Abstract
Objectives
Competency in diagnostic reasoning is integral to medical training and patient safety. Situativity theory highlights the importance of contextual factors on learning and performance, such as being informed of a provisional diagnosis prior to a patient encounter. This study aims to determine how being informed of a provisional diagnosis affects an intern’s approach to diagnostic reasoning.
Methods
This mixed methods study was conducted in a real-time workplace learning environment at a large teaching hospital. Interns were randomized to the Chief Complaint (CC) only or chief complaint with Provisional Diagnosis (PD) group. One blinded researcher assessed intern diagnostic reasoning using a validated tool. Mean group scores were compared using the two-sample t-test. The researcher was unblinded for think aloud interviews analyzed via thematic analysis.
Results
There was no difference in performance between the CC and PD groups (mean ± SD): 47.8 ± 8.1 vs. 43.9 ± 10.9, p=0.24. Thematic analysis identified that interns aware of the provisional diagnosis 1) invested less effort in diagnostic reasoning, 2) formulated a differential through a narrowly focused frame, 3) accepted a provisional diagnosis as definitive, and 4) sought to confirm rather than refute the provisional diagnosis.
Conclusions
Our discordant results highlight the complex interplay between a provisional diagnosis and diagnostic reasoning performance in early learners. Though an accurate provisional diagnosis may enhance diagnostic reasoning outcomes, our qualitative results suggest that it may pose certain risks to the diagnostic reasoning process. Metacognitive strategies may be a ripe field for exploration to optimize this complex interplay.
Acknowledgments
Thanks to Gal Barak, MD MEd for editorial support.
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Research ethics: The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and approved by the Baylor College of Medicine IRB.
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Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards. Study was exempt from written, informed consent by local IRB.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interests: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: The raw data can be obtained on request from the corresponding author.
References
1. pediatricsmilestones.pdf [Internet]. https://www.acgme.org/globalassets/pdfs/milestones/pediatricsmilestones.pdf [Accessed 9 Nov 2022].Search in Google Scholar
2. Gruppen, L. Clinical reasoning: de ning it, teaching it, assessing it, studying it. West J Emerg Med 2017;18:4–7. https://doi.org/10.5811/westjem.2016.11.33191.Search in Google Scholar PubMed PubMed Central
3. Balogh, E. Improving diagnosis in health care. Washington, DC: National Academies Press; 2015:473 p.10.17226/21794Search in Google Scholar PubMed
4. Norman, GR, Monteiro, SD, Sherbino, J, Ilgen, JS, Schmidt, HG, Mamede, S. The causes of errors in clinical reasoning: cognitive biases, knowledge deficits, and dual process thinking. Acad Med 2017;92:23–30. https://doi.org/10.1097/acm.0000000000001421.Search in Google Scholar PubMed
5. Croskerry, P, Singhal, G, Mamede, S. Cognitive debiasing 1: origins of bias and theory of debiasing. BMJ Qual Saf 2013;22:ii58–64. https://doi.org/10.1136/bmjqs-2012-001712.Search in Google Scholar PubMed PubMed Central
6. Croskerry, P, Singhal, G, Mamede, S. Cognitive debiasing 2: impediments to and strategies for change. BMJ Qual Saf 2013;22:ii65–72. https://doi.org/10.1136/bmjqs-2012-001713.Search in Google Scholar PubMed PubMed Central
7. Monteiro, S, Sherbino, J, Sibbald, M, Norman, G. Critical thinking, biases and dual processing: the enduring myth of generalisable skills. Med Educ 2020;54:66–73. https://doi.org/10.1111/medu.13872.Search in Google Scholar PubMed
