Evidence map›Paper›PMID 30287415›Full record

ArticleJMIR mental health2018

Interaction and Engagement with an Anxiety Management App: Analysis Using Large-Scale Behavioral Data.

Paul Matthews, Phil Topham, Praminda Caleb-Solly

Abstract read
In one paragraph

Article in JMIR mental health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Shifting Mindsets: The Impact of a Patient Portal on Functioning and Recovery in a Mental Health Setting.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2024
    Article
  5. Review
  6. Article
  7. Article
  8. 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

3 authors.

Paul Matthews *Data Science Group, Computer Science Research Centre, Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom.ORCID http://orcid.org/0000-0003-1021-2683
Phil TophamUniversity of the West of England, Bristol, United Kingdom.ORCID http://orcid.org/0000-0002-2125-059X
Praminda Caleb-SollyUniversity of the West of England, Bristol, United Kingdom.ORCID http://orcid.org/0000-0001-8821-0464

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSAM (Self-help for Anxiety Management) is a mobile phone app that provides self-help for anxiety management. Launched in 2013, the app has achieved over one million downloads on the iOS and Android platform app stores. Key features of the app are anxiety monitoring, self-help techniques, and social support via a mobile forum ("the Social Cloud"). This paper presents unique insights into eMental health app usage patterns and explores user behaviors and usage of self-help techniques.

objectiveThe objective of our study was to investigate behavioral engagement and to establish discernible usage patterns of the app linked to the features of anxiety monitoring, ratings of self-help techniques, and social participation.

methodsWe use data mining techniques on aggregate data obtained from 105,380 registered users of the app's cloud services.

resultsEngagement generally conformed to common mobile participation patterns with an inverted pyramid or "funnel" of engagement of increasing intensity. We further identified 4 distinct groups of behavioral engagement differentiated by levels of activity in anxiety monitoring and social feature usage. Anxiety levels among all monitoring users were markedly reduced in the first few days of usage with some bounce back effect thereafter. A small group of users demonstrated long-term anxiety reduction (using a robust measure), typically monitored for 12-110 days, with 10-30 discrete updates and showed low levels of social participation.

conclusionsThe data supported our expectation of different usage patterns, given flexible user journeys, and varying commitment in an unstructured mobile phone usage setting. We nevertheless show an aggregate trend of reduction in self-reported anxiety across all minimally-engaged users, while noting that due to the anonymized dataset, we did not have information on users also enrolled in therapy or other intervention while using the app. We find several commonalities between these app-based behavioral patterns and traditional therapy engagement.

Indexed as

anxietyeMental healthmHealthmobile phone

Identifiers

PMID30287415
PMCPMC6324647

What OpenQuestion holds

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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.