A broad v. focused digital intervention for recurrent binge eating: a randomized controlled non-inferiority trial

Background: Empirically validated digital interventions for recurrent binge eating typically target numerous hypothesized change mechanisms via the delivery of different modules, skills, and techniques. Emerging evidence suggests that interventions designed to target and isolate one key change mechanism may also produce meaningful change in core symptoms. Although both ‘broad’ and ‘focused’ digital programs have demonstrated efficacy, no study has performed a direct, head-to-head comparison of the two approaches. We addressed this through a randomized non-inferiority trial. Method: Participants with recurrent binge eating were randomly assigned to a broad (n = 199) or focused digital intervention (n = 199), or a waitlist (n = 202). The broad program targeted dietary restraint, mood intolerance, and body image disturbances, while the focused program exclusively targeted dietary restraint. Primary outcomes were eating disorder psychopathology and binge eating frequency. Results: In intention-to-treat analyses, both intervention groups reported greater improvements in primary and secondary outcomes than the waitlist, which were sustained at an 8-week follow-up. The focused intervention was not inferior to the broad intervention on all but one outcome, but was associated with higher rates of attrition and non-compliance. Conclusion: Focused digital interventions that are designed to target one key change mechanism may produce comparable symptom improvements to broader digital interventions, but appear to be associated with lower engagement

An exploratory application of machine learning methods to optimize prediction of responsiveness to digital interventions for eating disorder symptoms

Objective: Digital interventions show promise to address eating disorder (ED) symptoms. However, response rates are variable, and the ability to predict responsiveness to digital interventions has been poor. We tested whether machine learning (ML) techniques can enhance outcome predictions from digital interventions for ED symptoms. Method: Data were aggregated from three RCTs (n = 826) of self-guided digital interventions for EDs. Predictive models were developed for four key outcomes: uptake, adherence, drop-out, and symptom-level change. Seven ML techniques for classification were tested and compared against the generalized linear model (GLM). Results: The seven ML methods used to predict outcomes from 36 baseline variables were poor for the three engagement outcomes (AUCs = 0.48–0.52), but adequate for symptom-level change (R2 =.15–.40). ML did not offer an added benefit to the GLM. Incorporating intervention usage pattern data improved ML prediction accuracy for drop-out (AUC = 0.75–0.93) and adherence (AUC = 0.92–0.99). Age, motivation, symptom severity, and anxiety emerged as influential outcome predictors. Conclusion: A limited set of routinely measured baseline variables was not sufficient to detect a performance benefit of ML over traditional approaches. The benefits of ML may emerge when numerous usage pattern variables are modeled, although this validation in larger datasets before stronger conclusions can be made. © 2022 The Authors. International Journal of Eating Disorders published by Wiley Periodicals LLC

State-Based Markers of Disordered Eating Symptom Severity

Recent work using naturalistic, repeated, ambulatory assessment approaches have uncovered a range of within-person mood- and body image-related dynamics (such as fluctuation of mood and body dissatisfaction) that can prospectively predict eating disorder behaviors (e.g., a binge episode following an increase in negative mood). The prognostic significance of these state-based dynamics for predicting trait-level eating disorder severity, however, remains largely unexplored. The present study uses within-person relationships among state levels of negative mood, body image, and dieting as predictors of baseline, trait-level eating pathology, captured prior to a period of state-based data capture. Two-hundred and sixty women from the general population completed baseline measures of trait eating pathology and demographics, followed by a 7 to 10-day ecological momentary assessment phase comprising items measuring state body dissatisfaction, negative mood, upward appearance comparisons, and dietary restraint administered 6 times daily. Regression-based analyses showed that, in combination, state-based dynamics accounted for 34-43% variance explained in trait eating pathology, contingent on eating disorder symptom severity. Present findings highlight the viability of within-person, state-based dynamics as predictors of baseline trait-level disordered eating severity. Longitudinal testing is needed to determine whether these dynamics account for changes in disordered eating over time