8. Ludolph, R, Schulz, PJ. Debiasing health-related judgments and decision making: a systematic review. Med Decis Making 2018;38:3–13. https://doi.org/10.1177/0272989x17716672.Search in Google Scholar PubMed
9. Durning, SJ, Artino, AR. Situativity theory: a perspective on how participants and the environment can interact: AMEE Guide no. 52. Med Teach 2011;33:188–99. https://doi.org/10.3109/0142159x.2011.550965.Search in Google Scholar PubMed
10. Rencic, J, Schuwirth, LWT, Gruppen, LD, Durning, SJ. Clinical reasoning performance assessment: using situated cognition theory as a conceptual framework. Diagnosis 2020;7:241–9. https://doi.org/10.1515/dx-2019-0051.Search in Google Scholar PubMed
11. Torre, D, Durning, SJ, Rencic, J, Lang, V, Holmboe, E, Daniel, M. Widening the lens on teaching and assessing clinical reasoning: from “in the head” to “out in the world”. Diagnosis 2020;7:181–90. https://doi.org/10.1515/dx-2019-0098.Search in Google Scholar PubMed
12. Merkebu, J, Battistone, M, McMains, K, McOwen, K, Witkop, C, Konopasky, A, et al.. Situativity: a family of social cognitive theories for understanding clinical reasoning and diagnostic error. Diagnosis 2020;7:169–76. https://doi.org/10.1515/dx-2019-0100.Search in Google Scholar PubMed
13. Konopasky, A, Artino, AR, Battista, A, Ohmer, M, Hemmer, PA, Torre, D, et al.. Understanding context specificity: the effect of contextual factors on clinical reasoning. Diagnosis 2020;7:257–64. https://doi.org/10.1515/dx-2020-0016.Search in Google Scholar PubMed
14. Konopasky, A, Durning, SJ, Battista, A, Artino, AR, Ramani, D, Haynes, ZA, et al.. Challenges in mitigating context specificity in clinical reasoning: a report and reflection. Diagnosis 2020;7:291–7. https://doi.org/10.1515/dx-2020-0018.Search in Google Scholar PubMed
15. Holmboe, ES, Durning, SJ. Understanding the social in diagnosis and error: a family of theories known as situativity to better inform diagnosis and error. Diagnosis 2020;7:161–4. https://doi.org/10.1515/dx-2020-0080.Search in Google Scholar PubMed
16. Graber, ML. Progress understanding diagnosis and diagnostic errors: thoughts at year 10. Diagnosis 2020;7:151–9. https://doi.org/10.1515/dx-2020-0055.Search in Google Scholar PubMed
17. Nierenberg, RJ. Using the chief complaint driven medical history: theoretical background and practical steps for student clinicians. MedEdPublish 2020;9:17. https://doi.org/10.15694/mep.2020.000017.1.Search in Google Scholar PubMed PubMed Central
18. Staal, J, Speelman, M, Brand, R, Alsma, J, Zwaan, L. Does a suggested diagnosis in a general practitioners’ referral question impact diagnostic reasoning: an experimental study. BMC Med Educ 2022;22:256. https://doi.org/10.1186/s12909-022-03325-7.Search in Google Scholar PubMed PubMed Central
19. Leblanc, VR, Brooks, LR, Norman, GR. Believing is seeing: the influence of a diagnostic hypothesis on the interpretation of clinical features. Acad Med 2002;77:S67–9. https://doi.org/10.1097/00001888-200210001-00022.Search in Google Scholar PubMed
20. Creamer, E. (PDF) an introduction to fully integrated mixed methods research [Internet]. https://www.researchgate.net/publication/338748542_An_Introduction_to_Fully_Integrated_Mixed_Methods_Research [Accessed 9 Nov 2022].Search in Google Scholar
21. Creswell, JW, Creswell, JD. Research design: qualitative, quantitative, and mixed methods approaches. Los Angeles, CA: SAGE Publications; 2017:305 p.Search in Google Scholar
22. Ryan, G. Introduction to positivism, interpretivism and critical theory. Nurse Res 2018;25:14–20. https://doi.org/10.7748/nr.2018.e1466.Search in Google Scholar PubMed
23. Cameron, R. Lessons from the field: applying the good reporting of A mixed methods study (GRAMMS) framework. Electron J Bus Res Methods 2013;11:53–64.Search in Google Scholar
24. Thammasitboon, S, Sur, M, Rencic, JJ, Dhaliwal, G, Kumar, S, Sundaram, S, et al.. Psychometric validation of the reconstructed version of the assessment of reasoning tool. Med Teach 2021;43:168–73. https://doi.org/10.1080/0142159x.2020.1830960.Search in Google Scholar
