Objective. Multi-level treatment barriers prevent up to 80% of individuals experiencing eating disorders (EDs) from accessing care. This treatment gap creates a critical need to identify interventions that are accessible, easily completable, and optimized for effectiveness by targeting core mechanisms linked to ED onset and maintenance. We propose single-session interventions (SSIs) as a promising path toward catalyzing innovation in the development of accessible, effective ED interventions. SSIs are structured programs that intentionally involve one encounter with a program or provider; they may serve as standalone or adjunctive clinical supports. All SSIs are built to acknowledge that any session might be someone's last-and that any single session can nonetheless yield meaningful clinical benefit. Method.We define SSIs, summarize research supporting their utility for ED symptoms and other mental health problems, and recommend future directions for work in this domain. Results. SSIs may hold promise to reduce some ED symptoms and risk factors, including restrictive eating and negative body image. Steps toward realizing this promise include (1) testing whether existing evidence-based SSIs (e.g., for depression) can also reduce EDs, risk factors, and symptoms; (2) developing novel SSIs that target modifiable ED risk factors and symptoms largely unaddressed by SSIs, such as purging and binge eating;(3) studying diverse implementation pathways; (4) capitalizing on SSIs' transdiagnostic utility to broaden funding opportunities; and (5) educating ED researchers and clinicians about SSIs. Discussion.Understanding the strengths and limits of mechanism-targeted SSIs for ED-related problems could be a low-risk, high-reward avenue towards reducing EDs at scale. Public Health SignificanceStatement: Most individuals experiencing eating disorders (EDs) never access any form of treatment, creating an urgent need to identify ED interventions built to overcome barriers to engaging with care. This Forum article introduces Single-Session Interventions (SSIs) as a promising path to rapidly developing and testing accessible, evidence-based ED supports; supplementing existing ED treatment models; and reducing the individual, familial, and societal burdens of EDs at scale.

Objective Prevention of eating disorders (EDs) is of high importance. However, digital programs with human moderation are unlikely to be disseminated widely. The aim of this study was to test whether a chatbot (i.e., computer program simulating human conversation) would significantly reduce ED risk factors (i.e., weight/shape concerns, thin‐ideal internalization) in women at high risk for an ED, compared to waitlist control, as well as whether it would significantly reduce overall ED psychopathology, depression, and anxiety and prevent ED onset. Method Women who screened as high risk for an ED were randomized (N = 700) to (1) chatbot based on the StudentBodies© program; or (2) waitlist control. Participants were followed for 6 months. Results For weight/shape concerns, there was a significantly greater reduction in intervention versus control at 3‐ (d = −0.20; p = .03) and 6‐m‐follow‐up (d = −0.19; p = .04). There were no differences in change in thin‐ideal internalization. The intervention was associated with significantly greater reductions than control in overall ED psychopathology at 3‐ (d = −0.29; p = .003) but not 6‐month follow‐up. There were no differences in change in depression or anxiety. The odds of remaining nonclinical for EDs were significantly higher in intervention versus control at both 3‐ (OR = 2.37, 95% CI [1.37, 4.11]) and 6‐month follow‐ups (OR = 2.13, 95% CI [1.26, 3.59]). Discussion Findings provide support for the use of a chatbot‐based EDs prevention program in reducing weight/shape concerns through 6‐month follow‐up, as well as in reducing overall ED psychopathology, at least in the shorter‐term. Results also suggest the intervention may reduce ED onset. Public Significance We found that a chatbot, or a computer program simulating human conversation, based on an established, cognitive‐behavioral therapy‐based eating disorders prevention program, was successful in reducing women's concerns about weight and shape through 6‐month follow‐up and that it may actually reduce eating disorder onset. These findings are important because this intervention, which uses a rather simple text‐based approach, can easily be disseminated in order to prevent these deadly illnesses. Trial registration: OSF Registries; https://osf.io/7zmbv

Background Chatbots have the potential to provide cost-effective mental health prevention programs at scale and increase interactivity, ease of use, and accessibility of intervention programs. Objective The development of chatbot prevention for eating disorders (EDs) is still in its infancy. Our aim is to present examples of and solutions to challenges in designing and refining a rule-based prevention chatbot program for EDs, targeted at adult women at risk for developing an ED. Methods Participants were 2409 individuals who at least began to use an EDs prevention chatbot in response to social media advertising. Over 6 months, the research team reviewed up to 52,129 comments from these users to identify inappropriate responses that negatively impacted users’ experience and technical glitches. Problems identified by reviewers were then presented to the entire research team, who then generated possible solutions and implemented new responses. Results The most common problem with the chatbot was a general limitation in understanding and responding appropriately to unanticipated user responses. We developed several workarounds to limit these problems while retaining some interactivity. Conclusions Rule-based chatbots have the potential to reach large populations at low cost but are limited in understanding and responding appropriately to unanticipated user responses. They can be most effective in providing information and simple conversations. Workarounds can reduce conversation errors.

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Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users’ motivation and preferences.