Cited by 103Digital Mental Health InterventionsSocial Robot Interaction and HRIEmotion and Mood Recognition

The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.

A chatbot for mental health support: exploring the impact of Emohaa on reducing mental distress in China

Open access
Sabour, Sahand, Zhang, Wen, Xiao, Xiyao, Zhang, Yuwei, Zheng, Yinhe, Wen, Jiaxin, Zhao, Jialu, Huang, Minlie·2023·Frontiers in Digital Health

Abstract

Introduction The growing demand for mental health support has highlighted the importance of conversational agents as human supporters worldwide and in China. These agents could increase availability and reduce the relative costs of mental health support. The provided support can be divided into two main types: cognitive and emotional. Existing work on this topic mainly focuses on constructing agents that adopt Cognitive Behavioral Therapy (CBT) principles. Such agents operate based on pre-defined templates and exercises to provide cognitive support. However, research on emotional support using such agents is limited. In addition, most of the constructed agents operate in English, highlighting the importance of conducting such studies in China. To this end, we introduce Emohaa, a conversational agent that provides cognitive support through CBT-Bot exercises and guided conversations. It also emotionally supports users through ES-Bot, enabling them to vent their emotional problems. In this study, we analyze the effectiveness of Emohaa in reducing symptoms of mental distress. Methods and Results Following the RCT design, the current study randomly assigned participants into three groups: Emohaa (CBT-Bot), Emohaa (Full), and control. With both Intention-To-Treat ( N = 247 ) and PerProtocol ( N = 134 ) analyses, the results demonstrated that compared to the control group, participants who used two types of Emohaa experienced considerably more significant improvements in symptoms of mental distress, including depression ( F [ 2 , 244 ] = 6.26 , p = 0.002 ), negative affect ( F [ 2 , 244 ] = 6.09 , p = 0.003 ), and insomnia ( F [ 2 , 244 ] = 3.69 , p = 0.026 ). Discussion Based on the obtained results and participants’ satisfaction with the platform, we concluded that Emohaa is a practical and effective tool for reducing mental distress.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3389/fdgth.2023.1133987

Cites

58 of 58 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 44 references

Cited by

Sorted by citations

Items 101–103 of 103

Metadata

Authors
Sabour, S., Zhang, W., Xiao, X., Zhang, Y., Zheng, Y., Wen, J., Zhao, J., & Huang, M.
Affiliations
  • State Key Laboratory of Intelligent Technology and Systems (CN)
  • Beijing Normal University (CN)
  • Tsinghua University (CN)
Corresponding author
  • Sabour, Sahand
  • Huang, Minlie
Venue
Frontiers in Digital Health
Published
2023-05-04
Volume
5
Pages
1133987-1133987
ISSN
2673-253X (ISSN-L)
OpenAlex
W4377565325
Cited by
102
References
44
Citations by year
2026: 31 · 2025: 36 · 2024: 25 · 2023: 10
FWCI
26.33
Type
journal article
Language
en
Open access
Locations
  • Frontiers in Digital Health (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Keywords
chatbots, mental health support, cognitive behavioral therapy, depression, negative affect, insomnia, emotional support, psychological distress, China

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review