{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T15:13:59Z","timestamp":1783350839706,"version":"3.54.6"},"reference-count":35,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T00:00:00Z","timestamp":1783123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Current Oncology"],"abstract":"<jats:p>Background: Psychological distress, particularly anxiety and depression, is highly prevalent among cancer patients, and is associated with impaired quality of life, reduced treatment adherence, and increased mortality risk. Standardized screening instruments, such as the Hospital Anxiety and Depression Scale (HADS), are effective, but face implementation barriers in busy oncology outpatient settings. This cross-sectional study investigated whether BERT-based Natural Language Processing (NLP) analysis of brief patient-generated free texts would correlate with HADS scores in a consecutive cohort of cancer outpatients. Material and Methods: A total of 165 consecutive adult cancer outpatients were enrolled at a tertiary oncology center in Turkey. All participants completed the HADS questionnaire and were asked to write freely about their current emotional state in Turkish. Patient-generated texts were analyzed using a pre-trained Turkish BERT model to derive a continuous BERT Sentiment Score (BSS) and a categorical BERT Sentiment Cluster (BSC) via unsupervised hierarchical clustering. Univariate and multivariate linear regression analyses were performed to examine associations between clinical, demographic, and NLP-derived variables and the logarithmically transformed HADS score. Results: The mean total HADS score was 10.46 (range, 0\u201333), consistent with a moderate level of psychological distress. In multivariate analysis, two variables were independently associated with HADS scores: female sex (\u03b2 = 0.20, t = 2.14, p = 0.034), associated with higher HADS scores, and BERT Sentiment Score (BSS) (\u03b2 = \u22120.18, t = \u22122.43, p = 0.016), with higher values corresponding to lower HADS scores. Hierarchical clustering identified two distinct thematic groups: \u2018Coping and Fighting Spirit\u2019 (74%), and \u2018Hope and Negative Feelings\u2019 (26%); however, cluster membership (BSC) was not independently associated with HADS scores (\u03b2 = \u22120.02, p = 0.789). Clinical variables, including cancer stage, diagnosis type, treatment status, and time since diagnosis, also were not independently associated with HADS scores. Conclusions: BERT-based sentiment analysis of brief patient-generated free texts yielded a continuous measure that independently correlated with HADS scores in cancer outpatients, alongside female sex. These findings provide proof-of-concept evidence that NLP-derived sentiment scoring may offer a practical, scalable, and complementary approach to standardized psychological screening in routine oncology care.<\/jats:p>","DOI":"10.3390\/curroncol33070400","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T12:01:37Z","timestamp":1783339297000},"page":"400","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Analysing Emotional Well-Being in Cancer Patients: A Natural Language Processing Approach to Correlating Text with Hospital Anxiety and Depression Scale Scores"],"prefix":"10.3390","volume":"33","author":[{"given":"Mustafa Serkan","family":"Alemdar","sequence":"first","affiliation":[{"name":"Department of Medical Oncology, Istinye University, Istanbul 34396, Turkey"},{"name":"Department of Medical Oncology, Medical Park Hospital, Antalya 07160, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hakan \u015eat","family":"Bozcuk","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology, Lara Anatolia Hospital, Antalya 07230, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,4]]},"reference":[{"key":"ref_1","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/S1470-2045(11)70002-X","article-title":"Prevalence of depression, anxiety, and adjustment disorder in oncological, haematological, and palliative-care settings: A meta-analysis of 94 interview-based studies","volume":"12","author":"Mitchell","year":"2011","journal-title":"Lancet Oncol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1002\/pon.3409","article-title":"Prevalence of depression in cancer patients: A meta-analysis of diagnostic interviews and self-report instruments","volume":"23","author":"Krebber","year":"2014","journal-title":"Psychooncology"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3540","DOI":"10.1200\/JCO.2014.56.0086","article-title":"Four-week prevalence of mental disorders in patients with cancer across major tumor entities","volume":"32","author":"Mehnert","year":"2014","journal-title":"J. Clin. Oncol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.jad.2012.03.025","article-title":"Anxiety and depression after cancer diagnosis: Prevalence rates by cancer type, gender, and age","volume":"141","author":"Linden","year":"2012","journal-title":"J. Affect. Disord."