25. Thammasitboon, S, Rencic, JJ, Trowbridge, RL, Olson, AP, Sur, M, Dhaliwal, G. The Assessment of Reasoning Tool (ART): structuring the conversation between teachers and learners. Diagnosis 2018;5:197–203. https://doi.org/10.1515/dx-2018-0052.Search in Google Scholar PubMed
26. Assessment of Reasoning Tool [Internet]. Society to improve diagnosis in medicine. https://www.improvediagnosis.org/art/ [Accessed 13 Mar 2023].Search in Google Scholar
27. Wolcott, MD, Lobczowski, NG. Using cognitive interviews and think-aloud protocols to understand thought processes. Curr Pharm Teach Learn 2021;13:181–8. https://doi.org/10.1016/j.cptl.2020.09.005.Search in Google Scholar PubMed
28. Johnson, WR, Artino, AR, Durning, SJ. Using the think aloud protocol in health professions education: an interview method for exploring thought processes: AMEE guide no. 151. Med Teach 2022;45:1–12. https://doi.org/10.1080/0142159x.2022.2155123.Search in Google Scholar
29. Gehlbach, H, Artino, AR, Durning, S. AM last page: survey development guidance for medical education researchers. Acad Med 2010;85:925. https://doi.org/10.1097/ACM.0b013e3181dd3e88.Search in Google Scholar PubMed
30. Malterud, K, Siersma, VD, Guassora, AD. Sample size in qualitative interview studies: guided by information power. Qual Health Res 2016;26:1753–60. https://doi.org/10.1177/1049732315617444.Search in Google Scholar PubMed
31. Braun, V, Clarke, V. One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qual Res Psychol 2021;18:328–52. https://doi.org/10.1080/14780887.2020.1769238.Search in Google Scholar
32. Fetters, MD, Curry, LA, Creswell, JW. Achieving integration in mixed methods designs – principles and practices. Health Serv Res 2013;48:2134–56. https://doi.org/10.1111/1475-6773.12117.Search in Google Scholar PubMed PubMed Central
33. Sunderji, N, Waddell, AE. Mixed-methods convergent study designs in health professions education research: toward meaningful integration of qualitative and quantitative data. Acad Med 2018;93:1093. https://doi.org/10.1097/ACM.0000000000002241.Search in Google Scholar PubMed
34. Thammasitboon, S, Thammasitboon, S, Singhal, G. Diagnosing diagnostic error. Curr Probl Pediatr Adolesc Health Care 2013;43:227–31. https://doi.org/10.1016/j.cppeds.2013.07.002.Search in Google Scholar PubMed
35. Thammasitboon, S, Cutrer, WB. Diagnostic decision-making and strategies to improve diagnosis. Curr Probl Pediatr Adolesc Health Care 2013;43:232–41. https://doi.org/10.1016/j.cppeds.2013.07.003.Search in Google Scholar PubMed
36. Doubilet, P, Herman, P. Interpretation of radiographs: effect of clinical history. Am J Roentgenol 1981;137:1055–8. https://doi.org/10.2214/ajr.137.5.1055.Search in Google Scholar PubMed
37. Leslie, A, Jones, AJ, Goddard, PR. The influence of clinical information on the reporting of CT by radiologists. Br J Radiol 2000;73:1052–5. https://doi.org/10.1259/bjr.73.874.11271897.Search in Google Scholar PubMed
38. Loy, CT, Irwig, L. Accuracy of diagnostic tests read with and without clinical information: a systematic review. JAMA 2004;292:1602. https://doi.org/10.1001/jama.292.13.1602.Search in Google Scholar PubMed
39. Meyer, FML, Filipovic, MG, Balestra, GM, Tisljar, K, Sellmann, T, Marsch, S. Diagnostic errors induced by a wrong a priori diagnosis: a prospective randomized simulator-based trial. J Clin Med 2021;10:826. https://doi.org/10.3390/jcm10040826.Search in Google Scholar PubMed PubMed Central
40. Mamede, S, Goeijenbier, M, Schuit, SCE, De Carvalho Filho, MA, Staal, J, Zwaan, L, et al.. Specific disease knowledge as predictor of susceptibility to availability bias in diagnostic reasoning: a randomized controlled experiment. J Gen Intern Med 2021;36:640–6. https://doi.org/10.1007/s11606-020-06182-6.Search in Google Scholar PubMed PubMed Central
