{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,28]],"date-time":"2026-06-28T11:54:58Z","timestamp":1782647698984,"version":"3.54.5"},"reference-count":54,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,10,15]],"date-time":"2024-10-15T00:00:00Z","timestamp":1728950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Research Foundation of Korea (NRF) grant","award":["NRF-2022R1F1A1068236"],"award-info":[{"award-number":["NRF-2022R1F1A1068236"]}]},{"name":"Chung-Ang University Research Grants","award":["NRF-2022R1F1A1068236"],"award-info":[{"award-number":["NRF-2022R1F1A1068236"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>There has been a growing emphasis on data across various health-related fields, not just in nursing research, due to the increasing volume of unstructured data in electronic health records (EHRs). Natural Language Processing (NLP) provides a solution by transforming this unstructured data into structured formats, thereby facilitating valuable insights. This methodology paper explores the application of NLP in nursing, using an exemplar case study that analyzes YouTube data to investigate social phenomena among adults living alone. The methodology involves five steps: accessing data through YouTube\u2019s API, data cleaning, preprocessing (tokenization, sentence segmentation, linguistic normalization), sentiment analysis using Python, and topic modeling. This study serves as a comprehensive guide for integrating NLP into nursing research, supplemented with digital content demonstrating each step. For successful implementation, nursing researchers must grasp the fundamental concepts and processes of NLP. The potential of NLP in nursing is significant, particularly in utilizing unstructured textual data from nursing documentation and social media. Its benefits include streamlining nursing documentation, enhancing patient communication, and improving data analysis.<\/jats:p>","DOI":"10.3390\/ijerph21101357","type":"journal-article","created":{"date-parts":[[2024,10,15]],"date-time":"2024-10-15T08:09:08Z","timestamp":1728979748000},"page":"1357","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Exploring Natural Language Processing through an Exemplar Using YouTube"],"prefix":"10.3390","volume":"21","author":[{"given":"Joohyun","family":"Chung","sequence":"first","affiliation":[{"name":"Elaine Marieb College of Nursing, University of Massachusetts Amherst, 224 Skinner Hall, Amherst, MA 01003, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sangmin","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heesook","family":"Son","sequence":"additional","affiliation":[{"name":"Red Cross College of Nursing, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e31038","DOI":"10.2196\/31038","article-title":"Exploring Reasons for Delayed Start-of-Care Nursing Visits in Home Health Care: Algorithm Development and Data Science Study","volume":"4","author":"Zolnoori","year":"2021","journal-title":"JMIR Nurs."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e34681","DOI":"10.2196\/34681","article-title":"Identifying Patients with Hypoglycemia Using Natural Language Processing: Systematic Literature Review","volume":"7","author":"Zheng","year":"2022","journal-title":"JMIR Diabetes"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"104934","DOI":"10.1016\/j.ijmedinf.2022.104934","article-title":"An evaluation of copy and paste events in electronic notes of patients with hospital acquired conditions","volume":"170","author":"Wang","year":"2023","journal-title":"Int. J. Med. Inform."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1016\/j.outlook.2020.12.007","article-title":"Nursing documentation of symptoms is associated with higher risk of emergency department visits and hospitalizations in homecare patients","volume":"69","author":"Topaz","year":"2021","journal-title":"Nurs. Outlook"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1093\/jamia\/ocac023","article-title":"Documentation of hospitalization risk factors in electronic health records (EHRs): A qualitative study with home healthcare clinicians","volume":"29","author":"Hobensack","year":"2022","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Conway, A., Li, J., Rad, M.G., Mafeld, S., and Taati, B. (2024). Automating sedation state assessments using natural language processing. J. Nurs. Scholarsh., early view.","DOI":"10.1111\/jnu.12968"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Van Bulck, L., Turchioe, M.R., Topaz, M., and Song, J. (2024). Exploring the full potential of the electronic health record: The application of natural language processing for clinical practice. Eur. J. Cardiovasc. Nurs., online ahead of print.","DOI":"10.1093\/eurjcn\/zvae091"},{"key":"ref_8","first-page":"81","article-title":"Application of Natural Language Processing to Learn Insights on the Clinician\u2019s Lived Experience of Electronic Health Records","volume":"289","author":"Senathirajah","year":"2022","journal-title":"Stud. Health Technol. Inform."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1177\/02692163221141969","article-title":"The use of natural language processing in palliative care research: A scoping review","volume":"37","author":"Sarmet","year":"2023","journal-title":"Palliat. Med."},{"key":"ref_10","unstructured":"EPIC System (2024, June 10). Natural Language Processing in EHR Software. Available online: https:\/\/www.emrsystems.net\/blog\/natural-language-processing-in-ehr-software\/."},{"key":"ref_11","unstructured":"Healthcare IT News (2024, June 10). Oracle Cerner Adds Generative AI to Its EHR Platforms. Available online: https:\/\/www.healthcareitnews.com\/news\/oracle-cerner-adds-generative-ai-its-ehr-platforms."