Evidence map›Paper›PMID 34383678›Full record

ArticleJMIR mental health2021

Understanding People's Use of and Perspectives on Mood-Tracking Apps: Interview Study.

Stephen M Schueller, Martha Neary, Jocelyn Lai, Daniel A Epstein

Registry-linked trialOpen access · goldAbstract 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. It is linked to trial NCT06455397 (Implementing BEAM), which is not on this map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
9.2field-weighted citation impact, top 1% 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.

NCT06455397 narecruitingnot on this mapstarted 2024, after this paper: background citation

Implementing BEAM: An mHealth Tool to Prevent Mental Health Problems and Improve Developmental Outcomes in Young Children

TypeinterventionalSponsorLeslie E. RoosRan2024 to 2027Enrolled400ConditionsDepression, Anxiety, Anger, Parenting, Stress, PsychologicalArmsThe Building Emotional Awareness and Mental Health (BEAM) Program
3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 90 citations in OpenAlex.

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  13. Effect of Self-Quantification on Caregiver Burden and Depression Among Family Caregivers: A SWING-Japan Study.Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society · 2025
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  19. Recruitment and retention of adolescents for an ecological momentary assessment measurement burst mental health study: The MHIM engagement strategy.Health expectations : an international journal of public participation in health care and health policy · 2024
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  20. Approaches to Tailoring Between-Session Mental Health Therapy Activities.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024
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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

4 authors at 1 institution in 1 country.

Stephen M SchuellerDepartment of Psychological Science, University of California, Irvine, Irvine, CA, United States.ORCID https://orcid.org/0000-0002-1003-0399
Martha NearyDepartment of Psychological Science, University of California, Irvine, Irvine, CA, United States.ORCID https://orcid.org/0000-0002-1253-3459
Jocelyn LaiDepartment of Psychological Science, University of California, Irvine, Irvine, CA, United States.ORCID https://orcid.org/0000-0002-6457-3313
Daniel A EpsteinDepartment of Informatics, University of California, Irvine, Irvine, CA, United States.ORCID https://orcid.org/0000-0002-2657-6345
University of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSupporting mental health and wellness is of increasing interest due to a growing recognition of the prevalence and burden of mental health issues. Mood is a central aspect of mental health, and several technologies, especially mobile apps, have helped people track and understand it. However, despite formative work on and dissemination of mood-tracking apps, it is not well understood how mood-tracking apps used in real-world contexts might benefit people and what people hope to gain from them.

objectiveTo address this gap, the purpose of this study was to understand motivations for and experiences in using mood-tracking apps from people who used them in real-world contexts.

methodsWe interviewed 22 participants who had used mood-tracking apps using a semistructured interview and card sorting task. The interview focused on their experiences using a mood-tracking app. We then conducted a card sorting task using screenshots of various data entry and data review features from mood-tracking apps. We used thematic analysis to identify themes around why people use mood-tracking apps, what they found useful about them, and where people felt these apps fell short.

resultsUsers of mood-tracking apps were primarily motivated by negative life events or shifts in their own mental health that prompted them to engage in tracking and improve their situation. In general, participants felt that using a mood-tracking app facilitated self-awareness and helped them to look back on a previous emotion or mood experience to understand what was happening. Interestingly, some users reported less inclination to document their negative mood states and preferred to document their positive moods. There was a range of preferences for personalization and simplicity of tracking. Overall, users also liked features in which their previous tracked emotions and moods were visualized in figures or calendar form to understand trends. One gap in available mood-tracking apps was the lack of app-facilitated recommendations or suggestions for how to interpret their own data or improve their mood.

conclusionsAlthough people find various features of mood-tracking apps helpful, the way people use mood-tracking apps, such as avoiding entering negative moods, tracking infrequently, or wanting support to understand or change their moods, demonstrate opportunities for improvement. Understanding why and how people are using current technologies can provide insights to guide future designs and implementations.

Indexed as

affectemotionsmental healthmHealthmobile appsself-tracking

Identifiers

PMID34383678
PMCPMC8387890
OpenAlexW3173976674

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.