Evidence map›Paper›PMID 38867429›Full record

ArticleBehavioral sleep medicine

Integration of Sensor-Based and Self-Reported Metrics in a Sleep Diary: A Pilot Exploration.

Sarah Conklin, Jessica R Dietch, Golshan Kargosha, Faith Luyster, Molly Atwood, Matthew S Tenan, Gary Zammit, Nilanjan Banerjee, Justin Brooks

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Behavioral sleep medicine. 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.

Sarah ConklinDepartment of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA.
Jessica R DietchSchool of Psychological Science, Oregon State University, Corvallis, OR, USA.
Golshan KargoshaDepartment of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA.
Faith LuysterSchool of Nursing, University of Pittsburgh, Pittsburgh, PA, USA.
Molly AtwoodDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Matthew S TenanRockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA.
Gary ZammitAdministration, Clinilabs Drug Development Corporation, New York, NY, USA.
Nilanjan BanerjeeDepartment of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA.
Justin BrooksDepartment of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA.

Funding

Supplement to sleep health intervention for shift workersK23HL157698 · NHLBI · OREGON STATE UNIVERSITY · PI Jessica R Dietch · 2022 to 2026
$1.1M
Improved Patient Reported Outcomes (iPRO) -Sleep Diary: A Tool to Improve Sleep Assessment in Clinical TrialsR43HL167541 · NHLBI · D-PRIME LLC · PI BROOKS, JUSTIN · 2023 to 2024
$396k
NHLBI NIH HHS K23 HL157698NHLBI NIH HHS R43 HL167541
6 · The paper itself

Abstract

objectivesDiscrepancies between sleep diaries and sensor-based sleep parameters are widely recognized. This study examined the effect of showing sensor-based sleep parameters while completing a daily diary. The provision of sensor-based data was expected to reduce variance but not change the mean of self-reported sleep parameters, which would in turn align better with sensor-based data compared to a control diary.

methodIn a crossover study, 24 volunteers completed week-long periods of control diary (digital sleep diary without sensor-based data feedback) or integrated diary (diary with device feedback), washout, and then the other diary condition.

resultsThe integrated diary reduced self-reported total sleep time (TST) by <10 minutes and reduced variance in TST. The integrated diary did not impact mean sleep onset latency (SOL) and, unexpectedly, the variance in SOL increased. The integrated diary improved both bias and limits of agreement for SOL and TST.

conclusionsIntegration of wearable, sensor-based device data in a sleep diary has little impact on means, mixed evidence for less variance, and better agreement with sensor-based data than a traditional diary. How the diary impacts reporting and sensor-based sleep measurements should be explored.

Indexed as

Cross-Over StudiesSelf ReportSleepAdultDiaries as TopicFemaleHumansMaleMedical RecordsPilot ProjectsSleep LatencyWearable Electronic DevicesYoung Adult

Identifiers

PMID38867429
PMCPMC11365783

What OpenQuestion holds

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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.