The Usability and Experience of Artificial Intelligence‐Based Conversational Agents in Health Education for Cancer Patients: A Scoping Review
Open accessAbstract
Background: Artificial intelligence‐based conversational agents (CAs) have shown transformative potential in healthcare, yet their application in cancer health education has remained underexplored, particularly regarding usability and patients' experiences. Existing reviews lack a dedicated focus on user perspectives, limiting insights into how CAs can be optimised for patient needs. Aim: To explore the usability and experience of artificial intelligence‐based conversational agents in health education for cancer from the user perspective. Design: A scoping review was conducted with the Joanna Briggs Institute Scoping Reviews conduct guidance and reported according to the preferred reporting items for systematic reviews and meta‐analyses extension for scoping reviews checklist. Methods: A search was performed in PubMed, Embase, CINAHL, Web of Science, PsycINFO, IEEE Xplore Digital Library and ACM Digital Library from their inception to March 6, 2024. The references to the articles included were also searched. The Pillar Integration Process was employed to chart data. Results: A total of 12 studies were included in this scoping review, which revealed that CAs supported diverse educational contexts, including cancer‐related knowledge (41.7%), pretest genetics (33.3%), self‐management (16.7%) and psychological skills (8.3%). Three studies reported that patients preferred interactions with multiple options or ‘read more’ functions. Patients were generally optimistic about the CAs and reported that CAs provided informational, physical, and psychological support for them. However, limitations such as insufficient customisation, lack of empathy, and defects in understanding free‐input questions were noted. Conclusion: This review demonstrated that CAs are promising complementary tools in cancer education, alleviating healthcare burdens while enhancing patient engagement, which was particularly critical in resource‐limited settings. However, clinical implementation requires more rigorous validation of safety protocols and high‐quality original studies. Relevance to Clinical Practice: Nurses and policymakers should consider CAs valuable tools to enhance cancer health education, provided that they align with patient needs and institutional safety standards.
AI snapshot
Written from the paper’s full text.
TL;DR
This scoping review of 12 studies found that cancer patients generally viewed AI-based conversational agents positively for health education, valuing usability, informational/physical/psychological support, and 24/7 access. However, evidence remains limited by heterogeneity, geographic concentration, and concerns about customisation, empathy, free-input understanding, and safety.
Key findings
- Across 12 included studies and 1587 participants (1516 patients with cancer, 71 at risk), CAs addressed cancer-related knowledge (41.7%), pretest genetics (33.3%), self-management (16.7%), and psychological skills (8.3%).
- Patients were generally positive: five studies reported satisfaction with CA information as valuable, informative, and reliable; five found few interaction barriers; over 90% in one study agreed ChemoFreeBot was easy to use, and over three-quarters of a median-age-68 group needed no assistance.
- Three studies reported preferences for multiple options or “read more” functions; one study found smartphone preference, another computers/laptops, and lifestyle and breast biopsy side effects were the most reviewed topics among six offered.
- CAs provided informational, physical, and psychological/emotional support; one RCT showed alleviated physical and psychological symptoms after chemotherapy and promoted self-care, but limitations included insufficient customisation, lack of empathy, and unstable understanding of free-input questions.
Methods
- Scoping review following Joanna Briggs Institute Scoping Reviews conduct guidance and reported with PRISMA-ScR; searched PubMed, Embase, CINAHL, Web of Science, PsycINFO, IEEE Xplore Digital Library, and ACM Digital Library from inception to 6 March 2024, plus reference searching.
- Inclusion criteria covered patients diagnosed with cancer or at high risk, CAs applied in health education, and primary studies such as RCTs, pilot studies, and qualitative investigations; no publication date or language restrictions. Exclusions included noncancer/healthy individuals, non-education CAs, development-only studies, protocols/reviews/theses/editorials/comments/conference abstracts, and unavailable full texts.
- Data were charted in Excel, and the Pillar Integration Process (listing, matching, checking, pillar building) was used to integrate qualitative and quantitative findings; 12 studies were included.
Limitations
- Stated: heterogeneity in study designs, populations, and educational contexts limited synthesis and generalisability; the review did not evaluate study quality; potential publication bias may have skewed findings toward favourable perceptions; insufficient qualitative studies and a small number of studies limit findings; scoping review only maps evidence and does not determine utility.
- Stated: 11 of 12 studies originated from developed countries (USA 6, France 3, Germany 1, Norway 1; one from Egypt), limiting global generalisability; approximately 75% of studies were conducted on breast cancer patients (table reports 7/12, 58.3%), and participant ages spanned 19–90 years, which may influence feedback.
- Evident: only one RCT demonstrated symptom and self-care benefits; safety, severity identification, and long-term outcomes remain inadequately evaluated.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
55 of 90 cited sources checked · 29 supported · 0 flagged · accuracy not yet measured
- Findingcitation
Patients reported that CAs had an unstable understanding of self-written questions, failing to accurately provide the information they expected.
“During interaction with CAs, patients reported that CAs had an unstable understanding of self-written questions, failing to accurately provide the information they expected (Siglen et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
The Results (Emerging Concepts; page not available) say several interviewees reported that Rosa inconsistently understood self-composed questions and switched to suggested readings. The Discussion (Principal Findings; page not available) reports a high fallback rate for open-ended questions, but does not establish that the information Rosa provided was inaccurate or consistently failed to meet patients’ expectations. (LLM, conf=0.82)
Experimental — accuracy not yet measured
- Findingcitation
Patients preferred interactions with multiple options or 'read more' functions.
“Three studies reported that patients preferred interactions with multiple options or 'read more' functions.”
- Also stated in: § 3.3.1 | Attitude Towards CAs · plain
“In terms of interaction style, Chaix et al. found that patients preferred CAs with multiple options, making it easy to obtain relevant information by clicking buttons rather than typing responses (Chaix et al. 2019).”
- Also stated in: § 4.1.1 | User-Friendly Tools for Patients · plain
“Interestingly, the findings identified that multiple options and the function of 'read more' were the preferred interactions of patients (Chaix et al. 2019;Siglen et al. 2023).”
Quote in the paperNot a substantial claim2 of 2 sources checked - Also stated in: § 3.3.1 | Attitude Towards CAs · plain
- Findingcitation
Patients were not completely satisfied with CAs due to lacking customisation.
“limitations such as insufficient customisation, lack of empathy, and defects in understanding free-input questions were noted.”
- Also stated in: § 3.3.3 | Limitations of CAs · plain
“Two studies found that patients are not completely satisfied with CAs due to lacking customisation (Goertz et al. 2023;Qiu et al. 2021;Siglen et al. 2023).”
Quote in the paperNot a substantial claim2 of 3 sources checked- cites Goertz et al. 2023 source
The Results (Patient evaluation; page unavailable) report that patients wanted answers and therapy recommendations tailored to their situations, supporting the concern about insufficient customization. They do not establish that patients were dissatisfied because of it; the same section reports that all participants wanted to use a medical chatbot again. (LLM, conf=0.82)
Experimental — accuracy not yet measured - cites Qiu et al. 2021 source
- cites Siglen et al. 2023 source
The Results (Emerging Concepts; page unavailable) report participants’ concerns about Rosa’s lack of empathy and its difficulty understanding self-composed questions. The Introduction (Background; page unavailable) says personalized communication was not included, but the paper does not clearly say patients were dissatisfied because of insufficient customization; the Discussion (Principal Findings) instead describes an overall positive attitude toward Rosa. (LLM, conf=0.83)
Experimental — accuracy not yet measured
- Also stated in: § 3.3.3 | Limitations of CAs · plain
- Findingcitation
Five studies showed that most patients were satisfied with the information provided by CAs.
