Discussion
MDD
Our experiment examined how psychiatrists respond to information provided by CSTs, focusing on their quality (as providing correct or incorrect information) and perceived source (AI or a psychiatrist). Based on promising avenues for developing CSTs for treating MDD [Our primary finding that psychiatrists may be biased against information derived from AI is surprising, given positive perceptions of AI-based CSTs for treating MDD and other health conditions noted in prior work [For CST recommendation ratings, the source of information interacted with its quality (i.e. there was no preference for psychiatrist-derived recommendations on incorrect trials), whereas ratings were higher for psychiatrist-generated summaries, regardless of their quality. This discrepancy in findings between CST types may be related to differences in the potential negative impacts of consulting incorrect clinical note summaries and recommendations. An irrelevant summary may not be too detrimental, especially if other information is available, such as the patient’s symptom severity or prescribed medications depicted in the dashboard psychiatrists reviewed in our experiment (Fig. Our experiment provided little evidence that clinical expertise interacted with information quality to impact ratings, which does not support findings that inexperienced physicians are more likely to rely on incorrect diagnostic advice, as compared to experts [In our analysis examining the impact of familiarity with AI on CST ratings, psychiatrists who reported being more familiar with such methods rated AI-based summaries less favourably. This association is consistent with prior research, since psychiatrists more familiar with AI were less likely to follow AI-based treatment recommendations for MDD in another experiment [Although we did not design our experiment to examine why ratings of CSTs differ based on their perceived source, findings from our exploratory analyses provide some insight. We examined whether a preference for psychiatrist-generated information emerged due to a reluctance to criticise the opinions of a colleague, by examining whether this preference was more pronounced in residents, who may be more susceptible to such social pressures Although this was not found, the analysis does not rule out the possibility that social pressures influenced ratings, rather than unfavourable perceptions about AI. Furthermore, the human expert comparison in our experiment was described as the patient’s treating psychiatrist, which suggests a degree of expertise related to familiarity with the patient. This expertise would not be accessible to AI, but it may be particularly important given the interpersonal nature of MDD assessment and care [Our exploratory analysis of individual CST attributes nevertheless suggests that a preference for psychiatrist-generated CST information may be related to the use of heuristics. This preference was less pronounced for ratings of the summary’s accuracy and its inclusion of important information. Ratings for these attributes may have required a closer review of the summary’s information and a comparison with the full clinical note. This deeper review or reflection may have also been required for evaluating incorrect clinical recommendations, for which information source did not impact ratings. In contrast, psychiatrists may have relied on heuristic or intuitive thinking when rating their agreement with correct treatment recommendations, the utility of summaries, and their confidence in using both CSTs (Figs. 