Development and usability testing of a chatbot to promote mental health services use among individuals with eating disorders following screening

Adapting an Online Guided Self-Help CBT Programme Targeting Disordered Eating for Students in Aotearoa New Zealand: A Qualitative Study

Disordered eating is a significant issue in university student populations. Currently, access to interventions is limited. Online interventions present an innovative way to increase accessibility to treatment for those in need. The current study explored how an online intervention for disordered eating (everyBody) could be modified to suit the needs of university students in Aotearoa New Zealand. Aotearoa New Zealand is a unique cultural context, with an indigenous population that has a high incidence rate of disordered eating, highlighting the need to adapt everyBody to the local context. Individual interviews were conducted with nine students currently at university in Aotearoa New Zealand, aged between 18 and 33 years old (five females, four males). Three first-order themes were identified using template analysis. The themes indicate that participants perceived the programme as acceptable and feasible for use with Aotearoa New Zealand's university student population. Furthermore, the themes provide insight into potential adaptions to the programme to facilitate engagement and uptake. The suggested changes were largely consistent with previous research on E-therapy design (e.g., content length, therapeutic alliance), and also highlight changes specific to fit Aotearoa New Zealand's cultural context. The findings have implications for universities and other funders deciding on services for students with disordered eating and eating disorders.

Effects of Chatbot Components to Facilitate Mental Health Services Use in Individuals With Eating Disorders Following Online Screening: An Optimization Randomized Controlled Trial

OBJECTIVE

Few individuals with eating disorders (EDs) receive treatment. Innovations are needed to identify individuals with EDs and address care barriers. We developed a chatbot for promoting services uptake that could be paired with online screening. However, it is not yet known which components drive effects. This study estimated individual and combined contributions of four chatbot components on mental health services use (primary), chatbot helpfulness, and attitudes toward changing eating/shape/weight concerns ("change attitudes," with higher scores indicating greater importance/readiness).

METHODS

Two hundred five individuals screening with an ED but not in treatment were randomized in an optimization randomized controlled trial to receive up to four chatbot components: psychoeducation, motivational interviewing, personalized service recommendations, and repeated administration (follow-up check-ins/reminders). Assessments were at baseline and 2, 6, and 14 weeks.

RESULTS

Participants who received repeated administration were more likely to report mental health services use, with no significant effects of other components on services use. Repeated administration slowed the decline in change attitudes participants experienced over time. Participants who received motivational interviewing found the chatbot more helpful, but this component was also associated with larger declines in change attitudes. Participants who received personalized recommendations found the chatbot more helpful, and receiving this component on its own was associated with the most favorable change attitude time trend. Psychoeducation showed no effects.

DISCUSSION

Results indicated important effects of components on outcomes; findings will be used to finalize decision making about the optimized intervention package. The chatbot shows high potential for addressing the treatment gap for EDs.

Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review

BACKGROUND

Chatbots, or conversational agents, have emerged as significant tools in health care, driven by advancements in artificial intelligence and digital technology. These programs are designed to simulate human conversations, addressing various health care needs. However, no comprehensive synthesis of health care chatbots' roles, users, benefits, and limitations is available to inform future research and application in the field.

OBJECTIVE

This review aims to describe health care chatbots' characteristics, focusing on their diverse roles in the health care pathway, user groups, benefits, and limitations.

METHODS

A rapid review of published literature from 2017 to 2023 was performed with a search strategy developed in collaboration with a health sciences librarian and implemented in the MEDLINE and Embase databases. Primary research studies reporting on chatbot roles or benefits in health care were included. Two reviewers dual-screened the search results. Extracted data on chatbot roles, users, benefits, and limitations were subjected to content analysis.

RESULTS

The review categorized chatbot roles into 2 themes: delivery of remote health services, including patient support, care management, education, skills building, and health behavior promotion, and provision of administrative assistance to health care providers. User groups spanned across patients with chronic conditions as well as patients with cancer; individuals focused on lifestyle improvements; and various demographic groups such as women, families, and older adults. Professionals and students in health care also emerged as significant users, alongside groups seeking mental health support, behavioral change, and educational enhancement. The benefits of health care chatbots were also classified into 2 themes: improvement of health care quality and efficiency and cost-effectiveness in health care delivery. The identified limitations encompassed ethical challenges, medicolegal and safety concerns, technical difficulties, user experience issues, and societal and economic impacts.

