Meeting people where they are: Crowdsourcing goal-specific personalized wellness practices - PubMed (original) (raw)
. 2024 Nov 19;3(11):e0000650.
doi: 10.1371/journal.pdig.0000650. eCollection 2024 Nov.
Julia Kim 2 3, Jordan Llorin 2 3, Kathryn Stanton 2 3, Josh Cherian 4 5, Laura Bloomfield 2 3 6 7 8, Mikaela Fudolig 2 3 7, Matthew Price 1 2, Jennifer Ha 1 2, Natalie Noble 1 2, Christopher M Danforth 2 3 8 9, Peter Sheridan Dodds 2 3 6 9, Jason Fanning 10, Ryan S McGinnis 2 4 5, Ellen W McGinnis 2 4 5
Affiliations
- PMID: 39561203
- PMCID: PMC11575832
- DOI: 10.1371/journal.pdig.0000650
Meeting people where they are: Crowdsourcing goal-specific personalized wellness practices
Johanna E Hidalgo et al. PLOS Digit Health. 2024.
Abstract
Objectives: Despite 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.
Method: We 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.
Results: Responses 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.
Conclusions: Findings 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.
Copyright: © 2024 Hidalgo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Conflict of interest statement
The authors have declared that no competing interests exist.
Figures
Fig 1. Percentage difference between individuals who chose health goals by dichotomous demographic, health, and lifestyle factors.
Gender (men—women); Sexual Orientation (heterosexual—sexual minority); Income (family earnings < 50,000—familyearnings>50,000—family earnings > 50,000—familyearnings>50,000); Age (17–30–50–76); Mental Health (MH) Diagnosis (At least one mental health diagnosis—none); Physical Health (PH) Diagnosis (At least one physical health diagnosis—none); Wearable Use (Wears a wearable device—does not); Meditation App Use (Uses Calm or Headspace Apps—not); Extraversion (High—Low; cut at mean); Perseverance (high–low; cut at mean).
Fig 2. Rank biased overlap scores for each health goal across demographics.
Gender (woman vs man); Sexual Orientation (heterosexual vs sexual minority); Income (family earnings < vs > $50,000); Age (17–30 vs 50–76); Mental Health (MH) Diagnosis (At least one mental health diagnosis vs none); Physical Health (PH) Diagnosis (At least one physical health diagnosis vs none); Wearable Use (Wears a wearable device vs does not); Meditation App Use (Uses Calm or Headspace Apps vs not); Extraversion (High vs Low cut at mean); Perseverance (high vs low cut at mean). RBO is a similarity measure that falls between 0–1, where an RBO of 0 means the lists are disjoint, and an RBO of 1 means the lists are identical.
Fig 3. Sankey diagrams.
(A) Top ten practices for improving sleep as preferred by participants with and without the Headspace or Calm apps. (B) Top ten practices for improving physical health as preferred by participants with and without cardiovascular disease. (C) Top ten practices for improving emotional health as preferred by participants with depression compared to those without any mental health condition. (D) Top ten practices for improving social wellness as preferred by participants with anxiety compared to those without any mental health conditions.
Fig 4. Top ten practices for social wellness by region of the United States.
The base layer map of the United States depicted in this figure is adapted from an open source freely available at
https://www.fla-shop.com/svg/usa/
, which permits use for both commercial and personal purposes with proper attribution, under the Creative Commons Attribution 4.0 International License (
https://creativecommons.org/licenses/by/4.0/
).
Fig 5. Dashboard screenshots.
(A) The landing page for the dashboard allows users to select the dimension they are interested in exploring further. (B) Upon selecting a health goal, users will see the top 10 practices for that particular health goal which they can filter by demographic by selecting filters from the dropdown on the left side of the screen. In the top right corner is a “Download CSV” button that allows users to download the raw data that was used to identify the top practices. (C) By choosing to compare all goals on the landing page, users can select goals and filters to view a bar graph of the RBO scores. (D) Users can view a Sankey diagram of the wellness practices chosen for a specific goal separated by a particular demographic, health, or lifestyle factor by clicking on a specific bar in the bar graph. The images and clip-art were created using both free and Pro elements from Canva (
). All elements are used in accordance with Canva’s Content License Agreement (
https://www.canva.com/policies/content-license-agreement/
).
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