The Effectiveness and Feasibility of Conversational Agents in Supporting Care for Patients With Cancer: Systematic Review and Meta-Analysis
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Abstract
Background: Patients with cancer experience complex physical, psychosocial, and behavioral challenges that require continuous support. This need has intensified with the rising cancer burden worldwide and the limited scalability of traditional care models. In response, conversational agents (CAs) have emerged as promising digital interventions for enhancing cancer care, but evidence regarding their feasibility and effectiveness remains limited. Objective: This study aimed to evaluate the feasibility and effectiveness of CAs in supporting care for patients with cancer and to summarize the key characteristics of CA interventions to inform future design and implementation. Methods: We systematically searched PubMed, Cochrane Library, Web of Science, and Embase databases from the index date through February 3, 2025, and screened reference lists and trial registries for gray literature. Eligible studies included randomized controlled trials (RCTs) and nonrandomized interventions (NRIs) evaluating CA-delivered interventions targeting health outcomes in patients with cancer. Two reviewers independently selected studies and extracted data. Study quality was then appraised using the Cochrane Risk of Bias 2.0 tool for RCTs and the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for NRIs. Extracted data included study characteristics, CA features, and implementation outcomes, including feasibility, acceptability, and usability. Meta-analyses were conducted on physical activity, pain, anxiety, depression, psychological distress, and quality of life. Narrative synthesis was used for outcomes with inconsistent reporting across studies, including health information acquisition and treatment-related side effects. Results: In total, 17 studies involving 1817 patients with cancer were included, with 10 (58.8%) studies being included in the meta-analysis. The meta-analysis showed significant improvements in physical activity (mean difference [MD]=1.44, 95% CI 0.36-2.52, P<.01), pain (MD=–0.91, 95% CI –1.44 to –0.38, P<.01), anxiety (SMD=–0.19, 95% CI –0.35 to –0.02, P=.02), and quality of life (SMD=0.35, 95% CI 0.03-0.67, P=.03). No significant effects were observed on depression (SMD=–0.07, 95% CI –0.42 to 0.27, P=.68) or psychological distress (SMD=–0.33, 95% CI –0.66 to 0.01, P=.06). Narrative synthesis suggested that CAs have the potential to improve patients’ acquisition of health information and help manage treatment-related side effects. Notably, CAs were generally found to be safe, feasible, acceptable, and usable among patients with cancer, particularly during the initial phase of use. However, user engagement tended to decline over time, underscoring the need for strategies to sustain long-term use. Conclusions: This systematic review is the first comprehensive analysis to suggest that CAs are feasible, acceptable, usable, and effective interventions for patients with cancer. Nevertheless, the limited psychological benefits and suboptimal long-term user engagement indicate the need for further refinement. Future research should adopt theory-based designs and leverage emerging technologies to enhance personalization, empathy, and sustained engagement in CA interventions. Robust evidence from large-scale RCTs is needed to strengthen the evidence base. Trial Registration: PROSPERO CRD42025645982; https://www.crd.york.ac.uk/PROSPERO/view/CRD42025645982
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A systematic review and meta-analysis of 17 studies involving 1817 participants examined conversational agents across cancer care and identified heterogeneity in interventions, outcomes, and implementation.
“A systematic review and meta-analysis of 17 studies involving 1817 participants examined conversational agents across cancer care and identified heterogeneity in interventions, outcomes, and implementation”
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Cites
The PRISMA 2020 statement: An updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n71 · Cited by 108,283 · see citing works
RoB 2: a revised tool for assessing risk of bias in randomised trials
Sterne, J. A. C., Savović, J., Page, M. J., Elbers, R. G., Blencowe, N. S., Boutron, I., Cates, C. J., Cheng, H.-Y., Corbett, M. S., Eldridge, S. M., et al. (2019) · BMJ · doi:10.1136/bmj.l4898 · Cited by 33,583 · see citing works
Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., & Jemal, A. (2024) · CA: a cancer journal for clinicians · doi:10.3322/caac.21834 · Cited by 27,064 · 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 · cited 3× · see citing works
“CAs are dialogue systems capable of understanding and generating human language to enable effective human-computer interactions [7].”