CONCLUSIONS

Health care chatbots offer a wide spectrum of applications, potentially impacting various aspects of health care. While they are promising tools for improving health care efficiency and quality, their integration into the health care system must be approached with consideration of their limitations to ensure optimal, safe, and equitable use.

Eating disorder symptoms and comorbid mental health risk among teens recruited to a digital intervention research study via two online approaches

INTRODUCTION

It is crucial to identify and evaluate feasible, proactive ways to reach teens with eating disorders (EDs) who may not otherwise have access to screening or treatment. This study aimed to explore the feasibility of recruiting teens with EDs to a digital intervention study via social media and a publicly available online ED screen, and to compare the characteristics of teens recruited by each approach in an exploratory fashion.

METHOD

Teens aged 14-17 years old who screened positive for a clinical/subclinical ED or at risk for an ED and who were not currently in ED treatment completed a baseline survey to assess current ED symptoms, mental health comorbidities, and barriers to treatment. Bivariate analyses were conducted to examine differences between participants recruited via social media and those recruited after completion of a widely available online EDs screen (i.e., National Eating Disorders Association [NEDA] screen).

RESULTS

Recruitment of teens with EDs using the two online approaches was found to be feasible, with 934 screens completed and a total of 134 teens enrolled over 6 months: 77% (n = 103) via social media 23% (n = 31) via the NEDA screen. Mean age of participants (N = 134) was 16 years old, with 49% (n = 66) identifying as non-White, and 70% (n = 94) identifying as a gender and/or sexual minority. Teens from NEDA reported higher ED psychopathology scores (medium effect size) and more frequent self-induced vomiting and driven exercise (small effect sizes). Teens from NEDA also endorsed more barriers to treatment, including not feeling ready for treatment and not knowing where to find a counselor or other resources (small effect sizes).

DISCUSSION

Online recruitment approaches in this study reached a large number of teens with an interest in a digital intervention to support ED recovery, demonstrating the feasibility of these outreach methods. Both approaches reached teens with similar demographic characteristics; however, teens recruited from NEDA reported higher ED symptom severity and barriers to treatment. Findings suggest that proactive assessment and intervention methods should be developed and tailored to meet the needs of each of these groups.

PUBLIC SIGNIFICANCE

This study examined the feasibility of recruiting teens with EDs to a digital intervention research study via social media and NEDA's online screen, and demonstrated differences in ED symptoms among participants by recruitment approach.

Rates and correlates of study enrolment and use of a chatbot aimed to promote mental health services use for eating disorders following online screening

OBJECTIVE

We developed a chatbot aimed to facilitate mental health services use for eating disorders (EDs) and offered the opportunity to enrol in a research study and use the chatbot to all adult respondents to a publicly available online ED screen who screened positive for clinical/subclinical EDs and reported not currently being in treatment. We examined the rates and correlates of enrolment in the study and uptake of the chatbot.

METHOD

Following screening, eligible respondents (≥18 years, screened positive for a clinical/subclinical ED, not in treatment for an ED) were shown the study opportunity. Chi-square tests and logistic regressions explored differences in demographics, ED symptoms, suicidality, weight, and probable ED diagnoses between those who enroled and engaged with the chatbot versus those who did not.

RESULTS

6747 respondents were shown the opportunity (80.0% of all adult screens). 3.0% enroled, of whom 90.2% subsequently used the chatbot. Enrolment and chatbot uptake were more common among respondents aged ≥25 years old versus those aged 18-24 and less common among respondents who reported engaging in regular dietary restriction.

CONCLUSIONS

Overall enrolment was low, yet uptake was high among those that enroled and did not differ across most demographics and symptom presentations. Future directions include evaluating respondents' attitudes towards treatment-promoting tools and removing barriers to uptake.

Mental Distress, Label Avoidance, and Use of a Mental Health Chatbot: Results From a US Survey

BACKGROUND

For almost two decades, researchers and clinicians have argued that certain aspects of mental health treatment can be removed from clinicians' responsibilities and allocated to technology, preserving valuable clinician time and alleviating the burden on the behavioral health care system. The service delivery tasks that could arguably be allocated to technology without negatively impacting patient outcomes include screening, triage, and referral.

