Evidence map›Paper›PMID 24955033›Full record

ArticleSleep and biological rhythms2014

Sleepiness and Safety: Where Biology Needs Technology.

Takashi Abe, Daniel Mollicone, Mathias Basner, David F Dinges

Open access · bronzeAbstract read
In one paragraph

Article in Sleep and biological rhythms, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.6field-weighted citation impact, top 8% of its field
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

11 citing papers in PubMed, 36 citations in OpenAlex.

  1. Review
  2. Review
  3. PERCLOS-based technologies for detecting drowsiness: current evidence and future directions.Sleep advances : a journal of the Sleep Research Society · 2023
    Review
  4. Article
  5. Review
  6. Review
  7. Article
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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

4 authors at 3 institutions in 2 countries.

Takashi AbeSpace Biomedical Research Office, Flight Crew Operations and Technology Department, Tsukuba Space Center, Japan Aerospace Exploration Agency, Tsukuba, Ibaraki, Japan.
Daniel MolliconePulsar Informatics, Inc., Philadelphia, Pennsylvania, USA.
Mathias BasnerDivision of Sleep and Chronobiology, Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
David F DingesDivision of Sleep and Chronobiology, Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
University of Pennsylvania · USJapan Aerospace Exploration Agency · JPPulsar Informatics (United States) · US

Funding

NEUROBEHAVIORAL EFFECTS OF PARTIAL SLEEP DEPRIVATIONR01NR004281 · NINR · UNIVERSITY OF PENNSYLVANIA · PI DINGES, DAVID F · 1995 to 2014
$7.9M
NINR NIH HHS R01 NR004281
6 · The paper itself

Abstract

Maintaining human alertness and behavioral capability under conditions of sleep loss and circadian misalignment requires fatigue management technologies due to: (1) dynamic nonlinear modulation of performance capability by the interaction of sleep homeostatic drive and circadian regulation; (2) large differences among people in neurobehavioral vulnerability to sleep loss; (3) error in subjective estimates of fatigue on performance; and (4) to inform people of the need for recovery sleep. Two promising areas of technology have emerged for managing fatigue risk in safety-sensitive occupations. The first involves preventing fatigue by optimizing work schedules using biomathematical models of performance changes associated with sleep homeostatic and circadian dynamics. Increasingly these mathematical models account for individual differences to achieve a more accurate estimate of the timing and magnitude of fatigue effects on individuals. The second area involves technologies for detecting transient fatigue from drowsiness. The Psychomotor Vigilance Test (PVT), which has been extensively validated to be sensitive to deficits in attention from sleep loss and circadian misalignment, is an example in this category. Two shorter-duration versions of the PVT recently have been developed for evaluating whether operators have sufficient behavioral alertness prior to or during work. Another example is online tracking the percent of slow eyelid closures (PERCLOS), which has been shown to reflect momentary fluctuations of vigilance. Technologies for predicting and detecting sleepiness/fatigue have the potential to predict and prevent operator errors and accidents in safety-sensitive occupations, as well as physiological and mental diseases due to inadequate sleep and circadian misalignment.

Indexed as

biomathematical modelsdrowsinessfatiguePERCLOSPsychomotor Vigilance Test (PVT)safetySleepinessvigilance

Identifiers

PMID24955033
PMCPMC4061704
OpenAlexW1527884358

What OpenQuestion holds

Textmetadata
LicenceTDM
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.