SUMMARY OF THE STUDY
This study examines how health professions educators conceptualize costs and cost-conscious decision-making in the context of increasing resource scarcity. Using Q-methodology, the study systematically mapped the diverse viewpoints educators hold regarding the role of cost information in educational design and management. Participants ranked 34 statements about costs and engaged in semi-structured interviews. Using Q-method software and by-person inverted factor analysis with varimax rotation, this study identified shared patterns of thinking, which were interpreted through factor arrays, distinguishing and consensus statements, and interview data. The analysis revealed four distinct educator perspectives: Unaware Doubters, Cautious Realists, Pragmatic Supporters, and Empowered Agents, each representing different levels of awareness, motivation, and engagement with cost-conscious decision making. These perspectives highlight the need for tailored institutional strategies and clearer communication to meaningfully involve educators in cost-related decisions within health professions education.
ORCID ID
https://orcid.org/0000-0002-4976-5202
DESCRIPTION OF THE DATA FILES
Interview Questions.pdf
The semi-structured interview guide used to elicit educators’ reflections on resource use and cost-conscious decision-making.
Factor Arrays
Idealized Q-sorts representing the composite ranking of statements for each identified perspective. These arrays synthesize how participants aligned with a given factor collectively structured the statements and serve as the primary output for interpreting each viewpoint.
• Factor Array One Cautious Realistics.png
• Factor Array Two Unaware Doubters.png
• Factor Array Four Pragmatic Supporters.png
• Factor Array Six Empowered Agents.png
Q-Methodology Output Files.xlsx
This file contains the complete analytic output from the Q-Methodology software used in the study. Sheets fall into six functional categories:
A. Input Materials
• Statements: the full set of 34 Q-statements used in the study
• Q sorts: raw sort configurations provided by participants
B. Correlation and Factor Extraction
• Correlation Matrix, Unrotated Factor Matrix, Communalities Matrix: statistical outputs used to derive factors
C. Factor Loadings and Participant Assignment
• Factor Loadings, Factor Loadings Table, and sheets indicating sort–factor correlations and weights
D. Factor Arrays and Interpretation Materials
• Sheets labeled Fac. 1, Fac. 2, Fac. 4, Fac. 6: idealized Q-sorts representing each perspective
• Additional sheets include Factor Score Ranks and factor-score correlations
E. Distinguishing and Consensus Statements
• Sheets identifying distinguishing statements for each factor, consensus statements, and statistical comparisons (Standard Errors for Diffs)
F. Factor Characteristics
• Summary of eigenvalues, explained variance, and other factor-level diagnostics
How to Interpret the File
The structure of the excel file follows standard Q-methodology analytical conventions1. Factor arrays represent the central interpretive tool, indicating how each perspective ranks statements relative to others. Distinguishing statements highlight what makes perspectives unique, while consensus statements identify shared viewpoints. Users familiar with Q-analysis will be able to explore, verify, or extend the interpretation using the complete output supplied here.
