A Clinician-Controlled Just-in-time Adaptive Intervention System (CBT+) Designed to Promote Acquisition and Utilization of Cognitive Behavioral Therapy Skills in Bulimia Nervosa: Development and Preliminary Evaluation Study

The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality

The expanding domain of digital mental health is transitioning beyond traditional telehealth to incorporate smartphone apps, virtual reality, and generative artificial intelligence, including large language models. While industry setbacks and methodological critiques have highlighted gaps in evidence and challenges in scaling these technologies, emerging solutions rooted in co-design, rigorous evaluation, and implementation science offer promising pathways forward. This paper underscores the dual necessity of advancing the scientific foundations of digital mental health and increasing its real-world applicability through five themes. First, we discuss recent technological advances in digital phenotyping, virtual reality, and generative artificial intelligence. Progress in this latter area, specifically designed to create new outputs such as conversations and images, holds unique potential for the mental health field. Given the spread of smartphone apps, we then evaluate the evidence supporting their utility across various mental health contexts, including well-being, depression, anxiety, schizophrenia, eating disorders, and substance use disorders. This broad view of the field highlights the need for a new generation of more rigorous, placebo-controlled, and real-world studies. We subsequently explore engagement challenges that hamper all digital mental health tools, and propose solutions, including human support, digital navigators, just-in-time adaptive interventions, and personalized approaches. We then analyze implementation issues, emphasizing clinician engagement, service integration, and scalable delivery models. We finally consider the need to ensure that innovations work for all people and thus can bridge digital health disparities, reviewing the evidence on tailoring digital tools for historically marginalized populations and low- and middle-income countries. Regarding digital mental health innovations as tools to augment and extend care, we conclude that smartphone apps, virtual reality, and large language models can positively impact mental health care if deployed correctly.

Exploring Therapists' Approaches to Treating Eating Disorders to Inform User-Centric App Design: Web-Based Interview Study

BACKGROUND

The potential for digital interventions in self-management and treatment of mild to moderate eating disorders (EDs) has already been established. However, apps are infrequently recommended by ED therapists to their clients. Those that are recommended often have poor engagement and user satisfaction, leading to unsatisfactory outcomes. Barriers to recommendation include patient safety, data privacy, and a perception that they may not be effective. Many existing interventions have limited functionality or do not differ much from manual cognitive behavioral therapy (CBT) or self-help books, which may not adequately support the therapeutic process or sustain user engagement.

OBJECTIVE

This study aims to explore the perspectives of therapists who support people with mild to moderate EDs in the community, exploring their existing treatment approach and how an ED app might fit in the treatment pathway alongside treatment.

METHODS

Semistructured web-based interviews were completed with ED therapists in the United Kingdom. Participants were recruited from First Steps ED, a specialist community-based ED service, and Thrive Mental Wellbeing, a workplace mental health provider. Five main themes were covered: (1) therapists' treatment approach, (2) how therapy was implemented in practice, (3) strategies for engaging and motivating clients, (4) perspectives on a potential ED app, and (5) suggestions for app content and design. A structured thematic analysis was validated by 2 researchers.

RESULTS

Overall, 12 ED and mental health therapists (mean age 28.7, SD 7.3 y; female therapists: n=7, 58%; male therapists: n=5, 42%) participated. Therapists dealing with complex ED issues went beyond traditional CBT using additional therapeutic techniques and a flexible, person-centered approach to treatment. This included engagement and motivational strategies to support the client, elements of which could be mirrored in an app. Therapists identified the therapeutic relationship as key to success, which might have been hard to replicate in an app. They saw the potential for evidence-based apps across all stages of the treatment pathway. The need to address safeguarding, data privacy, and the potential for triggering content within the app was vital.

CONCLUSIONS

This study advanced our understanding of how to design and develop clinically safe, evidence-based ED apps that can complement therapy by extending the continuity of care and the self-management and psychoeducation of clients. It emphasized integrative, adaptive CBT that incorporated other therapeutic approaches based on individuals' needs, which could be replicated in an app, as could the strategies to support engagement and motivation. It gave a cautious yet optimistic perspective on the potential integration of apps into ED treatment across all stages of the treatment pathway, from pretreatment maintenance to posttreatment maintenance. It highlighted various concerns that could be addressed and potential limitations, such as the therapeutic relationship, while recognizing the growing potential of apps with rapid technology and artificial intelligence advancements.

Momentary Associations Across Specific Affective States and Dysregulated Eating Experiences Among Children and Adolescents With Loss of Control Eating Symptoms

OBJECTIVE

Dysregulated eating is common among youth and is associated with trait-level negative affect and emotion regulation difficulties. Despite the transient nature of affect, momentary associations among affect and eating behavior are unclear, which limits development of more impactful treatment tools, such as "just-in-time" intervention approaches (JITAI). The current study (N = 62) drew from two ecological momentary assessment (EMA) studies involving children and adolescents who endorsed loss of control (LOC) eating symptoms during a two-week assessment period.

METHOD

Intensive time series network analysis tested concurrent and prospective relationships across six specific affective states (i.e., upset, guilty, scared, tired, excited, attentive) and four eating-related experiences (e.g., LOC, overeating, hunger, craving) in real time. Additionally, we repeated these models within demographic subgroups of the sample based on age, race, and sex.

RESULTS

In the full-sample models, contemporaneously assessed guilt was associated with craving and LOC eating, and tiredness was associated with LOC eating. In the prospective analysis, tiredness was negatively predicted by LOC eating and positively predicted by overeating at the previous timepoint, and attentiveness positively predicted craving. Differences in affect-eating relationships were identified across teens and preteens as well as male and female participants.

DISCUSSION

These results suggest that specific affective states are associated with dysregulated eating-related experiences in real time among youth, and associations may differ depending on demographic characteristics. Findings may be used to inform the development and tailoring of momentary interventions.

Personalized interventions for behaviour change: A scoping review of just-in-time adaptive interventions

PURPOSE

Examine the development, implementation and evaluation of just-in-time adaptive interventions (JITAIs) in behaviour change and evaluate the quality of intervention reporting.