OBJECTIVE

We pilot-tested a chatbot for mental health screening and referral to understand the relationship between potential users' demographics and chatbot use; the completion rate of mental health screening when delivered by a chatbot; and the acceptability of a prototype chatbot designed for mental health screening and referral. This chatbot not only screened participants for psychological distress but also referred them to appropriate resources that matched their level of distress and preferences. The goal of this study was to determine whether a mental health screening and referral chatbot would be feasible and acceptable to users.

METHODS

We conducted an internet-based survey among a sample of US-based adults. Our survey collected demographic data along with a battery of measures assessing behavioral health and symptoms, stigma (label avoidance and perceived stigma), attitudes toward treatment-seeking, readiness for change, and technology readiness and acceptance. Participants were then offered to engage with our chatbot. Those who engaged with the chatbot completed a mental health screening, received a distress score based on this screening, were referred to resources appropriate for their current level of distress, and were asked to rate the acceptability of the chatbot.

RESULTS

We found that mental health screening using a chatbot was feasible, with 168 (75.7%) of our 222 participants completing mental health screening within the chatbot sessions. Various demographic characteristics were associated with a willingness to use the chatbot. The participants who used the chatbot found it to be acceptable. Logistic regression produced a significant model with perceived usefulness and symptoms as significant positive predictors of chatbot use for the overall sample, and label avoidance as the only significant predictor of chatbot use for those currently experiencing distress.

CONCLUSIONS

Label avoidance, the desire to avoid mental health services to avoid the stigmatized label of mental illness, is a significant negative predictor of care seeking. Therefore, our finding regarding label avoidance and chatbot use has significant public health implications in terms of facilitating access to mental health resources. Those who are high on label avoidance are not likely to seek care in a community mental health clinic, yet they are likely willing to engage with a mental health chatbot, participate in mental health screening, and receive mental health resources within the chatbot session. Chatbot technology may prove to be a way to engage those in care who have previously avoided treatment due to stigma.

Evaluation framework for conversational agents with artificial intelligence in health interventions: a systematic scoping review

OBJECTIVES

Conversational agents (CAs) with emerging artificial intelligence present new opportunities to assist in health interventions but are difficult to evaluate, deterring their applications in the real world. We aimed to synthesize existing evidence and knowledge and outline an evaluation framework for CA interventions.

MATERIALS AND METHODS

We conducted a systematic scoping review to investigate designs and outcome measures used in the studies that evaluated CAs for health interventions. We then nested the results into an overarching digital health framework proposed by the World Health Organization (WHO).

RESULTS

The review included 81 studies evaluating CAs in experimental (n = 59), observational (n = 15) trials, and other research designs (n = 7). Most studies (n = 72, 89%) were published in the past 5 years. The proposed CA-evaluation framework includes 4 evaluation stages: (1) feasibility/usability, (2) efficacy, (3) effectiveness, and (4) implementation, aligning with WHO's stepwise evaluation strategy. Across these stages, this article presents the essential evidence of different study designs (n = 8), sample sizes, and main evaluation categories (n = 7) with subcategories (n = 40). The main evaluation categories included (1) functionality, (2) safety and information quality, (3) user experience, (4) clinical and health outcomes, (5) costs and cost benefits, (6) usage, adherence, and uptake, and (7) user characteristics for implementation research. Furthermore, the framework highlighted the essential evaluation areas (potential primary outcomes) and gaps across the evaluation stages.

DISCUSSION AND CONCLUSION

This review presents a new framework with practical design details to support the evaluation of CA interventions in healthcare research.

PROTOCOL REGISTRATION

The Open Science Framework (https://osf.io/9hq2v) on March 22, 2021.

Evidence-Based Assessments for Transdiagnostic Eating Disorder Symptoms: Guidelines for Current Use and Future Directions

Eating disorders are severe and often chronic mental illnesses that are associated with high impairment and mortality rates. Recent estimates suggest that eating disorder prevalence rates are on the rise, indicating an increased need for accurate assessment and detection. The current review provides an overview of transdiagnostic eating disorder assessments, including interview, self-report, health and primary care screeners, and technology-based and objective assessments. We focused on assessments that are transdiagnostic in nature and exhibit high impact in the field. We provide recommendations for how these assessments should be used in research and clinical settings. We also discuss considerations that are crucial for assessment, including the use of a categorical versus dimensional diagnostic framework, assessment of eating disorders in related fields (i.e., anxiety and depression), and measurement-based care for eating disorders. Finally, we provide suggestions for future research, including the need for more research on short transdiagnostic screeners for use in health care settings, standardized assessments for ecological momentary assessment, development of state-based assessment of eating disorder symptoms, and consideration of assessment across multiple timescales.

