ArticleBMJ open2025
The introduction and adoption of artificial intelligence in systematic literature reviews: a discrete choice experiment.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
objectivesSystematic literature reviews (SLRs) are essential for synthesising research evidence and guiding informed decision-making. However, SLRs require significant resources and substantial efforts in terms of workload. The introduction of artificial intelligence (AI) tools can reduce this workload. This study aims to investigate the preferences in SLR screening, focusing on trade-offs related to tool attributes.
designA discrete choice experiment (DCE) was performed in which participants completed 13 or 14 choice tasks featuring AI tools with varying attributes.
settingData were collected via an online survey, where participants provided background on their education and experience.
participantsProfessionals who have published SLRs registered on Pubmed, or who were affiliated with a recent Health Economics and Outcomes Research conference were included as participants.
interventionsThe use of a hypothetical AI tool in SLRs with different attributes was considered by the participants. Key attributes for AI tools were identified through a literature review and expert consultations. These attributes included the AI tool's role in screening, required user proficiency, sensitivity, workload reduction and the investment needed for training. PRIMARY OUTCOME MEASURES: The participants' adoption of the AI tool, that is, the likelihood of preferring the AI tool in the choice experiment, considering different configurations of attribute levels, as captured through the DCE choice tasks. Statistical analysis was performed using conditional multinomial logit. An additional analysis was performed by including the demographic characteristics (such as education, experience with SLR publication and familiarity with AI) as interaction variables.
resultsThe study received responses from 187 participants with diverse experience in performing SLRs and AI use. The familiarity with AI was generally low, with 55.6% of participants being (very) unfamiliar with AI. In contrast, intermediate proficiency in AI tools is positively associated with adoption (p=0.030). Similarly, workload reduction is also strongly linked to adoption (p<0.001). Interestingly, if expert proficiency is needed for the AI, authors with more scientific experience in their profession are less likely to adopt AI (p=0.009). However, more experience specifically with SLR publications increases AI adoption likelihood (p=0.001).
conclusionsThe findings suggest that workload reduction is not the only consideration for SLR reviewers when using AI tools. The key to AI adoption in SLRs is creating reliable, workload-reducing tools that assist rather than replace human reviewers, with moderate proficiency requirements and high sensitivity.
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