InfluentialEstablishing and maintaining long-term human-computer relationships
Bickmore, T. W., & Picard, R. W. (2005) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1067860.1067867 · Cited by 1,333 · cited 1× · see citing works
“As a result, they are unable to recognize complex psychological states, respond empathetically, or support deep emotional regulation [40].”
Chatbots: History, technology, and applications
Adamopoulou, E., & Moussiades, L. (2020) · Machine Learning with Applications · doi:10.1016/j.mlwa.2020.100006 · Cited by 1,090 · see citing works
Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review.
Aggarwal, A., Tam, C. C., Wu, D., Li, X., & Qiao, S. (2023) · Journal of medical Internet research · doi:10.2196/40789 · Cited by 683 · cited 1× · see citing works
“This trend is consistent with findings from prior CA interventions in chronic disease management, where high attrition rates were commonly reported despite favorable early-phase implementation outcomes [43,44].”
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
Maguire, R., McCann, L., Kotronoulas, G., Kearney, N., Ream, E., Armes, J., Patiraki, E., Furlong, E., Fox, P., Gaiger, A., et al. (2021) · BMJ · doi:10.1136/bmj.n1647 · Cited by 243 · see citing works
Health dialog systems for patients and consumers
Bickmore, T., & Giorgino, T. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2005.12.004 · Cited by 242 · see citing works
Chatbot features for anxiety and depression: a scoping review
Ahmed, A., Hassan, A., Aziz, S., Abd-alrazaq, A. A., Ali, N., Alzubaidi, M., Al-Thani, D., Elhusein, B., Siddig, M. A., Ahmed, M., et al. (2023) · Health Informatics Journal · doi:10.1177/14604582221146719 · Cited by 82 · see citing works
The Use of Chatbots in Oncological Care: A Narrative Review
Wang, A., Qian, Z., Briggs, L., Cole, A. P., Reis, L. O., & Trinh, Q.-D. (2023) · International Journal of General Medicine · doi:10.2147/ijgm.s408208 · Cited by 73 · see citing works
Chatbots in cancer applications, advantages and disadvantages: all that glitters is not gold
Goumas, G., Dardavesis, T. I., Syrigos, K., Syrigos, N., & Simou, E. (2024) · Journal of Personalized Medicine · doi:10.3390/jpm14080877 · Cited by 24 · see citing works
Flagged first, then by citations
Research works printed but not linked: 36
- [2]Williams K Jackson SE Beeken RJ Steptoe A Wardle J The impact of a cancer diagnosis on health and well-being: a prospective, population-based study Psychooncology 2016 07 25 6 626 632 10.1002/pon.3998 26425927 26425927 PMC4915489 · DOI
- [3]Barlow J Wright C Sheasby J Turner A Hainsworth J Self-management approaches for people with chronic conditions: a review Patient Educ Couns 2002 48 2 177 187 10.1016/s0738-3991(02)00032-0 12401421 S0738399102000320 12401421 · DOI · Paper page
- [4]Rimmer B Brown MC Sotire T Beyer F Bolnykh I Balla M Richmond C Dutton L Williams S Araújo-Soares V Finch T Gallagher P Lewis J Burns R Sharp L Characteristics and components of self-management interventions for improving quality of life in cancer survivors: a systematic review Cancers (Basel) 2023 12 19 16 1 14 10.3390/cancers16010014 38201442 cancers16010014 38201442 PMC10777971 · DOI
- [5]Lee K Kim S Kim SH Yoo S Sung JH Oh EG Kim N Lee J Digital health interventions for adult patients with cancer evaluated in randomized controlled trials: scoping review J Med Internet Res 2023 01 06 25 e38333 10.2196/38333 36607712 v25i1e38333 36607712 PMC9862347 · DOI
- [6]Baumgärtner K Byczkowski M Schmid T Muschko M Woessner P Gerlach A Bonekamp D Schlemmer H Hohenfellner M Görtz M Effectiveness of the medical chatbot PROSCA to inform patients about prostate cancer: results of a randomized controlled trial Eur Urol Open Sci 2024 12 69 80 88 10.1016/j.euros.2024.08.022 39329071 S2666-1683(24)00655-4 39329071 PMC11424957 · DOI