“Five studies showed that most patients were satisfied with the information provided by CAs CAs were valuable, informative, and reliable (Bibault, Chaix, Guillemassé, et al. 2019;Chetlen et al. 2019;Greer et al. 2019;Siglen et al. 2023;Tawfik et al. 2023;Visvanathan et al. 2023).”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Bibault, Chaix, Guillemassé, et al. 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Chetlen et al. 2019 source
- cites Greer et al. 2019 source
In Results > Perceived Helpfulness and Open-Ended Feedback (page unavailable), participants rated Vivibot helpful on average and some praised its lessons. The paper does not report that most participants were satisfied with information it provided or that they considered it reliable; its participants were young people after cancer treatment, not patients generally. (LLM, conf=0.86)
Experimental — accuracy not yet measured
- Premisereasoning
These existing reviews did not explicitly focus on the domain of health education for patients.
“However, these reviews did not explicitly focus on the domain of health education for patients.”
Quote in the paperSubstantial claim2 of 2 sources checked
- Findingcitation
Patients felt that CAs resembled talking to a nurse because their knowledge base was based on global consensus, expert guidelines, and professional knowledge rather than mixed internet information.
“Due to CAs' knowledge base being based on global consensus, expert guidelines, and professional knowledge, rather than the mixed information available on the internet, patients felt that it resembled talking to a nurse (Siglen et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
The Results (Emerging Concepts; page not provided) say participants trusted Rosa because health care personnel wrote its information, and some felt its language resembled talking to a nurse or physician. The paper does not establish that Rosa’s knowledge base drew on global consensus or expert guidelines, or that patients made this comparison because internet information was mixed. (LLM, conf=0.86)
Experimental — accuracy not yet measured
- Premisecitation
CAs can meet cancer patients' needs for health education and self-management anytime and anywhere.
“CAs can meet cancer patients' needs for health education and self-management anytime and anywhere, thus addressing the unique requirements of cancer patients (Iannantuono et al. 2023).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Iannantuono et al. 2023 source
The Introduction (page unavailable) describes chatbots used in oncology for remote patient monitoring and lifestyle coaching, and the Results section describes LLMs answering cancer patients’ information questions. These passages support potential roles in education and aspects of self-management, but do not establish that conversational agents meet patients’ needs anytime and anywhere; the Discussion also notes a consequential error rate. (LLM, conf=0.86)
Experimental — accuracy not yet measured
- Findingcitation
Five studies found patients had few barriers to interacting with CAs.
“Five studies found patients had few barriers to interacting with CAs (Goertz et al. 2023;Qiu et al. 2021;Siglen et al. 2023;Tawfik et al. 2023;Visvanathan et al. 2023).”
Quote in the paperNot a substantial claim2 of 3 sources checked- cites Goertz et al. 2023 source
- cites Qiu et al. 2021 source
- cites Siglen et al. 2023 source
The Results (Emerging Concepts; page unavailable) describe easy access, helpful prompts, and positive engagement with Rosa, which support the idea that patients could interact with it. But 7 of 16 participants reported communication shortcomings, including difficulty getting answers to self-composed questions, and 8 of 16 noted the lack of human touch. Describing barriers as few omits these substantial limitations. (LLM, conf=0.83)
Experimental — accuracy not yet measured
- Findingcitation
Compared with routine online interventions, CAs delivering positive psychological skills equally reduced patients' anxiety.
“Compared with routine online interventions, CAs delivering positive psychological skills equally reduced patients' anxiety (Greer et al. 2019).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Greer et al. 2019 source
The Results (Well-Being Outcomes) report reduced anxiety in the Vivibot group, and the Discussion (Conclusions) describes that reduction as comparable to findings for other digital health interventions. But the trial did not compare Vivibot with a routine online intervention: the Methods (Intervention Conditions) say the control group received delayed access and no other chatbot content during the comparison period. The finding also concerns young adults after cancer treatment, not patients generally. (LLM, conf=0.88)
Experimental — accuracy not yet measured
- Findingcitation
CAs increased knowledge.
“In addition to physical and emotional benefits, another significant support by CAs was increased knowledge (Al-Hilli et al. 2023;Goertz et al. 2023).”
Quote in the paperSubstantial claim1 of 2 sources checked - Findingcitation
CAs facilitated communication with patients' families when patients had no idea how to explain the disease.
“Additionally, CAs not only benefited patients but also facilitated communication with patients' families when patients had no idea how to explain the disease (Siglen et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
- Findingcitation
In a group of patients with a median age of 68 (range 49-81 years), over three-quarters did not require any assistance while using CAs.
“In a group of patients with a median age of 68 (ranging from 49 to 81 years), over three-quarters did not require any assistance while using CAs (Goertz et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Goertz et al. 2023 source
- Findingcitation
Most patients said CAs were useful to improve their treatment adherence.
“Most patients said that CAs were useful to improve their treatment adherence (Chaix et al. 2019(Chaix et al. , 2020)), enhance the quality of care (Chetlen et al. 2019), and facilitate self-management (Qiu et al. 2021).”
Quote in the paperNot a substantial claim1 of 2 sources checked - Findingcitation
People felt more confident to make a wise choice about their treatment after getting information in advance.
“However, people felt more confident to make a wise choice about their treatment after getting information in advance (Siglen et al. 2023;Soley et al. 2023).”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites Siglen et al. 2023 source
- cites Soley et al. 2023
The Discussion reports that patients with more positive opinions about pre-visit chatbot education felt more able to decide whether to get genetic testing. The claim extends that finding to treatment choices, which the paper does not assess; the Self-reported Decision section also describes mixed agreement about whether the education helped patients make an informed decision. (LLM, conf=0.87)
Experimental — accuracy not yet measured
- Premisecitation
Most CAs are still in development trials and not yet publicly available.
“As Schachner et al. found (Schachner et al. 2020), most CAs are still in development trials and not yet publicly available.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Schachner et al. 2020 source
- Findingcitation
Over 90% of patients agreed ChemoFreeBot was easy to use on the Chatbot Usability Questionnaire.
“Tawfik (Tawfik et al. 2023) used the Chatbot Usability Questionnaire (CUQ), a chatbotspecific usability questionnaire, to evaluate ChemoFreeBot, finding that over 90% of patients agreed it was easy to use.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Tawfik et al. 2023 source
- Findingcitation
People at high risk for cancer felt comforted after acquiring cancer-related knowledge through CAs before genetic counselling.
“People at high risk for cancer felt comforted after acquiring cancer-related knowledge through CAs before genetic counselling (Siglen et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
In Results > Emerging Concepts, one participant who used Rosa before counseling said its information helped her feel calm and made the situation less difficult. Results > Participant Characteristics says only 1 of 16 participants downloaded Rosa before seeing the counselor; others described wanting earlier access or finding Rosa comforting alongside counseling. The claim overstates the evidence for people feeling comforted specifically after using a chatbot before counseling. (LLM, conf=0.88)
Experimental — accuracy not yet measured
- Findingcitation
Patients were willing to recommend CAs to their family and friends to help them understand disease-related knowledge.
“They were also willing to recommend CAs to their family and friends to help them understand disease-related knowledge (Chaix et al. 2019;Greer et al. 2019).”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites Chaix et al. 2019 source
The Results (‘The Way Patients Used Vik’; page not specified) say patients recommended Vik to friends. Patient testimonies also describe Vik as a source of information. The paper does not say patients recommended it to family or that they did so specifically to help others understand disease-related information. (LLM, conf=0.86)
Experimental — accuracy not yet measured - cites Greer et al. 2019 source
The Results section (“Perceived Helpfulness and Open-Ended Feedback”; page not provided) reports that participants were likely to recommend Vivibot to a friend. It does not report recommendations to family or say the purpose was to help others understand disease-related knowledge; the reported feedback concerns emotional support and positive psychology skills. (LLM, conf=0.90)
Experimental — accuracy not yet measured
- Findingcitation
CAs were primarily designed to provide general health education information related to cancer, such as treatment methods and post-chemotherapy self-management, causing them to be short of personalised advice tailored to individual situations.
