Home Ways that nurse practitioner students self-explain during diagnostic reasoning
Article
Licensed
Unlicensed Requires Authentication

Ways that nurse practitioner students self-explain during diagnostic reasoning

  • Leah Burt EMAIL logo , Susan Corbridge , Colleen Corte , Laurie Quinn , Lorna Finnegan and Lou Clark
Published/Copyright: April 26, 2021

Abstract

Objectives

An important step in mitigating the burden of diagnostic errors is strengthening diagnostic reasoning among health care providers. A promising way forward is through self-explanation, the purposeful technique of generating self-directed explanations to process novel information while problem-solving. Self-explanation actively improves knowledge structures within learners’ memories, facilitating problem-solving accuracy and acquisition of knowledge. When students self-explain, they make sense of information in a variety of unique ways, ranging from simple restatements to multidimensional thoughts. Successful problem-solvers frequently use specific, high-quality self-explanation types. The unique types of self-explanation present among nurse practitioner (NP) student diagnosticians have yet to be explored. This study explores the question: How do NP students self-explain during diagnostic reasoning?

Methods

Thirty-seven Family NP students enrolled in the Doctor of Nursing Practice program at a large, Midwestern U.S. university diagnosed three written case studies while self-explaining. Dual methodology content analyses facilitated both deductive and qualitative descriptive analysis.

Results

Categories emerged describing the unique ways that NP student diagnosticians self-explain. Nine categories of inference self-explanations included clinical and biological foci. Eight categories of non-inference self-explanations monitored students’ understanding of clinical data and reflect shallow information processing.

Conclusions

Findings extend the understanding of self-explanation use during diagnostic reasoning by affording a glimpse into fine-grained knowledge structures of NP students. NP students apply both clinical and biological knowledge, actively improving immature knowledge structures. Future research should examine relationships between categories of self-explanation and markers of diagnostic success, a step in developing prompted self-explanation learning interventions.


Corresponding author: Leah Burt, PhD, APRN, ANP-BC, Department of Biobehavioral Nursing Science (MC 802), College of Nursing, University of Illinois Chicago, 845 South Damen Avenue, 758 NURS, Chicago, IL 60612, USA, Phone: +262 227 0045, Fax: +312 996 4979, E-mail:

Acknowledgments

The authors thank Kevin Grandfield, Publication Manager for the UIC Department of Biobehavioral Nursing Science, for editorial assistance.

  1. Research funding: This research was funded by a grant from the American Association of Nurse Practitioners (AANP).

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: A waiver of written consent was presented to each student.

  5. Ethical approval: Research ethics approval was received from the University’s Office for the Protection of Research Subjects, IRB # 2019-0668.

References

1. American Association of Nurse Practitioners. What’s a nurse practitioner (NP)?; 2019. Available from: https://www.aanp.org/about/all-about-nps/whats-a-nurse-practitioner.Search in Google Scholar

2. American Association of Nurse Practitioners. Standards of practice for nurse practitioners; 2019. Available from: https://www.aanp.org/advocacy/advocacy-resource/position-statements/standards-of-practice-for-nurse-practitioners.Search in Google Scholar

3. American Association of Nurse Practitioners. The state of the nurse practitioner profession. Texas: American Association of Nurse Practitioners; 2018.Search in Google Scholar

4. Smith, VA, Morgan, PA, Edelman, D, Woolson, SL, Berkowitz, TSZ, Van Houtven, CH, et al.. Utilization and costs by primary care provider type: are there differences among diabetic patients of physicians, nurse practitioners, and physician assistants? Med Care 2020;58:681–8. https://doi.org/10.1097/mlr.0000000000001326.Search in Google Scholar PubMed PubMed Central

5. DesRoches, CM, Clarke, S, Perloff, J, O’Reilly-Jacob, M, Buerhaus, P. The quality of primary care provided by nurse practitioners to vulnerable Medicare beneficiaries. Nurs Outlook 2017;65:679–88. https://doi.org/10.1016/j.outlook.2017.06.007.Search in Google Scholar PubMed

6. Buerhaus, P, Perloff, J, Clarke, S, O’Reilly-Jacob, M, Zolotusky, G, DesRoches, CM. Quality of primary care provided to Medicare beneficiaries by nurse practitioners and physicians. Med Care 2018;56:484–90. https://doi.org/10.1097/mlr.0000000000000908.Search in Google Scholar PubMed

