Artificial intelligence and patient narratives: A novel approach to assessing hope in patients with cancer

Bozcuk,Hakan Şat; Güzel,Halil Göksel; Arici,Mustafa Özgür; Yildiz,Mustafa; Koçer,Murat; Kiliçtaş,Bilgeşah; Artaç,Mehmet; Karakaya,Gökhan; Coşkun,Hasan Şenol

doi:10.3892/mi.2025.240

Artificial intelligence and patient narratives: A novel approach to assessing hope in patients with cancer

Authors:
- Hakan Şat Bozcuk
- Halil Göksel Güzel
- Mustafa Özgür Arici
- Mustafa Yildiz
- Murat Koçer
- Bilgeşah Kiliçtaş
- Mehmet Artaç
- Gökhan Karakaya
- Hasan Şenol Coşkun
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Affiliations: Department of Medical Oncology, Medical Park Antalya Hospital, Antalya 07160, Turkey, Department of Medical Oncology, SBU Antalya Training and Research Hospital, Antalya 07100, Turkey, Department of Medical Oncology, Necmettin Erbakan University Hospital, Konya 04280, Turkey, Department of Medical Oncology, Vakıf (ASV) Yaşam Hospital, Antalya 07300, Turkey
Published online on: May 7, 2025 https://doi.org/10.3892/mi.2025.240
Article Number: 41
Copyright : © Bozcuk et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

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Abstract

The present study aimed to evaluate the feasibility of patient‑generated text and its interpretation by artificial intelligence (AI) as a valid correlate of hope levels in patients with cancer. For this purpose, four medical centers recruited consecutive patients with cancer and the patients were administered a questionnaire to collect data on patient characteristics and a shortened version of the Adult Trait Hope Scale (s‑ATHS). Additionally, all participants provided written text on their hope levels, which was then analyzed by a deep neural network model. AI predicted hope labels, as well as numerous patient, disease and center features which were then associated with the scores from s‑ATHS using univariate and multivariate gamma regression analyses. The present study comprised 461 patients with cancer, 194 (42.1%) of whom had metastatic disease. Multivariate gamma regression analysis identified three variables independently associated with hope index scores (s‑ATHS): Treatment center (B=‑0.09, Wald=4.77, P=0.029), Eastern Cooperative Oncology Group (ECOG) performance status (B=‑0.09, Wald=47.41, P<0.001) and AI‑predicted hope level (B=0.06, Wald=44.24, P<0.001). The results revealed that cases from one of the centers in the present study, a university hospital located in a different city than the other centers, exhibited higher hope levels. Additionally, a poorer ECOG performance status and lower AI‑predicted hope levels were associated with reduced hope index scores (s‑ATHS). On the whole, the present study demonstrates that AI‑predicted hope levels are associated with hope index scores (s‑ATHS), suggesting that monitoring AI‑predicted hope levels may provide valuable insight in the practice of oncology.

