Evidence map›Paper›PMID 41237331›Full record

ArticleJMIR cancer2025

Evaluation of Cancer Survivors' Experience of Using AI-Based Conversational Tools: Qualitative Study.

Saif Khairat, Hanna Mehraby, Safoora Masoumi, Melissa Coffel, Callie Rockey-Bartlett, Andrea Huang, William Wood, Ethan Basch

Abstract read
In one paragraph

Article in JMIR cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Exploring young adult cancer survivors' perspectives on generative AI chatbots for symptom support.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  3. Article
  4. Online support needs and preferences for survivors of testicular cancer: a qualitative descriptive study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  5. Article
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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

8 authors.

Saif KhairatCarolina Health Informatics Program, University of North Carolina at Chapel Hill, 428 Carrington Hall, Campus Box 7460, Chapel Hill, NC, 27514, United States, 1 9198435413.ORCID 0000-0002-8992-2946
Hanna MehrabyCarolina Health Informatics Program, University of North Carolina at Chapel Hill, 428 Carrington Hall, Campus Box 7460, Chapel Hill, NC, 27514, United States, 1 9198435413.ORCID 0009-0002-5443-6777
Safoora MasoumiCarolina Health Informatics Program, University of North Carolina at Chapel Hill, 428 Carrington Hall, Campus Box 7460, Chapel Hill, NC, 27514, United States, 1 9198435413.ORCID 0000-0002-7343-1771
Melissa CoffelSchool of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID 0009-0009-9124-4601
Callie Rockey-BartlettSchool of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID 0009-0005-0601-4002
Andrea HuangSchool of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID 0009-0007-8965-8579
William WoodLineberger Comprehensive Care Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID 0000-0001-7439-2543
Ethan BaschLineberger Comprehensive Care Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID 0000-0003-3813-9318

Funding

Center for Virtual Care Value and Excellence (ViVE). RC2TR004380 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Saif Khairat · 2023 to 2026
$3.0M
NCATS NIH HHS RC2 TR004380
6 · The paper itself

Abstract

Background: Cancer survivorship is a complicated, chronic, and long-lasting experience, causing uncertainty and a wide range of physical and emotional health concerns. Due to the complexity of cancer, patients often seek out multiple sources of health information to better understand the aspects of their cancer diagnosis. The high variability among patients with cancer presents significant challenges in treatment, prognosis, and overall disease management. Artificial intelligence (AI) chatbots can further personalize cancer care delivery. However, there is a knowledge gap regarding cancer survivors' perceived facilitators and barriers to adopting and using AI chatbots. Objective: In this study, we examined cancer survivors' experiences of using existing AI chatbots and identified their facilitators and barriers to the adoption of AI chatbots. Methods: We conducted a qualitative study to investigate the perceptions of cancer survivors, conducting semistructured interviews to understand their prior use of existing AI chatbots in general. We asked the participants about their perceptions regarding AI chatbot acceptability and comfort level; trust and adherence; and concerns, barriers, and suggestions. We used the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist for this qualitative report. Results: Of 21 participants, 17 (81%) were female patients with breast cancer, 15 (71%) were aged 50 to 64 years, 19 (90%) were White, and 9 (43%) had a graduate degree. Participants' responses were grouped into three overarching themes: (1) patients' perceptions of interacting with chatbots compared to health care professionals, (2) patient-chatbot interaction, and (3) chatbot information processing. All participants who were interviewed reported that they would prefer interacting with health care professionals over a chatbot. The lack of empathy shown by chatbots was a major concern among cancer survivors. Many patients criticized chatbots for tending to provide a general overarching response to their questions rather than being specific to their cancer diagnosis. The main concerns of cancer survivors with using chatbots were the overabundance of general information that was often not relevant to their diagnosis and privacy of patient information. Conclusions: The findings of this study underscore the critical importance of empathetic responses during AI chatbot interactions for cancer survivors, as the lack of personalized and emotional responses can lead to distrust and frustration. Clinically, these tools should be integrated as supplementary resources to enhance patient engagement while preserving essential human support. Policymakers need to develop guidelines that promote responsible use of AI in cancer care, prioritizing patient confidentiality and trustworthiness. AI chatbots have the potential to significantly improve the support provided to cancer survivors, but it is crucial to address the identified barriers and enhance user acceptance.

Indexed as

Artificial IntelligenceCancer SurvivorsCommunicationNeoplasmsAdultAgedFemaleHumansMaleMiddle AgedQualitative Researchadoptionartificial intelligencebarrierscancerfacilitatorssurvivorsuser experience

Identifiers

PMID41237331
PMCPMC12617959

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.