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e70077","DOI":"10.1002\/pon.70077","article-title":"Global Prevalence of Mental Health Problems Among Cancer Survivors: A Meta-Analysis From 31 Countries","volume":"34","author":"Ge","year":"2025","journal-title":"Psychooncology"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Getie, A., Ayalneh, M., and Bimerew, M. (2025). Global prevalence and determinant factors of pain, depression, and anxiety among cancer patients: An umbrella review of systematic reviews and meta-analyses. BMC Psychiatry, 25.","DOI":"10.1186\/s12888-025-06599-5"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1797","DOI":"10.1017\/S0033291709992285","article-title":"Depression and cancer mortality: A meta-analysis","volume":"40","author":"Pinquart","year":"2010","journal-title":"Psychol. Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2101","DOI":"10.1001\/archinte.160.14.2101","article-title":"Depression is a risk factor for noncompliance with medical treatment: Meta-analysis of the effects of anxiety and depression on patient adherence","volume":"160","author":"DiMatteo","year":"2000","journal-title":"Arch. Intern. Med."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/S0022-3999(00)00080-5","article-title":"Anxiety and depression in cancer patients: Relation between the Hospital Anxiety and Depression Scale and the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire","volume":"49","author":"Skarstein","year":"2000","journal-title":"J. Psychosom. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"k1415","DOI":"10.1136\/bmj.k1415","article-title":"Depression and anxiety in patients with cancer","volume":"361","author":"Pitman","year":"2018","journal-title":"BMJ"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"101155","DOI":"10.1016\/j.esmoop.2023.101155","article-title":"Anxiety and depression in adult cancer patients: ESMO Clinical Practice Guideline","volume":"8","author":"Grassi","year":"2023","journal-title":"ESMO Open"},{"key":"ref_13","unstructured":"National Comprehensive Cancer Network (2026). NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines\u00ae): Distress Management; Version 2.2026, National Comprehensive Cancer Network."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1111\/j.1600-0447.1983.tb09716.x","article-title":"The hospital anxiety and depression scale","volume":"67","author":"Zigmond","year":"1983","journal-title":"Acta Psychiatr. Scand."},{"key":"ref_15","first-page":"280","article-title":"Reliability and Validity of the Turkish version of Hospital Anxiety and Depression Scale","volume":"8","author":"Aydemir","year":"1997","journal-title":"Turk. J. Psychiatry"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/S0959-8049(05)80015-2","article-title":"Screening for anxiety and depression in cancer patients: The effects of disease and treatment","volume":"30","author":"Ibbotson","year":"1994","journal-title":"Eur. J. Cancer"},{"key":"ref_17","unstructured":"Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2019). BERT: Pre-Training of Deep Bidirectional Transformers for Language Understanding, Association for Computational Linguistics."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Pires, T., Schlinger, E., and Garrette, D. (2019). How Multilingual is Multilingual BERT?, Association for Computational Linguistics.","DOI":"10.18653\/v1\/P19-1493"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2255","DOI":"10.1093\/jamia\/ocae188","article-title":"Applying natural language processing to patient messages to identify depression concerns in cancer patients","volume":"31","author":"Fanconi","year":"2024","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e51925","DOI":"10.2196\/51925","article-title":"Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study","volume":"12","author":"Fanconi","year":"2024","journal-title":"JMIR Med. Inform."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1038\/s43856-024-00495-x","article-title":"Predicting which patients with cancer will see a psychiatrist or counsellor from their initial oncology consultation document using natural language processing","volume":"4","author":"Nunez","year":"2024","journal-title":"Commun. Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e2511922","DOI":"10.1001\/jamanetworkopen.2025.11922","article-title":"Large Language Models and Text Embeddings for Detecting Depression and Suicide in Patient Narratives","volume":"8","author":"Lho","year":"2025","journal-title":"JAMA Netw. Open"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1038\/s41746-025-01969-5","article-title":"Optimizing large language models for detecting symptoms of depression\/anxiety in chronic diseases patient communications","volume":"8","author":"Kim","year":"2025","journal-title":"NPJ Digit. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1390","DOI":"10.1093\/jamia\/ocaf072","article-title":"Large language models for identifying depression concerns in cancer patients","volume":"32","author":"Wang","year":"2025","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/S0022-3999(01)00296-3","article-title":"The validity of the Hospital Anxiety and Depression Scale. An updated literature review","volume":"52","author":"Bjelland","year":"2002","journal-title":"J. Psychosom. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/S0022-3999(96)00216-4","article-title":"International experiences with the Hospital Anxiety and Depression Scale-A review of validation data and clinical results","volume":"42","author":"Herrmann","year":"1997","journal-title":"J. Psychosom. Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/S2215-0366(14)70313-X","article-title":"Prevalence, associations, and adequacy of treatment of major depression in patients with cancer: A cross-sectional analysis of routinely collected clinical data","volume":"1","author":"Walker","year":"2014","journal-title":"Lancet Psychiatry"},{"key":"ref_28","first-page":"214","article-title":"Psychosocial interventions for anxiety and depression in adult cancer patients: Achievements and challenges","volume":"58","author":"Jacobsen","year":"2008","journal-title":"CA Cancer J. Clin."},{"key":"ref_29","first-page":"e88902","article-title":"Sentiment Analysis in Healthcare: A Comparison of VADER, BERT, and Flair NLP Models on Patient Reviews of Pain Management Physicians","volume":"17","author":"Aggarwal","year":"2025","journal-title":"Cureus"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3137","DOI":"10.1200\/JCO.2002.08.549","article-title":"Anxiety disorders in cancer patients: Their nature, associations, and relation to quality of life","volume":"20","author":"Stark","year":"2002","journal-title":"J. Clin. Oncol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Vitale, E., Halemani, K., Shetty, A., Chang, Y.C., Hu, W.Y., Massafra, R., and Moretti, A. (2024). Sex Differences in Anxiety and Depression Conditions among Cancer Patients: A Systematic Review and Meta-Analysis. Cancers, 16.","DOI":"10.3390\/cancers16111969"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Seiler, A., and Jenewein, J. (2019). Resilience in Cancer Patients. Front. Psychiatry, 10.","DOI":"10.3389\/fpsyt.2019.00208"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"8599","DOI":"10.1038\/s41598-025-93008-2","article-title":"Resilience as a mediator of quality of life in cancer patients in healthcare services","volume":"15","author":"Caldiroli","year":"2025","journal-title":"Sci. Rep."},{"key":"ref_34","first-page":"e70415","article-title":"Psychological Resilience and Associated Factors in Cancer Patients: A Cross-Sectional Analysis","volume":"9","year":"2026","journal-title":"Cancer Rep."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"e82336","DOI":"10.2196\/82336","article-title":"Empathic AI for Patient-Centered Cancer Care: A Scoping Review of Patient Navigation, Support, and Clinical Practice","volume":"12","author":"White","year":"2026","journal-title":"JMIR Cancer"}],"container-title":["Current Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1718-7729\/33\/7\/400\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T14:14:53Z","timestamp":1783347293000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1718-7729\/33\/7\/400"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,4]]},"references-count":35,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["curroncol33070400"],"URL":"https:\/\/doi.org\/10.3390\/curroncol33070400","relation":{},"ISSN":["1718-7729"],"issn-type":[{"value":"1718-7729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,4]]}}}