Kontakt 2018, 20(3):e210-e216 | DOI: 10.1016/j.kontakt.2018.03.002

Use of the Omaha System for ontology-based text mining to discover meaning within CaringBridge social media journalsNursing - Original article

Karen A. Monsena,*, Sasank Magantib, Robert A. Giaquintob, Michelle A. Mathiasona, Ragnhildur I. Bjarnadottirc, Mary Jo Kreitzerd
a University of Minnesota, School of Nursing, Minneapolis, USA
b University of Minnesota, Computer Science and Engineering, Minneapolis, USA
c University of Florida, College of Nursing, Gainesville, Florida, USA
d University of Minnesota, Earl E. Bakken Center for Spirituality and Healing, Minneapolis, USA

Objectives: The goals of this study were to examine the feasibility of using ontology-based text mining with CaringBridge social media journal entries in order to understand journal content from a whole-person perspective. Specific aims were to describe Omaha System problem concept frequencies in the journal entries over a four-step process overall, and relative to Omaha System Domains; and to examine the four step method including the use of standardized terms and related words.

Design: Ontology-based retrospective observational feasibility study using text mining methods.
Sample: A corpus of social media text consisting of 13,757,900 CaringBridge journal entries from June 2006 to June 2016.
Measures: The Omaha System terms, including problems and signs/symptoms, were used as the foundational lexicon for this study. Development of an extended lexicon with related words for each problem concept expanded the semantics-powered data analytics approach to reflect consumer word choices.

Results: All Omaha System problem concepts were identified in the journal entries, with consistent representation across domains. The approach was most successful when common words were used to represent clinical terms. Preliminary validation of journal examples showed appropriate representation of the problem concepts.

Conclusions: This is the first study to evaluate the feasibility of using an interface terminology and ontology (the Omaha System) as a text mining information model. Further research is needed to systematically validate these findings, refine the process as needed to advance the study of CaringBridge content, and extend the use of this method to other consumer-generated journal entries and terminologies.

Keywords: Text mining; Social media; Ontology; Omaha System; CaringBridge; Terminology

Received: November 15, 2017; Revised: January 31, 2018; Accepted: March 6, 2018; Published: October 12, 2018  Show citation

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Monsen KA, Maganti S, Giaquinto RA, Mathiason MA, Bjarnadottir RI, Jo Kreitzer M. Use of the Omaha System for ontology-based text mining to discover meaning within CaringBridge social media journals. Kontakt. 2018;20(3):e210-216. doi: 10.1016/j.kontakt.2018.03.002.
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    References

    1. Beaudoin CE, Tao CC. Benefiting from social capital in online support groups: an empirical study of cancer patients. Cyber Psychol Behav 2007;10(4):587-90. Go to original source... Go to PubMed...
    2. Rodgers S, Chen Q. Internet community group participation: Psychosocial benefits for women with breast cancer. Journal of Computer-Mediated Communication 2005;10(4):1-27. Go to original source...
    3. Wen KY, McTavish F, Kreps G, Wise M, Gustafson D. From diagnosis to death: a case study of coping with breast cancer as seen through online discussion group messages. J Comput Mediat Commun 2011;16(2): 331-61. Go to original source... Go to PubMed...
    4. Balatsoukas P, Kennedy CM, Buchan I, Powell J, Ainsworth J. The role of social network technologies in online health promotion: a narrative review of theoretical and empirical factors influencing intervention effectiveness. J Med Internet Res 2015;17(6):e141. Go to original source... Go to PubMed...
    5. Masic I, Sivic S, Toromanovic S, Borojevic T, Pandza H. Social networks in improvement of health care. Mater Sociomed 2012;24(1):48-53. Go to original source... Go to PubMed...
    6. Berkman LF. Social support, social networks, social cohesion and health. Soc Work Health Care 2000;31(2):3-14. Go to original source... Go to PubMed...
    7. Harpaz R, Callahan A, Tamang S, Low Y, Odgers D, Finlayson S, et al. Text mining for adverse drug events: the promise, challenges, and state of the art. Drug Saf 2014;37(10):777-90. Go to original source... Go to PubMed...
    8. Bakken S, Hyun S, Friedman C, Johnson SB. ISO reference terminology models for nursing: applicability for natural language processing of nursing narratives. Int J Med Inform 2005;74(7):615-22. Go to original source... Go to PubMed...
    9. Feng D, Burns G, Hovy E. Extracting data records from unstructured biomedical full text. In: Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, June 28-30, 2007, Prague, Czech Republic, 2007, pp. 837-46.
    10. McEwan R, Melton GB, Knoll BC, Wang Y, Hultman G, Dale JL, et al. NLP-PIER: a scalable natural language processing, indexing, and searching architecture for clinical notes. AMIA Jt Summits Transl Sci Proc 2016;2016:150-9.
    11. Shashirekha HL, Murali S. Ontology based structured representation for domain specific unstructured documents. In: Proceedings of the Conference on Computational Intelligence and Multimedia Applications 2007; pp. 50-4. Go to original source...
    12. Wen M, Rosé CP. Understanding participant behaviour trajectories in online health support groups using automatic extraction methods. In: Proceedings of the 17th ACM international conference on supporting group work 2012, Oct 27; pp. 179-88. Go to original source...
    13. Denecke K, Bamidis P, Bond C, Gabarron E, Househ M, Lau AY, et al. Ethical issues of social media usage in healthcare. Year Med Inform 2015;10(1):137-47. Go to original source...
    14. Mostafa MM. More than words: Social networks' text mining for consumer brand sentiments. Expert Systems with Applications 2013;40(10):4241-51. Go to original source...
    15. Mirhaji P, Byrne S, Kunapareddy N, Casscells SW. Semantic approach for text understanding of chief complaints data. In: AMIA Annual Symposium Proceedings 2006; p. 1033.
    16. Wei T, Lu Y, Chang H, Zhou Q, Bao X. A semantic approach for text clustering using WordNet and lexical chains. Expert Systems with Applications 2015;42(4):2264-75. Go to original source...
    17. American Nurses Association. ANA Recognized terminologies that support nursing practice; 2012. [online] [cit. 2017-11-01]. Available from: http://www.nursingworld.org/MainMenuCategories/Tools/Recognized-Nursing-Practice-Terminologies.pdf
    18. Martin KS. The Omaha System: a key to practice, documentation, and information management (reprinted 2nd edition). Omaha, NE: Health Connections Press; 2005.
    19. Kreitzer MJ, Koithan M (Eds). Integrative Nursing. New York: Oxford University Press; 2014. Go to original source...
    20. Monsen KA, Peters J, Schlesner S, Vanderboom CE, Holland DE. The gap in Big Data: getting to wellbeing, strengths, and a whole-person perspective. Glob Adv Health Med 2015;4(3):31-9. Go to original source... Go to PubMed...
    21. Bird S, Klein E, Loper E. Natural language processing with Python: analyzing text with the natural language toolkit. Boston: O'Reilly Media, Inc.; 2009.
    22. Olsen AM, Baisch MJ, Monsen KA. Interpretation of ecological theory for physical activity with the Omaha System. Public Health Nurs 2017;34(1):59-68. Go to original source... Go to PubMed...
    23. Cueller NG. Integrative nursing management of sleep. In: Kreitzer MJ, Koithan M (Eds). Integrative Nursing. New York: Oxford University Press; 2014, pp. 230-42. Go to original source...
    24. Wickwire EM. Financial costs of insomnia. Sleep Review: Journal for Sleep Specialists; 2014. [online] [cit. 2017-11-01]. Available from: http://www.sleepreviewmag.com/2014/12/financial-costs-insomnia/

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