Evidence map›Paper›PMID 39711534›Full record

ArticleResearch square2024

Can Wearable Technology Help Guide Dieting Safety?

Maya Tang, Joseph Powell, Xiao Li

Abstract readPreprint
In one paragraph

Article in Research square, 2024. 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

3 authors.

Maya TangHathaway Brown School.
Joseph PowellCase Western Reserve University.ORCID https://orcid.org/0000-0002-0798-2196
Xiao LiCase Western Reserve University.ORCID https://orcid.org/0000-0002-6413-3481

Funding

Using Wearable Technology to Assess Recovery and Detect Post-Operative Complications Following Cardiothoracic SurgeryR01HL159170 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI Xiao Li, Chi-Fu Yang · 2022 to 2026
$3.5M
NHLBI NIH HHS R01 HL159170
6 · The paper itself

Abstract

Background: The safety of dietary interventions is often unmonitored. Wearable technology can track elevations in resting heart rate (RHR), a marker of physiologic stress, which may provide safety information that is incremental to self-reported data. Methods: A single subject was placed on an isocaloric diet for four weeks. In weeks # 1 and 4, timing of food consumption was unregulated. In week #2, food was consumed during a three-hour feeding window (one-meal-a-day, OMAD). During week #3, food was consumed at six intervals, spaced three hours apart (6-meal diet). A Fitbit Versa Results: Meal frequency did not affect the subject's weight. Hunger scores from morning and night were widely split on OMAD and relatively constant on the 6-meal diet. Energy, happiness, irritability, and sleep scores were more favorable on the 6-meal diet than on OMAD. RHR extracted from the wearable device was lower during the 6-meal diet than during OMAD, especially in the late afternoon, evening, and nighttime (p<0.05). Lower RHR during the 6-meal diet corresponded to more favorable questionnaire scores. Conclusions: Changes in RHR patterns acquired by wearable technology are promising indicators of physiologic stress during dietary interventions. Wearable technology can provide physiologic data that are complementary to questionnaire scores or timed manual measurements.

Indexed as

dietingresting heart ratewearable technology

Identifiers

PMID39711534
PMCPMC11661416

What OpenQuestion holds

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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.