Evidence map›Paper›PMID 39072846›Full record

Trial reportThe International journal of eating disorders2024

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

Ellen E Fitzsimmons-Craft, Gavin N Rackoff, Jillian Shah, Jillian C Strayhorn, Laura D'Adamo, Bianca DePietro, Carli P Howe, Marie-Laure Firebaugh, Michelle G Newman, Linda M Collins and 2 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in The International journal of eating disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Trial
  2. Article
  3. Power Calculation in 2Prevention science : the official journal of the Society for Prevention Research · 2026
    Article
  4. Leveraging Technology to Enhance Eating Disorder Treatment Outcomes.The Psychiatric clinics of North America · 2026
    Review
  5. Article
  6. Article
  7. Using Machine Learning to Predict Uptake to an Online Self-Guided Intervention for Stress During the COVID-19 Pandemic.Stress and health : journal of the International Society for the Investigation of Stress · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Ellen E Fitzsimmons-CraftDepartment of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID 0000-0001-7064-3835
Gavin N RackoffDepartment of Psychology, The Pennsylvania State University, University Park, PA, USA.ORCID 0000-0003-3525-3975
Jillian ShahDepartment of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID 0000-0001-6006-3263
Jillian C StrayhornDepartment of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA.ORCID 0000-0003-3502-9623
Laura D'AdamoDepartment of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID 0000-0001-9963-7316
Bianca DePietroDepartment of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID 0000-0002-1794-2833
Carli P HoweDepartment of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID 0009-0003-1472-7374
Marie-Laure FirebaughDepartment of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID 0000-0002-3663-131X
Michelle G NewmanDepartment of Psychology, The Pennsylvania State University, University Park, PA, USA.ORCID 0000-0003-0873-1409
Linda M CollinsDepartment of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA.ORCID 0000-0003-4282-8722
C Barr TaylorDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0002-4564-6548
Denise E WilfleyDepartment of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID 0000-0002-3599-8689

Funding

WUSTL Transdisciplinary Pre- and Postdoctoral Training Program in Obesity and Cardiovascular DiseaseT32HL130357 · NHLBI · WASHINGTON UNIVERSITY · PI WILFLEY, DENISE ELLA · 2016 to 2025
$4.3M
Harnessing Mobile Technology to Reduce Mental Health Disorders in College PopulationsR01MH115128 · NIMH · WASHINGTON UNIVERSITY · PI EISENBERG, DANIEL, NEWMAN, MICHELLE G · 2018 to 2022
$4.1M
Developing an Optimized Conversational Agent or "Chatbot" to Facilitate Mental Health Services Use in Individuals with Eating DisordersK08MH120341 · NIMH · WASHINGTON UNIVERSITY · PI FITZSIMMONS-CRAFT, ELLEN E. · 2019 to 2023
$824k
NHLBI NIH HHS T32 HL130357NIMH NIH HHS K08 MH120341NIMH NIH HHS R01 MH115128NIMH NIH HHS R01 MH115128-04S1
6 · The paper itself

Abstract

objectiveFew 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).

methodsTwo 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.

resultsParticipants 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.

Indexed as

Feeding and Eating DisordersMental Health ServicesMotivational InterviewingAdolescentAdultFemaleHumansInternetMaleMass ScreeningPatient Acceptance of Health CareYoung Adultchatbotconversational agentdigital interventioneating disordermental health treatmentmHealthoptimizationscreening

Identifiers

PMID39072846
PMCPMC11560741

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.