Evidence map›Paper›PMID 40740477›Full record

ArticleBMC digital health2025

Using night shift worker and employee health stakeholder perspectives to inform the development of Arcashift

Paige Coyne, Matthew B Jennings, Sara Santarossa, Dana Murphy, Maya Zreik, Helena Bryans, Christopher Drake, Olivia Walch, Philip Cheng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Paige CoyneDepartment of Public Health Sciences, Henry Ford Health, Detroit, MI USA.
Matthew B JenningsSleep Disorders and Research Center, Henry Ford Health, Novi, MI USA.
Sara SantarossaDepartment of Public Health Sciences, Henry Ford Health, Detroit, MI USA.
Dana MurphyDepartment of Public Health Sciences, Henry Ford Health, Detroit, MI USA.
Maya ZreikDepartment of Public Health Sciences, Henry Ford Health, Detroit, MI USA.
Helena BryansSleep Disorders and Research Center, Henry Ford Health, Novi, MI USA.
Christopher DrakeHFH+MSU, East Lansing, MI USA.
Olivia WalchArcascope, Arlington, VA USA.
Philip ChengHFH+MSU, East Lansing, MI USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: More than a quarter of night shift workers (NSWs) have symptoms severe enough to meet diagnostic criteria for Shift Work Disorder (SWD). This study sought to understand the experiences of both NSWs and employee health stakeholders (EHSs) to inform the design of an effective digital precision circadian medicine intervention for NSWs experiencing SWD. Methods: NSWs ( Results: The reflexive thematic analysis produced three themes. The first theme, Conclusion: This study represents a strong preliminary step toward the development of an app for the intervention of SWD. There is a critical need for a real-world intervention for SWD, and stakeholders were optimistic about the potential of an app to help address SWD. Future work is needed to assess the extent to which the proposed app, informed by these stakeholder insights, is able to improve outcomes for employees and ROIs for EHSs. Supplementary Information: The online version contains supplementary material available at 10.1186/s44247-025-00167-3.

Indexed as

Circadian rhythmFocus groupsInterviewsReflexive thematic analysisSleep

Identifiers

PMID40740477
PMCPMC12304005

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.