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A Peer-recognition ("Like") Button Embedded in the Radiology Reporting Workflow: A Single-center Feasibility Study
Rintaro Ito1, Marina Higashi2, Rei Nakamichi2
1Department of Innovative BioMedical Visualization (iBMV), Nagoya University Graduate School of Medicine, Nagoya, Japan.
Rationale And Objectives:
Radiologists rarely receive routine positive feedback on their reports. We developed a single-click "Like" button for peer recognition, embedded it in a live reporting workflow, and assessed its feasibility and radiologist attitudes.
Materials And Methods:
This Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)-compliant single-center cross-sectional survey followed four months of routine use (January-May 2025). Of 25 eligible radiologists, 11 chose to use the system (users), and 14 did not (nonusers). Users rated experienced effects, and nonusers rated expected effects on 17 conceptually paired items, so group comparisons are associational; we used Mann-Whitney U tests, Hedges' g, and Bonferroni or Benjamini-Hochberg correction for multiplicity.
Results:
The system ran throughout the study without workflow disruption: 684 Likes on 658 reports, and 11 of 25 radiologists (44%) became active users. Overall satisfaction was significantly higher in Users (1.45 ± 0.52, n = 11) than nonusers (0.64 ± 0.63, n = 14; g = 1.34, 95% CI 0.49-2.18; Bonferroni p = 0.009); intradepartmental intent to keep using the system was the strongest item-level signal (g = 1.59). Motivation and perceived usefulness favored Users but were not significant after correction. In six nonusers who later used the system, experienced ratings resembled prior expectations; satisfaction decreased in none. The satisfaction difference was unchanged after adjusting for experience, and workload showed no significant change (n = 7, p = 0.297).
Conclusion:
A single-click peer-recognition system was feasible and achieved sustained voluntary adoption; radiologists who chose to use it reported high satisfaction, with no detectable workload penalty. These hypothesis-generating findings support a randomized or stepped-wedge trial with a common questionnaire and objective endpoints.
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