- [8]Tudor Car L Dhinagaran DA Kyaw BM Kowatsch T Joty S Theng Y Atun R Conversational agents in health care: scoping review and conceptual analysis J Med Internet Res 2020 08 07 22 8 e17158 10.2196/17158 32763886 v22i8e17158 32763886 PMC7442948 · DOI · Paper page
- [11]Tawfik E Ghallab E Moustafa A A nurse versus a chatbot ‒ the effect of an empowerment program on chemotherapy-related side effects and the self-care behaviors of women living with breast cancer: a randomized controlled trial BMC Nurs 2023 05 06 22 1 102 10.1186/s12912-023-01243-7 37024875 10.1186/s12912-023-01243-7 37024875 PMC10077642 · DOI · Paper page
- [13]MacNeill AL MacNeill L Luke A Doucet S Health professionals' views on the use of conversational agents for health care: qualitative descriptive study J Med Internet Res 2024 10 25 26 e49387 10.2196/49387 39320936 v26i1e49387 39320936 PMC11464950 · DOI
- [14]Chen X Xiang J Lu S Liu Y He M Shi D Evaluating large language models and agents in healthcare: key challenges in clinical applications Intell Med 2025 05 5 2 151 163 10.1016/j.imed.2025.03.002 · DOI
- [17]Barker TH Habibi N Aromataris E Stone JC Leonardi-Bee J Sears K Hasanoff S Klugar M Tufanaru C Moola S Munn Z The revised JBI critical appraisal tool for the assessment of risk of bias for quasi-experimental studies JBI Evid Synth 2024 03 01 22 3 378 388 10.11124/JBIES-23-00268 38287725 02174543-202403000-00004 38287725 · DOI · Paper page
- [18]Higgins JPT Thomas J Chandler J Cumpston M Li T Page MJ Welch VA Cochrane Handbook for Systematic Reviews of Interventions 2019 Chichester, UK John Wiley & Sons PMC10284251 31643080
- [19]Higgins JPT Thompson SG Deeks JJ Altman DG Measuring inconsistency in meta-analyses BMJ 2003 10 06 327 7414 557 560 10.1136/bmj.327.7414.557 12958120 327/7414/557 12958120 PMC192859 · DOI · Paper page
- [20]Schmitz KH Kanski B Gordon B Caru M Vasakar M Truica CI Wang M Doerksen S Lorenzo A Winkels R Qiu L Abdullah S Technology-based supportive care for metastatic breast cancer patients Support Care Cancer 2023 07 20 31 7 401 10.1007/s00520-023-07884-3 37338627 10.1007/s00520-023-07884-3 37338627 · DOI
- [21]Sikorskii A Given CW Given BA Vachon E Krauss JC Rosenzweig M McCorkle R Champion VL Banik A Majumder A An automated intervention did not improve adherence to oral oncolytic agents while managing symptoms: results from a two-arm randomized controlled trial J Pain Symptom Manage 2018 12 56 5 727 735 10.1016/j.jpainsymman.2018.07.021 30096441 S0885-3924(18)30395-6 30096441 PMC7646373 · DOI
- [22]Hassoon A Baig Y Naiman DQ Celentano DD Lansey D Stearns V Coresh J Schrack J Martin SS Yeh H Zeilberger H Appel LJ Randomized trial of two artificial intelligence coaching interventions to increase physical activity in cancer survivors NPJ Digit Med 2021 12 09 4 1 168 10.1038/s41746-021-00539-9 34887491 10.1038/s41746-021-00539-9 34887491 PMC8660785 · DOI
- [24]Lee J Byun HK Kim YT Shin J Kim YB A study on breast cancer patient care using chatbot and video education for radiation therapy: a randomized controlled trial Int J Radiat Oncol Biol Phys 2025 05 01 122 1 84 92 10.1016/j.ijrobp.2024.12.012 39732344 S0360-3016(24)03732-5 39732344 · DOI
- [25]Horesh D Kohavi S Shilony-Nalaboff L Rudich N Greenman D Feuerstein JS Abbasi MR Virtual reality combined with artificial intelligence (VR-AI) reduces hot flashes and improves psychological well-being in women with breast and ovarian cancer: a pilot study Healthcare (Basel) 2022 12 11 10 11 2261 10.3390/healthcare10112261 36421585 healthcare10112261 36421585 PMC9690775 · DOI
