Evidence map›Paper›PMID 41859537›Full record

ArticleJournal of multidisciplinary healthcare2026

Attitudes of Breast Cancer Chemotherapy Patients and Nurses Toward Acceptance of AI Psychological Nursing: A Qualitative Study.

Tianyu Chu, Xian Chen, Qian Zhang, Hui Zhou, Ling Chen, Kai Jiang

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2026. 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
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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

6 authors.

Tianyu Chu *Obstetrics, Gynecology and Reproduction Research Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214000, People's Republic of China.
Xian Chen *Obstetrics, Gynecology and Reproduction Research Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214000, People's Republic of China.
Qian ZhangObstetrics, Gynecology and Reproduction Research Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214000, People's Republic of China.
Hui ZhouObstetrics, Gynecology and Reproduction Research Center, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214000, People's Republic of China.ORCID 0000-0002-9781-8145
Ling ChenDepartment of Breast Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214062, People's Republic of China.
Kai JiangDepartment of General Surgery, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214062, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Psychosocial nursing for breast cancer patients is increasingly challenged by the high demand for support. The rapid development of AI technology offers a potential solution to address this challenge. Therefore, exploring the acceptance of AI psychological nursing by breast cancer chemotherapy patients and nurses is of great significance. The study aims to investigate the acceptability of AI in psychosocial nursing and the expectations and needs for its application from the perspective of breast cancer chemotherapy patients and nurses. Patients and Methods: Semi-structured interviews were conducted with 17 breast cancer chemotherapy patients and 8 nurses. The data were coded and analyzed using the Technology Acceptance Model in conjunction with context-specific psychological variables for cancer patients. Results: The final analysis identified four main themes and ten sub-themes, including AI nursing technology functionality features: ease of use of the AI system, human-like design, and stability of the AI. Emotional perception credibility and support effectiveness: accuracy of emotion recognition, appropriateness of responses, and sustainability of emotional support. Psychological safety protection: perception of privacy boundaries and psychological privacy protection. Drivers of acceptance of AI Psychological Nursing: Feelings of loneliness and pathways to integration. Conclusion: This study underscores the potential of AI to enhance psychosocial nursing for breast cancer patients by addressing emotional support needs and alleviating nursing shortages. The findings provide valuable insights into the expectations, concerns, and perceived benefits of AI, offering a foundation for the design of future AI-driven nursing programs aimed at improving both the psychological and physical health of cancer patients.

Indexed as

AIattitudebreast cancerpsychological nursingqualitative research

Identifiers

PMID41859537
PMCPMC12998659

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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.