ArticlemedRxiv : the preprint server for health sciences2025
Identifying chest-worn light logger adherence: a validation study.
Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Updated by
Authors and funding
7 authors.
Funding
Abstract
Background: Light exposure plays an important role in overall health because it entrains circadian rhythms. Recent technological advances in wearable light loggers allow measurement daily light exposure habits. Using a chest-worn light logger, our goal was to 1) develop methodology for differentiating adherent versus non-adherent use, and 2) define differences in lighting intensity in indoor and outdoor environments, to improve data reliability in future clinical studies using this technology. Methods: Five testers used a 10-channel chest worn light logging device under different conditions of wear and non-wear, and across a variety of indoor and outdoor lighting environments. Measurements from the light logger (photopic illuminance, device orientation, accelerometer data, time of day) were used to train and validate a logistic regression model to differentiate wear from non-wear and correct nighttime placement. This model was then applied to 20 adolescents and young adults with migraine who wore the light logger device for one week. Furthermore, measurements of photopic illuminance and melanopic equivalent daytime illuminance (mEDI) of indoor versus outdoor lighting environments were compared to identify the optimal distinction point between darker indoor and brighter outdoor environments for the chest-worn light logger. Results: Movement, device orientation, light, and time-of-day used as predictors in a logistic regression model had excellent differentiation between wear, non-wear and nighttime use (AUC 0.93 - 0.94), and retained good-to-excellent differentiation when applied to the validation dataset (AUC 0.84 - 0.91). When this model was applied to 20 participants with migraine, we found that 92.9% of participant-days and 71.4% of participant-nights demonstrated at least 80% appropriate use. For differentiating indoor and outdoor lighting environments, the optimal cut-point was 442 lux for photopic illuminance, and 412 lux for mEDI. Conclusions: We demonstrate that internal measurements from a chest-worn light logging device can reliably differentiate wear from non-wear. We also found that the optimal cut-off to differentiate indoor and outdoor lighting environments was similar though slightly lower than then 1,000 lux cut-offs traditionally used to define bright light conditions. These findings can be used to improve data reliability in studies of everyday light exposure in clinical populations using chest-worn light loggers.
Indexed as
Identifiers
What Socratic 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 Socratic graph.