7. Everett, CM, Morgan, P, Smith, VA, Woolson, S, Edelman, D, Hendrix, CC, et al.. Primary care provider type: are there differences in patients’ intermediate diabetes outcomes? JAAPA 2019;32:36–42. https://doi.org/10.1097/01.jaa.0000558239.06875.0b.Search in Google Scholar

8. Gracias, VH, Sicoutris, CP, Stawicki, SP, Meredith, DM, Horan, AD, Gupta, R, et al.. Critical care nurse practitioners improve compliance with clinical practice guidelines in “semi-closed” surgical intensive care unit. J Nurs Care Qual 2008;23:338–44. https://doi.org/10.1097/01.ncq.0000323286.56397.8c.Search in Google Scholar PubMed

9. Jackson, GL, Smith, VA, Edelman, D, Woolson, SL, Hendrix, CC, Everett, CM, et al.. Intermediate diabetes outcomes in patients managed by physicians, nurse practitioners, or physician assistants: a cohort study. Ann Intern Med 2018;169:825–35. https://doi.org/10.7326/m17-1987.Search in Google Scholar

10. Kuo, YF, Adhikari, D, Eke, CG, Goodwin, JS, Raji, MA. Processes and outcomes of congestive heart failure care by different types of primary care models. J Card Fail 2018;24:9–18. https://doi.org/10.1016/j.cardfail.2017.08.459.Search in Google Scholar PubMed PubMed Central

11. Kurtzman, ET, Barnow, BS. A comparison of nurse practitioners, physician assistants, and primary care physicians’ patterns of practice and quality of care in health centers. Med Care 2017;55:615–22. https://doi.org/10.1097/mlr.0000000000000689.Search in Google Scholar

12. Makary, MA, Daniel, M. Medical error-the third leading cause of death in the US. BMJ 2016;353:i2139. https://doi.org/10.1136/bmj.i2139.Search in Google Scholar PubMed

13. Saber Tehrani, AS, Lee, H, Mathews, SC, Shore, A, Makary, MA, Pronovost, PJ, et al.. 25-Year summary of US malpractice claims for diagnostic errors 1986-2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf 2013;22:672–80. https://doi.org/10.1136/bmjqs-2012-001550.Search in Google Scholar PubMed

14. Balogh, EP, Miller, BT, Ball, JR. Improving diagnosis in healthcare. Washington, D.C.: The National Academies of Sciences, Engineering, Medicine; 2015.10.17226/21794Search in Google Scholar PubMed

15. Chamberland, M, St-Onge, C, Setrakian, J, Lanthier, L, Bergeron, L, Bourget, A, et al.. The influence of medical students’ self-explanations on diagnostic performance. Med Educ 2011;45:688–95. https://doi.org/10.1111/j.1365-2923.2011.03933.x.Search in Google Scholar PubMed

16. Chamberland, M, Mamede, S, St-Onge, C, Rivard, MA, Setrakian, J, Levesque, A, et al.. Students’ self-explanations while solving unfamiliar cases: the role of biomedical knowledge. Med Educ 2013;47:1109–16. https://doi.org/10.1111/medu.12253.Search in Google Scholar PubMed

17. Chamberland, M, Mamede, S, St-Onge, C, Setrakian, J, Bergeron, L, Schmidt, H. Self-explanation in learning clinical reasoning: the added value of examples and prompts. Med Educ 2015;49:193–202. https://doi.org/10.1111/medu.12623.Search in Google Scholar PubMed

18. Chamberland, M, Mamede, S, St-Onge, C, Setrakian, J, Schmidt, HG. Does medical students’ diagnostic performance improve by observing examples of self-explanation provided by peers or experts? Adv Health Sci Educ 2015;20:981–93. https://doi.org/10.1007/s10459-014-9576-7.Search in Google Scholar PubMed

19. Chi, MT, Bassok, M, Lewis, MW, Reimann, P, Glaser, R. Self-explanations: how students study and use examples in learning to solve problems. Cogn Sci 1989;13:145–82. https://doi.org/10.1207/s15516709cog1302_1.Search in Google Scholar

20. Chi, MT. Self-explaining expository texts: the dual processes of generating inferences and repairing mental models. In: Glaser, R, editor. Advances in instructional psychology. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.; 2000:161–238 pp.Search in Google Scholar

21. Rittle-Johnson, B, Loehr, AM. Eliciting explanations: constraints on when self-explanation aids learning. Psychon Bull Rev 2017;24:1501–10. https://doi.org/10.3758/s13423-016-1079-5.Search in Google Scholar PubMed