Using chatbot technology to improve Brazilian adolescents' body image and mental health at scale: Randomized controlled trial

Accessible, cost-effective, and scalable mental health interventions are limited, particularly in low- and middle-income countries, where disparities between mental health needs and services are greatest. Microinterventions (ie, brief, stand-alone, or digital approaches) aim to provide immediate reprieve and enhancements in mental health states and offer a novel and scalable framework for embedding evidence-based mental health promotion techniques into digital environments. Body image is a global public health issue that increases young peoples' risk of developing more severe mental and physical health issues. Embedding body image microinterventions into digital environments is one avenue for providing young people with immediate and short-term reprieve and protection from the negative exposure effects associated with social media. This 2-armed, fully remote, and preregistered randomized controlled trial assessed the impact of a body image chatbot containing microinterventions on Brazilian adolescents' state and trait body image and associated well-being outcomes. Geographically diverse Brazilian adolescents aged 13-18 years (901/1715, 52.54% girls) were randomized into the chatbot or an assessment-only control condition and completed web-based self-assessments at baseline, immediately after the intervention time frame, and at 1-week and 1-month follow-ups. The primary outcomes were mean change in state (at chatbot entry and at the completion of a microintervention technique) and trait body image (before and after the intervention), with the secondary outcomes being mean change in affect (state and trait) and body image self-efficacy between the assessment time points. Most participants who entered the chatbot (258/327, 78.9%) completed ≥1 microintervention technique, with participants completing an average of 5 techniques over the 72-hour intervention period. Chatbot users experienced small significant improvements in primary (state: P<.001, Cohen d=0.30, 95% CI 0.25-0.34; and trait body image: P=.02, Cohen d range=0.10, 95% CI 0.01-0.18, to 0.26, 95% CI 0.13-0.32) and secondary outcomes across various time points (state: P<.001, Cohen d=0.28, 95% CI 0.22-0.33; trait positive affect: P=.02, Cohen d range=0.15, 95% CI 0.03-0.27, to 0.23, 95% CI 0.08-0.37; negative affect: P=.03, Cohen d range=-0.16, 95% CI -0.30 to -0.02, to -0.18, 95% CI -0.33 to -0.03; and self-efficacy: P=.02, Cohen d range=0.14, 95% CI 0.03-0.25, to 0.19, 95% CI 0.08-0.32) relative to the control condition. Intervention benefits were moderated by baseline levels of concerns but not by gender. This is the first large-scale randomized controlled trial assessing a body image chatbot among Brazilian adolescents. Intervention attrition was high (531/858, 61.9%) and reflected the broader digital intervention literature; barriers to engagement were discussed. Meanwhile, the findings support the emerging literature that indicates microinterventions and chatbot technology are acceptable and effective web-based service provisions. This study also offers a blueprint for accessible, cost-effective, and scalable digital approaches that address disparities between health care needs and provisions in low- and middle-income countries. Clinicaltrials.gov NCT04825184; http://clinicaltrials.gov/ct2/show/NCT04825184. RR2-10.1186/s12889-021-12129-1. [Abstract copyright: ©Emily L Matheson, Harriet G Smith, Ana C S Amaral, Juliana F F Meireles, Mireille C Almeida, Jake Linardon, Matthew Fuller-Tyszkiewicz, Phillippa C Diedrichs. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 19.06.2023.

