Evidence map›Paper›PMID 41234618›Full record

ArticleDigital health

BetterMood: A human-like AI counseling service for adolescents and young adults.

Do Hyung Kim, Soeun Baek, Joonsung Lee, Taehwi Lee, Soyeon Park, Beomchan You, Ji-Won Hur, Minah Kim, Chang-Gun Lee

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Do Hyung KimDepartment of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-1881-4323
Soeun BaekDepartment of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0003-5620-5419
Joonsung LeeDepartment of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0001-3732-0804
Taehwi LeeDepartment of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0008-2050-6785
Soyeon ParkDepartment of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0001-6100-086X
Beomchan YouDepartment of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0009-0001-1091-1516
Ji-Won HurSchool of Psychology, Korea University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-1939-7365
Minah KimDepartment of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-8668-0817
Chang-Gun LeeDepartment of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-7434-0495

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: In-person counseling faces limitations in timing and geographical accessibility, often causing adolescents and young adults (AYAs) to miss timely psychological support. With the advent of large language models (LLMs), the mental health care industry has increasingly focused on developing chat counseling services as supplementary tools to reduce these barriers. However, existing services have two primary limitations: tendency toward generic advice and absence of human-like dialogue. To overcome these limitations, this article proposes BetterMood, a human-like AI counseling service specifically for Korean-speaking AYAs. Methods: Our design for BetterMood separately addressed the content and delivery of counseling dialogue. For content, we develop a concern-aware counseling LLM refined through prompt-engineering with a novel prompt derived from collected counseling data. For delivery, we create a human-like AI counselor that employs a chunk-based streaming methodology to enable human-like dialogue. We then conducted a user study with 10 adolescents, 110 young adults, and 8 professional clinicians to assess the feasibility and user experience across four domains: (i) interaction capability, (ii) perceived support, (iii) usability, and (iv) ethical safety. Results: Our user study indicates that BetterMood's interactive capabilities, particularly its ability to suggest appropriate responses, received positive feedback from 90.0% of adolescents, 90.9% of young adults, and 75.0% of professional clinicians. Stratified analysis revealed that outcomes regarding perceived support and usability of the service differed across cohorts and initial screening status. Furthermore, independent evaluations by eight professional clinicians demonstrated moderate agreement for individual ratings but excellent reliability for the aggregated assessment. Conclusion: Positive user experience and high inter-rater reliability among clinicians support BetterMood's potential as an accessible supplementary tool for initial psychological support.

Indexed as

Adolescents’ and young adults’ mental health careAI counselingchunk-based streamingconcern-aware counseling LLMhuman-like AI counselor

Identifiers

PMID41234618
PMCPMC12605886

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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.