METHODS

A scoping review of JITAIs incorporating mobile health (mHealth) technologies to improve health-related behaviours in adults. We searched MEDLINE, Embase and PsycINFO using terms related to JITAIs, mHealth, behaviour change and intervention methodology. Narrative analysis assessed theoretical foundations, real-time data capturing and processing methods, outcome evaluation and summarized JITAI efficacy. Quality of intervention reporting was assessed using the template for intervention description and replication (TIDieR) checklist.

RESULTS

Sixty-two JITAIs across physical activity, sedentary behaviour, dietary behaviour, substance use, sexual behaviour, fluid intake, treatment adherence, social skills, gambling behaviour and self-management skills were included. The majority (71%) aimed to evaluate feasibility, acceptability and/or usability. Supporting evidence for JITAI development was identified in 46 studies, with 67% applying this to develop tailored intervention content. Over half (55%) relied solely on self-reported data for tailoring, and 13 studies used only passive monitoring data. While data processing methods were commonly reported, 44% did not specify their techniques. 89% of JITAI designs achieved full marks on the TIDieR checklist and provided sufficient details on JITAI components. Overall, JITAIs proved to be feasible, acceptable and user-friendly across behaviours and settings. Randomized trials showed tailored interventions were efficacious, though outcomes varied by behaviour.

CONCLUSIONS

JITAIs offer a promising approach to developing personalized interventions, with their potential effects continuously growing. The recommended checklist emphasizes the importance of reporting transparency in establishing robust intervention designs.

Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review

Background

Just-In-Time Adaptive Interventions (JITAIs) are interventions designed to deliver timely tailored support by adjusting to changes in users' internal states and external contexts. To accomplish this, JITAIs often apply complex analytic techniques, such as machine learning or Bayesian algorithms to real- or near-time data acquired from smartphones and other sensors. Given the idiosyncratic, dynamic, and context dependent nature of mental health symptoms, JITAIs hold promise for mental health. However, the development of JITAIs is still in the early stages and is complex due to the multifactorial nature of JITAIs. Considering this complexity, Nahum-Shani et al. developed a conceptual framework for developing and testing JITAIs for health-related problems. This review evaluates the current state of JITAIs in the field of mental health including their alignment with Nahum-Shani et al.'s framework.

Methods

Nine databases were systematically searched in August 2023. Protocol or empirical studies self-identifying their intervention as a "JITAI" targeting mental health were included in the qualitative synthesis if they were published in peer-reviewed journals and written in English.

Results

Of the 1,419 records initially screened, 9 papers reporting on 5 JITAIs were included (sample size range: 5 to an expected 264). Two JITAIs were for bulimia nervosa, one for depression, one for insomnia, and one for maternal prenatal stress. Although most core components of Nahum-Shani's et al.'s framework were incorporated in the JITAIs, essential elements (e.g., adaptivity and receptivity) within the core components were missing and the core components were only partly substantiated by empirical evidence (e.g., interventions were supported, but the decision rules and points were not). Complex analytical techniques such as data from passive monitoring of individuals' states and contexts were hardly used. Regarding the current state of studies, initial findings on usability, feasibility, and effectiveness appear positive.

Conclusions

JITAIs for mental health are still in their early stages of development, with opportunities for improvement in both development and testing. For future development, it is recommended that developers utilize complex analytical techniques that can handle real-or near-time data such as machine learning, passive monitoring, and conduct further research into empirical-based decision rules and points for optimization in terms of enhanced effectiveness and user-engagement.

Sexual minority stressors and disordered eating behaviors in daily life: a daily diary study of sexual minority cisgender female couples

Young cisgender sexual minority women (e.g. lesbian, queer) in the U.S. are at risk for disordered eating behaviors (DEB). Minority stress theory proposes sexual minority stressors (SMS; e.g. discrimination) related to marginalized statuses are culturally specific stressors that may explain engagement in these behaviors. However, little is known about daily SMS-DEB associations. We conducted a 14-day daily diary study of 321 U.S.-based sexual minority cisgender women ages 19-35 who were in a relationship with a woman. SMS were assessed using an 8-item daily measure of distal SMS (e.g. heard anti-LGBT talk, verbal harassment), and DEB with single items capturing dietary restraint, overeating, loss of control eating, and emotional eating. Multi-level models revealed on days when women experienced SMS, they were more likely to report dietary restraint and emotional eating, but not overeating or loss of control eating. Women who generally reported more frequent SMS were more likely to report all four DEB. There were no significant couple-level SMS-DEB associations. These findings expand our understanding of how SMS is associated with DEB in the daily lives of cisgender sexual minority women. Future studies are needed to explore the temporal sequencing of the associations. Findings may also help to inform the design of culturally tailored interventions aimed at reducing DEB among sexual minority women.

Social media delivered mental health campaigns and public service announcements: A systematic literature review of public engagement and help-seeking behaviours

Social media (SM) is increasingly utilised to disseminate mental health (MH) public service announcements (PSAs) and campaigns, connecting the public with support or resources. However, the effectiveness of MH campaigns/PSAs is often overlooked, and actions following exposure are rarely measured. We aimed to i) systematically review research on MH campaigns/PSAs disseminated via SM to determine their efficacy in eliciting engagement, help-seeking/behavioural change and ii) identify components that may facilitate engagement, help-seeking/behavioural change. The review followed PRISMA guidelines. Fourteen studies were eligible. The campaigns/PSAs targeted various MH concerns and country dissemination was diverse. Twitter/X was the most prevalent SM platform (n = 11), followed by Facebook (n = 8). All campaigns/PSAs generated engagement although engagement level benchmarks were inconsistent or absent, a proportion measured formal help-seeking behaviours (n = 1) or behavioural/language/knowledge change (n = 8). Components influencing engagement included videos/live streams, relatable content, the organisation/account disseminating the content, how information was conveyed, and external events. We highlight the heterogeneity of research in SM MH campaign/PSA evaluation and identify commonalities across studies potentially responsible for eliciting engagement, behavioural change and/or help-seeking in future campaigns/PSAs.