“CAs were primarily designed to provide general health education information related to cancer, such as treatment methods and post-chemotherapy self-management, causing them to be short of personalised advice tailored to individual situations (Goertz et al. 2023;Qiu et al. 2021).”
Quote in the paperNot a substantial claim1 of 2 sources checked - Findingcitation
Both quantitative and qualitative studies indicated that CAs provided emotional support for cancer patients before talking to doctors face-to-face.
“Additionally, both quantitative (Chaix et al. 2019;Greer et al. 2019) and qualitative studies (Siglen et al. 2023) indicated that CAs provided emotional support for cancer patients before talking to doctors face-to-face.”
Quote in the paperNot a substantial claim3 of 3 sources checked- cites Chaix et al. 2019 source
The Discussion (Principal Findings; page unavailable) says patients found support in Vik and that its dialogue can be reassuring and comforting. It proposes using a chatbot before an in-office conversation with a doctor, but does not establish that patients received emotional support specifically before face-to-face consultations. (LLM, conf=0.85)
Experimental — accuracy not yet measured - cites Greer et al. 2019 source
The Results and Discussion report that young adults who had undergone cancer treatment found Vivibot helpful and nonjudgmental, with a tentative reduction in anxiety. That supports the emotional-support aspect, but the paper does not say participants used the chatbot before speaking with doctors face-to-face. (LLM, conf=0.87)
Experimental — accuracy not yet measured - cites Siglen et al. 2023 source
The Results (Emerging Concepts; page unavailable) describe a participant who felt calm before meeting a genetic counselor after using Rosa, and another who found the chatbot comforting. However, the study concerned people at risk of hereditary cancer, not necessarily patients with cancer, and it does not establish that the subsequent conversations were face-to-face with doctors. (LLM, conf=0.88)
Experimental — accuracy not yet measured
- Findingcitation
Chaix et al. found that patients preferred CAs with multiple options, making it easy to obtain relevant information by clicking buttons rather than typing responses.
“In terms of interaction style, Chaix et al. found that patients preferred CAs with multiple options, making it easy to obtain relevant information by clicking buttons rather than typing responses (Chaix et al. 2019).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Chaix et al. 2019 source
- Findingcitation
Conversational agents could provide medication reminders to help patients improve medication adherence.
“For example, CAs could provide medication reminders to help patients improve medication adherence (Chaix et al. 2019).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Chaix et al. 2019 source
- Findingcitation
Some knowledge bases of conversational agents were pre-programmed based on common cancer-related issues or professional guidelines.
“Specifically, some knowledge bases of CAs were pre-programmed based on common cancer-related issues or professional guidelines (Siglen et al. 2023)”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
The Introduction (Background; page unavailable) says Rosa has a database of predefined answers about hereditary breast and ovarian cancer written by genetic counselors and geneticists. This supports a pre-programmed, cancer-related knowledge base, but the paper does not say its answers were selected based on common issues or derived from professional guidelines. (LLM, conf=0.82)
Experimental — accuracy not yet measured
- Findingcitation
Little evidence remained to assess the user safety and reliability of conversational agents.
“Little evidence remained to assess the user safety and reliability of CAs, consistent with findings from previous systematic reviews (Laranjo et al. 2018;Milne-Ives et al. 2020).”
Quote in the paperSubstantial claim2 of 2 sources checked- cites Laranjo et al. 2018 source
- cites Milne-Ives et al. 2020 source
The Discussion’s Principal Findings (no page supplied) say that high-quality evidence on patient safety was limited, supporting the user-safety part of the claim. The review also finds that study quality limits assessment of effectiveness, but it does not specifically conclude that there is little evidence to assess agents’ reliability. (LLM, conf=0.81)
Experimental — accuracy not yet measured
- Interpretationreasoning
These issues highlighted the risks of over-reliance on conversational agents, as outdated or generic information may exacerbate existing health issues.
“These issues highlighted the risks of over-reliance on CAs, as outdated or generic information may exacerbate existing health issues (Laymouna et al. 2024).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Laymouna et al. 2024 source
The Discussion (Principal Findings; page not provided) says overreliance on chatbots for health decisions may lead to misjudgments that exacerbate health issues. The Introduction (Background; page not provided) says generic responses can overlook individual health profiles. Our copy does not establish the claim about outdated information. (LLM, conf=0.87)
Experimental — accuracy not yet measured
- Findingcitation
Only one randomized controlled trial proved that patients with breast cancer in the conversational agent group experienced milder symptoms and more effective self-care behaviours.
“with only one RCT proving that patients with breast cancer in the CA group experienced milder symptoms and more effective self-care behaviours (Tawfik et al. 2023).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Tawfik et al. 2023 source
- Findingcitation
Most included studies reported patient-perceived effectiveness of conversational agents.
“or reported patient-perceived effectiveness (Chaix et al. 2019(Chaix et al. , 2020;;Chetlen et al. 2019;Goertz et al. 2023;Greer et al. 2019;Qiu et al. 2021;Siglen et al. 2023;Soley et al. 2023;Visvanathan et al. 2023).”
Quote in the paperNot a substantial claim2 of 3 sources checked - Findingown data
Patients were generally optimistic about CAs.
“Patients were generally optimistic about the CAs”
- Also stated in: § 3.3.1 | Attitude Towards CAs · plain
“Patients' attitudes towards CAs were positive in general.”
Quote in the paperNot a substantial claim - Also stated in: § 3.3.1 | Attitude Towards CAs · plain
- Findingown data
The included studies supported diverse educational contexts: cancer-related knowledge (41.7%), pretest genetics (33.3%), self-management (16.7%), and psychological skills (8.3%).
“CAs supported diverse educational contexts, including cancer-related knowledge (41.7%), pretest genetics (33.3%), self-management (16.7%) and psychological skills (8.3%).”
Quote in the paperNot a substantial claim - Findingnone given
Almost all CAs in the reviewed studies were text-based.
“Almost all CAs in the reviewed studies were text-based.”
Quote in the paperNot a substantial claim - Findingown data
The scoping review included 12 studies.
“A total of 12 studies were included in this scoping review”
- Also stated in: § 3.1 | Search Results · plain
“In total, 12 articles were included in this review.”
Quote in the paperNot a substantial claim - Also stated in: § 3.1 | Search Results · plain
- Findingcitation
Four studies reported user preferences, including device used, interaction style, and focused topic.
“Four studies reported user preferences, including device used, interaction style, and focused topic.”
Quote in the paperNot a substantial claim - Findingcitation
Chatting with CAs as digital companionship would break patients' feelings of isolation related to the disease when they may have no peers to discuss their cancer.
“Chatting with CAs as digital companionship would break patients' feelings of isolation related to the disease when they may have no peers to discuss their cancer (Chaix et al. 2020).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Chaix et al. 2020 source
- Findingreasoning
The impact of health education by CAs on patients' treatment decisions is currently uncertain.
“The impact of health education by CAs on patients' treatment decisions is currently uncertain.”
Quote in the paperNot a substantial claim - Findingcitation
Al-Hilli et al. found there was no significant difference in the improvement of patient knowledge between CAs and professional genetic counselling.
“Al-Hilli et al. found there was no significant difference in the improvement of patient knowledge between CAs and professional genetic counselling, and pretest genetic counselling did not affect patients' pre-determined surgical decisions (Al-Hilli et al. 2023).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Al-Hilli et al. 2023 source
- Findingcitation
Most patients said CAs were useful to facilitate self-management.
“Most patients said that CAs were useful to improve their treatment adherence (Chaix et al. 2019(Chaix et al. , 2020)), enhance the quality of care (Chetlen et al. 2019), and facilitate self-management (Qiu et al. 2021).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Qiu et al. 2021 source
- Findingcitation
Most patients said CAs were useful to enhance the quality of care.
