Index to Chiropractic Literature

• Lawson DM

OBJECTIVE: The purpose of this research project was to determine if SEM can be successfully applied to the CCEB measures to explore the inferential nature of the “causal” relationship between academic ability and success on the CCEB examinations, specifically the ability to make correct clinical decisions (diagnosis and management).

METHODS: Data were supplied by the Canadian Chiropractic Examining Board (CCEB) and consisted of anonymized data from 292 candidates for its March and June 2004 Clinical Skills Examinations. There were six data variables provided by the CCEB: standardized scores for the Basic Science, Applied Science, Clinical Decision Making and OSCE examinations. The last two variables were undergraduate grade-point average, and chiropractic college grade-point average. As this was a time-series study (undergraduate grade point average to licensure examination data), a latent variable path analysis was the SEM method of choice. The theoretical model proposed that: 1) a latent trait called Academic Ability had a causal relationship to another latent trait called Professional Knowledge, and 2) that the latent trait Professional Knowledge had a causal relationship to a third and final latent trait called Clinical Reasoning Ability. The model to data fit was analyzed with EQS version 6.1 (B83).

RESULTS: The Comparative Fit Index (CFI) for the model to data fit was 0.98. All but one path coefficient were higher than 0.40. From Academic Ability to Professional Knowledge, the path coefficient was 0.84. From Professional Knowledge to Clinical Reasoning Ability, the path coefficient was 0.88. The path coefficients from the observed variables reveal that the weakest path coefficient was between Applied Science and Clinical Reasoning Ability (0.24). The Clinical Decision Making variable had a much stronger path coefficient to Clinical Reasoning Ability (0.81).

DISCUSSION: A CFI of 0.98 indicates that there was a strong fit of the data to the theoretical model. The strong path coefficients between latent variables infer that: if chiropractors with strong Clinical Reasoning Ability are desired, then students should not move from the second year of their education unless they have demonstrated a substantial grasp of underlying concepts. Further, in order for students to be able to achieve a large measure of the latent trait Professional Knowledge, they should enter the chiropractic education process with a large measure of the latent trait Academic Ability. The weak path coefficient from Applied Science to Clinical Reasoning Ability infers that the 5-option short-format clinical vignette questions on the Applied Science examination are not as good a measure of the latent trait Clinical Reasoning Ability as is the 26-option long-format clinical vignettes from the Clinical Decision Making examination.

CONCLUSION: Structural Equation Modeling, in the form of a latent variable path analysis, can be successfully applied to data from the Canadian Chiropractic Examining Board. There is acceptable model to data fit, and inferences can be made from the data. These inferences include the need to recruit students with strong academic abilities, the need to hold back students who have not achieved a high level of understanding of the first two-years of work at chiropractic college, and that the extended-matching, long-format questions are a better estimate of clinical reasoning ability than 5-option short-format questions or the OSCE.

This abstract is reproduced with the permission of the publisher.

• Association of Chiropractic Colleges / conference proceedings