22. Chi, MTH, de Leeuw, N, Chiu, M-H, LaVancher, C. Eliciting self-explanations improves understanding. Cogn Sci 1994;18:439–77. https://doi.org/10.1207/s15516709cog1803_3.Search in Google Scholar

23. Renkl, A. Learning from worked-out examples: a study on individual differences. Cogn Sci 1997;21:1–29. https://doi.org/10.1207/s15516709cog2101_1.Search in Google Scholar

24. Renkl, A, Stark, R, Gruber, H, Mandl, H. Learning from worked-out examples: the effects of example variability and elicited self-explanations. Contemp Educ Psychol 1998;23:90–108. https://doi.org/10.1006/ceps.1997.0959.Search in Google Scholar PubMed

25. Nokes, TJ, Hausmann, RGM, VanLehn, K, Gershman, S. Testing the instructional fit hypothesis: the case of self-explanation prompts. Instr Sci 2011;39:645–66. https://doi.org/10.1007/s11251-010-9151-4.Search in Google Scholar

26. Schworm, S, Renkl, A. Learning argumentation skills through the use of prompts for self-explaining examples. J Educ Psychol 2007;99:285–96. https://doi.org/10.1037/0022-0663.99.2.285.Search in Google Scholar

27. Berthold, K, Eysink, THS, Renkl, A. Assiting self-explanation prompts are more effective than open prompts when learning with multiple representations. Instr Sci 2009;37:345–63. https://doi.org/10.1007/s11251-008-9051-z.Search in Google Scholar

28. Peixoto, JM, Mamede, S, de Faria, RMD, Moura, AS, Santos, SME, Schmidt, HG. The effect of self-explanation of pathophysiological mechanisms of diseases on medical students’ diagnostic performance. Adv Health Sci Educ 2017;22:1183–97. https://doi.org/10.1007/s10459-017-9757-2.Search in Google Scholar PubMed

29. Muhoza-Butoke, C, St-Onge, C, Chamberland, M. Self-Explanation as a strategy for supporting the development of diagnostic reasoning in medical students: an exploratory study on knowledge development. Health Prof Educ 2018;4:78–85. https://doi.org/10.1016/j.hpe.2017.03.005.Search in Google Scholar

30. Gilhooly, KJ. Cognitive psychology and medical diagnosis. Appl Cogn Psychol 1990;4:261–72. https://doi.org/10.1002/acp.2350040404.Search in Google Scholar

31. Lehman, DR, Lempert, RO, Nisbett, RE. The effects of graduate training on reasoning: formal discipline and thinking about everyday-life events. Am Psychol 1988;43:431–42. https://doi.org/10.1037/0003-066x.43.6.431.Search in Google Scholar

32. Pirret, AM. Nurse practitioners’ versus physicians’ diagnostic reasoning style and use of maxims: a comparative study. J Nurse Pract 2016;12:381–9. https://doi.org/10.1016/j.nurpra.2016.02.006.Search in Google Scholar

33. Pirret, AM, Neville, SJ, La Grow, SJ. Nurse practitioners versus doctors diagnostic reasoning in a complex case presentation to an acute tertiary hospital: a comparative study. Int J Nurs Stud 2015;52:716–26. https://doi.org/10.1016/j.ijnurstu.2014.08.009.Search in Google Scholar PubMed

34. van der Linden, C, Reijnen, R, de Vos, R. Diagnostic accuracy of emergency nurse practitioners versus physicians related to minor illnesses and injuries. J Emerg Nurs 2010;36:311–6. https://doi.org/10.1016/j.jen.2009.08.012.Search in Google Scholar PubMed

35. State of Illinois. Occupational employment statistics: wage data, 2018 edition. State of Illinois; 2018.Search in Google Scholar

36. Elo, S, Kyngas, H. The qualitative content analysis process. J Adv Nurs 2008;62:107–15. https://doi.org/10.1111/j.1365-2648.2007.04569.x.Search in Google Scholar PubMed

37. Chi, MT. Quantifying qualitative analyses of verbal data: a practical guide. J Learn Sci 1997;6:271–315. https://doi.org/10.1207/s15327809jls0603_1.Search in Google Scholar

38. Tracy, SJ. Qualitative research methods: collecting evidence, crafting analysis, communicating impact. New York: John Wiley & Sons; 2019.Search in Google Scholar

