Evidence map›Paper›PMID 33650986›Full record

ArticleJMIR mental health2021

Characterizing Emotional State Transitions During Prolonged Use of a Mindfulness and Meditation App: Observational Study.

Argus Athanas, Jamison McCorrison, Julie Campistron, Nick Bender, Jamie Price, Susan Smalley, Nicholas J Schork

Abstract read
In one paragraph

Article in JMIR mental health, 2021. 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

7 authors.

Argus AthanasBioinformatics and Systems Biology, University California San Diego, San Diego, CA, United States.ORCID https://orcid.org/0000-0001-7293-0096
Jamison McCorrisonBioinformatics and Systems Biology, University California San Diego, San Diego, CA, United States.ORCID https://orcid.org/0000-0002-4807-0847
Julie CampistronStop, Breathe & Think, Inc, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0003-4408-6240
Nick BenderStop, Breathe & Think, Inc, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0003-0223-9472
Jamie PriceStop, Breathe & Think, Inc, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0002-3169-344X
Susan SmalleyUniversity California Los Angeles, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0002-5092-8400
Nicholas J SchorkBioinformatics and Systems Biology, University California San Diego, San Diego, CA, United States.ORCID https://orcid.org/0000-0003-0920-5013

Funding

Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI FRED H GAGE · 2004 to 2026
$102.6M
Integrative Resource to Develop Translational Strategies to Promote LongevityU24AG051129 · NIA · CALIFORNIA PACIFIC MED CTR RES INSTITUTE · PI CUMMINGS, STEVEN RON, EVANS, DANIEL SPENCER · 2015 to 2019
$5.3M
Integrative Omics to enhance therapeutics development for healthy agingUH2AG064706 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI MILLER, RICHARD A, SCHORK, NICHOLAS JOSEPH · 2019 to 2020
$1.4M
NIA NIH HHS U19 AG023122NIA NIH HHS U24 AG051129NIA NIH HHS UH2 AG064706
6 · The paper itself

Abstract

backgroundThe increasing demand for mental health care, a lack of mental health care providers, and unequal access to mental health care services have created a need for innovative approaches to mental health care. Digital device apps, including digital therapeutics, that provide recommendations and feedback for dealing with stress, depression, and other mental health issues can be used to adjust mood and ultimately show promise to help meet this demand. In addition, the recommendations delivered through such apps can also be tailored to an individual's needs (ie, personalized) and thereby potentially provide greater benefits than traditional "one-size-fits-all" recommendations.

objectiveThis study aims to characterize individual transitions from one emotional state to another during the prolonged use of a digital app designed to provide a user with guided meditations based on their initial, potentially negative, emotional state. Understanding the factors that mediate such transitions can lead to improved recommendations for specific mindfulness and meditation interventions or activities (MMAs) provided in mental health apps.

methodsWe analyzed data collected during the use of the Stop, Breathe & Think (SBT) mindfulness app. The SBT app prompts users to input their emotional state before and immediately after engaging with MMAs recommended by the app. Data were collected from more than 650,000 SBT users engaging in nearly 5 million MMAs. We limited the scope of our analysis to users with 10 or more MMA sessions that included at least 6 basal emotional state evaluations. Using clustering techniques, we grouped emotions recorded by individual users and then applied longitudinal mixed effect models to assess the associations between individual recommended MMAs and transitions from one group of emotions to another.

resultsWe found that basal emotional states have a strong influence on transitions from one emotional state to another after MMA engagement. We also found that different MMAs impact these transitions, and many were effective in eliciting a healthy transition but only under certain conditions. In addition, we observed gender and age effects on these transitions.

conclusionsWe found that the initial emotional state of an SBT app user determines the type of SBT MMAs that will have a favorable effect on their transition from one emotional state to another. Our results have implications for the design and use of guided mental health recommendations for digital device apps.

Indexed as

emotional distressmental healthmindfulnessmobile appsmobile phonesmartphone

Identifiers

PMID33650986
PMCPMC7967231

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LicenceCC BY
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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.