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PURPOSE: Because multiple management options exist for clinical T1 renal masses, patients may experience a state of uncertainty about the course of action to pursue (ie, decisional conflict). To better support patients, we examined patient, clinical, and decision-making factors associated with decisional conflict among patients newly diagnosed with clinical T1 renal masses suspicious for kidney cancer. MATERIALS AND METHODS: From a prospective clinical trial, participants completed the Decisional Conflict Scale (DCS), scored 0 to 100 with < 25 associated with implementing decisions, at 2 time points during the initial decision-making period. The trial further characterized patient demographics, health status, tumor burden, and patient-centered communication, while a subcohort completed additional questionnaires on decision-making. Associations of patient, clinical, and decision-making factors with DCS scores were evaluated using generalized estimating equations to account for repeated measures per patient. RESULTS: Of 274 enrollees, 250 completed a DCS survey; 74% had masses ≤ 4 cm in size, while 11% had high-complexity tumors. Model-based estimated mean DCS score across both time points was 17.6 (95% CI 16.0-19.3), though 50% reported a DCS score ≥ 25 at least once. On multivariable analysis, DCS scores increased with age (+2.64, 95% CI 1.04-4.23), high- vs low-complexity tumors (+6.50, 95% CI 0.35-12.65), and cystic vs solid masses (+9.78, 95% CI 5.27-14.28). Among decision-making factors, DCS scores decreased with higher self-efficacy (-3.31, 95% CI -5.77 to -0.86]) and information-seeking behavior (-4.44, 95% CI -7.32 to -1.56). DCS scores decreased with higher patient-centered communication scores (-8.89, 95% CI -11.85 to -5.94). CONCLUSIONS: In addition to patient and clinical factors, decision-making factors and patient-centered communication relate with decisional conflict, highlighting potential avenues to better support patient decision-making for clinical T1 renal masses.
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Purpose: This paper aims to characterize the use of demographic data in multiple-choice questions from a commercial preclinical question bank and determine if there is appropriate use of different distractors. Background: Multiple-choice questions for medical students often include vignettes describing a patient's presentation to help guide students to a diagnosis, but overall patterns of usage between different types of nonmedical patient information in question stems have yet to be determined. Methods: Three hundred eighty of 453 randomly selected questions were included for analysis after determining they contained a clinical vignette and required a diagnosis. The vignettes and following explanations were then examined for the presence/absence of 11 types of demographic information, including age, sex/gender, and socioeconomic status. We compared both the usage frequency and relevance between the 11 information types. Results: Most information types were present in less than 10% of clinical vignettes, but age and sex/gender were present in over 95% of question stems. Over 50% of questions included irrelevant information about age and sex/gender, but 75% of questions did not include any irrelevant information of other types. Patient weight and environmental exposures were significantly more likely to be relevant than age or sex/gender. Discussion: Students using the questions in this study will frequently gain practice incorporating age and sex/gender into their clinical reasoning while receiving little exposure to other demographic information. Based on our findings, we posit that questions could include more irrelevant information, outside age and sex/gender, to better approximate real clinical scenarios and ensure students do not overvalue certain demographic data. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-023-01778-z.