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1	Mardhiyah A, Philip K, Mediani HS and Yosep I: The association between hope and quality of life among adolescents with chronic diseases: A systematic review. Child Health Nurs Res. 26:323–328. 2020.PubMed/NCBI View Article : Google Scholar
2	Rustøen T: Hope and quality of life, two central issues for cancer patients: A theoretical analysis. Cancer Nurs. 18:355–361. 1995.PubMed/NCBI
3	Soleimani MA, Mohammad A, Zarabadi-Pour S, Huak Chan Y, Allen KA and Shamsizadeh M: Factors associated with hope and quality of life in patients with coronary artery disease. J Nurs Res. 30(e200)2022.PubMed/NCBI View Article : Google Scholar
4	Cheavens J: Hope and Depression: Light Through the Shadows. In: Handbook of Hope. Snyder CR (ed). Academic Press, Cambridge, MA, pp321-340, 2000.
5	Corn BW, Feldman DB, Hull JG, O'Rourke MA and Bakitas MA: Dispositional hope as a potential outcome parameter among patients with advanced malignancy: An analysis of the ENABLE database. Cancer. 128:401–409. 2022.PubMed/NCBI View Article : Google Scholar
6	Bunston T, Mings D, Mackie A and Jones D: Facilitating Hopefulness. J Psychosoc Oncol. 13:79–103. 1995.
7	van Baalen CN, Grypdonck M, van Hecke A and Verhaeghe S: Associated factors of hope in cancer patients during treatment: A systematic literature review. J Adv Nurs. 76:1520–1537. 2020.PubMed/NCBI View Article : Google Scholar
8	Oken MM, Creech RH, Tormey DC, Horton J, Davis TE, McFadden ET and Carbone PP: Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 5:649–655. 1982.PubMed/NCBI
9	Snyder CR, Harris C, Anderson JR, Holleran SA, Irving LM, Sigmon ST, Yoshinobu L, Gibb J, Langelle C and Harney P: The will and the ways: Development and validation of an individual-differences measure of hope. J Pers Soc Psychol. 60:570–585. 1991.PubMed/NCBI View Article : Google Scholar
10	Beam AL, Drazen JM, Kohane IS, Leong TY, Manrai AK and Rubin EJ: Artificial intelligence in medicine. N Engl J Med. 388:1220–1221. 2023.PubMed/NCBI View Article : Google Scholar
11	Obayuwana AO, Collins JL, Carter AL, Rao MS, Mathura CC and Wilson SB: Hope index scale: An instrument for the objective assessment of hope. J Natl Med Assoc. 74:761–765. 1982.PubMed/NCBI
12	Herth P: Measuring hope: Development of the Herth Hope Index. J Nurs Scholarsh. 32:309–315. 2000.
13	Anastaisya Z: Text classification in artificial intelligence. InData Labs, 2023. https://indatalabs.com/blog/text-classification-in-artificial-intelligence. Accessed September 21, 2024.
14	Sandoval AM: Text Analytics: The convergence of big data and artificial intelligence. Int J Interact Multimed Artif Intell. 3:57–64. 2016.
15	Pleeging E: Measuring hope: Validity of short versions of four popular hope scales. Qual Quant. 56:4437–4464. 2022.
16	Acharya S: What are RMSE and MAE? A Simple Guide to evaluation metrics. Towards Data Science, 2021. https://towardsdatascience.com/what-are-rmse-and-mae-e405ce230383. Accessed September 21, 2024.
17	Wahl AK, Rustoen T, Lerdal A, Hanestad BR, Knudsen O Jr and Moum T: The Norwegian version of the Herth Hope Index (HHI-N): A psychometric study. Palliat Support Care. 2:255–263. 2004.PubMed/NCBI View Article : Google Scholar
18	Geiser F, Zajackowski K, Conrad R, Imbierowicz K, Wegener I, Herth KA and Urbach AS: The German version of the Herth Hope Index (HHI-D): Development and psychometric properties. Oncol Res Treat. 38:356–360. 2015.PubMed/NCBI View Article : Google Scholar
19	Mystakidou K, Parpa E, Tsilika E, Athanasouli P, Pathiaki M, Galanos A, Pagoropoulou A and Vlahos L: Preparatory grief, psychological distress and hopelessness in advanced cancer patients. Eur J Cancer Care (Engl). 17:145–151. 2008.PubMed/NCBI View Article : Google Scholar
20	Pinquart M and Duberstein PR: Associations of social networks with cancer mortality: A meta-analysis. Crit Rev Oncol Hematol. 75:122–137. 2010.PubMed/NCBI View Article : Google Scholar
21	Cohen MG, Althouse AD, Arnold RM, Bulls HW, White DB, Chu E, Rosenzweig MQ, Smith KJ and Schenker Y: Hope and advance care planning in advanced cancer: Is there a relationship? Cancer. 128:1339–1345. 2022.PubMed/NCBI View Article : Google Scholar
22	de Hond A, van Buchem M, Fanconi C, Roy M, Blayney D, Kant I, Steyerberg E and Hernandez-Boussard T: Predicting depression risk in patients with cancer using multimodal data: Algorithm development study. JMIR Med Inform. 12(e51925)2024.PubMed/NCBI View Article : Google Scholar
23	Haug CJ and Drazen JM: Artificial intelligence and machine learning in clinical medicine, 2023. N Engl J Med. 388:1201–1208. 2023.PubMed/NCBI View Article : Google Scholar
24	Feldman DB and Corn BW: Hope and cancer. Curr Opin Psychol. 49(101506)2023.PubMed/NCBI View Article : Google Scholar
25	Everson SA, Goldberg DE, Kaplan GA, Cohen RD, Pukkala E, Tuomilehto J and Salonen JT: Hopelessness and risk of mortality and incidence of myocardial infarction and cancer. Psychosom Med. 58:113–121. 1996.PubMed/NCBI View Article : Google Scholar
26	Nikoloudi M, Tsilika E, Kostopoulou S and Mystakidou K: Hope and distress symptoms of oncology patients in a palliative care setting. Cureus. 15(e38041)2023.PubMed/NCBI View Article : Google Scholar