International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

Frequency: 12

line decor
  
line decor

 Volume 5, Issue 8 (August 2018), Pages: 37-46

----------------------------------------------

 Original Research Paper

 Title: Recognition of patient pain cues among staff nurses working in the intensive care unit: A mixed-method study

 Author(s): Salman Hamdan Alsaqri, Joannes Paulus Tolentino Hernandez *

 Affiliation(s):

 College of Nursing, Medical-Surgical Department, University of Hail, Hail, Saudi Arabia

 https://doi.org/10.21833/ijaas.2018.08.006

 Full Text - PDF          XML

 Abstract:

Interpretation of pain messages from patients is an important communicative action in the intensive care unit (ICU). This study explored how “pain” is recognized in pain assessment through (a) clinical knowledge, (b) neurocognitive perception, and (c) communicative actions among ICU staff nurses. A 2-phase explanatory sequential mixed-method design was applied. Data are collected from May 14 to 22, 2017 in different government ICUs. Forty female expatriate nurses mostly with baccalaureate degree (82.5%), mean age of 33 years, and mean work experience of 6 years have participated. Five themes were isolated: pain is physical, emotional, or mixed; pain assessment is facial and behavioral/physiological; barriers to pain assessment are related to healthcare team and system; pain assessment functions between task and diagnostic; and pain assessment is valued as task and diagnostic. Pain assessment is usually done at the beginning of the shift (75%) or as needed (25%). Emotional intelligence scores were at average and high levels. Nurses scored pain more often (51.04%) than no pain (48.96%) and had more neutral facial expression (0.6498 msec) when deciphering pain. The communicative meaning of pain assessment is “knowing patient’s feeling”. Neurocognitive perception of nurses to pain in nonvocal patients is connected to their clinical knowledge and learned practices within the ICU. Clinical training on facial expressions of pain in nonvocal patients should be included. 

 © 2018 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Pain, Communication, Intensive care unit, Mixed method design, Symbolic interactionism, Textual analysis, Facial expression

 Article History: Received 11 March 2018, Received in revised form 18 May 2018, Accepted 24 May 2018

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2018.08.006

 Citation:

 Alsaqri SH and Hernandez JPT (2018). Recognition of patient pain cues among staff nurses working in the intensive care unit: A mixed-method study. International Journal of Advanced and Applied Sciences, 5(8): 37-46

 Permanent Link:

 http://www.science-gate.com/IJAAS/2018/V5I8/Alsaqri.html

----------------------------------------------

 References (35) 