“Most patients said that CAs were useful to improve their treatment adherence (Chaix et al. 2019(Chaix et al. , 2020)), enhance the quality of care (Chetlen et al. 2019), and facilitate self-management (Qiu et al. 2021).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chetlen et al. 2019 source
- Findingcitation
Pretest genetic counselling did not affect patients' pre-determined surgical decisions.
“Al-Hilli et al. found there was no significant difference in the improvement of patient knowledge between CAs and professional genetic counselling, and pretest genetic counselling did not affect patients' pre-determined surgical decisions (Al-Hilli et al. 2023).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Al-Hilli et al. 2023 source
- Findingown data
The review found that AI-based conversational agents potentially undertake part of health education.
“The findings of this review showed that AI-based CAs potentially undertake part of health education”
Quote in the paperSubstantial claim - Findingown data
Geographically, 11 of 12 identified studies originated from the United States and developed countries in Europe.
“Geographically, there were no prominent diversities among the identified studies, with 11 of 12 originating from the United States and developed countries in Europe, meaning that the results may not be generalisable worldwide.”
Quote in the paperSubstantial claim - Findingnone given
The age ranges of participants spanned from 19 to 90 years.
“Moreover, the age ranges of participants spanned from 19 to 90 years, which may influence their feedback on CAs.”
Quote in the paperNot a substantial claim - Findingreasoning
The review found that AI-based conversational agents showed promise in promoting health for cancer patients by addressing gaps in conventional nursing care outside clinical hours.
“The findings of this review indicated that the CAs showed promise in promoting health for cancer patients by addressing gaps in conventional nursing care outside of clinical hours.”
Quote in the paperSubstantial claim - Findingreasoning
Because of the heterogeneity of evaluation criteria of conversational agents, there is a lack of systematic evidence on the usability and experience of conversational agents for health education.
“Moreover, because of the heterogeneity of evaluation criteria of CAs, there is a lack of systematic evidence on the usability and experience of CAs for health education.”
Quote in the paperSubstantial claim - Findingnone given
Other study designs primarily assessed CAs' feasibility.
“Other study designs primarily assessed CAs' feasibility.”
Quote in the paperSubstantial claim - Findingnone given
This review did not reveal patients' preference for text or voice interaction.
“However, this review did not reveal patients' preference for text or voice interaction.”
Quote in the paperNot a substantial claim - Findingcitation
Patients preferred conversational agents' frequent reminders throughout the day to maintain healthy behaviours.
“Patients preferred CAs' frequent reminders throughout the day to maintain healthy behaviours (Qiu et al. 2021)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Qiu et al. 2021 source
- Findingnone given
A gap in the literature is that insufficient qualitative studies explore patients' experiences of conversational agents for health education.
“Third, a gap in the literature is that insufficient qualitative studies explore patients' experiences of CAs for health education.”
Quote in the paperNot a substantial claim - Findingcitation
Most included studies demonstrated the non-inferiority of conversational agents.
“While most studies demonstrated the non-inferiority of CAs (Al-Hilli et al. 2023;Bibault, Chaix, Guillemassé, et al. 2019)”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Al-Hilli et al. 2023 source
- cites Bibault, Chaix, Guillemassé, et al. 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Findingnone given
AI-based conversational agents have positive effects on health outcomes of cancer patients.
“and they have positive effects on health outcomes of cancer patients.”
Quote in the paperSubstantial claim - Findingreasoning
Robust evidence on conversational agents in cancer health education remains limited.
“Robust evidence remains limited, with only one RCT proving that patients with breast cancer in the CA group experienced milder symptoms and more effective self-care behaviours (Tawfik et al. 2023).”
Quote in the paperSubstantial claim - Findingown data
Approximately 75% of the studies were conducted on breast cancer patients.
“Approximately 75% of the studies were conducted on breast cancer patients, which potentially biassed the results towards the needs of this population.”
Quote in the paperSubstantial claim - Findingnone given
Almost all included studies were conducted in developed countries.
“Almost all studies were conducted in the developed countries.”
Quote in the paperSubstantial claim - Findingreasoning
Substantial gaps persist in evaluating the effectiveness of conversational agents in health education, particularly in measurable outcomes such as symptom management, quality of life, and long-term behavioural changes.
“Substantial gaps persist in evaluating the effectiveness of CAs in health education, particularly in terms of measurable outcomes such as symptom management, quality of life, and long-term behavioural changes.”
Quote in the paperSubstantial claim - Findingnone given
Patients report that conversational agents help them improve self-management and knowledge.
“and they report that the CAs help them improve self-management and knowledge”
Quote in the paperSubstantial claim - Findingnone given
Patients show positive attitudes towards conversational agents.
“concludes that patients show positive attitudes towards CAs”
Quote in the paperSubstantial claim - Premisecitation
CAs are especially well suited for cancer, particularly in the context of health education.
“Although CAs have significant potential for medicine overall, they are especially well suited for cancer (Greene et al. 2019), particularly in the context of health education.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Greene et al. 2019 source
- Interpretationreasoning
The application of CAs for health education of cancer patients is still in a nascent stage.
“The application of CAs for health education of cancer patients is still in a nascent stage.”
Quote in the paperSubstantial claim - Interpretationcitation
Conversational agents' frequent reminders compensated for nurses' inability to offer 24/7 available support.
“which compensated for the inability of nurses to offer 24/7 available support.”
Quote in the paperSubstantial claim - Interpretationnone given
Conversational agents could not completely replace nurses and doctors.
“Although the CAs could not completely replace nurses and doctors”
Quote in the paperSubstantial claim - Study design and conductnone given
The heterogeneity of the included studies in terms of study designs, populations, and educational contexts poses challenges in synthesising findings and drawing generalisable conclusions.
“First, the heterogeneity of the included studies in terms of study designs, populations, and educational contexts poses challenges in synthesising findings and drawing generalisable conclusions.”
Quote in the paperSubstantial claim - Interpretationreasoning
These technical limitations allowed conversational agents to act as a supplement to health education rather than a replacement.
“allowed the CAs to act as a supplement to health education rather than a replacement.”
Quote in the paperSubstantial claim - Interpretationreasoning
Pre-programmed knowledge bases may fail to address the unique needs of individual patients.
“which may fail to address the unique needs of individual patients.”
Quote in the paperSubstantial claim - Study design and conductreasoning
The review did not evaluate the quality of included studies due to their heterogeneity.
“The review also did not evaluate the quality due to the studies' heterogeneity.”
Quote in the paperNot a substantial claim - Interpretationown data
The predominance of breast cancer patients potentially biassed the results towards the needs of this population.
“Approximately 75% of the studies were conducted on breast cancer patients, which potentially biassed the results towards the needs of this population.”
Quote in the paperSubstantial claim - Interpretationreasoning
Design disparities may hinder direct comparisons and synthesis of findings across studies.
“Consequently, such design disparities may hinder direct comparisons and synthesis of findings across studies.”
Quote in the paperSubstantial claim - Interpretationown data
The results of this review may not be generalisable worldwide.
“Geographically, there were no prominent diversities among the identified studies, with 11 of 12 originating from the United States and developed countries in Europe, meaning that the results may not be generalisable worldwide.”
Quote in the paperSubstantial claim - Premisecitation
A previous review found that many conversational agents failed to confirm whether their databases were updated, which was crucial for ensuring accurate answers.
“Moreover, a previous review found that many CAs failed to confirm whether their databases were updated, which was crucial for ensuring accurate answers (Li et al. 2023).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Li et al. 2023
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
Conversational agents potentially play a significant adjunctive role in cancer education to reduce the pressure of education and follow-up visits of nurses, especially for developing countries and areas with limited medical resources.
“CAs potentially play a significant adjunctive role in cancer education to reduce the pressure of education and follow-up visits of nurses, especially for those developing countries and areas with limited medical resources.”
Quote in the paperSubstantial claim- Rests on an assumption: Developing countries have limited medical resources.
- May combine two claims. 35
- Classified as probably not a substantial claim. 23
May combine two claims.