39. Corbin, J, Strauss, A. Basics of qualitative research, 4th ed. Los Angeles: SAGE; 2015.Search in Google Scholar

40. Saldana, J. The coding manual for qualitative researchers, 3rd ed. Los Angeles: SAGE; 2016.Search in Google Scholar

41. Landis, JR, Koch, GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159–74. https://doi.org/10.2307/2529310.Search in Google Scholar

42. Cohen, J. A coefficient of agreement for nominal scales. Educ Psychol Meas 1960;20:37–46.10.1177/001316446002000104Search in Google Scholar

43. Schmidt, HG, Rikers, RM. How expertise develops in medicine: knowledge encapsulation and illness script formation. Med Educ 2007;41:1133–9.10.1111/j.1365-2923.2007.02915.xSearch in Google Scholar PubMed

44. Charlin, B, Boshuizen, HP, Custers, EJ, Feltovich, PJ. Scripts and clinical reasoning. Med Educ 2007;41:1178–84.10.1111/j.1365-2923.2007.02924.xSearch in Google Scholar PubMed

45. Van de Wiel, MW, Boshuizen, HPA, Schmidt, H. Knowledge restructuring in expertise development: evidence from pathophysiological representations of clinical cases by students and physicians. Eur J Cogn Psychol 2000;12:323–55.10.1080/09541440050114543Search in Google Scholar

46. Boshuizen, HPA, Schmidt, H. On the role of biomedical knowledge in clinical reasoning by experts, intermediates, and novices. Cogn Sci 1992;16:153–84.10.1207/s15516709cog1602_1Search in Google Scholar

47. Tracy, SJ. Qualitative quality: eight “big-tent” criteria for excellent qualitative research. Qual Inq 2010;16:837–51.10.1177/1077800410383121Search in Google Scholar

48. Frambach, JM, van der Vleuten, CP, Durning, SJ. AM last page. Quality criteria in qualitative and quantitative research. Acad Med 2013;88:552.10.1097/ACM.0b013e3182a36cc6Search in Google Scholar

Received: 2020-10-13
Accepted: 2021-03-02
Published Online: 2021-04-26

© 2021 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. From Camille Nούς to Apollonian and the Dionysian scientists
  4. Review
  5. The role of D-dimer in periprosthetic joint infection: a systematic review and meta-analysis
  6. Mini Reviews
  7. Updated picture of SARS-CoV-2 variants and mutations
  8. Systematic review and cumulative meta-analysis of the diagnostic accuracy of glial fibrillary acidic protein vs. S100 calcium binding protein B as blood biomarkers in observational studies of patients with mild or moderate acute traumatic brain injury
  9. Opinion Papers
  10. The 6C model for accurately capturing the patient’s medical history
  11. Webside manner: maskless communication
  12. Original Articles
  13. Ways that nurse practitioner students self-explain during diagnostic reasoning
  14. Diagnostic reasoning: relationships among expertise, accuracy, and ways that nurse practitioner students self-explain
  15. Perspectives on the current state of pre-clerkship clinical reasoning instruction in United States medical schools: a survey of clinical skills course directors
  16. Use of a structured approach and virtual simulation practice to improve diagnostic reasoning
  17. Analyzing diagnostic errors in the acute setting: a process-driven approach
  18. Morning report goes virtual: learner experiences in a virtual, case-based diagnostic reasoning conference
  19. Stroke hospitalization after misdiagnosis of “benign dizziness” is lower in specialty care than general practice: a population-based cohort analysis of missed stroke using SPADE methods
  20. Discrepancy between emergency department admission diagnosis and hospital discharge diagnosis and its impact on length of stay, up-triage to the intensive care unit, and mortality
  21. Automated capture-based NGS workflow: one thousand patients experience in a clinical routine framework
  22. Short Communication
  23. Characterizing the relationship between diagnostic intensity and quality of care
  24. Case Reports – Lessons in Clinical Reasoning
  25. Lessons in clinical reasoning ‒ pitfalls, myths, and pearls: a case of confusion, disequilibrium, and “picking at the air”
  26. Hickam’s dictum, Occam’s razor, and Crabtree’s bludgeon: a case of renal failure and a clavicular mass
  27. Letters to the Editor
  28. Three learning concepts to improve diagnosis and enhance the practice of medicine
  29. Distributed cognition: a framework for conceptualizing telediagnosis in teams
  30. Performance of Fujirebio Espline SARS-CoV-2 rapid antigen test for identifying potentially infectious individuals
Downloaded on 18.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/dx-2020-0136/html
Scroll to top button