- [26]Mlakar I Lin S Aleksandraviča I Arcimoviča K Eglītis J Leja M Salgado Barreira Á Gómez JG Salgado M Mata JG Batorek D Horvat M Molan M Ravnik M Kaux J Bleret V Loly C Maquet D Sartini E Smrke U Patients-centered SurvivorShIp care plan after cancer treatments based on big data and artificial intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors BMC Med Inform Decis Mak 2021 08 14 21 1 243 10.1186/s12911-021-01603-w 34391413 10.1186/s12911-021-01603-w 34391413 PMC8364016 · DOI
- [28]Bibault J Chaix B Guillemassé A Cousin S Escande A Perrin M Pienkowski A Delamon G Nectoux P Brouard B A chatbot versus physicians to provide information for patients with breast cancer: blind, randomized controlled noninferiority trial J Med Internet Res 2019 12 27 21 11 e15787 10.2196/15787 31774408 v21i11e15787 31774408 PMC6906616 · DOI
- [29]Al-Hilli Z Noss R Dickard J Wei W Chichura A Wu V Renicker K Pederson HJ Eng C A randomized trial comparing the effectiveness of pre-test genetic counseling using an artificial intelligence automated chatbot and traditional in-person genetic counseling in women newly diagnosed with breast cancer Ann Surg Oncol 2023 10 30 10 5990 5996 10.1245/s10434-023-13888-4 37567976 10.1245/s10434-023-13888-4 37567976 · DOI · Paper page
- [30]Kamdar M Jethwani K Centi AJ Agboola S Fischer N Traeger L Rinaldi S Strand J Ritchie C Temel JS Greer JA Kvedar J El-Jawarhi A Jackson V A digital therapeutic application (ePAL) to manage pain in patients with advanced cancer: a randomized controlled trial J Pain Symptom Manage 2024 10 68 3 261 271 10.1016/j.jpainsymman.2024.05.033 38866116 S0885-3924(24)00800-5 38866116 · DOI
- [31]Albino de Queiroz D Silva Passarello R Veloso de Moura Fé V Rossini A Folchini da Silveira E Aparecida Isquierdo Fonseca de Queiroz E André da Costa C A wearable chatbot-based model for monitoring colorectal cancer patients in the active phase of treatment Healthcare Anal 2023 12 4 100257 10.1016/j.health.2023.100257 · DOI
- [32]Bickmore TW Utami D Matsuyama R Paasche-Orlow MK Improving access to online health information with conversational agents: a randomized controlled experiment J Med Internet Res 2016 01 04 18 1 e1 10.2196/jmir.5239 26728964 v18i1e1 26728964 PMC4717285 · DOI · Paper page
- [33]Gomaa S Posey J Bashir B Basu Mallick A Vanderklok E Schnoll M Zhan T Wen K Feasibility of a text messaging-integrated and chatbot-interfaced self-management program for symptom control in patients with gastrointestinal cancer undergoing chemotherapy: pilot mixed methods study JMIR Form Res 2023 12 10 7 e46128 10.2196/46128 37948108 v7i1e46128 37948108 PMC10674151 · DOI
- [34]Caru M Abdullah S Qiu L Kanski B Gordon B Truica CI Vasakar M Doerksen S Schmitz KH Women with metastatic breast cancer don't just follow step-count trends, they exceed them: an exploratory study Breast Cancer Res Treat 2023 07 200 2 265 270 10.1007/s10549-023-06980-6 37227610 10.1007/s10549-023-06980-6 37227610 PMC10208908 · DOI
- [35]Noh E Won J Jo S Hahm D Lee H Conversational agents for body weight management: systematic review J Med Internet Res 2023 05 26 25 e42238 10.2196/42238 37234029 v25i1e42238 37234029 PMC10257112 · DOI
- [36]Wu Y Zhang J Ge P Duan T Zhou J Wu Y Zhang Y Liu S Liu X Wan E Sun X Application of chatbots to help patients self-manage diabetes: systematic review and meta-analysis J Med Internet Res 2024 12 03 26 e60380 10.2196/60380 39626235 v26i1e60380 39626235 PMC11653048 · DOI
- [37]Yang Q Cheung K Zhang Y Zhang Y Qin J Xie YJ Conversational agents in physical and psychological symptom management: a systematic review of randomized controlled trials Int J Nurs Stud 2025 03 163 104991 10.1016/j.ijnurstu.2024.104991 39799832 S0020-7489(24)00304-3 39799832 · DOI
