In the fast-changing landscape of scientific research, standardization and increasing the useability of data are becoming increasingly important. Understanding the nuances of non-visual responses to light and its powerful effects on physiology and behavior beyond enabling vision is a frontier with immense potential. However, a significant challenge persists: a need for more consensus in reporting light characteristics across studies. This inconsistency hampers reproducibility and complicates direct comparisons between findings, limiting the ability to conduct meta-analyses and synthesize evidence in the field comprehensively.
Neurobiological studies delving into the non-visual effects of light are, without a doubt, resource-intensive endeavors. Often spanning months to years, these studies require considerable time and effort. The stakes are high, making the need for enhanced reporting practices paramount. Improved reporting represents a pivotal step forward, streamlining methodologies, fostering reproducibility, and advancing the field.
One way to enhance reporting in biomedical research is by creating reporting checklists via consensus processes that engage extensive groups of experts. We conducted a four-step Delphi process to create a dedicated reporting checklist and an accompanying Elaboration and Explanation (E&E) document for laboratory-based intervention studies that investigate the impact of ocular light exposure on non-visual physiology in human research participants.
The Delphi process consisted of three online questionnaire-based feedback rounds, one face-to-face group discussion, and a pilot-testing phase to determine which items should be included in the survey, to specify their preferred reporting format, and to reach consensus on which items are deemed essential to report. In the face-to-face discussion, we addressed any unresolved questions or concerns and explored the dissemination and impact of the checklist and E&E document. Independent pilot testing aimed to determine the checklist’s usability and clarity to induce minor refinements.
A preliminary inventory of 61 items associated with reporting light-based interventions underwent a consolidation process, resulting in a final checklist comprising 25 items, achieved through consensus among experts (final n = 60). Nine items were identified as essential for reporting, irrespective of the research question or context. The Explanation and Elaboration (E&E) document provides detailed descriptions for each item. The independent pilot testing phase prompted minor textual refinements in the checklist and E&E document.
Implementing a consensus-based approach promises to change the landscape of studies using light as an intervention. The ENLIGHT (Expert Network on LIGHT Interventions: ENLIGHT) Checklist is the first consensus-driven checklist for documenting and reporting light-based interventions in biomedical studies. Formulated through a systematic approach involving extensive interactions with field experts and prospective checklist users, its development recognizes the significant complexities in the field and provides an accessible tool for all working in this area. Even minimal exposure to light can elicit effects, and slight differences in delivery method, intensity, or spectral composition may lead to substantial variations in observed responses, necessitating agreement on reporting practices. This initiative will pave the way for increased reproducibility, facilitate direct comparisons between studies, and unlock the potential for meta-analyses and evidence synthesis.
If you are involved in light-based research or are passionate about advancing scientific methodologies, we invite you to explore the ENLIGHT Checklist and join us in revolutionizing how we document and report findings in this crucial area.
ENLIGHT Checklist website: http://enlight-statement.org/
Spitschan, M., Kervezee, L., Lok, R., McGlashan, E., Najjar, R. P., & Consortium, E. (2023). ENLIGHT: A consensus checklist for reporting laboratory-based studies on the non-visual effects of light in humans. EBioMedicine, 98, 104889. https://doi.org/10.1016/j.ebiom.2023.104889
Renske Lok, Stanford University
Manuel Spitschan, Technical University of Munich
Laura Kervezee, Leiden University Medical Center
Elise McGlashan, University of Melbourne
Raymond P. Najjar, National University of Singapore
