Evidence map›Paper›PMID 39211574›Full record

ArticleBMC digital health2024

Metadata recommendations for light logging and dosimetry datasets.

Manuel Spitschan, Grégory Hammad, Christine Blume, Christina Schmidt, Debra J Skene, Katharina Wulff, Nayantara Santhi, Johannes Zauner, Mirjam Münch

Abstract read
In one paragraph

Article in BMC digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Manuel SpitschanTranslational Sensory & Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.ORCID 0000-0002-8572-9268
Grégory HammadChronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID 0000-0003-1083-3869
Christine BlumeCentre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland.ORCID 0000-0003-2328-9612
Christina SchmidtSleep & Chronobiology Group, GIGA-CRC-In Vivo Imaging Research Unit, University of Liège, Liège, Belgium.ORCID 0000-0002-1114-5112
Debra J SkeneChronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.ORCID 0000-0001-8202-6180
Katharina WulffDepartment of Molecular Biology, Umeå University, Umeå, Sweden.ORCID 0000-0003-2480-3329
Nayantara SanthiDepartment of Psychology, Northumbria University, Newcastle, UK.ORCID 0000-0003-4568-1447
Johannes ZaunerTranslational Sensory & Circadian Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.ORCID 0000-0003-2171-4566
Mirjam MünchCentre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland.ORCID 0000-0003-2087-9916

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background: Light exposure significantly impacts human health, regulating our circadian clock, sleep-wake cycle and other physiological processes. With the emergence of wearable light loggers and dosimeters, research on real-world light exposure effects is growing. There is a critical need to standardize data collection and documentation across studies. Results: This article proposes a new metadata descriptor designed to capture crucial information within personalized light exposure datasets collected with wearable light loggers and dosimeters. The descriptor, developed collaboratively by international experts, has a modular structure for future expansion and customization. It covers four key domains: study design, participant characteristics, dataset details, and device specifications. Each domain includes specific metadata fields for comprehensive documentation. The user-friendly descriptor is available in JSON format. A web interface simplifies generating compliant JSON files for broad accessibility. Version control allows for future improvements. Conclusions: Our metadata descriptor empowers researchers to enhance the quality and value of their light dosimetry datasets by making them FAIR (findable, accessible, interoperable and reusable). Ultimately, its adoption will advance our understanding of how light exposure affects human physiology and behaviour in real-world settings.

Indexed as

IprgcJsonLight loggerLight loggingMelanopicMelanopsinMetadataMetadata descriptorNon-visual effects of lightPersonal light exposure

Identifiers

PMID39211574
PMCPMC11349852

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.