Evidence map›Paper›PMID 40686565›Full record

ArticlePatient preference and adherence2025

Identifying Patients' Preference During Their Hospital Experience. A Sentiment and Topic Analysis of Patient-Experience Comments via Natural Language Techniques.

Jie Yuan, Xiao Chen, Chun Yang, JianYou Chen, PengFei Han, YuHong Zhang, YuXia Zhang

Abstract read
In one paragraph

Article in Patient preference and adherence, 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

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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

2 citing papers in PubMed.

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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

7 authors.

Jie Yuan *School of Nursing, Fudan University, Shanghai, 200032, People's Republic of China.ORCID 0000-0003-0341-1756
Xiao Chen *Department of Nursing, Zhongshan Hospital of Fudan University, Shanghai, 200032, People's Republic of China.
Chun YangDepartment of Information, Zhongshan Hospital of Fudan University, Shanghai, 200032, People's Republic of China.
JianYou ChenDepartment of Information, Zhongshan Hospital of Fudan University, Shanghai, 200032, People's Republic of China.
PengFei HanDepartment of Information, Zhongshan Hospital of Fudan University, Shanghai, 200032, People's Republic of China.
YuHong ZhangDepartment of Nursing, Zhongshan Hospital of Fudan University, Shanghai, 200032, People's Republic of China.
YuXia ZhangDepartment of Nursing, Zhongshan Hospital of Fudan University, Shanghai, 200032, People's Republic of China.ORCID 0000-0003-4419-7004

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Open-ended questions in patient experience surveys provide a valuable opportunity for people to express and discuss their authentic opinions. The analysis of free-text comments can add value to quantitative measures by offering information which matters most to patients and by providing detailed descriptions of the service issues that closed-ended items may not cover. Objective: To extract useful information from large amounts of free-text patient experience comments and to explore differences in patient satisfaction and loyalty between patients who provided negative comments and those who did not. Methods: We collected free-text comments on a broad, open-ended question in a cross-sectional patient satisfaction survey. We adopted a mixed-methods approach involving a literature review, human annotation, and natural language processing technique to analyze free-text comments. The associations of patient satisfaction and loyalty scores with the occurrence of certain patient comments were tested via logistic regression analysis. Results: In total, 28054 free-text comments were collected (comment rate: 72.67%). The accuracy of the machine learning approach and the deep learning approach for topic modeling and sentiment analysis was 0.98 and 0.91 respectively, indicating a satisfactory prediction. Participants tended to leave positive comments (69.0%, 19356/28054). There were 22 patient experience themes discussed in the open-ended comments. The regression analysis showed that the occurrence of negative comments about "humanity of care", "information, communication, and education", "sense of responsibility of staff", "technical competence", "responding to requests", and "continuity of care" was significantly associated with a worse patient satisfaction and loyalty, while the occurrence of negative comments about other aspects of healthcare services had no impact on patient satisfaction and loyalty. Conclusion: The results of this study highlight the interpersonal and functional aspects of care, especially the interpersonal aspects, which are often the "moment of truth" during a service encounter when patients critically evaluate hospital services.

Indexed as

free-text commentsnatural language processingpatient experiencesentiment analysistopic modelling

Identifiers

PMID40686565
PMCPMC12276748

What OpenQuestion holds

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LicenceCC BY-NC
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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.