Evidence map›Paper›PMID 40746673›Full record

ArticleFrontiers in public health2025

Determinants of rural middle school students' adoption of AI chatbots for mental health.

Shuo Li, Lei Liu, Yuhui Wang, Xinyun Deng

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Shuo Li *School of Architecture and Art, Central South University, Changsha, China.
Lei Liu *School of Architecture and Art, Central South University, Changsha, China.
Yuhui WangSchool of Architecture and Art, Central South University, Changsha, China.
Xinyun DengSchool of Architecture and Art, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adolescent mental health challenges constitute an important global public health issue. Despite the rapid development of AI technology in various fields, its adoption in rural mental health remains constrained. The purpose of this study is to examine the factors that influence the adoption of AI chatbots for mental health education among rural Chinese secondary school students. Utilizing the UTAUT2 framework, we included Perceived Risk (PR) and Perceived Anthropomorphism (PA) to construct a theoretical model. A questionnaire survey of 317 rural adolescents was conducted, analyzed via SPSS and AMOS. Results showed PE, EE, SI, and PA positively correlated with BI; PR negatively correlated; HM had no effect. Grade level moderated specific paths. The study extends UTAUT2 to marginalized populations, filling a gap in AI-driven rural adolescent mental health interventions.

Indexed as

Health EducationMental HealthRural PopulationStudentsAdolescentChinaFemaleGenerative Artificial IntelligenceHumansMaleSurveys and Questionnairesartificial intelligencebehavioral intentionmental healthrural middle school studentsUTAUT2

Identifiers

PMID40746673
PMCPMC12310474

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.