ArticleJournal of the American Pharmacists Association : JAPhA
Pharmacists' propensity to trust automated technologies: A demographic analysis.
Article in Journal of the American Pharmacists Association : JAPhA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundArtificial intelligence (AI), in conjunction with automated technologies, is being deployed in pharmacies. Little research has been published regarding pharmacists' general willingness to trust AI. Understanding pharmacists' propensity to trust (PTT) AI may help guide the successful implementation and adoption of AI tools.
objectiveThe objective is to assess pharmacists' PTT AI with automated technology and identify factors that may influence this tendency.
methodsAs part of a larger study, licensed pharmacists completed a demographics survey and the PTT survey before testing AI advice on medication fills. The PTT survey consisted of 6 statements about AI and pharmacists indicated their level of agreement using a 5-point Likert scale, with higher numbers indicating more agreement. Summary statistics, Kruskal-Wallis tests, linear regressions, and confidence intervals were calculated.
resultsNinety-nine pharmacists completed the surveys. The mean pharmacist age was 38.1 years and the median PTT score was 3.83 (P < 0.001). Age was a statistically significant predictor of PTT (β = 0.02, P < 0.001, and R
conclusionsOlder and more experienced pharmacists had higher PTT scores. Exposure to AI tools during pharmacy education may help younger pharmacists optimize their PTT AI.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.