Evidence map›Paper›PMID 37184904›Full record

ArticleJMIR mental health2023

Associations Between Smartphone Keystroke Metadata and Mental Health Symptoms in Adolescents: Findings From the Future Proofing Study.

Taylor A Braund, Bridianne O'Dea, Debopriyo Bal, Kate Maston, Mark Larsen, Aliza Werner-Seidler, Gabriel Tillman, Helen Christensen

Open access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Taylor A BraundFaculty of Medicine and Health, University of New South Wales, Kensington, Australia.ORCID https://orcid.org/0000-0001-8408-9070
Bridianne O'DeaFaculty of Medicine and Health, University of New South Wales, Kensington, Australia.ORCID https://orcid.org/0000-0003-1731-210X
Debopriyo BalBlack Dog Institute, University of New South Wales, Randwick, Australia.ORCID https://orcid.org/0009-0009-5903-6124
Kate MastonBlack Dog Institute, University of New South Wales, Randwick, Australia.ORCID https://orcid.org/0000-0002-6912-8550
Mark LarsenFaculty of Medicine and Health, University of New South Wales, Kensington, Australia.ORCID https://orcid.org/0000-0002-0272-2053
Aliza Werner-SeidlerFaculty of Medicine and Health, University of New South Wales, Kensington, Australia.ORCID https://orcid.org/0000-0002-9046-6159
Gabriel TillmanInstitute of Health and Wellbeing, Federation University, Ballarat, Australia.ORCID https://orcid.org/0000-0002-9601-3660
Helen ChristensenFaculty of Medicine and Health, University of New South Wales, Kensington, Australia.ORCID https://orcid.org/0000-0003-0435-2065
Black Dog Institute · AUFederation University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMental disorders are prevalent during adolescence. Among the digital phenotypes currently being developed to monitor mental health symptoms, typing behavior is one promising candidate. However, few studies have directly assessed associations between typing behavior and mental health symptom severity, and whether these relationships differs between genders.

objectiveIn a cross-sectional analysis of a large cohort, we tested whether various features of typing behavior derived from keystroke metadata were associated with mental health symptoms and whether these relationships differed between genders.

methodsA total of 934 adolescents from the Future Proofing study undertook 2 typing tasks on their smartphones through the Future Proofing app. Common keystroke timing and frequency features were extracted across tasks. Mental health symptoms were assessed using the Patient Health Questionnaire-Adolescent version, the Children's Anxiety Scale-Short Form, the Distress Questionnaire 5, and the Insomnia Severity Index. Bivariate correlations were used to test whether keystroke features were associated with mental health symptoms. The false discovery rates of P values were adjusted to q values. Machine learning models were trained and tested using independent samples (ie, 80% train 20% test) to identify whether keystroke features could be combined to predict mental health symptoms.

resultsKeystroke timing features showed a weak negative association with mental health symptoms across participants. When split by gender, females showed weak negative relationships between keystroke timing features and mental health symptoms, and weak positive relationships between keystroke frequency features and mental health symptoms. The opposite relationships were found for males (except for dwell). Machine learning models using keystroke features alone did not predict mental health symptoms.

conclusionsIncreased mental health symptoms are weakly associated with faster typing, with important gender differences. Keystroke metadata should be collected longitudinally and combined with other digital phenotypes to enhance their clinical relevance.

trial registrationAustralian and New Zealand Clinical Trial Registry, ACTRN12619000855123; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377664&isReview=true.

Indexed as

adolescentsanxietydepressiondigital phenotypekeystroke dynamicskeystroke metadatasmartphonestudents

Identifiers

PMID37184904
PMCPMC10227695
OpenAlexW4360585512

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.