Review of machine learning solutions for eating disorders

BACKGROUND

Eating Disorders (EDs) are one of the most complex psychiatric disorders, with significant impairment of psychological and physical health, and psychosocial functioning, and are associated with low rates of early detection, low recovery and high relapse rates. This underscores the need for better diagnostic and treatment methods.

OBJECTIVE

This narrative review explores current Machine Learning (ML) and Artificial Intelligence (AI) applications in the domain of EDs, with a specific emphasis on clinical management in treatment settings. The primary objective are to (i) decrease the knowledge gap between ED researchers and AI-practitioners, by presenting the current state-of-the-art AI applications (including models for causality) in different ED use-cases; (ii) identify limitations of these existing AI interventions and how to address them.

RESULTS

AI/ML methods have been applied in different ED use-cases, including ED risk factor identification and incidence prediction (including the analysis of social media content in the general population), diagnosis, monitoring patients and treatment response and prognosis in clinical populations. A comparative analysis of AI-techniques deployed in these use-cases have been performed, considering factors such as complexity, flexibility, functionality, explainability and adaptability to healthcare constraints.

CONCLUSION

Multiple restrictions have been identified in the existing methods in ML and Causality in terms of achieving actionable healthcare for ED, like lack of good quality and quantity of data for models to train on, while requiring models to be flexible, high-performing, yet being explainable and producing counterfactual explanations, for ensuring the fairness and trustworthiness of its decisions. We conclude that to overcome these limitations and for future AI research and application in clinical management of ED, (i) careful considerations are required with regards to AI-model selection, and (ii) joint efforts from ED researcher and patient community are essential in building better quality and quantity of dedicated ED datasets and secure AI-solution framework.

Latent Change Trajectories in Mood During Focused CBT Enhanced for Eating Disorders Are Associated With Global Eating Pathology at Posttreatment and Follow-Up Among Individuals With Bulimia Nervosa Spectrum Disorders: A Preliminary Examination

Bulimia nervosa (BN) is characterized by recurrent loss of control over eating (LOC) and inappropriate compensatory behaviors. Although cognitive-behavioral therapy (CBT) is efficacious for BN, many patients continue to experience symptoms at posttreatment. One potential driver of this low treatment response may be low mood, which maintains BN symptoms through negative reinforcement. Thus, it is important to understand how mood changes over enhanced cognitive-behavioral therapy (CBT-E) and whether these changes are associated with improved treatment outcomes. Participants (N = 56) with BN-spectrum eating disorders (EDs) received 16 sessions of the focused version of CBT-E. The Eating Disorder Examination (EDE) was used to measure ED symptoms (global ED pathology, frequency of binge episodes, and compensatory behaviors) at pre- and posttreatment. Latent growth mixture modeling (LGMM) of affective ratings via digital self-monitoring identified latent growth classes. Kruskal-Wallis H tests examined the effect of trajectory of change in mood on pre- to posttreatment symptom change. LGMM yielded a four-class model that best fit the data representing distinct mood trajectories over the course of treatment: (a) highest baseline mood, linear improving; (b) moderate baseline mood, stable; (c) moderate baseline mood, quadratic worsening; and (d) lowest baseline mood, quadratic improving. Participants who demonstrated worsening mood over treatment (i.e., individuals in the "moderate baseline mood, quadratic worsening" class) had significantly higher EDE global scores at posttreatment and follow-up compared to participants with stable mood across treatment. Change in LOC eating frequency and compensatory behaviors across treatment did not significantly differ by mood class. The main effect of mood class or interaction effect between time and mood class on objective binge episodes, subjective binge episodes, and compensatory behaviors was not significant. There were no significant differences in global ED pathology at either posttreatment or follow-up for any other class comparisons. These results suggest that certain trajectories of change in mood during treatment are particularly associated with change in pre- to posttreatment EDE global score. If replicated, our findings could suggest that future iterations of CBT-E should target mood early in treatment in order to maximize reductions in global eating pathology.

Behavior Change Techniques Within Digital Interventions for the Treatment of Eating Disorders: Systematic Review and Meta-Analysis

BACKGROUND

Previous systematic reviews of digital eating disorder interventions have demonstrated effectiveness at improving symptoms of eating disorders; however, our understanding of how these interventions work and what contributes to their effectiveness is limited. Understanding the behavior change techniques (BCTs) that are most commonly included within effective interventions may provide valuable information for researchers and developers. Establishing whether these techniques have been informed by theory will identify whether they target those mechanisms of action that have been identified as core to changing eating disorder behaviors. It will also evaluate the importance of a theoretical approach to digital intervention design.

OBJECTIVE

This study aims to define the BCTs within digital self-management interventions or minimally guided self-help interventions for adults with eating disorders that have been evaluated within randomized controlled trials. It also assessed which of the digital interventions were grounded in theory and the range of modes of delivery included.

METHODS

A literature search identified randomized controlled trials of digital intervention for the treatment of adults with eating disorders with minimal therapist support. Each digital intervention was coded for BCTs using the established BCT Taxonomy v1; for the application of theory using an adapted version of the theory coding scheme (TCS); and for modes of delivery using the Mode of Delivery Ontology. A meta-analysis evaluated the evidence that any individual BCT moderated effect size or that other potential factors such as the application of theory or number of modes of delivery had an effect on eating disorder outcomes.

RESULTS

Digital interventions included an average of 14 (SD 2.6; range 9-18) BCTs. Self-monitoring of behavior was included in all effective interventions, with Problem-solving, Information about antecedents, Feedback on behavior, Self-monitoring of outcomes of behavior, and Action planning identified in >75% (13/17) of effective interventions. Social support and Information about health consequences were more evident in effective interventions at follow-up compared with postintervention measurement. The mean number of modes of delivery was 4 (SD 1.6; range 2-7) out of 12 possible modes, with most interventions (15/17, 88%) being web based. Digital interventions that had a higher score on the TCS had a greater effect size than those with a lower TCS score (subgroup differences: χ21=9.7; P=.002; I²=89.7%) within the meta-analysis. No other subgroup analyses had statistically significant results.