Secure Messaging Intervention in Patients Starting New Antidepressant to Promote Adherence: Pilot Randomized Controlled Trial

BACKGROUND

There are a range of effective pharmacological and behavioral treatments for depression. However, approximately one-third of patients discontinue antidepressants within the first month of treatment and 44% discontinue them by the third month of treatment. The major reasons reported for discontinuation were side effect burden, patients experiencing that the medications were not working, and patients wanting to resolve their depression without using medication.

OBJECTIVE

This study tested the acceptability, feasibility, and preliminary effectiveness of an SMS messaging intervention designed to improve antidepressant adherence and depression outcomes in veterans. The intervention specifically targeted the key reasons for antidepressant discontinuation. For example, the secure message included reminders that it can take up to 6 weeks for an antidepressant to work, or prompts to call their provider should the side effect burden become significant.

METHODS

This pilot was a 3-armed randomized controlled trial of 53 veterans undergoing depression treatment at the Iowa City Veterans Affairs Health Care System. Veterans starting a new antidepressant were randomized to secure messaging only (SM-Only), secure messaging with coaching (SM+Coach), or attention control (AC) groups. The intervention lasted 12 weeks with follow-up assessments of key outcomes at 6 and 12-weeks. This included a measure of antidepressant adherence, depressive symptom severity, and side effect burden.

RESULTS

The 2 active interventions (SM-Only and SM+Coach) demonstrated small to moderate effect sizes (ESs) in improving antidepressant adherence and reducing side effect burden. They did not appear to reduce the depressive symptom burden any more than in the AC arm. Veteran participants in the SM arms demonstrated improved medication adherence from baseline to 12 weeks on the Medication Adherence Rating Scale compared with those in the AC arm, who had a decline in adherence (SM-Only: ES=0.09; P=.19; SM+Coach: ES=0.85; P=.002). Depression scores on the 9-Item Patient Health Questionnaire decreased for all 3 treatment arms, although the decline was slightly larger for the SM-Only (ES=0.32) and the SM+Coach (ES=0.24) arms when compared with the AC arm. The 2 intervention arms indicated a decrease in side effects on the Frequency, Intensity, and Burden of Side Effects Ratings, whereas the side effect burden for the AC arm increased. These differences indicated moderate ES (SM-Only vs AC: ES=0.40; P=.07; SM+Coach: ES=0.54; P=.07).

CONCLUSIONS

A secure messaging program targeting specific reasons for antidepressant discontinuation had small-to-moderate ES in improving medication adherence. Consistent with prior research, the intervention that included brief synchronic meetings with a coach appeared to have a greater benefit than the SMS-alone intervention. Veterans consistently engaged with the SMS messaging in both treatment arms throughout the study period. They additionally provided feedback on which texts were most helpful, tending to prefer messages providing overall encouragement rather than specific wellness recommendations.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03930849; https://clinicaltrials.gov/study/NCT03930849.

User-Centered Development of Bolster, an mHealth Intervention for Early Psychosis Caregivers: Needs Assessment, Prototyping, and Field Trial

BACKGROUND

Caregivers play a critical role in the treatment and recovery of youth and young adults at risk for psychosis. Caregivers often report feeling isolated, overwhelmed, and lacking in resources. Mobile health (mHealth) has the potential to provide scalable, accessible, and in-the-moment support to caregivers. To date, few if any mHealth resources have been developed specifically for this population.

OBJECTIVE

The aim of this study was to conduct user-centered design and testing of an mHealth intervention to support early psychosis caregivers.

