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ENLIGHT: A consensus checklist for reporting laboratory-based studies on the non-visual effects of light in humans

MPG-Autoren
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Spitschan,  M       
Research Group Translational Sensory and Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Spitschan, M., Kervezee, L., Lok, R., McGlashan, E., Najjar, R., & ENLIGHT Consortium (2023). ENLIGHT: A consensus checklist for reporting laboratory-based studies on the non-visual effects of light in humans. EBioMedicine, 98: 104889. doi:10.1016/j.ebiom.2023.104889.


Zitierlink: https://hdl.handle.net/21.11116/0000-000E-00F5-D
Zusammenfassung
Background: There is no consensus on reporting light characteristics in studies investigating non-visual responses to light. This project aimed to develop a reporting checklist for laboratory-based investigations on the impact of light on non-visual physiology.
Methods: A four-step modified Delphi process (three questionnaire-based feedback rounds and one face-to-face group discussion) involving international experts was conducted to reach consensus on the items to be included in the checklist. Following the consensus process, the resulting checklist was tested in a pilot phase with independent experts.
Findings: An initial list of 61 items related to reporting light-based interventions was condensed to a final checklist containing 25 items, based upon consensus among experts (final n = 60). Nine items were deemed necessary to report regardless of research question or context. A description of each item is provided in the accompanying Explanation and Elaboration (E&E) document. The independent pilot testing phase led to minor textual clarifications in the checklist and E&E document.
Interpretation: The ENLIGHT Checklist is the first consensus-based checklist for documenting and reporting ocular light-based interventions for human studies. The implementation of the checklist will enhance the impact of light-based research by ensuring comprehensive documentation, enhancing reproducibility, and enabling data aggregation across studies.