CONCLUSIONS

There was a high level of consistency in terms of the most common BCTs within effective interventions; however, there was no evidence that any specific BCT contributed to intervention efficacy. The interventions that were more strongly informed by theory demonstrated greater improvements in eating disorder outcomes compared to waitlist or treatment-as-usual controls. These results can be used to inform the development of future digital eating disorder interventions.

TRIAL REGISTRATION

PROSPERO CRD42023410060; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=410060.

A naturalistic examination of feeling fat: Characteristics, predictors, and the relationship with eating disorder behaviors

OBJECTIVE

Although literature implicates feeling fat in the maintenance of binge-spectrum eating disorders (EDs; e.g., bulimia nervosa, binge-ED), research in this area is small, nascent, and relies on retrospective self-report. The current study sought to understand the temporal pattern of feeling fat and its role as a precipitant and consequence of ED behaviors.

METHODS

Totally 106 treatment-seeking adults with binge-spectrum EDs completed 7-14-day ecological momentary assessments. They rated feeling fat, negative affect states, and reported on ED behaviors six times per day. Multilevel models evaluated whether feeling fat mediates prospective links between negative affect states and ED behaviors, assessed if negative affect states mediate the prospective association of feeling fat on ED behaviors, and examined the bidirectional prospective association between feeling fat and ED behaviors.

RESULTS

Feeling fat was highest in the early morning (6-8:59 a.m.). Individuals with binge-ED-spectrum EDs demonstrated greater variability in feeling fat than those with bulimia nervosa-spectrum EDs who had stable and high levels of feeling fat. Guilt, sadness, anxiety, and the overall NA at Time 2 mediated the prospective associations between at Time 1 feeling fat and Time 3 dietary restraint, actual dietary restriction, and compensatory exercise. There was a bidirectional prospective association between feeling fat and binge eating.

DISCUSSION

Feeling fat serves as a proximal predictor and mediator of the prospective association between guilt and binge eating. Feeling fat and binge eating mutually reinforce each other.

PUBLIC SIGNIFICANCE

Little is understood regarding the experience of feeling fat in natural environments among individuals with binge-spectrum eating disorders. We found that the risk for having the experience of feeling fat is high in the morning and evening. Feeling fat triggers guilt, anxiety, and sadness which in turn, increases engagement in dietary restraint/restriction and compensatory exercise. Feeling fat also triggers binge eating, and binge eating leads to feelings of fatness.

Bulimia Nervosa and Binge-Eating Disorder Across the Lifespan

This article aims to review the current evidence-based psychotherapy and psychopharmacological treatments for adults and youths with bulimia nervosa (BN) and binge-eating disorder (BED). Treatments for adults and for children and adolescents are discussed separately, including developmental considerations in the management of these disorders among youths. Although several evidence-based psychotherapy and psychopharmacological treatment options have been established for adults with BN or BED, there is much less empirical support for the management of these eating disorders among children and adolescents. This review concludes by discussing promising modalities and innovations, highlighting the potential utility of integrating technology into treatment approaches. Despite decades of treatment development and testing, a sizable proportion of individuals with BN or BED do not respond to the current evidence-based treatments, highlighting the need for continued research in these domains. Future research should focus on testing psychotherapy treatments among diverse samples in large, randomized controlled trials, as well as on treatments that can be easily scaled and implemented in community settings.

Advancing randomized controlled trial methodologies: The place of innovative trial design in eating disorders research

Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.

Momentary skills use predicts decreased binge eating and purging early in day treatment: An ecological momentary assessment study

OBJECTIVE

Emerging research indicates that skills acquisition may be important to behavior change in cognitive behavior therapy (CBT) for eating disorders. This study investigated whether skills use assessed in real time during the initial 4 weeks of CBT-based day treatment was associated with momentary eating disorder behavior change and rapid response to treatment.

METHODS

Participants with DSM-5 bulimia nervosa or purging disorder (N = 58) completed ecological momentary assessments (EMA) several times daily for the first 28 days of treatment. EMA assessed skills use, the occurrence of binge eating and/or purging, and state negative affect. Rapid response was defined as abstinence from binge eating and/or purging in the first 4 weeks of treatment.

RESULTS

Greater real-time skills use overall, and use of "planning ahead," "distraction," "social support," and "mechanical eating" skills in particular, were associated with a lower likelihood of engaging in binge eating or purging during the same period. After controlling for baseline group differences in overall difficulties with emotion regulation, rapid and non-rapid responders did not differ in overall skills use, or skills use at times of higher negative affect, during the EMA period.

DISCUSSION

Momentary use of skills appears to play an important role in preventing binge eating and purging, and certain skills appear to be particularly helpful. These findings contribute to the literature elucidating the processes by which CBT treatments for eating disorders work by providing empirical evidence that skills use helps to prevent binge eating and purging behaviors.

PUBLIC SIGNIFICANCE

Individuals with eating disorders learn new skills during treatment to help them improve their symptoms. This study shows that for people with eating disorders, using skills helps prevent eating disorder behaviors in the moment. Certain skills may be particularly helpful, including planning ahead, distracting activities, support from others, and focusing on eating meals and snacks regardless of how one is feeling. These findings help us better understand how treatments work.

Noradrenergic control of neurobehavior in human binge-eating disorder and obesity (NOBEAD): A smartphone-supported behavioral emotion regulation intervention study protocol integrating molecular brain imaging

OBJECTIVE

The neurobehavioral underpinnings of binge-eating disorder (BED), co-occurring with obesity (OB), are largely unknown. This research project conceptualizes BED as a disorder with dysfunctional emotion regulation (ER) linked with changes in central noradrenaline (NA) transmission and NA-modulated neuronal networks.