METHODS

We conducted a multiphase user-centered development process to develop the Bolster mobile app. In phase 1, a total of 21 caregivers were recruited to participate in a qualitative needs assessment and respond to an initial prototype of the Bolster platform. Content analysis was used to identify key needs and design objectives, which guided the development of the Bolster mobile app. In phase 2, a total of 11 caregivers were recruited to participate in a 1-week field trial wherein they provided qualitative and quantitative feedback regarding the usability and acceptability of Bolster; in addition, they provided baseline and posttest assessments of the measures of distress, illness appraisals, and family communication.

RESULTS

In phase 1, participants identified psychoeducation, communication coaching, a guide to seeking services, and support for coping as areas to address. Live prototype interaction sessions led to multiple design objectives, including ensuring that messages from the platform were actionable and tailored to the caregiver experience, delivering messages in multiple modalities (eg, video and text), and eliminating a messaging-style interface. These conclusions were used to develop the final version of Bolster tested in the field trial. In phase 2, of the 11 caregivers, 10 (91%) reported that they would use Bolster if they had access to it and would recommend it to another caregiver. They also reported marked changes in their appraisals of illness (Cohen d=0.55-0.68), distress (Cohen d=1.77), and expressed emotion (Cohen d=0.52).

CONCLUSIONS

To our knowledge, this study is the first to design an mHealth intervention specifically for early psychosis caregivers. Preliminary data suggest that Bolster is usable, acceptable, and promising to improve key targets and outcomes. A future fully powered clinical trial will help determine whether mHealth can reduce caregiver burdens and increase engagement in services among individuals affected by psychosis.

Utilizing User Preferences in Designing the AGILE (Accelerating Access to Gender-Based Violence Information and Services Leveraging on Technology Enhanced) Chatbot

INTRODUCTION

Technology advancements have enhanced artificial intelligence, leading to a user shift towards virtual assistants, but a human-centered approach is needed to assess for acceptability and effectiveness. The AGILE chatbot is designed in Kenya with features to redefine the response towards gender-based violence (GBV) among vulnerable populations, including adolescents, young women and men, and sexual and gender minorities, to offer accurate and reliable information among users.

METHODS

We conducted an exploratory qualitative study through focus group discussions (FGDs) targeting 150 participants sampled from vulnerable categories; adolescent girls and boys, young women, young men, and sexual and gender minorities. The FGDs included multiple inquiries to assess knowledge and prior interaction with intelligent conversational assistants to inform the user-centric development of a decision-supportive chatbot and a pilot of the chatbot prototype. Each focus group comprised 9-10 members, and the discussions lasted about two hours to gain qualitative user insights and experiences. We used thematic analysis and drew on grounded theory to analyze the data.

RESULTS

The analysis resulted in 14 salient themes composed of sexual violence, physical violence, emotional violence, intimate partner violence, female genital mutilation, sexual reproductive health, mental health, help-seeking behaviors/where to seek support, who to talk to, and what information they would like, features of the chatbot, access of chatbot, abuse and HIV, family and community conflicts, and information for self-care.

CONCLUSION

Adopting a human-centered approach in designing an effective chatbot with as many human features as possible is crucial in increasing utilization, addressing the gaps presented by marginalized/vulnerable populations, and reducing the current GBV epidemic by moving prevention and response services closer to people in need.

Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing

BACKGROUND

The delivery of education on pain neuroscience and the evidence for different treatment approaches has become a key component of contemporary persistent pain management. Chatbots, or more formally conversation agents, are increasingly being used in health care settings due to their versatility in providing interactive and individualized approaches to both capture and deliver information. Research focused on the acceptability of diverse chatbot formats can assist in developing a better understanding of the educational needs of target populations.

OBJECTIVE

This study aims to detail the development and initial pilot testing of a multimodality pain education chatbot (Dolores) that can be used across different age groups and investigate whether acceptability and feedback were comparable across age groups following pilot testing.

METHODS

Following an initial design phase involving software engineers (n=2) and expert clinicians (n=6), a total of 60 individuals with chronic pain who attended an outpatient clinic at 1 of 2 pain centers in Australia were recruited for pilot testing. The 60 individuals consisted of 20 (33%) adolescents (aged 10-18 years), 20 (33%) young adults (aged 19-35 years), and 20 (33%) adults (aged >35 years) with persistent pain. Participants spent 20 to 30 minutes completing interactive chatbot activities that enabled the Dolores app to gather a pain history and provide education about pain and pain treatments. After the chatbot activities, participants completed a custom-made feedback questionnaire measuring the acceptability constructs pertaining to health education chatbots. To determine the effect of age group on the acceptability ratings and feedback provided, a series of binomial logistic regression models and cumulative odds ordinal logistic regression models with proportional odds were generated.

