Abstract Title
What are the barriers to learning clinical reasoning?


Janina Iwaszko
Kamal Nathavitharana




University of Birmingham Clinical Teaching Academy


There have been many studies looking at the ways in which new clinical students approach the acquisition of clinical competence, this phenomenon includes mastering the skills of clinical reasoning and diagnostic problem solving1However, the results from this large and informative area of medical education research have yet to percolate, in any major way, into real clinical training. This study explored the experience of newly clinical medical undergraduates as they initially approached the task of learning clinical reasoning. There continues to be no unified model of this complex process2, but the component parts are now well understood3. It is clear that the initial part of the diagnostic process involves the acquisition of data from the patient, re-organising and evaluating this in a clinical manner, then integrating this with previously memorised biomedical data and generating a set of differential diagnoses. This study showed that there were issues for many students with the process of collecting patient data, prioritising it appropriately and then integrating this information, and therefore there were problems with the generation of differential diagnoses.

Summary of Work

This was a mixed method study looking at the experiences of newly clinical medical undergraduates as they began to acquire their clinical competence.Twenty 3rd year, newly clinical undergraduate medical students interviewed a simulated patient individually. The students then reviewed their consultations, using a semi-structured interview with the researcher. Student commentaries were taped digitally and the reasons behind the methods they used to construct their hypotheses and generate their diagnoses were thematically coded, in line with qualitative studies protocol4. Students then completed a previously validated Diagnostic Thinking Inventory Form5, and these forms were then analysed to add a quantitative aspect to the study. 

Summary of Results

Qualitatively, participants described difficulty in interpreting, clinically organising and prioritising the patient data they acquired, and at the same time retaining a direction for the consultation. In addition, they had problems formulating questions, and interpreting and prioritising the information obtained. This lead to some problems with the generation of diagnoses.

The percentage of the answers grouped within each of the qualitative themes was:

Theme 1 Problems with patient data acquisition and interpretation (Problem Representation) 27%

Theme 2 Lack of knowledge of reasoning processes/Clinical Reasoning 24%

Theme 3 High cognitive work load issues 18%

Theme 4 Lack of clarity with prioritisation/diagnosis construction 13%

Theme 5 Lack of knowledge/Access to knowledge 11%

Theme 6 Personal and Environmental issues 7%

The topics that achieved the lowest scores in the quantitative data were: a lack of illness scripts/clinical knowledge; high cognitive work load in working memory (germane load) and the acquisition and interpretation of patient data. High scores were found in willingness to re-evaluate chosen conclusions. 


The major themes for barriers to acquisition of clinical reasoning for novice clinical students were found to be similar, in both the qualitative and quantitative analyses. The main areas in which problems were encountered were, understanding the information that the patients offered and then realising the clinical importance of the data collected. To collect this data the students followed a poorly understood formulaic approach for data acquisition (i.e. history, examination etc) which they applied with little knowledge of how it related to the process of clinical reasoning. They also experienced problems maintaining the direction of the interview whilst manipulating data. This could be due to problems of high cognitive load, resulting in an inability to both collect data and use higher-order processes, such as problem solving and metacognition, concurrently.

In addition, the students experienced problems retrieving previous biomedical knowledge, integrating patient details with this and then generating a set of differential diagnoses. This problem with retrieval of pre-clinically acquired knowledge remains an issue, despite extensive curriculum changes, that were designed to mitigate it. These above problems resulted in a slower, less effective and ill-structured approach to their early acquisition of clinical reasoning. The main issue stems from an initial overload of cognitive processes that all need to be recognised, learnt and then smoothly integrated. A lack of initial explicit clinical reasoning scaffolding appears to be a central issue. Lastly, and maybe most importantly, for those students with problems, they were unaware of the source of the problems and therefore were unable to develop strategies for remedying them.

Take-home Messages

These barriers to the early acquisition of clinical reasoning may be overcome using a variety of techniques:

  • The early teaching of the processes underlying both clinical reasoning and the practicalities of metacognitive scaffolding, may give students an opportunity to design their own approach to the acquisition of these skills6.
  • A stepwise introduction to acquiring patient data by commencing with well structured problems and then moving to less well structured or real bedside clinical experience, may reduce the initial cognitive load on working memory, thus allowing students to use their higher-order cognitive abilities earlier in their learning and allowing them to clinically organise their patient data 7
  • This may also allow students more time to reorganise their existing biomedical knowledge, so that it can be stored in a more clinically accessible fashion.
  • The use of advance organisers and access to procedural and metacognitive scaffolding8, may well improve early student experience, by reducing their germane load and making their early efforts more focused and productive.

This should result in a better structured foundation to clinical studies and may allow students to process clinical data more effectively and possibly even achieve a higher quality of clinical competence in the time available.


Many Thanks to my supervisor Dr Kamal Nathavitharana, for his continuing support and encouragement.


1 Kaufman,D. (2003) ABC of learning and teaching in medicine. Applying educational theory in practice. BMJ 326:213-216.

Charlin,B., Lubarsky,S., Millette,B., Crevier,F., Audetat,M., Charbonneau,A., Fon, NC., Hoff,L. and Bourdy,C. (2012) Clinical reasoning    processes: unravelling complexity through graphical representation. Medical Education 46:454-463.

3 Groves,M., Scott,I. and Alexander,H. (2002) Assessing clinical reasoning: a method to monitor its development in a PBL curriculum.      Medical Teacher 24(5): 507-515.

4 Higgs, J. and Jones, M.A. In: Higgs,J., Jones, M., Loftus, S. and Christensen, N. (Eds) Clinical Reasoning in the Health Professions 3rd ed. London: Butterworth Heinemann Elsevier pp.

5 Bordage, G., Grant,J. and Marsden,P. (1990) Quantitative assessment of diagnostic ability. Medical Education 24:413-425.

6 Mc Curdy, N., Naismith, L. and Lajoie, S. (2010) Using metacognitive tools to scaffold medical students developing clinical reasoning skills. Cognitive and Metacognitive Educational Systems: Papers from the AAAI Fall Symposium (FS-10-01) pp.52-56

7 van Merrienboer,J. & Sweller,J. (2010) Cognitive load theory in health professional education: design principles and strategies. Medical Education 44: 85-93.

8 Edmunson, K.M. (1995) Concept mapping for the development of medical curricula Journal of Research in Science Teaching 32 pp.777–793.


Summary of Work
Summary of Results
Take-home Messages
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