Evidence map›Paper›PMID 35943788›Full record

ArticleJMIR mental health2022

The Effect of Mental Health App Customization on Depressive Symptoms in College Students: Randomized Controlled Trial.

Stephanie G Six, Kaileigh A Byrne, Heba Aly, Maggie W Harris

Open access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 5 pooled it
5.1field-weighted citation impact, top 4% 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

18 citing papers in PubMed, 5 syntheses or guidelines pooled it, 35 citations in OpenAlex.

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  16. Asynchronous Technologies in Mental Health Care and Education.Current treatment options in psychiatry · 2023
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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.

Stephanie G SixDepartment of Psychology, Clemson University, Clemson, SC, United States.ORCID https://orcid.org/0000-0002-7435-1773
Kaileigh A ByrneDepartment of Psychology, Clemson University, Clemson, SC, United States.ORCID https://orcid.org/0000-0002-3935-3108
Heba AlyDepartment of Computer Science, Clemson University, Clemson, SC, United States.ORCID https://orcid.org/0000-0003-3309-5862
Maggie W HarrisDepartment of Psychology, Clemson University, Clemson, SC, United States.ORCID https://orcid.org/0000-0002-2376-157X
Clemson University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental health apps have shown promise in improving mental health symptoms, including depressive symptoms. However, limited research has been aimed at understanding how specific app features and designs can optimize the therapeutic benefits and adherence to such mental health apps.

objectiveThe primary purpose of this study is to investigate the effect of avatar customization on depressive symptoms and adherence to use a novel cognitive behavioral therapy (CBT)-based mental health app. The secondary aim is to examine whether specific app features, including journaling, mood tracking, and reminders, affect the usability of the mental health app.

methodsCollege students were recruited from a university study recruitment pool website and via flyer advertisements throughout campus. A total of 94 participants completed a randomized controlled trial in which they were randomized to either customization or no customization version of the app. Customization involved personalizing a virtual avatar and a travel vehicle to one's own preferences and use of one's name throughout the app. Participants completed a 14-day trial using a novel CBT-based mental health app called AirHeart. Self-report scores for depressive symptoms, anxiety, and stress were measured at baseline and after the intervention. Postintervention survey measures also included usability and avatar identification questionnaires.

resultsOf the 94 enrolled participants, 83 (88%) completed the intervention and postintervention assessments. AirHeart app use significantly reduced symptoms of depression (P=.006) from baseline to the end of the 2-week intervention period for all participants, regardless of the customization condition. However, no differences in depressive symptoms (P=.17) or adherence (P=.80) were observed between the customization (39/83, 47%) and no customization (44/83, 53%) conditions. The frequency of journaling, usefulness of mood tracking, and helpfulness of reminders were not associated with changes in depressive symptoms or adherence (P>.05). Exploratory analyses showed that there were 3 moderate positive correlations between avatar identification and depressive symptoms (identification: r=-0.312, P=.02; connection: r=-0.305, P=.02; and lack of relatability: r=0.338, P=.01).

conclusionsThese results indicate that CBT mental health apps, such as AirHeart, have the potential to reduce depressive symptoms over a short intervention period. The randomized controlled trial results demonstrated that customization of app features, such as avatars, does not further reduce depressive symptoms over and above the CBT modules and standard app features, including journal, reminders, and mood tracking. However, further research elucidating the relationship between virtual avatar identification and mental health systems is needed as society becomes increasingly more digitized. These findings have potential implications for improving the optimization of mental health app designs.

trial registrationOpen Science Framework t28gm; https://osf.io/t28gm.

Indexed as

avatarscognitive behavioral therapycustomizationdepressionmental health appsmobile phonepersonalization

Identifiers

PMID35943788
PMCPMC9399839
OpenAlexW4285738088

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.