FindingcitationPatients thought CAs lacked empathy and a human touch, which limited their ability to handle special and complex issues.
“Patients thought that CAs lacked empathy and a human touch, which limited their ability to handle special and complex issues (Siglen et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
May combine two claims.
PremisereasoningExisting reviews lack a dedicated focus on user perspectives, limiting insights into how CAs can be optimised for patient needs.
“Existing reviews lack a dedicated focus on user perspectives, limiting insights into how CAs can be optimised for patient needs.”
- Also stated in: § 1 | Introduction · plain
“However, these reviews did not explicitly focus on the domain of health education for patients.”
Quote in the paperSubstantial claim2 of 2 sources checked- cites Bibault, Chaix, Nectoux, et al. 2019 source
The Introduction (page not provided) describes this review as an overview of conversational agents in oncology, rather than a review dedicated to user perspectives. The Conclusion identifies a lack of objective evidence about chatbot relevance and efficacy, but the paper does not establish that existing reviews generally lack a user-perspective focus or that this limits insights into optimising CAs for patient needs. (LLM, conf=0.75)
Experimental — accuracy not yet measured - cites Wang et al. 2023 source
The Results section (‘Evaluation of Chatbots’; page unavailable) examines user acceptability, and the Conclusion says more user testing is needed to optimise satisfaction. The ‘Strengths and Limitations of Review’ section notes limited and heterogeneous acceptability data, but does not establish that existing reviews lack a dedicated focus on user perspectives. (LLM, conf=0.78)
Experimental — accuracy not yet measured
- Also stated in: § 1 | Introduction · plain
May combine two claims.
PremisecitationOnly two existing reviews investigated the use of CAs in oncology: one examined the landscape of CAs and the other assessed applications, limitations, and challenges of employing CAs in cancer care.
“There are only two existing reviews investigating the use of CAs in oncology: one examined the landscape of the use of CAs (Bibault, Chaix, Nectoux, et al. 2019) and the other assessed the applications, limitations and challenges of employing CAs in cancer care (Wang et al. 2023).”
Quote in the paperSubstantial claim2 of 2 sources checkedClassified as probably not a substantial claim.
Study design and conductcitationThe Pillar Integration Process was employed to map and synthesise qualitative and quantitative findings.
“The pillar integration process (PIP), a transparent and rigorous four-stage method consisting of listing, matching, checking and pillar building for integrating and presenting qualitative and quantitative findings jointly (Johnson et al. 2017), was employed to map and synthesise the extracted data visually to produce meaningful results.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Johnson et al. 2017 source
May combine two claims.
FindingcitationCAs were valuable, informative, and reliable.
“CAs were valuable, informative, and reliable (Bibault, Chaix, Guillemassé, et al. 2019;Chetlen et al. 2019;Greer et al. 2019;Siglen et al. 2023;Tawfik et al. 2023;Visvanathan et al. 2023).”
Quote in the paperSubstantial claim1 of 3 sources checked- cites Bibault, Chaix, Guillemassé, et al. 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Chetlen et al. 2019 source
- cites Greer et al. 2019 source
In Results > Perceived Helpfulness and Open-Ended Feedback (page not provided), participants rated Vivibot as helpful and described its lessons as useful, supporting the claims that it was valuable and informative. The paper does not establish that Vivibot was reliable. (LLM, conf=0.86)
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationCAs provided informational, physical, and psychological support for cancer patients, potentially enhancing their health across various dimensions.
“reported that CAs provided informational, physical, and psychological support for them.”
- Also stated in: § 3.3.2 | Support by CAs · hedged
“Six studies (Chaix et al. 2019(Chaix et al. , 2020;;Chetlen et al. 2019;Qiu et al. 2021;Soley et al. 2023;Tawfik et al. 2023) confirmed that CAs potentially enhanced patients' health across various dimensions.”
Quote in the paperSubstantial claim1 of 3 sources checked- cites Chaix et al. 2019 source
The Introduction (Objectives; page unavailable) says Vik supplied quality-checked information on breast cancer, treatments, side effects, and quality-of-life topics. The Results (The Way Patients Used Vik; page unavailable) report that patients felt supported and helped with treatment, and the Discussion (General Appreciation; page unavailable) notes emotional attachment. The paper does not establish that Vik provided distinct physical and psychological support or improved health across those dimensions. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites Chetlen et al. 2019 source
- cites Qiu et al. 2021 source
- Also stated in: § 3.3.2 | Support by CAs · hedged
May combine two claims.
FindingcitationOnly one study mentioned user data security, and it reported that no one was concerned about personal data safety when using CAs.
“Only one study mentioned user data security, and it reported that no one was concerned about personal data safety when using CAs (Goertz et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Goertz et al. 2023 source
May combine two claims.
FindingcitationTawfik et al. conducted an RCT proving that CAs could effectively alleviate both physical and psychological symptoms after chemotherapy and promote self-care behaviours.
“Tawfik et al. conducted an RCT proving that CAs could effectively alleviate both physical and psychological symptoms after chemotherapy and promote self-care behaviours (Tawfik et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Tawfik et al. 2023 source
The Methods describe a three-arm randomized controlled trial, and the Results report less frequent, less severe physical and psychological symptoms and more effective self-care behaviors in the ChemoFreeBot group than in the nurse-led education and routine-care groups. The claim overstates this as proof about conversational agents generally: the trial tested one chatbot in women receiving chemotherapy for breast cancer, and measured the effectiveness of self-care behaviors rather than simply whether those behaviors increased. (LLM, conf=0.86)
Experimental — accuracy not yet measured
May combine two claims.
FindingcitationCAs were available 24/7 and integrated into daily routine, allowing users to get instant consultations via mobile devices anytime and anywhere.
“Moreover, CAs were available 24/7 (Siglen et al. 2023) and integrated into daily routine (Qiu et al. 2021), allowing users to get instant consultations via their mobile devices anytime and anywhere.”
Quote in the paperNot a substantial claim1 of 2 sources checkedMay combine two claims.
FindingcitationAfter using CAs, many patients intended to re-use CAs in the future and supported applying CAs in clinical routine.
“After using CAs, many patients intended to re-use CAs in the future and supported applying CAs in the clinical routine (Goertz et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Goertz et al. 2023 source
May combine two claims.
FindingcitationOne study found patients preferred using CAs on their smartphones, while another reported they frequently used computers or laptops to access CAs.
“One study found that patients preferred using CAs on their smartphones (Chetlen et al. 2019), while the other one reported they frequently used computers or laptops to access CAs (Goertz et al. 2023).”
Quote in the paperNot a substantial claim1 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationSiglen et al. found patients tended to use the 'read more' function to continue conversations with CAs.
“Siglen et al. found patients tended to use the 'read more' function to continue conversations with CAs (Siglen et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
May combine two claims.
FindingcitationTechnical limitations identified by the review include a lack of customisation and weakness in natural language processing.
“Technical limitations identified by this review, including a lack of customisation and weakness in natural language processing (Qiu et al. 2021;Siglen et al. 2023)”
Quote in the paperSubstantial claim1 of 2 sources checkedMay combine two claims.
InterpretationcitationWith a global nursing shortage, CAs can take on some of the health education for cancer survivors and allow nurses and doctors to spend more time with patients who truly need a consultation.
“In particular, with a global nursing shortage (Drennan and Ross 2019), CAs can take on some of the health education for the huge numbers of cancer survivors and allow nurses and doctors to spend more time with patients who truly need a consultation.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Drennan and Ross 2019 source
Probably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationA patient described the conversational agent as a friend who remained with her throughout her disease journey.
“A patient described the CAs as a friend who remained with her throughout her disease journey (Siglen et al. 2023).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siglen et al. 2023 source
The Discussion’s Principal Findings say a participant described Rosa as “having a friend beside them, one who is there for the whole ride.” The paper places that description in the genetic testing process, not a journey through a diagnosed disease. (LLM, conf=0.86)
Experimental — accuracy not yet measured
May combine two claims.