RESULTS

Overall, acceptability was high for the following constructs: engagement, perceived value, usability, accuracy, responsiveness, adoption intention, esthetics, and overall quality. The effect of age group on all acceptability ratings was small and not statistically significant. An analysis of open-ended question responses revealed that major frustrations with the app were related to Dolores' speech, which was explored further through a comparative analysis. With respect to providing negative feedback about Dolores' speech, a logistic regression model showed that the effect of age group was statistically significant (χ22=11.7; P=.003) and explained 27.1% of the variance (Nagelkerke R2). Adults and young adults were less likely to comment on Dolores' speech compared with adolescent participants (odds ratio 0.20, 95% CI 0.05-0.84 and odds ratio 0.05, 95% CI 0.01-0.43, respectively). Comments were related to both speech rate (too slow) and quality (unpleasant and robotic).

CONCLUSIONS

This study provides support for the acceptability of pain history and education chatbots across different age groups. Chatbot acceptability for adolescent cohorts may be improved by enabling the self-selection of speech characteristics such as rate and personable tone.

Using Chatbot Technology to Improve Brazilian Adolescents' Body Image and Mental Health at Scale: Randomized Controlled Trial

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

TRIAL REGISTRATION

Clinicaltrials.gov NCT04825184; http://clinicaltrials.gov/ct2/show/NCT04825184.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s12889-021-12129-1.

Decreasing the public health burden of eating disorders: Commentary Schleider et al. (2023)

Eating disorders (EDs) are common, disabling, and costly; yet, less than 20% of those with EDs receive treatment. EDs have also skyrocketed in the COVID-19 pandemic, with access to care worse than ever, further solidifying the need to not only make EDs a priority but also embrace new approaches to address this major public health problem. Schleider et al. argue for the single-session intervention (SSI) as one such option and outline an agenda that would aid in building the evidence base and realizing the promise of SSIs for EDs. This commentary details three additional key issues that need to be addressed in order to realize the full potential of SSIs and related approaches and ultimately decrease the public health burden of EDs. These include conducting work to optimize interventions for greatest effectiveness, recognizing the value and working to massively increase reach of interventions like SSIs that can scale and meet diverse needs, and engaging in the work needed to address structural barriers to widespread dissemination of these approaches. Through this agenda, we will do more than embrace a single-session "mindset" and will catalyze the work needed to disseminate SSIs and related approaches at massive scale and maximize their impact.

Intention to use digital mental health solutions: A cross-sectional survey of university students attitudes and perceptions toward online therapy, mental health apps, and chatbots

Background

Globally, the high prevalence of mental disorders among university students is a growing public health problem, yet a small minority of students with mental health problems receive treatment. Digital mental health solutions could bridge treatment gaps and overcome many barriers students face accessing treatment. However, there is scant evidence, especially in South Africa (SA), relating to university students' use of and intention to use digital mental health solutions or their attitudes towards these technologies. We aim to explore university 2students attitudes towards and perceptions of digital mental health solutions, and the factors associated with their intention to use them.

Methods

University students from four SA universities (n = 17 838) completed an online survey to assess experience with, attitudes and perceptions of, and intentions to use, digital mental health solutions. We conducted an exploratory factor analysis to identify factors underlying attitudes and perceptions, and then used multivariate ordinal regression analysis was used to investigate the factors' association with students' intention to use digital mental health solutions.

Results

Intention to use digital mental health solutions was high, and attitudes towards and perceptions of digital mental health solutions were largely positive. Importantly, our analysis also shows that 12.6% of users were willing to utilise some form of digital mental health solutions but were unwilling to utilise traditional face-to-face therapies. The greatest proportion of variance was explained by the factor 'Attitudes towards digital technologies' utility to improve student counselling services, provided they are safe'.

Conclusion

SA university students are already engaging with digital mental health solutions, and their intention to do so is high. Certain attitudes and perceptions, particularly concerning the utility, effectiveness, and safety, underlie willingness to engage with these solutions, providing potential targets for interventions to increase uptake.