Evidence map›Paper›PMID 41425775›Full record

ArticleFrontiers in sleep2022

Pilot study of personalized sleep-coaching messages to promote healthy sleeping behaviors.

Logan D Schneider, Andrew Barakat, Zainab Ali, Christian Concepcion, James A Taylor, Allen Jiang

Abstract read
In one paragraph

Article in Frontiers in sleep, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Logan D SchneiderAlphabet, Inc, Mountain View, CA, United States.
Andrew BarakatAlphabet, Inc, Mountain View, CA, United States.
Zainab AliPacific Bioscience, Menlo Park, CA, United States.
Christian ConcepcionAlphabet, Inc, Mountain View, CA, United States.
James A TaylorAlphabet, Inc, Mountain View, CA, United States.
Allen JiangAlphabet, Inc, Mountain View, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Assess a program of sleep schedule recommendations and behavior change "nudges" algorithmically selected using passively collected, longitudinal sleep data. Improvements were primarily measured by sleep schedule adherence and changes in sleep health (quantified by the RU_SATED framework). Methods: This study used a convenience sample of self-screening volunteers, responding to recruitment emails. Sleep data was gathered with a commercial under-mattress sensor through three phases: baseline passive data collection-2 weeks; intervention-4 weeks; maintenance monitoring passive data collection-8 weeks. The intervention included sleep schedule recommendations and SMS "nudges," based on rules and recommendations derived from the extant literature. A daily sleep-health score (based on RU_SATED) was derived from passively collected sleep data and daily self-reports of alertness and sleep quality. Results: Twenty-six participants (34.92 ± 10.08-years-old; 20M:6F) had adequate data for analysis. The main findings were: (1) Adherence-defined as a wake time (WT) within 30 min of the recommendation-rates did not differ significantly between the three study phases. However, there was a general decline in adherence over the course of the study, with adherence rates dropping by about 1.5%/week in a pattern of progressive delay of WTs. (2) Linear mixed models (LMMs) of individual sleep metrics did not demonstrate a significant change over the course of the intervention, possibly due to widely varying, yet relatively healthy, sleep patterns at baseline. (3) Comparatively, the composite, sleep-health (RU_SATED) score demonstrated general improvement over the intervention period, in association with higher rates of WT adherence. Conclusions: While, in general, adherence to a sleep schedule and individual dimensions of sleep health did not demonstrate meaningful improvements during the intervention phase, those individuals that were more consistently meeting the wake-time schedule recommendation had associated improvements in their overall sleep-health. As such, this pilot study demonstrates the feasibility and potential efficacy among more adherent individuals of implementing a sleep wellness coaching framework using passively collected sleep data and a rule-based coaching infrastructure.

Indexed as

behavior changecoachinghealthsleepwellness

Identifiers

PMID41425775
PMCPMC12713798

What OpenQuestion holds

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LicenceCC BY
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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.