InterpretationcitationUnlike face-to-face interactions with nurses, conversational agents just answered questions and would not evaluate patients' true feelings, which may encourage patients to share more openly during interactions to ease anxiety.
“Unlike face-to-face interactions with nurses, CAs just answered questions and would not evaluate patients' true feelings, which may encourage patients to share more openly during interactions to ease anxiety (Laymouna et al. 2024;Marita et al. 2021).”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Laymouna et al. 2024 source
The Results section (‘Health Care Chatbot Benefits’; page unavailable) says friendly chatbot interactions could enhance self-disclosure, supporting the possibility that patients may share more openly. It does not compare chatbots with face-to-face nursing interactions, say that chatbots do not evaluate patients’ feelings, or link this disclosure to easing anxiety. (LLM, conf=0.86)
Experimental — accuracy not yet measured - cites Marita et al. 2021
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Classified as probably not a substantial claim.
Findingown dataThree Pillar themes were determined following PIP analysis: Attitude towards CAs, Support by CAs, and Limitations of CAs.
“Three Pillar themes were determined following PIP analysis: Attitude towards CAs, Support by CAs, and Limitations of CAs (Figure 2).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataAll conversations employed text output.
“These conversations all employed text output”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingnone givenPatients wanted to know more details about sexual health, which they felt uncomfortable asking nurses.
“For example, they wanted to know more details about sexual health, which they felt uncomfortable asking nurses.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingnone givenAll included studies were published between 2019 and 2023, and half were pilot studies or evaluation surveys.
“All included studies were published between 2019 and 2023, and half were pilot studies or evaluation surveys.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationMost patients thought CAs helped them better understand their health conditions and treatment, enhancing their patient experience.
“Most patients thought CAs helped them better understand their health conditions and treatment, enhancing their patient experience (Chetlen et al. 2019).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chetlen et al. 2019 source
Probably not a substantial claim: may not pass S3 (load-bearing).
FindingcitationLifestyle and side effects of breast biopsy were the most frequently reviewed topics of 6 topics offered by CA.
“On topics of interest, lifestyle and side effects of breast biopsy were the most frequently reviewed topics of 6 topics offered by CA (Chetlen et al. 2019).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Chetlen et al. 2019 source
May combine two claims.
FindingcitationThe visual design of CAs was user-friendly, allowing patients to navigate the interface with ease.
“The visual design of CAs was user-friendly, allowing patients to navigate the interface with ease (Visvanathan et al. 2023).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Visvanathan et al. 2023 source
Probably not a substantial claim: may not pass S4 (based).
Findingnone givenThis is the first review focusing on the usability and patients' experience of CAs in health education for cancer.
“This is the first review focusing on the usability and patients' experience of CAs in health education for cancer.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingnone givenHalf of the included studies were pilot studies or surveys, and only four were randomised controlled trials.
“Half of the included studies were pilot studies or surveys, and only four were randomised controlled trials.”
Quote in the paperSubstantial claimMay combine two claims.
FindingreasoningIt is unclear whether conversational agents can accurately identify the severity of patient issues, define appropriate severity criteria, or prevent potential adverse consequences.
“It is unclear whether CAs can accurately identify the severity of patient issues, define appropriate severity criteria, or prevent potential adverse consequences.”
Quote in the paperSubstantial claimMay combine two claims.
Findingnone givenRCTs demonstrated CAs' efficacy, while qualitative studies highlighted patients' subjective preferences but lacked generalisability.
“Methodologically, RCTs demonstrated CAs' efficacy, while qualitative studies highlighted patients' subjective preferences but lacked generalisability.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe included studies exhibited significant heterogeneity in both methodology and demographic characteristics.
“Notably, the included studies exhibited significant heterogeneity in both methodology and demographic characteristics.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Findingnone givenThe security of conversational agents is still uncertain.
“The security of CAs is still uncertain; future research should focus on testing and updating the ability of CAs to identify serious health problems.”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationConversational agents functioned as digital companions, offering emotional support to cancer patients.
“Beyond self-management, CAs also functioned as digital companions, offering emotional support to cancer patients.”
Quote in the paperSubstantial claimMay combine two claims.
Findingnone givenPatients report that conversational agents relieve negative emotions and make them feel more comfortable.
“relieve negative emotions and feel more comfortable.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataParticipants' ages ranged from 19 to 90 years, and three studies recruited patients with an average or median age over 60.
“Participants' ages ranged from 19 to 90 years, and three studies (Al-Hilli et al. 2023; Goertz et al. 2023; Visvanathan et al. 2023) recruited patients with an average or median age over 60.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationDiverse health education contexts were observed, including cancer-related knowledge education (n = 5), pretest genetic education (n = 4), self-management education (n = 2), and positive psychological skills education (n = 1).
“Diverse health education contexts were observed, with cancer-related knowledge education (n = 5) (Bibault, Chaix, Guillemassé, et al. 2019; Chaix et al. 2019, 2020; Chetlen et al. 2019; Goertz et al. 2023), pretest genetic education (n = 4)”
- Also stated in: § 5 | Conclusion · plain
“self-management education (n = 2) (Qiu et al. 2021; Tawfik et al. 2023), and positive psychological skills education (n = 1) (Greer et al. 2019).”
Quote in the paperNot a substantial claim- Also stated in: § 5 | Conclusion · plain
May combine two claims.
Findingown dataThis scoping review involved a total of 1587 participants, comprising 1516 (95.5%) patients confirmed with cancer and 71 (4.5%) at risk of cancer but not yet diagnosed.
“This scoping review involved a total of 1587 participants, comprising 1516 (95.5%) patients confirmed with cancer and 71 (4.5%) were at risk of cancer but not yet diagnosed.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationRegular clinical consultation and effective health education are essential to optimise the outcomes of cancer patients by enhancing cancer knowledge, promoting self-management, providing psychological support, and ultimately improving quality of life.
“Regular clinical consultation and effective health education are essential to optimise the outcomes of cancer patients by enhancing cancer knowledge, promoting self-management, providing psychological support, and ultimately improving quality of life (Chang et al. 2020).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chang et al. 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataDiscrepancies between the two reviewers were resolved through discussion with a third reviewer.
“If discrepancies arose between the decisions of the two reviewers, a consensus was reached through discussion with the third reviewer (Y.Z.).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataData extraction items were pretested by two reviewers with an additional reviewer sampling two included studies before formal extraction.
“Before formal data extraction, two reviewers (K.L. and S.W.) conducted a pretest, with an additional reviewer (Y.Z.) sampling two from the included studies.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe scoping review was reported according to the PRISMA-ScR checklist.
“This scoping review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist (see Appendix S1).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningCAs are promising complementary tools in cancer education, alleviating healthcare burdens while enhancing patient engagement, particularly in resource-limited settings.
“This review demonstrated that CAs are promising complementary tools in cancer education, alleviating healthcare burdens while enhancing patient engagement, which was particularly critical in resource-limited settings.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationThe user's experience and requirements are integral to determining the successful development and improvement of digital products.
“Although the design method is important to developing digital products, the user's experience and requirements are also integral to determining their successful development and improvement (Fu et al. 2022).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Fu et al. 2022
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
PremisecitationJiang et al. focused on the development and evaluation of embodied conversational agents for chronic diseases including cancer, and offered insights into the development and implementation of CAs from the design process perspective.
“Jiang et al. focused on the development and evaluation of embodied conversational agents for chronic diseases including cancer, and offered technicians and healthcare professional's insights into the development and implementation of CAs from the design process perspective (Jiang et al. 2024).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Jiang et al. 2024
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe retrieved studies were screened independently by two reviewers.
“The studies retrieved were imported into Endnote X9 to eliminate duplicates and then screened independently by two reviewers (K.L. and B.Z.).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningAI-based CAs served as user-friendly and accessible tools for health education among cancer patients.
