Evidence map›Paper›PMID 37791242›Full record

ArticleAJPM focus2022

Patterns of Engagement With an Application-Based Dietary Self-Monitoring Tool Within a Randomized Controlled Feasibility Trial.

Melissa C Kay, Hailey N Miller, Sandy Askew, Erin M Spaulding, Miriam Chisholm, Jacob Christy, Qing Yang, Dori M Steinberg

Registry-linked trialAbstract read
In one paragraph

Article in AJPM focus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03215472 (DASH Cloud), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

NCT03215472 nacompletednot on this map

DASH Cloud: Using Digital Health to Improve Adherence to the DASH Diet Among Women at Risk for Cardiovascular Disease

TypeinterventionalSponsorDuke UniversityRan2017 to 2018Enrolled59ConditionsDiet Modification, Hypertension, Women's Health, Cardiovascular DiseasesArmsDASH Cloud, Nutritionix Track app
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Melissa C KayDepartment of Pediatrics, Duke University, Durham, North Carolina.
Hailey N MillerDuke Global Digital Health Science Center, Duke University, Durham, North Carolina.
Sandy AskewDuke Global Digital Health Science Center, Duke University, Durham, North Carolina.
Erin M SpauldingWelch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Miriam ChisholmDuke Global Digital Health Science Center, Duke University, Durham, North Carolina.
Jacob ChristyDuke Global Digital Health Science Center, Duke University, Durham, North Carolina.
Qing YangSchool of Nursing, Duke University, Durham, North Carolina.
Dori M SteinbergSchool of Nursing, Duke University, Durham, North Carolina.

Funding

Interdisciplinary Research Careers in Women's HealthK12HD043446 · NICHD · DUKE UNIVERSITY · PI AMUNDSEN, CINDY · 2002 to 2023
$9.6M
Research Project 3U54MD012530 · NIMHD · DUKE UNIVERSITY · PI JOHNSON, KIMBERLY S. · 2017 to 2022
$8.8M
Institutional Career Development CoreKL2TR002554 · NCATS · DUKE UNIVERSITY · PI SVETKEY, LAURA P · 2018 to 2022
$8.2M
NCATS NIH HHS KL2 TR002554NICHD NIH HHS K12 HD043446NIMHD NIH HHS U54 MD012530
6 · The paper itself

Abstract

Introduction: The Dietary Approaches to Stop Hypertension dietary pattern is a proven way to manage hypertension, but adherence remains low. Dietary tracking applications offer a highly disseminable way to self-monitor intake on the pathway to reaching dietary goals but require consistent engagement to support behavior change. Few studies use longitudinal dietary self-monitoring data to assess trajectories and predictors of engagement. We used dietary self-monitoring data from participants in Dietary Approaches to Stop Hypertension Cloud (N=59), a feasibility trial to improve diet quality among women with hypertension, to identify trajectories of engagement and explore associations between participant characteristics. Methods: We used latent class growth modeling to identify trajectories of engagement with a publicly available diet tracking application and used bivariate and regression analyses to assess the associations of classifications of engagement with participant characteristics. Results: We identified 2 latent classes of engagement: consistent engagers and disengagers. Consistent engagers were more likely to be older, more educated, and married or living with a partner. Although consistent engagers exhibited slightly greater changes in Dietary Approaches to Stop Hypertension score, the difference was not significant. Conclusions: This study highlights an important yet underutilized methodologic approach for uncovering dietary self-monitoring engagement patterns. Understanding how certain individuals engage with digital technologies is an important step toward designing cost-effective behavior change interventions. Trial registration: This study is registered at www.clinicaltrials.gov NCT03215472.

Indexed as

DASHdiet qualityengagementhypertensionLatent class analysismhealth

Identifiers

PMID37791242
PMCPMC10546506

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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.