- [38]Oh YJ Zhang J Fang M Fukuoka Y A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss Int J Behav Nutr Phys Act 2021 12 11 18 1 160 10.1186/s12966-021-01224-6 34895247 10.1186/s12966-021-01224-6 34895247 PMC8665320 · DOI · Paper page
- [41]Chen D Chauhan K Parsa R Liu ZA Liu F Mak E Eng L Hannon BL Croke J Hope A Fallah-Rad N Wong P Raman S Patient perceptions of empathy in physician and artificial intelligence chatbot responses to patient questions about cancer NPJ Digit Med 2025 07 21 8 1 275 10.1038/s41746-025-01793-x 40544179 10.1038/s41746-025-01793-x 40360673 PMC12075825 · DOI
- [42]Wutz M Hermes M Winter V Köberlein-Neu J Factors influencing the acceptability, acceptance, and adoption of conversational agents in health care: integrative review J Med Internet Res 2023 10 26 25 e46548 10.2196/46548 37751279 v25i1e46548 37751279 PMC10565637 · DOI
- [44]Jabir AI Lin X Martinengo L Sharp G Theng Y Tudor Car L Attrition in conversational agent-delivered mental health interventions: systematic review and meta-analysis J Med Internet Res 2024 03 27 26 e48168 10.2196/48168 38412023 v26i1e48168 38412023 PMC10933752 · DOI
- [45]Yu K Gorbachev G Eck U Pankratz F Navab N Roth D Avatars for teleconsultation: effects of avatar embodiment techniques on user perception in 3D asymmetric telepresence IEEE Trans Vis Comput Graph 2021 12 27 11 4129 4139 10.1109/TVCG.2021.3106480 34449373 34449373 · DOI
- [47]Martinengo L Jabir AI Goh WWT Lo NYW Ho MR Kowatsch T Atun R Michie S Tudor Car L Conversational agents in health care: scoping review of their behavior change techniques and underpinning theory J Med Internet Res 2022 10 03 24 10 e39243 10.2196/39243 36190749 v24i10e39243 36190749 PMC9577715 · DOI
- [48]Sun X de WJ Li Z Pei J El AA Bosch J Script-strategy aligned generation: aligning LLMs with expert-crafted dialogue scripts and therapeutic strategies for psychotherapy 2025-07-31 https://arxiv.org/abs/2411.06723 · arXiv
- [49]Tumuhimbise W Theuring S Kaggwa F Atukunda EC Rubaihayo J Atwine D Sekandi JN Musiimenta A Enhancing the implementation and integration of mHealth interventions in resource-limited settings: a scoping review Implement Sci 2024 10 14 19 1 72 10.1186/s13012-024-01400-9 39402567 10.1186/s13012-024-01400-9 39402567 PMC11476919 · DOI
Cited by
Sorted by citations
Shen, Z., Shi, S., Mao, L., Li, C., & Xie, J. (2026) · Journal of Medical Internet Research · doi:10.2196/105599
- Authors
- Jiang, X.-H., Yuan, X.-H., Zhao, H., & Peng, J.-S.
- Affiliations
- Sun Yat-sen University (CN)
- Sun Yat-sen University Cancer Center (CN)
- Corresponding author
- Jiang, Xiao-han
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2025-08-08
- Volume
- 27
- Pages
- e76968
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC12374140
- OpenAlex
- W4412750116
- Cited by
- 10
- References
- 13
- Citations by year
- 2026: 9 · 2025: 1
- FWCI
- 1.16
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Oncology › Cancer survivorship and care
- Keywords
- chatbots, cancer patients, digital health interventions, feasibility, acceptability, usability, physical activity, pain, anxiety, depression, psychological distress, quality of life, treatment side effects, health information acquisition, implementation outcomes, patient support, virtual assistants, mobile health apps, telemedicine, patient-reported outcomes, implementation research, implementation fidelity
- MeSH terms
- Communication, Feasibility Studies, Humans, Neoplasms, Palliative Care, Quality of Life
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