Evidence map›Paper›PMID 34806986›Full record

ArticleJMIR cardio2021

The Effects of a Digital Mental Health Intervention in Adults With Cardiovascular Disease Risk Factors: Analysis of Real-World User Data.

Robert M Montgomery, Eliane M Boucher, Ryan D Honomichl, Tyler A Powell, Sharelle L Guyton, Samantha L Bernecker, Sarah Elizabeth Stoeckl, Acacia C Parks

Open access · goldAbstract read
In one paragraph

Article in JMIR cardio, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 17% of its field
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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Trial
  2. Review
  3. Lifestyle Medicine and Cardiovascular Health.American journal of lifestyle medicine · 2026
    Review
  4. Review
  5. Article
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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.

Robert M MontgomeryHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0001-9637-9753
Eliane M BoucherHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0002-1384-7177
Ryan D HonomichlHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0002-0535-4268
Tyler A PowellHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0001-9349-8810
Sharelle L GuytonHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0002-0133-3128
Samantha L BerneckerHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0002-8803-3311
Sarah Elizabeth StoecklHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0003-2719-2957
Acacia C ParksHappify Health, New York, NY, United States.ORCID https://orcid.org/0000-0001-6643-0116

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe American Heart Association has identified poor mental health as a key barrier to healthy behavior change for those with cardiovascular disease (CVD) risk factors such as high blood pressure, high cholesterol, and diabetes. Digital mental health interventions, like those delivered via the internet to computers or smartphones, may provide a scalable solution to improving the mental and physical health of this population. Happify is one such intervention and has demonstrated evidence of efficacy for improving aspects of mental health in both the general population and in users with chronic conditions.

objectiveThe objectives of this analysis of real-world data from Happify users with self-reported CVD risk factors, including high blood pressure and cholesterol, diabetes, and heart disease, were to examine whether these users would report improvements in subjective well-being and anxiety over time (H1) and use of Happify as recommended would be associated with significantly greater improvement in subjective well-being and anxiety over time compared to less-than-recommended usage (H2).

methodsData were obtained from existing Happify users who reported the aforementioned CVD risk factors. The sample included 1803 users receiving at least 6 weeks' exposure to Happify (ranging from 42 days to 182 days) who completed at least one activity and two assessments within the app during that time. Subjective well-being was assessed with the Happify Scale, a 9-item measure of positive emotionality and life satisfaction, and anxiety was assessed with the Generalized Anxiety Disorder 2 (GAD-2). To evaluate H1, changes over time in both outcomes were assessed using mixed effects linear regression models, controlling for demographics and usage. For H2, an interaction term was added to the models to assess whether usage as recommended was associated with greater improvement over time.

resultsBoth hypotheses were supported. For both the Happify scale and GAD-2, the initial multivariable model without an interaction demonstrated an effect for time from baseline, and the addition of the interaction term between time and recommended use was significant as well.

conclusionsThis analysis of real-world data provides preliminary evidence that Happify users with self-reported CVD risk factors including high blood pressure or cholesterol, diabetes, and heart disease experienced improved well-being and anxiety over time and that those who used Happify as recommended experienced greater improvements in these aspects of mental health than those who completed fewer activities. These findings extend previous research, which demonstrated that engagement with Happify as recommended was associated with improved well-being among physically healthy users and in those with chronic conditions, to a new population for whom mental health is especially critical: those at risk of developing CVD.

Indexed as

anxietycardiovascular disease riskcardiovascular healthdiabetesdigital healthdigital mental healthhappinesshigh blood pressurehigh cholesterolinternet-based interventionmobile appsmobile healthreal-world datasubjective well-being

Identifiers

PMID34806986
PMCPMC8663463
OpenAlexW3201715571

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.