Evidence map›Paper›PMID 40841815›Full record

ArticleScientific reports2025

Parents' information needs and perceptions of chatbots regarding self medicating their children.

Xueyi Wei, Xiuwen Chen, Liqing Yue, Peng Liao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

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

4 authors.

Xueyi WeiXiangya School of Nursing, Central South University, Changsha, China.
Xiuwen ChenTeaching and Research Section of Clinical Nursing, Xiangya Hospital, Central South University, Changsha, China. chenxiuwen2020@163.com.
Liqing YueTeaching and Research Section of Clinical Nursing, Xiangya Hospital, Central South University, Changsha, China.
Peng LiaoTeaching and Research Section of Clinical Nursing, Xiangya Hospital, Central South University, Changsha, China.

Funding

2024 Annual Graduate Student Independent Exploration and Innovation Project of Central South University 2024ZZTS0548the Research Project of China Hunan Provincial Science and Technology Department 2022ZK4059the Research Project of Natural Science Foundation of Hunan Province 2023JJ40922
6 · The paper itself

Abstract

This qualitative study aimed to better understand parents' information needs and perceptions of chatbots for self-medicating their children and developing chatbots for self-medication. A qualitative study was employed. Semi-structured interviews were conducted from October 2023 to December 2023. The interview data were analysed using a thematic analysis method. A total of 26 participants were interviewed by trained interviewers. Four key themes were identified: (1) Multiple information needs for self-medication; (2) Factors promoting the use of chatbots in self-medication; (3) Factors hindering the use of chatbots in self-medication; and (4) Expectations and suggestions for chatbots design. The parents' perspective provided important insights into the design of the chatbot conversational interfaces that could help improve parents' practice of self-medicating their children. Although most participants were unfamiliar with chatbots, they were generally optimistic about their convenience, reliability, and benefits that would reduce medical burdens and cross-infection. When designing chatbots in the future, we will focus on the privacy and financial security, information recognition and cost issues to design chatbots with various transmission forms, communication interaction, health tracking and feedback functions.

Indexed as

ParentsSelf MedicationAdultChildCommunicationFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedPerceptionQualitative ResearchChatbotsChildrenInformation needsParentsQualitative studySelf-medication

Identifiers

PMID40841815
PMCPMC12370943

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.