METHODS

We expect abnormalities in NA activity in both BED and OB, but most pronounced in BED. We expect these abnormalities to be modifiable through state-of-the-art ER intervention, specifically in BED. To assess the role of NA transmission, we will quantify changes in NA transporter (NAT) availability using the highly NAT-specific [11 C]methylreboxetin (MRB) and positron emission tomography-magnetic resonance imaging (PET-MRI) that allows measuring molecular and neuronal changes before and after an ER intervention. Individual 12-session smartphone-supported acceptance-based behavioral therapy will be conducted to improve ER. Thirty individuals with OB and BED (OB + BED), 30 individuals with OB without BED (OB - BED), and 20 individuals with normal weight will undergo assessments of NAT availability and neuronal network activity under rest and stimulated conditions, clinical interviews, self-report questionnaires on eating behavior, ER, mental and physical health, and quality of life, and neuropsychological tests on executive function. Afterwards, in an experimental randomized-controlled design, individuals with OB + BED and OB - BED will be allocated to smartphone-supported ER intervention versus a waitlist and re-assessed after 10 weeks.

DISCUSSION

By obtaining biological and behavioral markers, the proposed study will disentangle the involvement of NAT and the central NA system in the modulation of emotion-supporting neuronal networks that influence eating behavior. Neurobehavioral mechanisms of change during an ER intervention will be determined.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS): DRKS00029367.

PUBLIC SIGNIFICANCE

This study investigates the central noradrenaline system by using hybrid brain imaging in conjunction with emotion regulation as a putative core biological mechanism in individuals with obesity with or without binge-eating disorder that is targeted by emotion regulation intervention. The results will provide a molecular signature beyond functional imaging biomarkers as a predictive biomarker toward precision medicine for tailoring treatments for individuals with binge-eating disorders and obesity.

Trajectories of therapeutic skills use and their dynamic relations to symptom change during cognitive-behavioral therapy for bulimia nervosa

OBJECTIVE

To examine trajectories of therapeutic skills use and weekly relations between skills use and symptom change during the enhanced version of cognitive-behavioral therapy (CBT-E) for bulimia nervosa (BN).

METHOD

Fifty-five adults (M age: 39.0 ± 14.1; 83.9% female; 64.3% White, 93.6% non-Hispanic/Latino) receiving CBT-E for BN-spectrum eating disorders (EDs) self-monitored their use of five therapeutic skills (i.e., regular eating, eating enough to prevent excessive hunger and eating a range of macronutrients, breaking dietary rules, urge management strategies, and mood management strategies) several times per day during treatment. Patients also self-reported their ED symptoms (i.e., frequency of binge eating, compensatory behaviors, and dietary restraint) weekly. We examined trajectories of use of each CBT-E skill and temporal relations between skills use and ED symptoms from week-to-week during treatment.

RESULTS

Participants showed significant increases in eating enough to prevent excessive hunger and eating a range of macronutrients from week-to-week (p < .05). Regular eating, eating enough to prevent excessive hunger, and eating a range of macronutrients 1 week predicted lower binge eating and compensatory behaviors the same week and the following week, and urge management strategy use predicted greater binge eating the same week and the following week (p < .05).

CONCLUSIONS

Results showed temporal relationships between therapeutic skills use and symptom change on a weekly level, with evidence that using skills targeting dietary restraint was associated with lower BN symptoms. Findings highlight the promise of future work to elucidate the most potent CBT-E skills for symptom improvement and inform more targeted interventions.

PUBLIC SIGNIFICANCE

Findings showed weekly relationships between therapeutic skills use and symptom change during treatment, with evidence that using CBT-E skills aimed to reduce dietary restraint (i.e., regular eating, eating enough to prevent excessive hunger, and eating a range of macronutrients) was associated with lower BN symptoms. Future work has the potential to identify the most potent CBT-E skills for symptom improvement and inform more targeted interventions.

Weight status is associated with clinical characteristics among individuals with bulimia nervosa

Recent studies have found increasing rates of overweight and obesity in bulimia nervosa (BN). However, the relationships between body mass index (BMI) and BN symptoms and other clinically relevant constructs are unknown. Participants (N = 152 adults with BN) were assigned to three groups by BMI: group with no overweight or obesity (NOW-BN; BMI <25; N = 32), group with overweight (OW-BN; BMI ≥25 and <30; N = 66), and group with obesity (O-BN; BMI ≥30; N = 54). We compared the groups on demographics, diet and weight histories, body esteem, BN symptoms, and depression using chi square, analysis of variance, analysis of covariance, and Poisson regression models. The O-BN group was older (d = 0.57) and OW-BN and O-BN groups had greater proportions of race/ethnic minorities than NOW-BN group. The O-BN group was significantly younger at first diet (d = 0.41) and demonstrated significantly higher cognitive dietary restraint (d = 0.31). Compared to NOW-BN, O-BN participants had lower incidence of objective binge eating (incidence rate ratio [IRR] = 4.86) and driven exercise (IRR = 7.13), and greater incidence of vomiting (IRR = 9.30), laxative misuse (IRR = 4.01), and diuretic misuse (d = 2.08). O-BN participants also experienced higher shape (d = 0.41) and weight (d = 0.42) concerns than NOW-BN and OW-BN, although NOW-BN experienced higher shape (d = 0.44) and weight (d = 0.39) concerns than OW-BN. Groups did not differ on depression scores. These results were replicated when examining BMI as a continuous predictor across the full sample, with the exception of objective binge eating and driven exercise, which were not significantly associated with BMI. Individuals with BN and comorbid obesity have distinct clinical characteristics. Existing interventions may need to be adapted to meet clinical needs of these individuals.

The engagement problem: A review of engagement with digital mental health interventions and recommendations for a path forward

Purpose of the review

Digital mental health interventions (DMHIs) are an effective and accessible means of addressing the unprecedented levels of mental illness worldwide. Currently, however, patient engagement with DMHIs in real-world settings is often insufficient to see clinical benefit. In order to realize the potential of DMHIs, there is a need to better understand what drives patient engagement.

Recent findings

We discuss takeaways from the existing literature related to patient engagement with DMHIs and highlight gaps to be addressed through further research. Findings suggest that engagement is influenced by patient-, intervention- and systems-level factors. At the patient-level, variables such as sex, education, personality traits, race, ethnicity, age and symptom severity appear to be associated with engagement. At the intervention-level, integrating human support, gamification, financial incentives and persuasive technology features may improve engagement. Finally, although systems-level factors have not been widely explored, the existing evidence suggests that achieving engagement will require addressing organizational and social barriers and drawing on the field of implementation science.