“AI-based CAs served as user-friendly and accessible tools for health education among cancer patients.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningPotential publication bias should be acknowledged in this review.
“Second, potential publication bias should be acknowledged.”
Quote in the paperNot a substantial claim- Rests on an assumption: Studies with positive outcomes or significant results are more likely to be published.
May combine two claims.
InterpretationcitationConversational agents empower healthcare providers to work more effectively and improve the experience of patients.
“they empower healthcare providers to work more effectively and improve the experience of patients (Greene et al. 2019).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Greene et al. 2019 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenStudies screening and data extraction were conducted independently after two reviewers reached a strong agreement to minimise selection bias.
“Additionally, studies screening and data extraction were conducted independently after two reviewers reached a strong agreement to minimise selection bias.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductreasoningThe review employed the Pillar Integration Process to integrate mixed-methods data, but differences in methodological rigour and focus may affect the comparability of results.
“While we employed the PIP to integrate mixed-methods data, differences in methodological rigour and focus may affect the comparability of results.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenEspecially in developing countries with limited medical resources, there may be a greater need to integrate conversational agents into primary care to provide healthcare support for cancer patients and share the educational burden of nurses.
“Especially in developing countries with limited medical resources, there may be a greater need to integrate CAs into primary care to provide healthcare support for cancer patients and share the educational burden of nurses.”
Quote in the paperNot a substantial claim- Rests on an assumption: Developing countries have limited medical resources.
Classified as probably not a substantial claim. May combine two claims.
InterpretationreasoningDeveloped countries have solid financial and technological support to develop CAs, potentially leading to the exacerbation of medical inequity.
“The reason may be that developed countries have solid financial and technological support to develop CAs, potentially leading to the exacerbation of medical inequity.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenProvided that patients possess a mobile device, they can access the system directly via a link or app.
“Provided that patients possess a mobile device, they can access the system directly via a link or app.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenCompared to mixed information from broad internet sources, patients would feel comfortable and trustworthy with conversational agents who are admitted professional virtual educators.
“Compared to the mixed information from broad sources on the internet, patients would feel comfortable and trustworthy with CAs who are admitted professional virtual educators.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationYounger patients may exhibit higher digital literacy and thus be more likely to use digital tools and have positive experiences.
“Younger patients may exhibit higher digital literacy and thus be more likely to use digital tools and have positive experiences (Paillaud et al. 2025).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Paillaud et al. 2025
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
InterpretationreasoningThis delivery relieves the need for additional expenditure on access devices or extensive time in learning how to use CAs.
“This delivery relieves the need for additional expenditure on access devices or extensive time in learning how to use CAs.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPrevious research showed that compared to typing on the keyboard, patients may feel more comfortable through voice interaction.
“In terms of interactive modality, previous research showed that compared to typing on the keyboard, patients may feel more comfortable through voice interaction (Car et al. 2020).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Car et al. 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductreasoningThe study designs and a small number of studies limit the findings of this review.
“The study designs and a small number of studies limit the findings of this review.”
Quote in the paperSubstantial claim
The paper relies on this without support.
Traditional face-to-face consultation is restricted by time and location, which can lead to insufficient or delayed health education for cancer patients.
“However, traditional face-toface consultation is restricted by time and location.For example, patients may face difficulties in accessing healthcare providers due to geographical distance or the unavailability of timely appointments, which could lead to insufficient or delayed health education for cancer patients.”
The paper relies on this without support.
Developing countries have limited medical resources.
“Especially in developing countries with limited medical resources, there may be a greater need to integrate CAs into primary care to provide healthcare support for cancer patients and share the educational burden of nurses.”
“especially for those developing countries and areas with limited medical resources.”
The paper relies on this without support.
Studies with positive outcomes or significant results are more likely to be published.
“Studies with positive outcomes or significant results are more likely to be published, which may have skewed the findings towards favourable perceptions of CAs.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Abstract counts three interaction-preference studies; results identify two
MinorThe abstract reports three studies on preferences for multiple options or "read more," but the results identify only Chaix and Siglen for those interaction preferences.
“Three studies reported that patients preferred interactions with multiple options or 'read more' functions.”
“In terms of interaction style, Chaix et al. found that patients preferred CAs with multiple options, making it easy to obtain relevant information by clicking buttons rather than typing responses (Chaix et al. 2019).Siglen et al. found patients tended to use the 'read more' function to continue conversations with CAs (Siglen et al. 2023).”
Customisation claim counts two studies but cites three
MinorThe statement attributes the finding to two studies, while its citation list names Goertz, Qiu, and Siglen.
“Two studies found that patients are not completely satisfied with CAs due to lacking customisation”
“(Goertz et al. 2023;Qiu et al. 2021;Siglen et al. 2023)”
Population categories total 13 studies, not 12
MinorThe population counts in Table 2 sum to 13, although the table says it covers 12 included studies.
Reported 12 · recomputed 13
“| Population | | | Breast cancer | 7 (58.3%) | | Prostate cancer | 2 (16.7%) | | At risk of hereditary breast and ovarian | 1 (8.3%) | | cancer | | | At risk of breast cancer and recommended | 1 (8.3%) | | to undergo breast biopsy | | | Pancreatic cancer | 1 (8.3%) | | Cancer | 1 (8.3%) |”
Satisfaction claim counts five studies but cites six
MinorThe statement says five studies, but its supporting citation list names six distinct included studies.
“Five studies showed that most patients were satisfied with the information provided by CAs”
“(Bibault, Chaix, Guillemassé, et al. 2019;Chetlen et al. 2019;Greer et al. 2019;Siglen et al. 2023;Tawfik et al. 2023;Visvanathan et al. 2023)”
Cites
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Siegel, R. L., Miller, K. D., Fuchs, H. E., & Jemal, A. (2021) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21654 · Cited by 16,522 · see citing works
Munn, Z., Peters, M. D. J., Stern, C., Tufanaru, C., McArthur, A., & Aromataris, E. (2018) · BMC Medical Research Methodology · doi:10.1186/s12874-018-0611-x · Cited by 11,385 · see citing works
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · see citing works
ELIZA — a computer program for the study of natural language communication between man and machine
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Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017) · JMIR Mental Health · doi:10.2196/mental.7785 · Cited by 2,730 · see citing works
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JBI Manual for Evidence Synthesis
(2024) · doi:10.46658/jbimes-24-01 · Cited by 2,483 · see citing works
Conversational agents in healthcare: a systematic review
Laranjo, L., Dunn, A. G., Tong, H. L., Kocaballi, A. B., Chen, J., Bashir, R., Surian, D., Gallego, B., Magrabi, F., Lau, A. Y. S., et al. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy072 · Cited by 1,388 · see citing works
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My Chatbot Companion - a Study of Human-Chatbot Relationships