  1. Ayasrah SM, O'Neill TM, Abdalrahim MS, Sutary MM, and Kharabsheh MS (2014). Pain assessment and management in critically ill intubated patients in Jordan: A prospective study. International Journal of Health Sciences, 8(3): 287-298. https://doi.org/10.12816/0023981   [Google Scholar] 
  2. Batiha AM (2014). Pain management barriers in critical care units: A qualitative study. International Journal of Advanced Nursing Studies, 3(1): 1-5.   [Google Scholar]    
  3. Bengtsson M (2016). How to plan and perform a qualitative study using content analysis. NursingPlus Open, 2: 8-14. https://doi.org/10.1016/j.npls.2016.01.001   [Google Scholar]   
  4. Busso C, Deng Z, Yildirim S, Bulut M, Lee CM, Kazemzadeh A, and Narayanan S (2004). Analysis of emotion recognition using facial expressions, speech and multimodal information. In the 6th International Conference on Multimodal Interfaces, ACM, Pennsylvania, USA: 205-211. https://doi.org/10.1145/1027933.1027968   [Google Scholar]   
  5. Cheng S, Foster RL, and Huang C (2003). Concept analysis of pain. Tzu Chi Nursing Journal, 2(3): 20-30.   [Google Scholar]     
  6. Craig KD (2015). Social communication model of pain. Pain, 156(7): 1198-1199. https://doi.org/10.1097/j.pain.0000000000000185   [Google Scholar]  PMid:26086113 
  7. De la Torre F, Chu WS, Xiong X, Vicente F, Ding X, and Cohn J (2015). IntraFace. In the IEEE International Conference on Automatic Face and Gesture Recognition, Ljubljana, Slovenia: 1-8.  
  8. Georgiou E, Hadjibalassi M, Lambrinou E, Andreou P, and Papathanassoglou ED (2015). The impact of pain assessment on critically ill patients' outcomes: A systematic review. BioMed Research International, 2015: Article ID 503830, 18 pages. https://doi.org/10.1155/2015/503830   [Google Scholar] 
  9. Greaves J (2010). How do you stack up? EQ trends by industry. TalentSmart: 1-5. Available online at: http://www.talentsmart.com/articles/How-Do-You-Stack-Up--EQ-Trends-by-Industry-41897549-p-1.html  
  10. Gregory J (2012). How can we assess pain in people who have difficulty communicating? A practice development project identifying a pain assessment tool for acute care. International Practice Development Journal, 2(2): 1-22.   [Google Scholar]     
  11. Hussain M (2015). Acute pain for postoperative patients in Kuwait: A study of how surgical nurses assess postoperative pain. Ph.D. Dissertation, University of Salford, Manchester, UK.   [Google Scholar]     
  12. Kawagoe CK, Matuoka JY, and Salvetti MDG (2017). Pain assessment tools in critical patients with oral communication difficulties: A scope review. Revista Dor, 18(2): 161-165. https://doi.org/10.5935/1806-0013.20170032   [Google Scholar] 
  13. Kizza IB, Muliira JK, Kohi TW, and Nabirye RC (2016). Nurses' knowledge of the principles of acute pain assessment in critically ill adult patients who are able to self-report. International Journal of Africa Nursing Sciences, 4: 20-27. https://doi.org/10.1016/j.ijans.2016.02.001   [Google Scholar] 
  14. Kovács G and Spens KM (2005). Abductive reasoning in logistics research. International Journal of Physical Distribution and Logistics Management, 35(2): 132-144. https://doi.org/10.1108/09600030510590318   [Google Scholar] 
  15. Kumar KH and Elavarasi P (2016). Definition of pain and classification of pain disorders. Journal of Advanced Clinical and Research Insights, 3: 87-90. https://doi.org/10.15713/ins.jcri.112   [Google Scholar] 
  16. Kunz M and Lautenbacher S (2014). The faces of pain: a cluster analysis of individual differences in facial activity patterns of pain. European Journal of Pain, 18(6): 813-823. https://doi.org/10.1002/j.1532-2149.2013.00421.x   [Google Scholar]  PMid:24174396 
  17. Matsumoto D and Hwang HS (2011). Reading facial expressions of emotion: Basic research leads to training programs that improve people's ability to detect emotions. Psychological Science Agenda. American Psychological Association, 25(5). Available online at: http://www.apa.org/science/about/psa/2011/05/facial-expressions.aspx   [Google Scholar]     
  18. Mattsson JY (2012). A qualitative national study of nurses' clinical knowledge development of pain in pediatric intensive care. Journal of Nursing Education and Practice, 2(2): 107-118. https://doi.org/10.5430/jnep.v2n2p107   [Google Scholar] 
