Study 3: Educator perspectives on costs and cost-conscious decision-making in health professions education: a Q-Method study

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 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.