SynthesisJournal of the American Medical Informatics Association : JAMIA2017
Automation bias and verification complexity: a systematic review.
Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 141 papers, 3 of them syntheses that pooled it.
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
141 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Effectiveness, Safety, and Workflow Burden of Large Language Model-Based Medical Report Generation: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Contrastive explainable AI in healthcare: a systematic review of trends, benefits, research gaps, and future directions.BMC medical informatics and decision making · 2026Pooled it
- Drug-drug interactions and their harmful effects in hospitalised patients: a systematic review and meta-analysis.European journal of clinical pharmacology · 2018Pooled it
- Does the accuracy of medication administration documentation improve with electronic medication systems? A stepped-wedge cluster randomised trial.BMJ health & care informatics · 2026Trial
- Artificial intelligence algorithm improves radiologists' bone age assessment accuracy.Journal of the Chinese Medical Association : JCMA · 2025Trial
- Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial.Journal of the American Medical Informatics Association : JAMIA · 2024Trial
- From promise to practice: digital health through the lens of neonatal care.Lancet regional health. Americas · 2026Review
- Network-based characterization of latent co-testing patterns in antimicrobial susceptibility testing.iScience · 2026Article
- Regulating the drafting fiction: A qualitative content analysis of official guidance and regulator documents on AI scribe adoption and use in healthcare.PLOS digital health · 2026Article
- Ethical and Legal Challenges of Partially and Fully Autonomous AI in Healthcare: Reinterpreting Liability and Preserving Trust.Bioethics · 2026Article
- Article
- Multimodal Large Language Models for Dental Chart Image Interpretation: Cross-Sectional Benchmarking Study With Students and Clinicians.JMIR medical education · 2026Article
- Artificial Intelligence for Cerebral Aneurysm Management: Integrating Imaging, Hemodynamics, and Clinical Decision Support.Journal of imaging informatics in medicine · 2026Review
- Closed-Loop AI Systems for Arrhythmia Management: Toward Predictive, Personalized, and Safe Cardiac Care.Clinical cardiology · 2026Review
- Artificial intelligence as cognitive support in emergency medicine.Clinical and experimental emergency medicine · 2026Article
- Theoretical Exploration of Error Thresholds for Clinical AI Decision Support in Nursing: Exploratory Simulation Study Grounded in Human-AI Reliance Data.JMIR nursing · 2026Article
- Divergent impacts of explainable AI for dermatological diagnosis on clinicians versus lay people.Nature medicine · 2026Article
- Explainability in context: calibrating appropriate trust and reliance in artificial intelligence.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Clinical predictive artificial intelligence evaluation: A narrative review of trial designs and practical considerations.PLOS digital health · 2026Review
- Needs and Concerns Regarding a Pediatric Palliative Telehealth App for Use in Palliative Home Care for Adults Among Providers in Germany: Embedded Mixed Methods Study.JMIR formative research · 2026Article
81 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionWhile potentially reducing decision errors, decision support systems can introduce new types of errors. Automation bias (AB) happens when users become overreliant on decision support, which reduces vigilance in information seeking and processing. Most research originates from the human factors literature, where the prevailing view is that AB occurs only in multitasking environments.
objectivesThis review seeks to compare the human factors and health care literature, focusing on the apparent association of AB with multitasking and task complexity. DATA SOURCES: EMBASE, Medline, Compendex, Inspec, IEEE Xplore, Scopus, Web of Science, PsycINFO, and Business Source Premiere from 1983 to 2015. STUDY SELECTION: Evaluation studies where task execution was assisted by automation and resulted in errors were included. Participants needed to be able to verify automation correctness and perform the task manually.
methodsTasks were identified and grouped. Task and automation type and presence of multitasking were noted. Each task was rated for its verification complexity.
resultsOf 890 papers identified, 40 met the inclusion criteria; 6 were in health care. Contrary to the prevailing human factors view, AB was found in single tasks, typically involving diagnosis rather than monitoring, and with high verification complexity. LIMITATIONS: The literature is fragmented, with large discrepancies in how AB is reported. Few studies reported the statistical significance of AB compared to a control condition.
conclusionAB appears to be associated with the degree of cognitive load experienced in decision tasks, and appears to not be uniquely associated with multitasking. Strategies to minimize AB might focus on cognitive load reduction.
Indexed as
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What OpenQuestion 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 OpenQuestion graph.