41. Kreiner, H, Gamliel, E. Looking at both sides of the coin: mixed representation moderates attribute-framing bias in written and auditory messages: looking at both sides of the coin. Appl Cognit Psychol 2016;30:332–40. https://doi.org/10.1002/acp.3203.Search in Google Scholar
42. Dyche, L, Epstein, RM. Curiosity and medical education: supporting curiosity in medical education. Med Educ 2011;45:663–8. https://doi.org/10.1111/j.1365-2923.2011.03944.x.Search in Google Scholar PubMed
43. Rudolph, JW, Morrison, JB. Sidestepping superstitious learning, ambiguity, and other roadblocks: a feedback model of diagnostic problem solving. Am J Med 2008;121:S34–7. https://doi.org/10.1016/j.amjmed.2008.02.003.Search in Google Scholar PubMed
44. Gallagher, MW, Lopez, SJ. Curiosity and well-being. J Posit Psychol 2007;2:236–48. https://doi.org/10.1080/17439760701552345.Search in Google Scholar
45. Fry, JP. Interactive relationship between inquisitiveness and student control of instruction. J Educ Psychol 1972;63:459–65. https://doi.org/10.1037/h0033237.Search in Google Scholar
46. Dunlop, M, Schwartzstein, RM. Reducing diagnostic error in the intensive care unit. Engaging uncertainty when teaching clinical reasoning. ATS Sch 2020;1:364–71. https://doi.org/10.34197/ats-scholar.2020-0043ps.Search in Google Scholar
47. Cleary, TJ, Durning, SJ, Artino, AR. Microanalytic assessment of self-regulated learning during clinical reasoning tasks: recent developments and next steps. Acad Med 2016;91:1516–21. https://doi.org/10.1097/acm.0000000000001228.Search in Google Scholar
48. Bagga, R, McKee, A. Metacognition in oral health education: a pedagogy worthy of further exploration. Med Teach 2024;46:911–8. https://doi.org/10.1080/0142159x.2023.2287399.Search in Google Scholar
Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/dx-2024-0097).
© 2024 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Frontmatter
- Editorial
- Pioneering diagnosis in Asia: advancing clinical reasoning expertise through the lens of 3M
- Short Communication
- The foundations of the diagnostic error movement: a tribute to Eta Berner, PhD
- Reviews
- Interventions to improve timely cancer diagnosis: an integrative review
- Technical aspects and clinical applications of synthetic MRI: a scoping review
- Mini Review
- Challenges and barriers for the adoption of personalized medicine in Europe: the case of Oncotype DX Breast Recurrence Score® test
- Opinion Papers
- Beyond thinking fast and slow: a Bayesian intuitionist model of clinical reasoning in real-world practice
- Diagnostic scope: the AI can’t see what the mind doesn’t know
- Guidelines and Recommendations
- CDC’s Core Elements to promote diagnostic excellence
- Original Articles
- Trends of diagnostic adverse events in hospital deaths: longitudinal analyses of four retrospective record review studies
- The effect of a provisional diagnosis on intern diagnostic reasoning: a mixed methods study
- On context specificity and management reasoning: moving beyond diagnosis
- Diagnostic errors in patients admitted directly from new outpatient visits
- Breaking the guidelines: how financial unawareness fuels guideline deviations and inefficient DVT diagnostics
- Harbingers of sepsis misdiagnosis among pediatric emergency department patients
- Factors affecting diagnostic difficulties in aseptic meningitis: a retrospective observational study
- Prenatal diagnostic errors in hemoglobin Bart’s hydrops fetalis caused by rare genetic interactions of α-thalassemia
- Screening fasting glucose before the OGTT: near-patient glucometer- or laboratory-based measurement?
- Three-way comparison of different ESR measurement methods and analytical performance assessment of TEST1 automated ESR analyzer
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- Medical language matters: impact of clinical summary composition on a generative artificial intelligence’s diagnostic accuracy
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