Evidence map›Paper›PMID 40805917›Full record

ArticleHealthcare (Basel, Switzerland)2025

Application of AI Mind Mapping in Mental Health Care.

Hsin-Shu Huang, Bih-O Lee, Chin-Ming Liu

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Hsin-Shu HuangDepartment of Nursing, Central Taiwan University of Science and Technology, Taichung 40601, Taiwan.
Bih-O LeeCollege of Nursing, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.ORCID 0000-0003-1903-8378
Chin-Ming LiuDepartment of Psychiatry, Cheng Ching Hospital, Taichung 40045, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSchizophrenia affects patients' organizational thinking, as well as their ability to identify problems. The main objective of this study was to explore healthcare consultants' application of AI mind maps to educate patients with schizophrenia regarding their perceptions of family function, social support, quality of life, and loneliness, and to help these patients think more organizationally and understand problems more effectively.

methodsThe study used a survey research design and purposive sampling method to recruit 66 participants with schizophrenia who attended the psychiatric outpatient clinic of a hospital in central Taiwan. They needed to be literate, able to respond to the topic, and over 18 years old (inclusive), and they attended individual and group health education using AI mind maps over a 3-month period during regular outpatient clinic visits.

resultsThe study results show that patients' family function directly affects their quality of life (

conclusionsTherefore, this study confirms the need to provide holistic, integrated mental health social care support for patients with schizophrenia, showing that healthcare consultants can apply AI mind maps to empower patients with schizophrenia to think more effectively about how to mobilize their social supports.

Indexed as

artificial intelligenceempowermentthinking function

Identifiers

PMID40805917
PMCPMC12345955

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.