Radiologists are Human Too: Addressing the Impacts of Occupational Exhaustion, Travel History, and Hunger on...

To investigate how occupational exhaustion, travel, and hunger affect mammography reading performance among radiologists and radiology trainees.

Thirty participants (22 radiologists, eight radiology trainees) completed mammography reading assessments using the DetectedX platform during two radiology conferences in Saudi Arabia. Each participant interpreted 30 de-identified mammographic cases (15 abnormal, 15 normal) under standardized conditions. Performance was measured using jackknife alternative free-response receiver operating characteristic (JAFROC), lesion sensitivity, area under the receiver operating characteristic curve (ROC AUC), sensitivity, and specificity. Three independent variables were self-reported using a questionnaire completed immediately before the mammography reading session: occupational exhaustion (low to moderate or high, assessed by the Emotional Exhaustion subscale of the Maslach Burnout Inventory-General Survey), recent travel (traveler or non-traveler), and hunger status (hungry or not hungry). Mann-Whitney U tests were used to examine differences in reading performance associated with each variable.

Participants with high occupational exhaustion had significantly lower JAFROC scores compared to those with low to moderate exhaustion (0.213 vs 0.383; p=0.041). Recently traveled participants had significantly lower ROC AUC scores (0.681 vs. 0.772; p=0.03) and lower sensitivity (70.0% vs. 80.0%; p=0.04) than non-travelers. Hungry participants exhibited higher sensitivity (85.0% vs. 70.0%; p=0.04) but lower specificity (40.0% vs. 65.0%; p=0.02) compared to non-hungry participants.

Occupational exhaustion was associated with poorer JAFROC scores, recent travel lowered sensitivity and overall diagnostic accuracy, and hunger increased sensitivity at the cost of specificity. These findings highlight the importance of addressing radiologists' well-being by optimizing workloads, allowing recovery periods after travel, and ensuring structured meal schedules. Future research should explore real-world clinical settings and targeted interventions, including AI integration.