Summary

Future research clarifying the patient-, intervention- and systems-level factors that drive engagement will be essential. Additionally, to facilitate improved understanding of DMHI engagement, we propose the following: (a) widespread adoption of a minimum necessary 5-element engagement reporting framework; (b) broader application of alternative clinical trial designs; and (c) directed efforts to build upon an initial parsimonious conceptual model of DMHI engagement.

Using Wearable Passive Sensing to Predict Binge Eating in Response to Negative Affect Among Individuals With Transdiagnostic Binge Eating: Protocol for an Observational Study

BACKGROUND

Binge eating (BE), characterized by eating a large amount of food accompanied by a sense of loss of control over eating, is a public health crisis. Negative affect is a well-established antecedent for BE. The affect regulation model of BE posits that elevated negative affect increases momentary risk for BE, as engaging in BE alleviates negative affect and reinforces the behavior. The eating disorder field's capacity to identify moments of elevated negative affect, and thus BE risk, has exclusively relied on ecological momentary assessment (EMA). EMA involves the completion of surveys in real time on one's smartphone to report behavioral, cognitive, and emotional symptoms throughout the day. Although EMA provides ecologically valid information, EMA surveys are often delivered only 5-6 times per day, involve self-report of affect intensity only, and are unable to assess affect-related physiological arousal. Wearable, psychophysiological sensors that measure markers of affect arousal including heart rate, heart rate variability, and electrodermal activity may augment EMA surveys to improve accurate real-time prediction of BE. These sensors can objectively and continuously measure biomarkers of nervous system arousal that coincide with affect, thus allowing them to measure affective trajectories on a continuous timescale, detect changes in negative affect before the individual is consciously aware of them, and reduce user burden to improve data completeness. However, it is unknown whether sensor features can distinguish between positive and negative affect states, given that physiological arousal may occur during both negative and positive affect states.

OBJECTIVE

The aims of this study are (1) to test the hypothesis that sensor features will distinguish positive and negative affect states in individuals with BE with >60% accuracy and (2) test the hypothesis that a machine learning algorithm using sensor data and EMA-reported negative affect to predict the occurrence of BE will predict BE with greater accuracy than an algorithm using EMA-reported negative affect alone.

METHODS

This study will recruit 30 individuals with BE who will wear Fitbit Sense 2 wristbands to passively measure heart rate and electrodermal activity and report affect and BE on EMA surveys for 4 weeks. Machine learning algorithms will be developed using sensor data to distinguish instances of high positive and high negative affect (aim 1) and to predict engagement in BE (aim 2).

RESULTS

This project will be funded from November 2022 to October 2024. Recruitment efforts will be conducted from January 2023 through March 2024. Data collection is anticipated to be completed in May 2024.

CONCLUSIONS

This study is anticipated to provide new insight into the relationship between negative affect and BE by integrating wearable sensor data to measure affective arousal. The findings from this study may set the stage for future development of more effective digital ecological momentary interventions for BE.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47098.

A Digital Mental Health App Incorporating Wearable Biosensing for Teachers of Children on the Autism Spectrum to Support Emotion Regulation: Protocol for a Pilot Randomized Controlled Trial

BACKGROUND

As much as 80% of children on the autism spectrum exhibit challenging behaviors (ie, behaviors dangerous to the self or others, behaviors that interfere with learning and development, and behaviors that interfere with socialization) that can have a devastating impact on personal and family well-being, contribute to teacher burnout, and even require hospitalization. Evidence-based practices to reduce these behaviors emphasize identifying triggers (events or antecedents that lead to challenging behaviors); however, parents and teachers often report that challenging behaviors surface with little warning. Exciting recent advances in biometric sensing and mobile computing technology allow the measurement of momentary emotion dysregulation using physiological indexes.

OBJECTIVE

We present the framework and protocol for a pilot trial that will test a mobile digital mental health app, the KeepCalm app. School-based approaches to managing challenging behaviors in children on the autism spectrum are limited by 3 key factors: children on the autism spectrum often have difficulties in communicating their emotions; it is challenging to implement evidence-based, personalized strategies for individual children in group settings; and it is difficult for teachers to track which strategies are successful for each child. KeepCalm aims to address those barriers by communicating children's stress to their teachers using physiological signaling (emotion dysregulation detection), supporting the implementation of emotion regulation strategies via smartphone pop-up notifications of top strategies for each child according to their behavior (emotion regulation strategy implementation), and easing the task of tracking outcomes by providing the child's educational team with a tool to track the most effective emotion regulation strategies for that child based on physiological stress reduction data (emotion regulation strategy evaluation).

METHODS

We will test KeepCalm with 20 educational teams of students on the autism spectrum with challenging behaviors (no exclusion based on IQ or speaking ability) in a pilot randomized waitlist-controlled field trial over a 3-month period. We will examine the usability, acceptability, feasibility, and appropriateness of KeepCalm as primary outcomes. Secondary preliminary efficacy outcomes include clinical decision support success, false positives or false negatives of stress alerts, and the reduction of challenging behaviors and emotion dysregulation. We will also examine technical outcomes, including the number of artifacts and the proportion of time children are engaged in high physical movement based on accelerometry data; test the feasibility of our recruitment strategies; and test the response rate and sensitivity to change of our measures, in preparation for a future fully powered large-scale randomized controlled trial.

RESULTS

The pilot trial will begin by September 2023.

CONCLUSIONS

Results will provide key data about important aspects of implementing KeepCalm in preschools and elementary schools and will provide preliminary data about its efficacy to reduce challenging behaviors and support emotion regulation in children on the autism spectrum.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05277194; https://www.clinicaltrials.gov/ct2/show/NCT05277194.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/45852.