},{"key":"ref_12","unstructured":"Athenahealth (2024, June 01). Get 3-Hours of Documentation Time Back Per Provider, Weekly. Available online: https:\/\/www.athenahealth.com."},{"key":"ref_13","first-page":"305","article-title":"Using Natural Language Processing on Expert Panel Discussions to Gain Insights for Recruitment, Retention and Intervention Adherence for Online Social Support Interventions on a Stage II\u2013III Clinical Trial Among Hispanic and African American Dementia Caregivers","volume":"316","author":"Odlum","year":"2024","journal-title":"Stud. Health Technol. Inform."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"21","DOI":"10.5334\/egems.237","article-title":"What Can We Learn about Fall Risk Factors from EHR Nursing Notes? A Text Mining Study","volume":"6","author":"Bjarnadottir","year":"2018","journal-title":"EGEMS"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.hrtlng.2022.05.004","article-title":"Factors associated with poor self-management documented in home health care narrative notes for patients with heart failure","volume":"55","author":"Chae","year":"2022","journal-title":"Heart Lung"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Song, J., Topaz, M., Landau, A.Y., Klitzman, R., Shang, J., Stone, P., McDonald, M., and Cohen, B. (2022). Using natural language processing to identify acute care patients who lack advance directives, decisional capacity, and surrogate decision makers. PLoS ONE, 17.","DOI":"10.1371\/journal.pone.0270220"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/j.ijrobp.2021.01.044","article-title":"Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer","volume":"110","author":"Bitterman","year":"2021","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"ref_18","first-page":"1757","article-title":"A scoping review of preprocessing methods for unstructured text data to assess data quality","volume":"7","author":"Nesca","year":"2022","journal-title":"Int. J. Popul. Data Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1080\/0142159X.2024.2316223","article-title":"Twelve tips for Natural Language Processing in medical education program evaluation","volume":"46","author":"Maslej","year":"2024","journal-title":"Med. Teach."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"106517","DOI":"10.1016\/j.dib.2020.106517","article-title":"Enhancing text pre-processing for Swahili language: Datasets for common Swahili stop-words, slangs and typos with equivalent proper words","volume":"33","author":"Masua","year":"2020","journal-title":"Data Brief"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1177\/16094069231214144","article-title":"Natural Language Processing Enhanced Qualitative Methods: An Opportunity to Improve Health Outcomes","volume":"22","author":"Parker","year":"2023","journal-title":"Int. J. Qual. Methods"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.artmed.2018.08.003","article-title":"An architecture of open-source tools to combine textual information extraction, faceted search and information visualisation","volume":"93","author":"Sonntag","year":"2019","journal-title":"Artif. Intell. Med."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Harrison, C.J., and Sidey-Gibbons, C.J. (2021). Machine learning in medicine: A practical introduction to natural language processing. BMC Med. Res. Methodol., 21.","DOI":"10.1186\/s12874-021-01347-1"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1016\/j.jacr.2011.09.010","article-title":"Practical examples of natural language processing in radiology","volume":"8","author":"Lacson","year":"2011","journal-title":"J. Am. Coll. Radiol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1446","DOI":"10.1148\/rg.2021200113","article-title":"Practical Guide to Natural Language Processing for Radiology","volume":"41","author":"Mozayan","year":"2021","journal-title":"Radiographics"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1007\/978-3-030-85292-4_24","article-title":"Natural Language Processing: Practical Applications in Medicine and Investigation of Contextual Autocomplete","volume":"134","author":"Voytovich","year":"2022","journal-title":"Acta Neurochir. Suppl."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1093\/mind\/LIX.236.433","article-title":"Computing machinery and intelligence","volume":"49","author":"Turing","year":"1950","journal-title":"Mind"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zavoral, F. (2010). Communications in Computer and Information Science: 87. Networked Digital Technologies: Second International Conference, NDT 2010, Prague, Czech Republic, 7\u20139 July 2010, Springer.","DOI":"10.1007\/978-3-642-14292-5"},{"key":"ref_29","first-page":"56","article-title":"Chatbots Introduce Conversational User Interfaces","volume":"41","author":"Fichter","year":"2017","journal-title":"Online Search."},{"key":"ref_30","unstructured":"Winograd, T. (1971). Procedures as a Representation for Data in a Computer Program for Understanding Natural Language, Cambridge Massachusetts Institute of Technology. Collection of Jamie and Michael Kassler."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1145\/365153.365168","article-title":"ELIZA\u2014A computer program for the study of natural language communication between man and machine","volume":"9","author":"Weizenbaum","year":"1966","journal-title":"Commun. ACM"},{"key":"ref_32","first-page":"313","article-title":"Building a Large Annotated Corpus of English: The Penn Treebank","volume":"19","author":"Marcus","year":"1993","journal-title":"Comput. Linguist."