Study Protocol for the COVID-19 Pandemic Adjustment Survey (CPAS): A Longitudinal Study of Australian Parents of a Child 0–18 Years

Background: The COVID-19 pandemic presents significant risks to the mental health and wellbeing of Australian families. Employment and economic uncertainty, chronic stress, anxiety, and social isolation are likely to have negative impacts on parent mental health, couple and family relationships, as well as child health and development. Objective: This study aims to: (1) provide timely information on the mental health impacts of the emerging COVID-19 crisis in a close to representative sample of Australian parents and children (0–18 years), (2) identify adults and families most at risk of poor mental health outcomes, and (3) identify factors to target through clinical and public health intervention to reduce risk. Specifically, this study will investigate the extent to which the COVID-19 pandemic is associated with increased risk for parents’ mental health, lower well-being, loneliness, and alcohol use; parent-parent and parent-child relationships (both verbal and physical); and child and adolescent mental health problems. Methods: The study aims to recruit a close to representative sample of at least 2,000 adults aged 18 years and over living in Australia who are parents of a child 0–4 years (early childhood, N = 400), 5–12 years (primary school N = 800), and 13–18 years (secondary school, N = 800). The design will be a longitudinal cohort study using an online recruitment methodology. Participants will be invited to complete an online baseline self-report survey (20 min) followed by a series of shorter online surveys (10 min) scheduled every 2 weeks for the duration of the COVID-19 pandemic (i.e., estimated to be 14 surveys over 6 months). Results: The study will employ post stratification weights to address differences between the final sample and the national population in geographic communities across Australia. Associations will be analyzed using multilevel modeling with time-variant and time-invariant predictors of change in trajectory over the testing period. Conclusions: This study will provide timely information on the mental health impacts of the COVID-19 crisis on parents and children in Australia; identify communities, parents, families, and children most at risk of poor outcomes; and identify potential factors to address in clinical and public health interventions to reduce risk

Psychiatric and medical comorbidities of eating disorders : findings from a rapid review of the literature

Background: Eating disorders (EDs) are potentially severe, complex, and life-threatening illnesses. The mortality rate of EDs is signifcantly elevated compared to other psychiatric conditions, primarily due to medical complications and suicide. The current rapid review aimed to summarise the literature and identify gaps in knowledge relating to any psychiatric and medical comorbidities of eating disorders. Methods: This paper forms part of a rapid review) series scoping the evidence base for the feld of EDs, conducted to inform the Australian National Eating Disorders Research and Translation Strategy 2021–2031, funded and released by the Australian Government. ScienceDirect, PubMed and Ovid/Medline were searched for English-language studies focused on the psychiatric and medical comorbidities of EDs, published between 2009 and 2021. High-level evidence such as meta-analyses, large population studies and Randomised Control Trials were prioritised. Results: A total of 202 studies were included in this review, with 58% pertaining to psychiatric comorbidities and 42% to medical comorbidities. For EDs in general, the most prevalent psychiatric comorbidities were anxiety (up to 62%), mood (up to 54%) and substance use and post-traumatic stress disorders (similar comorbidity rates up to 27%). The review also noted associations between specifc EDs and non-suicidal self-injury, personality disorders, and neurodevelopmental disorders. EDs were complicated by medical comorbidities across the neuroendocrine, skeletal, nutritional, gastrointestinal, dental, and reproductive systems. Medical comorbidities can precede, occur alongside or emerge as a complication of the ED. Conclusions: This review provides a thorough overview of the comorbid psychiatric and medical conditions cooccurring with EDs. High psychiatric and medical comorbidity rates were observed in people with EDs, with comorbidities contributing to increased ED symptom severity, maintenance of some ED behaviours, and poorer functioning as well as treatment outcomes. Early identifcation and management of psychiatric and medical comorbidities in people with an ED may improve response to treatment and overall outcomes

Informing the development of Australia's national eating disorders research and translation strategy : a rapid review methodology

