Emotional intelligence and the perception of good leadership in healthcare: a mixed-methods study

Abstract Objective. To identify and rank the leadership traits most valued by medical staff in public hospitals, and to compare them with an established generic instrument and a generative artificial intelligence source. Design. Sequential exploratory qualitative-quantitative (QUAL QUAN) mixed-methods study: focus groups followed by an online ranking survey, with cross-comparison against the Northouse Leadership Traits Questionnaire (LTQ) and a ChatGPT derived list (LAIT). Setting. Major public hospital affiliated with Monash University, Melbourne, Australia, in 2023. Participants. Twenty-four senior medical staff (16 men, 8 women; 18 clinicians, 6 administrators) recruited through opportunistic sampling. Main outcome measures. Weighted ranking of the ten most desired leadership traits (Leadership Enabling Traits Survey, LETS); internal consistency (Cronbach s alpha); agreement between LETS and LTQ self-scores; and strong overlap with the AI-derived list. Results. The first most-weighted LETS traits were integrity (1.526), communication (1.435), compelling vision (1.404), emotional intelligence (1.040) and empathy (0.969), the same five identified by the AI source. Integrity was weighted 3.6 times more heavily than rebelliousness (0.424). Both LETS and LTQ achieved Cronbach s alpha > 0.7. Unweighted total self-scores did not differ between LETS (77.4 +/- 7.6) and LTQ (78.4 +/-6.9); weighted emotional intelligence related and other-trait sub-scores diverged significantly (p<0.001). Survey power was 45% at alpha=0.05.