Evidence map›Paper›PMID 39561203›Full record

ArticlePLOS digital health2024

Meeting people where they are: Crowdsourcing goal-specific personalized wellness practices.

Johanna E Hidalgo, Julia Kim, Jordan Llorin, Kathryn Stanton, Josh Cherian, Laura Bloomfield, Mikaela Fudolig, Matthew Price, Jennifer Ha, Natalie Noble and 5 more

Abstract read
In one paragraph

Article in PLOS digital health, 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

15 authors.

Johanna E HidalgoDepartment of Psychological Science, University of Vermont, Burlington, VT, United States of America.ORCID https://orcid.org/0000-0002-2604-3741
Julia KimProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.
Jordan LlorinProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.
Kathryn StantonProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.
Josh CherianWake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America.
Laura BloomfieldProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.ORCID https://orcid.org/0000-0003-0416-3440
Mikaela FudoligProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.
Matthew PriceDepartment of Psychological Science, University of Vermont, Burlington, VT, United States of America.
Jennifer HaDepartment of Psychological Science, University of Vermont, Burlington, VT, United States of America.ORCID https://orcid.org/0000-0002-8882-2011
Natalie NobleDepartment of Psychological Science, University of Vermont, Burlington, VT, United States of America.
Christopher M DanforthProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.
Peter Sheridan DoddsProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.
Jason FanningDepartment of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, United States of America.
Ryan S McGinnisProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.
Ellen W McGinnisProject LEMURS (Lived Experience Measured Using Rings), University of Vermont, Burlington, VT, United States of America.

Funding

Digital Phenotyping To Screen For Early Childhood Internalizing DisordersK23MH123031 · NIMH · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI MCGINNIS, ELLEN WAXLER · 2021 to 2024
$643k
NIMH NIH HHS K23 MH123031
6 · The paper itself

Abstract

objectivesDespite the development of efficacious wellness interventions, sustainable wellness behavior change remains challenging. To optimize engagement, initiating small behaviors that build upon existing practices congruent with individuals' lifestyles may promote sustainable wellness behavior change. In this study, we crowd-sourced helpful, flexible, and engaging wellness practices to identify a list of those commonly used for improving sleep, productivity, and physical, emotional, and social wellness from participants who felt they had been successful in these dimensions.

methodWe recruited a representative sample of 992 U.S. residents to survey the wellness dimensions in which they had achieved success and their specific wellness practices.

resultsResponses were aggregated across demographic, health, lifestyle factors, and wellness dimension. Exploration of these data revealed that there was little overlap in preferred practices across wellness dimensions. Within wellness dimensions, preferred practices were similar across demographic factors, especially within the top 3-4 most selected practices. Interestingly, daily wellness practices differ from those typically recommended as efficacious by research studies and seem to be impacted by health status (e.g., depression, cardiovascular disease). Additionally, we developed and provide for public use a web dashboard that visualizes and enables exploration of the study results.

conclusionsFindings identify personalized, sustainable wellness practices targeted at specific wellness dimensions. Future studies could leverage tailored practices as recommendations for optimizing the development of healthier behaviors.

Identifiers

PMID39561203
PMCPMC11575832

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.