Emotional intelligence and the perception of good leadership in healthcare: a mixed-methods study
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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 (AI) 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 α); 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 α >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 α=0.05.
Summary Box
What this paper adds
What is already known on this topic
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Emotional intelligence (EI) is consistently identified as an important attribute of effective healthcare leaders, and a range of generic leadership instruments are available (e.g. Northouse’s LTQ).
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Leadership-selection criteria in healthcare have historically been derived top-down from organisational, regulatory or academic frameworks rather than from the views of the clinicians who must follow those leaders.
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Existing instruments treat candidate leadership traits as equally weighted, even though clinical leaders intuitively rank some attributes (e.g. integrity) far above others.
What this study adds
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10-item, follower-derived, weighted Leadership Enabling Traits Survey (LETS) instrument was developed from focus groups with senior medical staff and ranked by survey, providing an empirically-weighted alternative to existing equally-weighted tools.
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top five LETS traits (integrity, communication, vision, emotional intelligence, empathy) matched the unprompted top five traits generated by a contemporary large-language model (LAIT), suggesting that EI-related attributes are a stable feature of leadership representations in both human and machine-generated sources.
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empirically-derived weights revealed material divergence between context-specific (LETS) and generic (LTQ) instruments when EI-related and non-EI traits were considered separately, supporting the case for situation-specific leadership tools rather than universal scoring.