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The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review
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Xu, L., Sanders, L., Li, K., & Chow, J. C. L. (2021) · JMIR Cancer · doi:10.2196/27850 · Cited by 571 · see citing works
Self-citationConversational Agents in Health Care: Scoping Review and Conceptual Analysis
Tudor Car, L., Dhinagaran, D. A., Kyaw, B. M., Kowatsch, T., Joty, S., Theng, Y.-L., & Atun, R. (2020) · Journal of Medical Internet Research · doi:10.2196/17158 · Cited by 553 · see citing works
Global nurse shortages—the facts, the impact and action for change
Drennan, V. M., & Ross, F. (2019) · British Medical Bulletin · doi:10.1093/bmb/ldz014 · Cited by 493 · see citing works
Mariani, M. M., Hashemi, N., & Wirtz, J. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113838 · Cited by 378 · see citing works
Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review
Laymouna, M., Ma, Y., Lessard, D., Schuster, T., Engler, K., & Lebouché, B. (2024) · Journal of Medical Internet Research · doi:10.2196/56930 · Cited by 305 · see citing works
Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review (Preprint)
Laymouna, M., Ma, Y., Lessard, D., Schuster, T., Engler, K., & Lebouché, B. (2024) · doi:10.2196/preprints.56930 · Cited by 302 · see citing works
Pillar Integration Process: A Joint Display Technique to Integrate Data in Mixed Methods Research
Johnson, R. E., Grove, A. L., & Clarke, A. (2019) · Journal of Mixed Methods Research · doi:10.1177/1558689817743108 · Cited by 272 · see citing works
Schachner, T., Keller, R., & v Wangenheim, F. (2020) · Journal of Medical Internet Research · doi:10.2196/20701 · Cited by 267 · see citing works
Greer, S., Ramo, D., Chang, Y.-J., Fu, M., Moskowitz, J., & Haritatos, J. (2019) · JMIR mHealth and uHealth · doi:10.2196/15018 · Cited by 265 · see citing works
Chaix, B., Bibault, J.-E., Pienkowski, A., Delamon, G., Guillemassé, A., Nectoux, P., & Brouard, B. (2019) · JMIR Cancer · doi:10.2196/12856 · Cited by 227 · see citing works
Automated interventions for multiple health behaviors using conversational agents
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Bibault, J., Chaix, B., Guillemassé, A., Cousin, S., Escande, A., Perrin, M., Pienkowski, A., Delamon, G., Nectoux, P., & Brouard, B. (2019) · Journal of Medical Internet Research · doi:10.2196/15787 · Cited by 198 · see citing works
Conversational Agents: Goals, Technologies, Vision and Challenges
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AI Chatbot Design during an Epidemic like the Novel Coronavirus
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Security Implications of AI Chatbots in Health Care
Li, J. (2023) · Journal of Medical Internet Research · doi:10.2196/47551 · Cited by 148 · see citing works
Applications of large language models in cancer care: current evidence and future perspectives
Iannantuono, G. M., Bracken-Clarke, D., Floudas, C. S., Roselli, M., Gulley, J. L., & Karzai, F. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1268915 · Cited by 115 · see citing works
Görtz, M., Baumgärtner, K., Schmid, T., Muschko, M., Woessner, P., Gerlach, A., Byczkowski, M., Sültmann, H., Duensing, S., & Hohenfellner, M. (2023) · DIGITAL HEALTH · doi:10.1177/20552076231173304 · Cited by 96 · see citing works
Healthcare ex Machina: Are conversational agents ready for prime time in oncology?
Bibault, J.-E., Chaix, B., Nectoux, P., Pienkowski, A., Guillemasé, A., & Brouard, B. (2019) · Clinical and Translational Radiation Oncology · doi:10.1016/j.ctro.2019.04.002 · Cited by 84 · see citing works
Tawfik, E., Ghallab, E., & Moustafa, A. (2023) · BMC Nursing · doi:10.1186/s12912-023-01243-7 · Cited by 82 · see citing works
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The Use of Chatbots in Oncological Care: A Narrative Review
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Contextual Chatbot for Healthcare Purposes (using Deep Learning)
Kandpal, P., Jasnani, K., Raut, R., & Bhorge, S. (2020) · World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4) · doi:10.1109/worlds450073.2020.9210351 · Cited by 70 · see citing works
TensioBot: a chatbot assistant for self-managed in-house blood pressure checking
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AI-enhanced chatbot for improving healthcare usability and accessibility for older adults
Khamaj, A. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.12.090 · Cited by 56 · see citing works
Embodied Conversational Agents for Chronic Diseases: Scoping Review
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A scoping review of consumer needs for cancer information
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Chavez‐Yenter, D., Kimball, K. E., Kohlmann, W. K., Chambers, R. L., Bradshaw, R. L., Espinel, W., Flynn, M. C., Gammon, A., Goldberg, E., Hagerty, K. J., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/29447 · Cited by 43 · see citing works
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Novel Use of Chatbot Technology to Educate Patients Before Breast Biopsy
Chetlen, A., Artrip, R., Drury, B., Arbaiza, A., & Moore, M. (2019) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2019.05.050 · Cited by 28 · see citing works
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Semi-autonomous Conversational Robot to Deal with Problematic Behaviors from People with Dementia
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Artificial intelligence in medicine and the pursuit of environmentally responsible science
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Self-citationHealthcare ex Machina: Are conversational agents ready for prime time? (Preprint)Preprint
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Conversational Agents in Health Care: Scoping Review and Conceptual Analysis (Preprint)
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Siglen, E., Vetti, H. H., Augestad, M., et al. (2023) · doi:10.2196/preprints.46571
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Chavez-Yenter, D., Kimball, K. E., Kohlmann, W., et al. (2021) · doi:10.2196/preprints.29447
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Yang, E.-W., Waldrup, B., & Velazquez-Villarreal, E. I. (2025) · Cancers · doi:10.3390/cancers17172865 · Cited by 7 · see citing works
Li, M., Zhang, J., Zheng, J., Wu, C., Shao, Z., Cheng, L., Yu, H., Xu, L., Zhang, Y., Wang, X., et al. (2025) · Journal of Medical Internet Research · doi:10.2196/78333 · Cited by 2 · see citing works
Self-citationYıldırım, A., Açıkgöz, G., & Kutlu, L. (2026) · Healthcare · doi:10.3390/healthcare14142042 · Cited by 2 · see citing works
Shi, Q., Lou, N., & Xue, C. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1769097 · Cited by 1 · see citing works
Huang, Y., Liang, Q., Lin, Z., Zhang, M., Liu, X., Ding, L., Peng, R., & Yu, R. (2026) · BMJ Open · doi:10.1136/bmjopen-2025-102637
Wang, X., Li, L., Cai, X., Luo, W., Shen, M., Zuo, Y., Zhang, J., Bai, Z., Yao, Y., Zhang, M., et al. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1779200
Self-citationHu, S., 林邠芬, & 林丰兰 (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1850486
ADAPTIC: Adapting Dialog and Pragmatic Traits in Context
Spillner, L., Rockstroh, J., Goerke, P., Jensen, J., Skardelly, S., Winterpacht, L., Wermter, J., Zargham, N., & Malaka, R. (2026) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3816046.3816324
Same, Same But Different? A Cross-Domain Analysis of Chatbot User Interfaces
Rockstroh, J., Spillner, L., Wenig, N., Mildner, T., Zargham, N., & Malaka, R. (2026) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3816046.3816229
Pavão, J., Bastardo, R., Silva, A. G., & Rocha, N. P. (2026) · JMIR Human Factors · doi:10.2196/102911
- Authors
- Li, K., Wu, S., Zhang, Y., Zhu, B., Qi, Z., Hou, S., & Wang, W.
- Affiliations
- First Affiliated Hospital Zhejiang University (CN)
- Corresponding author
- Wang, Wei
- Venue
- Journal of Clinical Nursing
- Publisher
- Wiley
- Published
- 2025-07-14
- Volume
- 35
- Issue
- 10
- Pages
- 4038-4048
- ISSN
- 0962-1067 (ISSN-L)
- 1365-2702
- PMC
- PMC13569306
- OpenAlex
- W4412388442
- Semantic Scholar
- e27bc9b9df48edecfaa12e725ce8855e9d54e130
- Cited by
- 10
- References
- 50
- Citations by year
- 2026: 8 · 2025: 2
- FWCI
- 2.02
- Type
- journal article
- Language
- en
- Open access
- green
- pmc.ncbi.nlm.nih.gov
- Licence
- Locations
- Journal of Clinical Nursing (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- Zhejiang University (HL202402)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- chatbots, artificial intelligence, usability, patient experience, patient engagement, self-management, psychological support, genetic testing, resource-limited settings, nurse-led care
- MeSH terms
- Artificial Intelligence, Communication, Health Education, Humans, Neoplasms, Patient Education as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-23.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-23.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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