A Randomized Controlled Trial of CBT+: A Clinician-Controlled, Just-In-Time, Adjunctive Intervention for Bulimia-Spectrum Disorders

Cognitive Behavior Therapy (CBT) for bulimia nervosa (BN) requires patient skill utilization (use of treatment skills) and skill acquisition (successful skill use) for symptom improvement. Treatment outcomes are unsatisfactory, possibly due to poor skill acquisition and utilization by post-treatment. Just-in-time adaptive interventions (JITAIs), momentary interventions delivered at opportunities for skill practice, may improve skill acquisition and utilization. Participants (N = 56 individuals with bulimia-spectrum eating disorders) completed electronic self-monitoring in CBT+ and received JITAIs or no JITAIs alongside 16 sessions of CBT. Feasibility, acceptability, target engagement, and treatment outcomes were evaluated. JITAIs demonstrated feasibility and acceptability. Treatment outcomes and target engagement did not differ between conditions. The lack of group differences in target engagement and treatment outcomes may be explained by skill use self-monitoring promoting skill utilization and acquisition or low statistical power. Our findings suggest that JITAIs are feasible and acceptable during CBT for BN and warrant additional study.

Reward retraining: A pilot randomized controlled trial of a novel treatment approach for transdiagnostic binge eating

OBJECTIVE

Low reward response to conventionally rewarding stimuli and high reward response to food (i.e., reward imbalance), has been supported as a maintenance factor for eating disorders characterized by binge eating. The current study was a pilot randomized controlled trial testing a novel treatment approach for binge eating targeting reward imbalance, called Reward Re-Training (RRT), in comparison to a therapeutic attention control condition (supportive psychotherapy; ST).

METHOD

Fifty-nine participants were randomly assigned to receive either 10 group sessions of RRT or ST via videoconferencing software. Assessments of eating pathology and hypothesized treatment targets were completed at pretreatment, mid-treatment, and posttreatment, and 3-month following the end of treatment.

RESULTS

Feasibility and acceptability success benchmarks were achieved. Results found a significant indirect effect of RRT on lower posttreatment global eating pathology through decreases in reward to food from pretreatment to mid-treatment. No significant differences were observed between groups in terms of change in hypothesized treatment mechanisms or outcomes at posttreatment or 3-month follow-up.

DISCUSSION

The current study supports the feasibility and acceptability of RRT, and the preliminary efficacy of both RRT and ST. Further research comparing these approaches to CBT would help to inform who might benefit from non-CBT based treatment approaches.

PUBLIC SIGNIFICANCE

The current pilot study supports the feasibility and acceptability of Reward Re-Training (RRT) as a treatment for binge eating (BE). RRT produced large, but similar, reductions in overall eating pathology and BE frequency compared to supportive psychotherapy (ST) by 3-month follow-up. This study supports further testing of indirect treatments such as RRT for binge eating.

Optimizing digital health technologies to improve therapeutic skill use and acquisition alongside enhanced cognitive-behavior therapy for binge-spectrum eating disorders: Protocol for a randomized controlled trial

OBJECTIVE

Adjunctive mobile health (mHealth) technologies offer promise for improving treatment response to enhanced cognitive-behavior therapy (CBT-E) among individuals with binge-spectrum eating disorders, but research on the key "active" components of these technologies has been very limited. The present study will use a full factorial design to (1) evaluate the optimal combination of complexity of two commonly used mHealth components (i.e., self-monitoring and microinterventions) alongside CBT-E and (2) test whether the optimal complexity level of these interventions is moderated by baseline self-regulation. Secondary aims of the present study include evaluating target engagement associated with each level of these intervention components and quantifying the component interaction effects (i.e., partially additive, fully additive, or synergistic effects).

METHOD

Two hundred and sixty-four participants with binge-spectrum eating disorders will be randomized to six treatment conditions determined by the combination of self-monitoring condition (i.e., standard self-monitoring or skills monitoring) and microinterventions condition (i.e., no microinterventions, automated microinterventions, or just-in-time adaptive interventions) as an augmentation to 16 sessions of CBT-E. Treatment outcomes will be measured using the Eating Disorder Examination and compared by treatment condition using multilevel models.

RESULTS

Results will clarify the "active" components in mHealth interventions for binge eating.

DISCUSSION

The present study will provide critical insight into the efficacy of commonly used digital intervention components (i.e., skills monitoring and microinterventions) alongside CBT-E. Furthermore, results of this study may inform personalization of digital intervention intensity based on patient profiles of self-regulation.

PUBLIC SIGNIFICANCE

This study will examine the relative effectiveness of commonly used components of application-based interventions as an augmentation to cognitive-behavioral therapy for binge eating. Findings from this study will inform the development of an optimized digital intervention for individuals with binge eating.

Accelerating the research-to-practice translation of eating disorder apps and other digital interventions: Commentary on O'Leary and Torous (2022)

Smartphone apps are increasingly being developed to address mental health problems, including eating disorders. Yet a review by O'Leary and Torous (2022) revealed the dearth of publicly available evidence-based apps for eating disorders, despite growing research in this area in recent years. The lack of publicly available evidence-based apps is problematic for society and reflects a gap in the research-to-practice translation of the advances that have been made through academic research in this area. We detail barriers that academic researchers face to such translation, including the lack of incentives and pathways for making these interventions available beyond the academic institutions in which they are often created. The effective translation of eating disorder apps, and other digital approaches, from research to practice will require new approaches, including bolstering successful and sustainable translation through partnerships across sectors, being more proactive toward research-to-practice translation, and designing more sustainable digital interventions. Harnessing such approaches can improve the availability of evidence-based eating disorder apps and other digital approaches. Additionally, academic researchers are encouraged to be advocates within their institutions and with funding agencies to find ways to better incentivize and fund these efforts.

Latent trajectories of symptom change during cognitive-behavior therapy predict post-treatment worsening of symptoms: a preliminary examination among outpatients with bulimia-spectrum eating disorders

PURPOSE

Up to 44% of individuals with bulimia nervosa (BN) experience worsening of symptoms after cognitive behavior therapy (CBT). Identifying risk for post-treatment worsening of symptoms using latent trajectories of change in eating disorder (ED) symptoms during treatment could allow for personalization of treatment to improve long-term outcomes METHODS: Participants (N = 56) with BN-spectrum EDs received 16 sessions of CBT and completed digital self-monitoring of eating episodes and ED behaviors. The Eating Disorder Examination was used to measured ED symptoms at post-treatment and 3-month follow-up. Latent growth mixture modeling of digital self-monitoring data identified latent growth classes. Kruskal-Wallis H tests examined effect of trajectory of change in ED symptoms on post-treatment to follow-up symptom change.

