ArticleJournal of sleep research2026
World of ScoreCraft: Novel Multi-Scorer Experiment on the Impact of a Decision Support System in Sleep Staging.
Article in Journal of sleep research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- World of ScoreCraft: Novel Multi-Scorer Experiment on the Impact of a Decision Support System in Sleep Staging.Journal of sleep research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Manual scoring of polysomnography (PSG) is a time-intensive task, prone to inter-scorer variability that can impact diagnostic reliability. This study investigates the integration of decision support systems (DSS) into PSG scoring workflows, focusing on their effects on accuracy, scoring time and potential biases toward recommendations from artificial intelligence (AI) compared to human-generated recommendations. Using a novel online scoring platform, we conducted a repeated-measures study with sleep technologists, who scored traditional and self-applied PSGs. Participants were occasionally presented with recommendations labelled as either human- or AI-generated. As the goal of this study was to isolate the effect of perceived recommendation sources on scorer behaviour, all recommendations were human-generated. We found that traditional PSGs tended to be scored slightly more accurately than self-applied PSGs, but this difference was not statistically significant. Correct recommendations significantly improved scoring accuracy for both PSG types, while incorrect recommendations reduced accuracy. No significant bias was observed toward or against AI-generated recommendations compared to human-generated recommendations. These findings highlight the potential of DSSs to enhance PSG scoring reliability. However, ensuring the accuracy of the suggestions is critical to maximising its benefits. Future research should explore the long-term impacts of DSS on scoring workflows and strategies for integrating AI in clinical practice.
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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.