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Eye tracking: empirical foundations for a minimal reporting guideline.

Kenneth HolmqvistSaga Lee ÖrbomIgnace T C HoogeDiederick C NiehorsterRobert G AlexanderRichard AnderssonJeroen S BenjaminsPieter BlignautAnne-Marie BrouwerLewis L ChuangKirsten A DalrympleDenis DriegheMatt J DunnUlrich EttingerSusann FiedlerTom FoulshamJos N van der GeestDan Witzner HansenSamuel B HuttonEnkelejda KasneciAlan KingstonePaul C KnoxEllen M KokHelena LeeJoy Yeonjoo LeeJukka M LeppänenStephen MacknikPäivi MajarantaSusana Martinez-CondeAntje NuthmannMarcus NyströmJacob L OrquinJorge Otero-MillanSoon Young ParkStanislav PopelkaFrank ProudlockFrank RenkewitzAustin RoordaMichael Schulte-MecklenbeckBonita SharifFrederick ShicMark ShovmanMervyn G ThomasWard VenrooijRaimondas ZemblysRoy S Hessels
Published in: Behavior research methods (2022)
In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section "An empirically based minimal reporting guideline").
Keyphrases
  • adverse drug
  • healthcare
  • primary care
  • emergency department
  • randomized controlled trial
  • machine learning
  • systematic review
  • artificial intelligence
  • drug induced