RESULTS

Multi-class models of change in binge eating, compensatory behaviors, and regular eating improved fit over one-class models. Individuals with high frequency-rapid response in binge eating (H(1) = 10.68, p =0 .001, η² = 0.24) had greater recurrence of compensatory behaviors compared to individuals with low frequency-static response. Individuals with static change in regular eating exhibited greater recurrence of binge eating than individuals with moderate response (H(1) = 8.99, p = 0.003, η² = 0.20).

CONCLUSION

Trajectories of change in ED symptoms predict post-treatment worsening of symptoms. Personalized treatment approaches should be evaluated among individuals at risk of poor long-term outcomes.

LEVEL OF EVIDENCE

IV, evidence obtained from multiple time series.

TRIAL REGISTRATION

ClinicalTrials.gov registration number NCT03673540, registration date: September 17, 2018.

Associations between emotion regulation and remission following cognitive behavioural therapy for adults with bulimia nervosa

OBJECTIVE

Emotion regulation (ER) deficits are associated with illness severity in individuals with bulimia nervosa. We examined whether baseline ER abilities are associated with remission following enhanced cognitive behavioural therapy for eating disorders (CBT-E).

METHOD

Participants (N = 50, 85.0% female) receiving CBT-E completed a measure (yielding a global score and six subscale scores) of ER pre-treatment. Remission was assessed by the Eating Disorder Examination at post-treatment and follow-up. Analyses tested associations between baseline ER and behavioural, cognitive, or full remission at post-treatment and three-month follow-up.

RESULTS

Lower global ER abilities, measured by the Difficulties in Emotion Regulation Scale, were associated with lower likelihood of behavioural and full, but not cognitive, remission at post-treatment. Specifically, individuals low in emotional clarity and impulse control were less likely to be behaviourally remitted. Those low in emotional acceptance, awareness, clarity, or strategies to manage emotion were less likely to be fully remitted. Global ER scores were not associated with any remission type at follow-up.

DISCUSSION

Baseline ER deficits were associated with lower likelihood of behavioural or full remission at post-treatment. However, ER was less associated with remission at follow-up, indicating that ER is most important during treatment. Findings highlight a need for targeted treatments aimed at improving ER.

Self-regulation deficits moderate treatment outcomes in a clinical trial evaluating just-in-time adaptive interventions as an augmentation to cognitive-behavioral therapy for bulimia-spectrum eating disorders

Objective:

Just-in-time adaptive interventions (JITAIs), momentary interventions delivered at identified times of risk, may improve skill utilization during cognitive-behavioral therapy (CBT-E) for bulimia-spectrum eating disorders (BN-EDs). JITAIs may be especially helpful for individuals with self-regulation deficits, including emotion regulation deficits and elevated impulsivity.

Method:

Participants (N = 55 with BN-EDs) received 16 sessions of CBT-E with electronic self-monitoring and were randomized to receive JITAIs (JITAIs-On) or not receive JITAIs (JITAIs-Off). Baseline Difficulties in Emotion Regulation Scale (DERS) and UPPS-P Impulsive Behavior Scale (UPPS-P) total scores were examined as moderators of baseline to post-treatment change in binge episodes, compensatory behaviors, and Eating Disorder Examination (EDE) global score using repeated measures ANOVAs.

Results:

Emotion regulation difficulties significantly moderated compensatory behavior change (F [1, 51] = 4.31, p = .04, ηp2 = 0.08) such that individuals with emotion regulation deficits demonstrated greater improvements in the JITAIs-On condition. Impulsivity moderated change in binge episodes (F [1, 51] = 8.94, p = .004, ηp2 = 0.15) and compensatory behaviors (F [1, 51] = 7.83, p = .007, ηp2 = 0.13), such that individuals with high impulsivity showed greater improvement in the JITAIs-On condition. Neither DERS nor UPPS-P scores moderated EDE global score change.

Discussion:

JITAIs appear particularly beneficial for facilitating skill use during treatment for BN-EDs for individuals with self-regulation deficits, yielding improved treatment outcomes.

Public Significance Statement:

Reminders to use therapy skills that are delivered via smartphone as an individual goes about their daily life may improve treatment response among individuals with bulimia nervosa who have difficulty coping with emotions or who tend to act impulsively. Results from this study indicate that individuals with these difficulties benefitted more from cognitive-behavioral therapy when it was accompanied by in-the-moment reminders to use therapeutic skills, which may facilitate long-term recovery.

Clinical Trials.gov Registration Number:

NCT03673540 .

Momentary associations between fear of weight gain and dietary restriction among individuals with binge-spectrum eating disorders

OBJECTIVE

Fear of weight gain (FOWG) is increasingly implicated in the maintenance of binge-spectrum eating disorders (EDs; e.g., bulimia nervosa [BN], binge-eating disorder [BED]) through the pathway of increased dietary restriction. However, particularly in binge-spectrum EDs, research is nascent and based on retrospective self-report. To improve treatment outcomes, it is critical to better understand the momentary relations between FOWG and dietary restriction.

METHOD

Sixty-seven adults with binge spectrum EDs completed a 7-14-day ecological momentary assessment protocol that included items regarding FOWG, ED behaviors, and types of dietary restriction (e.g., attempted restraint vs. actual restriction) several times per day. Multilevel models were used to evaluate reciprocal associations between FOWG and dietary restriction, and to evaluate the indirect of effects of dietary restriction on the relation between FOWG and binge eating.

RESULTS

While main effects were not statistically significant, ED presentation significantly moderated the association between increases in FOWG at time1 and both attempted and actual avoidance of enjoyable foods at time2 such that those with BN-spectrum EDs were more likely to avoid enjoyable foods following increased FOWG compared to those with BED-spectrum EDs. Engagement in restriction at time1 was not associated with decreased FOWG at time2.

DISCUSSION

Prospective associations between FOWG and restriction suggest that individuals with BN may be more likely to restrict their eating following increased FOWG. These findings suggest FOWG may be an important target for future treatments.