Trial reportJournal of medical Internet research2025
Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial.
Trial report in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06795477 (Preventing Medication Dispensing Errors in Pharmacy Practice with Interpretable Machine Intelligence), which is not on this map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Preventing Medication Dispensing Errors in Pharmacy Practice with Interpretable Machine Intelligence: Wave 2
Who cites it
6 citing papers in PubMed.
- Effects of AI Assistance Timing on Pharmacists' Trust in Automated Pill Recognition Technology: Within-Participants Experimental Study.JMIR human factors · 2026Article
- AI-mediated environments and the reconfiguration of symbolic convergence: cognitive implications for shared meaning formation.Frontiers in psychology · 2026Article
- Beyond willingness: unpacking pharmacists' adoption of AI-driven clinical decision support systems through an extended UTAUT framework.Frontiers in public health · 2026Article
- Beyond Binary Decisions: Evaluating the Effects of AI Error Type on Trust and Performance in AI-Assisted Tasks.Human factors · 2025Article
- Difficulties in Emotion Regulation as a Mediator and Gender as a Moderator in the Relationship Between Problematic Digital Gaming and Life Satisfaction Among Adolescents.Behavioral sciences (Basel, Switzerland) · 2025Article
- Pharmacists' propensity to trust automated technologies: A demographic analysis.Journal of the American Pharmacists Association : JAPhAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundClinical decision support systems leveraging artificial intelligence (AI) are increasingly integrated into health care practices, including pharmacy medication verification. Communicating uncertainty in an AI prediction is viewed as an important mechanism for boosting human collaboration and trust. Yet, little is known about the effects on human cognition as a result of interacting with such types of AI advice.
objectiveThis study aimed to evaluate the cognitive interaction patterns of pharmacists during medication product verification when using an AI prototype. Moreover, we examine the impact of AI's assistance, both helpful and unhelpful, and the communication of uncertainty of AI-generated results on pharmacists' cognitive interaction with the prototype.
methodsIn a randomized controlled trial, 30 pharmacists from professional networks each performed 200 medication verification tasks while their eye movements were recorded using an online eye tracker. Participants completed 100 verifications without AI assistance and 100 with AI assistance (either with black box help without uncertainty information or uncertainty-aware help, which displays AI uncertainty). Fixation patterns (first and last areas fixated, number of fixations, fixation duration, and dwell times) were analyzed in relation to AI help type and helpfulness.
resultsPharmacists shifted 19%-26% of their total fixations to AI-generated regions when these were available, suggesting the integration of AI advice in decision-making. AI assistance did not reduce the number of fixations on fill images, which remained the primary focus area. Unhelpful AI advice led to longer dwell times on reference and fill images, indicating increased cognitive processing. Displaying AI uncertainty led to longer cognitive processing times as measured by dwell times in original images.
conclusionsUnhelpful AI increases cognitive processing time in the original images. Transparency in AI is needed in "black box" systems, but showing more information can add a cognitive burden. Therefore, the communication of uncertainty should be optimized and integrated into clinical workflows using user-centered design to avoid increasing cognitive load or impeding clinicians' original workflow.
trial registrationClinicalTrials.gov NCT06795477; https://clinicaltrials.gov/study/NCT06795477.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.