Evidence map›Paper›PMID 33438575›Full record

ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2021

The accuracy of the THIM wearable device for estimating sleep onset latency.

Hannah Scott, Ashwin Whitelaw, Alex Canty, Nicole Lovato, Leon Lack

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In one paragraph

Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Hannah ScottCollege of Education, Psychology and Social Work, Flinders University, Adelaide, Australia.
Ashwin WhitelawCollege of Medicine and Public Health, Adelaide Institute for Sleep Health: A Flinders Centre of Research Excellence, Flinders University, Adelaide, Australia.
Alex CantyCollege of Education, Psychology and Social Work, Flinders University, Adelaide, Australia.
Nicole LovatoCollege of Medicine and Public Health, Adelaide Institute for Sleep Health: A Flinders Centre of Research Excellence, Flinders University, Adelaide, Australia.
Leon LackCollege of Education, Psychology and Social Work, Flinders University, Adelaide, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectivesTHIM is a wearable device designed to accurately estimate sleep onset. This article presents 2 studies that tested the original (study 1) and a refined (study 2) THIM algorithm against polysomnography (PSG) for estimating sleep onset latency.

methodsTwelve (study 1) and 20 (study 2) individuals slept in the laboratory on 2 nights where participants underwent THIM-administered sleep onset trials with simultaneous PSG recording. Participants attempted to fall asleep while using THIM, which woke them once it determined sleep onset.

resultsIn study 1, there was no significant difference between PSG (mean = 1.94 minutes, SD = 1.32) and THIM sleep onset latency (mean = 2.05 minutes, SD = 1.38) on the first or second night (P > .07). There were moderate correlations between PSG and THIM on both nights [r

conclusionsTHIM showed a high degree of correspondence and agreement with PSG for estimating sleep onset latency. Future research will investigate whether THIM is accurate with an insomnia sample for clinical purposes.

Indexed as

Sleep LatencyWearable Electronic DevicesActigraphyHumansPolysomnographyReproducibility of ResultsSleepactigraphyconsumer sleep technologyintensive sleep retrainingpolysomnographysleep onset latencywearable device

Identifiers

PMID33438575
PMCPMC8320504

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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.