliminary findings where applicable, identify problems that arose during development, and provide recommendations for researchers who are currently undertaking their own JITAI development efforts. Issues such as missing data, the rarity of lapses, advantages/disadvantages of machine learning, and user engagement are discussed.

Executive functioning and dietary intake: Neurocognitive correlates of fruit, vegetable, and saturated fat intake in adults with obesity.

Obesity is a significant public health issue, and is associated with poor diet. Evidence suggests that eating behavior is related to individual differences in executive functioning. Poor executive functioning is associated with poorer diet (few fruits and vegetables and high saturated fat) in normal weight samples; however, the relationship between these specific dietary behaviors and executive functioning have not been investigated in adults with obesity. The current study examined the association between executive functioning and intake of saturated fat, fruits, and vegetables in an overweight/obese sample using behavioral measures of executive function and dietary recall. One-hundred-ninety overweight and obese adults completed neuropsychological assessments measuring intelligence, planning ability, and inhibitory control followed by three dietary recall assessments within a month prior to beginning a behavioral weight loss treatment program. Inhibitory control and two of the three indices of planning each independently significantly predicted fruit and vegetable consumption such that those with better inhibition and planning ability consumed more fruits and vegetables. No relationship was found between executive functioning and saturated fat intake. Results increase understanding of how executive functioning influences eating behavior in overweight and obese adults, and suggest the importance of including executive functioning training components in dietary interventions for those with obesity. Further research is needed to determine causality as diet and executive functioning may bidirectionally influence each other.

Behavioral weight loss outcomes in individuals with binge-eating disorder: A meta-analysis.

OBJECTIVE: Binge-eating disorder (BED) is highly comorbid with obesity. Weight loss may benefit individuals with BED; however, these individuals are often excluded from behavioral weight loss interventions (BWLIs), and findings from BWLIs including participants with and without BED are mixed. To the authors' knowledge, this study represents the first meta-analysis of weight loss outcomes of individuals with and without BED in BWLIs, while adjusting for weight-influencing variables. Treatment dropout rates were also examined. METHODS: Electronic search engines and grey literature search methods were used to identify manuscripts published through December 2022 related to BWLIs and BED. Thirty manuscripts (BED n = 1519; 25 non-BED n = 6345) were included. RESULTS: A meta-regression found that individuals with BED lost less weight compared with individuals without BED (~1.4 kg; ~2.9 kg among studies without meal replacements), but they still lost ~8.1 kg at post-treatment. A random-effects model showed that BED diagnosis increased odds of treatment dropout by 50%. CONCLUSIONS: BWLIs produced robust weight loss in those with BED, but those with BED lost less weight and had higher risk of dropout compared with those without. Future research should aim to close the gap in weight loss outcomes and retention between those with and without BED.

Sleep Well! An adapted behavioral sleep intervention implemented in urban primary care.

STUDY OBJECTIVES: To describe the adaptation, feasibility, and initial outcomes of Sleep Well!, an intervention for early childhood insomnia and insufficient sleep, designed for families from lower-socioeconomic status backgrounds presenting to large metropolitan primary care sites. METHODS: Fifteen caregiver-child dyads (caregivers: 92.3% mothers, 80.0% Black, 53.3% ≤ 125% US poverty level; children: 73.3% female, 86.7% Black, mean age = 3.0 years) participated in this multimethod, single-arm trial. A family advisory board of caregivers (n = 4) and a clinician advisory board of sleep experts, primary care clinicians, and psychologists (n = 13) provided intervention feedback throughout the pilot. Most adaptations were related to intervention delivery methods, with some related to sleep strategies. At postintervention, caregivers completed surveys on intervention acceptability and cultural humility (primary outcomes) and completed semistructured interviews. Caregivers also reported on child sleep pre- and postintervention. RESULTS: Thirteen (86.6%) families completed Sleep Well! and 12 (80.0%) completed pre- and postintervention measures. Caregivers reported strong intervention acceptability and cultural humility. There were preintervention to postintervention reductions in child sleep problems, bedroom electronics, sleep onset latency, and night awakening frequency and duration. Nighttime sleep duration and overall insufficient sleep also improved. Qualitative data also showed strong intervention acceptability and perceived flexibility, with few participation barriers. CONCLUSIONS: A brief, early childhood behavioral sleep intervention delivered in primary care with families from primarily lower-socioeconomic status backgrounds and/or racially minoritized backgrounds is feasible to implement, with strong retention rates, acceptability, and perceptions of cultural humility. Child sleep improvements are positive and warrant replication in a randomized controlled trial. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Name: Implementing Behavioral Sleep Intervention in Urban Primary Care; URL: https://clinicaltrials.gov/ct2/show/NCT04046341; Identifier: NCT04046341. CITATION: Williamson AA, Okoroji C, Cicalese O, et al. Sleep Well! An adapted behavioral sleep intervention implemented in urban primary care. J Clin Sleep Med. 2022;18(4):1153-1166.

OnTrack: development and feasibility of a smartphone app designed to predict and prevent dietary lapses.

Given that the overarching goal of weight loss programs is to remain adherent to a dietary prescription, specific moments of nonadherence known as "dietary lapses" can threaten weight control via the excess energy intake they represent and by provoking future lapses. Just-in-time adaptive interventions could be particularly useful in preventing dietary lapses because they use real-time data to generate interventions that are tailored and delivered at a moment computed to be of high risk for a lapse. To this end, we developed a smartphone application (app) called OnTrack that utilizes machine learning to predict dietary lapses and deliver a targeted intervention designed to prevent the lapse from occurring. This study evaluated the feasibility, acceptability, and preliminary effectiveness of OnTrack among weight loss program participants. An open trial was conducted to investigate subjective satisfaction, objective usage, algorithm performance, and changes in lapse frequency and weight loss among individuals (N = 43; 86% female; body mass index = 35.6 kg/m2) attempting to follow a structured online weight management plan for 8 weeks. Participants were adherent with app prompts to submit data, engaged with interventions, and reported high levels of satisfaction. Over the course of the study, participants averaged a 3.13% weight loss and experienced a reduction in unplanned lapses. OnTrack, the first Just-in-time adaptive intervention for dietary lapses was shown to be feasible and acceptable, and OnTrack users experienced weight loss and lapse reduction over the study period. These data provide the basis for further development and evaluation.

Rates of cerebral protein synthesis in primary visual cortex during sleep-dependent memory consolidation, a study in human subjects.

If protein synthesis during sleep is required for sleep-dependent memory consolidation, we might expect rates of cerebral protein synthesis (rCPS) to increase during sleep in the local brain circuits that support performance on a particular task following training on that task. To measure circuit-specific brain protein synthesis during a daytime nap opportunity, we used the L-[1-(11)C]leucine positron emission tomography (PET) method with simultaneous polysomnography. We trained subjects on the visual texture discrimination task (TDT). This was followed by a nap opportunity during the PET scan, and we retested them later in the day after the scan. The TDT is considered retinotopically specific, so we hypothesized that higher rCPS in primary visual cortex would be observed in the trained hemisphere compared to the untrained hemisphere in subjects who were randomized to a sleep condition. Our results indicate that the changes in rCPS in primary visual cortex depended on whether subjects were in the wakefulness or sleep condition but were independent of the side of the visual field trained. That is, only in the subjects randomized to sleep, rCPS in the right primary visual cortex was higher than the left regardless of side trained. Other brain regions examined were not so affected. In the subjects who slept, performance on the TDT improved similarly regardless of the side trained. Results indicate a regionally selective and sleep-dependent effect that occurs with improved performance on the TDT.