},{"key":"ref_33","unstructured":"Jurafsky, D., and Martin, J.H. (2009). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, Pearson Prentice Hall. [2nd ed.]. Prentice Hall Series in Artificial Intelligence."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Manning, C.D., Raghavan, P., and Sch\u00fctze, H. (2008). Introduction to Information Retrieval, Cambridge University Press.","DOI":"10.1017\/CBO9780511809071"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1613\/jair.4992","article-title":"A primer on neural network models for natural language processing","volume":"57","author":"Goldberg","year":"2016","journal-title":"J. Artif. Intell. Res."},{"key":"ref_36","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G., and Dean, J. (2013). Distributed Representations of Words and Phrases and their Compositionality. Adv. Neural Inf. Process. Syst., 26."},{"key":"ref_37","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., and Polosukhin, I. (2017, January 4\u20139). Attention Is All You Need. Presented at the 31st International Conference on Neural Information Processing Systems, Long Beach, CA, USA."},{"key":"ref_38","unstructured":"Bahdanau, D., Cho, K., and Bengio, Y. (2014). Neural Machine Translation by Jointly Learning to Align and Translate. arXiv."},{"key":"ref_39","unstructured":"Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv."},{"key":"ref_40","unstructured":"Brown, T.B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., and Askell, A. (2020). Language Models are Few-Shot Learners. arXiv."},{"key":"ref_41","first-page":"120","article-title":"Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity","volume":"23","author":"Fedus","year":"2022","journal-title":"J. Mach. Learn. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1186\/s13018-024-04774-0","article-title":"Preoperative prediction model for risk of readmission after total joint replacement surgery: A random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness","volume":"19","author":"Digumarthi","year":"2024","journal-title":"J. Orthop. Surg. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1111\/hsc.12648","article-title":"Older people living alone in Shanghai: A questionnaire survey of their life experience","volume":"27","author":"Chen","year":"2019","journal-title":"Health Soc. Care Community"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1017\/S0144686X16000374","article-title":"Living arrangement and cognitive decline among older people in Europe","volume":"37","author":"Mazzuco","year":"2017","journal-title":"Ageing Soc."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"667","DOI":"10.21215\/kjfp.2017.7.5.667","article-title":"Health Behaviors and Mental Health of Korean Young Adults from Single Households: Data Analysis from the 5th Korea National Health and Nutrition Examination Survey (2010\u20132012)","volume":"7","author":"Kim","year":"2017","journal-title":"Korean J. Fam. Pract."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1186\/s12955-015-0398-y","article-title":"Factors associated with the life satisfaction amongst the rural elderly in Odisha, India","volume":"13","author":"Banjare","year":"2015","journal-title":"Health Qual. Life Outcomes"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2809","DOI":"10.1007\/s11136-014-0726-4","article-title":"Assessing the validity of single-item life satisfaction measures: Results from three large samples","volume":"23","author":"Cheung","year":"2014","journal-title":"Qual. Life Res."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Kooshiar, H., Yahaya, N., Hamid, T.A., Abu Samah, A., and Sedaghat Jou, V. (2012). Living arrangement and life satisfaction in older Malaysians: The mediating role of social support function. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0043125"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1186\/s12955-018-0947-2","article-title":"Life satisfaction among elderly patients in Nepal: Associations with nutritional and mental well-being","volume":"16","author":"Ghimire","year":"2018","journal-title":"Health Qual. Life Outcomes"},{"key":"ref_50","first-page":"1","article-title":"Life satisfaction across life course transitions","volume":"8","author":"Qu","year":"2015","journal-title":"Aust. Fam. Trends"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2307\/3090242","article-title":"Health in Household Context: Living Arrangements and Health in Late Middle Age","volume":"43","author":"Hughes","year":"2002","journal-title":"J. Health Soc. Behav."},{"key":"ref_52","unstructured":"(2024, June 10). Community Health Promotion Project Guide, Available online: https:\/\/www.health.vic.gov.au\/publications\/community-health-health-promotion-2021-25."},{"key":"ref_53","unstructured":"Thanaki, J. (2017). Python Natural Language Processing: Explore NLP with Machine Learning and Deep Learning Techniques, Packt Publishing."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Lee, R.S.T. (2023). Natural Language Processing: A Textbook with Python Implementations, Springer.","DOI":"10.1007\/978-981-99-1999-4"}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/21\/10\/1357\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:13:24Z","timestamp":1760112804000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/21\/10\/1357"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,15]]},"references-count":54,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["ijerph21101357"],"URL":"https:\/\/doi.org\/10.3390\/ijerph21101357","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,15]]}}}