Background Eating disorders (EDs) are highly complex mental illnesses associated with significant medical complications. There are currently knowledge gaps in research relating to the epidemiology, aetiology, treatment, burden, and outcomes of eating disorders. To clearly identify and begin addressing the major deficits in the scientific, medical, and clinical understanding of these mental illnesses, the Australian Government Department of Health in 2019 funded the InsideOut Institute (IOI) to develop the Australian Eating Disorder Research and Translation Strategy, the primary aim of which was to identify priorities and targets for building research capacity and outputs. A series of rapid reviews (RR) were conducted to map the current state of knowledge, identify evidence gaps, and inform development of the national research strategy. Published peer-reviewed literature on DSM-5 listed EDs, across eight knowledge domains was reviewed: (1) population, prevalence, disease burden, Quality of Life in Western developed countries; (2) risk factors; (3) co-occurring conditions and medical complications; (4) screening and diagnosis; (5) prevention and early intervention; (6) psychotherapies and relapse prevention; (7) models of care; (8) pharmacotherapies, alternative and adjunctive therapies; and (9) outcomes (including mortality). While RRs are systematic in nature, they are distinct from systematic reviews in their aim to gather evidence in a timely manner to support decision-making on urgent or high-priority health concerns at the national level. Results Three medical science databases were searched as the primary source of literature for the RRs: Science Direct, PubMed and OVID (Medline). The search was completed on 31st May 2021 (spanning January 2009-May 2021). At writing, a total of 1,320 articles met eligibility criteria and were included in the final review. Conclusions For each RR, the evidence has been organised to review the knowledge area and identify gaps for further research and investment. The series of RRs (published separately within the current series) are designed to support the development of research and translation practice in the field of EDs. They highlight areas for investment and investigation, and provide researchers, service planners and providers, and research funders rapid access to quality current evidence, which has been synthesised and organised to assist decision-making

The cognitive-behavioural theory and treatment for eating disorders and disordered eating: A direct evaluation

In a series of four studies, the aim of the current research project was to evaluate the cognitive-behavioral theory and treatment (CBT) of eating disorders. The first study (Chapter 5) was a meta-analysis (Linardon, Wade, De la Piedad Garcia, & Brennan, in press) of randomized controlled trials (RCT) testing the efficacy of CBT for eating disorders. Pooling data from 79 RCTs, results showed that therapist-led and guided self-help CBT were efficacious for individuals with bulimia nervosa (BN) and binge eating disorder (BED). There was no evidence to suggest that CBT was more efficacious than other psychological interventions in anorexia nervosa (AN). Having found evidence supporting the efficacy of CBT for certain eating disorder presentations, the second study (Chapter 6), which was a systematic review, focused on identifying the reliable factors that mediate, moderate, or predict outcome during CBT (Linardon, de la Piedad Garcia, & Brennan, 2016b). This review found that mediators and moderators of change have been largely unexplored, and that no reliable predictors of outcome emerged. Therefore, based on existing evidence, it was concluded that it remains unclear how, for whom, and under what conditions, CBT for eating disorders works. To understand the mechanisms through which CBT for eating disorders may work, a cross-sectional evaluation of the cognitive-behavioral model in a large non-clinical sample was employed for the third study (Chapter 8; under review). This study validated the conceptual pathways hypothesized by the cognitive model; it also identified two additional variables that might be important mechanisms of change during CBT, body checking and dichotomous thinking. The inclusion of body checking and dichotomous thinking within the cognitive-behavioral model explained nearly three times the amount of variance in disordered eating symptoms than the model without these variables. The third study offered the necessary statistical support for the cognitive-behavioral model and its hypotheses. The final study (Chapter 10) utilized a single case experimental design (n=8) to test the hypothesized cognitive-behavioral mechanisms of change during a CBT guided self-help program. The potential mechanisms of change examined were shape and weight concerns, dietary restraint, and adherence to regular eating strategies. Preliminary evidence showed that an adherence to regular eating in the second week of CBT was associated with a concurrent decrease in dietary restraint and binge eating. From this study, there was no evidence that other potential mechanisms were operating to reduce binge eating behavior. Based on these four independent research studies, this thesis gathered converging evidence in support for the underling cognitive-behavioral model of eating disorders. Further, these findings suggest that CBT for eating disorders is likely to contain several theory-specific mechanisms that are responsible for this treatments effectiveness. More broadly, the current thesis offers support for the contention that CBT for eating disorders “works” because of the reason outlined by its underlying model and because of its specific therapeutic mechanisms