  19. Medlej J (2014). Human anatomy fundamentals: Mastering facial expressions. Available online at: https://design.tutsplus.com/ tutorials/human-anatomy-fundamentals-mastering-facial-expressions--cms-21140.       
  20. Meissner JO (2005). Relationship quality in the context of computer-mediated communication-a social constructionist approach. WWZ Discussion Paper (No. 05/01), Universität Basel, Switzerland.   [Google Scholar]     
  21. Nascimento LAD and Kreling MCGD (2011). Assessment of pain as the fifth vital sign: Opinion of nurses. Acta Paulista de Enfermagem, 24(1): 50-54. https://doi.org/10.1590/S0103-21002011000100007   [Google Scholar] 
  22. Nippert AR (2015). The expression of chronic pain: A multimodal analysis of chronic pain patients. Bachelors Thesis, University of Arizona, Tucson, Arizona, USA.   [Google Scholar]     
  23. Okeson JP (2005). Bell's orofacial pains: the clinical management of orofacial pain. Quintessence Publishing Company, Chicago, USA.   [Google Scholar]     
  24. Paranyushkin D (2011). Identifying the pathways for meaning circulation using text network analysis. Nodus Labs, Berlin, Germany. Available online at: http://noduslabs.com/research/pathways-meaning-circulation-text-network-analysis   [Google Scholar]     
  25. Price TF and Harmon‐Jones E (2015). Embodied emotion: the influence of manipulated facial and bodily states on emotive responses. Wiley Interdisciplinary Reviews: Cognitive Science, 6(6): 461-473. https://doi.org/10.1002/wcs.1370   [Google Scholar]  PMid:26401657 
  26. Prkachin KM and Craig KD (1995). Expressing pain: The communication and interpretation of facial pain signals. Journal of Nonverbal Behavior, 19(4): 191-205. https://doi.org/10.1007/BF02173080   [Google Scholar] 
  27. Rose L, Smith O, Gélinas C, Haslam L, Dale C, Luk E, Burry L, McGillion M, Mehta S, Watt-Watson J (2012). Critical care nurses' pain assessment and management practices: a survey in Canada. American Journal of Critical Care, 21(4): 251-259. https://doi.org/10.4037/ajcc2012611   [Google Scholar]  PMid:22751367     
  28. Roy C, Blais C, Fiset D, Rainville P, and Gosselin F (2015). Efficient information for recognizing pain in facial expressions. European Journal of Pain, 19(6): 852-860. https://doi.org/10.1002/ejp.676   [Google Scholar] PMid:25708816 
  29. Severgnini P, Pelosi P, Contino E, Serafinelli E, Novario R, and Chiaranda M (2016). Accuracy of critical care pain observation tool and behavioral pain scale to assess pain in critically-ill conscious and unconscious patients: Prospective, observational study. Journal of Intensive Care, 4(1): 68. https://doi.org/10.1186/s40560-016-0192-x   [Google Scholar] 
  30. Souza RCS, Garcia DM, Sanches MB, Gallo AMA, Martins CPB, and Siqueira ILCP (2013). Nursing team knowledge on behavioral assessment of pain in critical care patients. Revista Gaucha De Enfermagem, 34(3): 55-63. https://doi.org/10.1590/S1983-14472013000300007   [Google Scholar]  PMid:24344585 
  31. Stys Y and Brown SL (2004). A review of the emotional intelligence literature and implications for corrections. Research Report N R-150, Research Branch Correctional Service of Canada, Ottawa, Canada.   [Google Scholar]     
  32. Subedi D (2016). Explanatory sequential mixed method design as the third research community of knowledge claim. American Educational Research Journal, 4(7): 570-577.   [Google Scholar]     
  33. Touati N, Denis JL, Roberge D, and Brabant B (2015). Learning in health care organizations and systems: An alternative approach to knowledge management. Administration and Society, 47(7): 767-801. https://doi.org/10.1177/0095399712459730   [Google Scholar] 
  34. Varndell W, Fry M, and Elliott D (2017). Exploring how nurses assess, monitor and manage acute pain for adult critically ill patients in the emergency department: protocol for a mixed methods study. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 25(1): 75-84. https://doi.org/10.1186/s13049-017-0421-x   [Google Scholar]  PMid:28764789 PMCid:PMC5540572 
  35. Wieser MJ, Gerdes A, Reicherts P, and Pauli P (2014). Mutual influences of pain and emotional face processing. Frontiers in Psychology, 5(1160): 1-6. https://doi.org/10.3389/fpsyg.2014.01160   [Google Scholar]