Cited by 247Digital Mental Health InterventionsMobile Health and mHealth ApplicationsHealth, Technology, Consumer Behavior

State of the Field of Mental Health Apps

Open access
Neary, Martha, Schueller, Stephen M.·2018·Cognitive and Behavioral Practice

Abstract

Mental health apps offer unique opportunities for self-management of mental health and well-being in mobile, cost-effective ways. There is an abundance of apps available to consumers, but selecting a useful one presents a challenge. Most available apps are not supported by empirical evidence and thus consumers have access to a range of unreviewed apps, the benefits of which are not known or supported. While user ratings exist, and are likely to be considered by consumers when selecting an app, they do not actually yield information on app suitability. A possible alternative way for consumers to choose an app would be to use an app review platform. A number of attempts have been made to construct such a platform, and this paper introduces PsyberGuide, which offers a step towards providing objective and actionable information for publicly available mental health apps.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cbpra.2018.01.002

Cites

24 of 24 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The time and resources required for planning and undertaking an RCT are not always appropriate for the assessment of dMH tools due to their rapid development and the accelerating time to the obsolescence of technological innovations.

    “The time and resources required for planning and undertaking an RCT are not always appropriate for the assessment of dMH tools due to their rapid development and the accelerating time to the obsolescence of technological innovations [9,22,23].”

    From Feasibility and Acceptability of the Aboriginal and Islander Mental Health Initiative for Youth App: Nonrandomized Pilot With First Nations Young People (2023) · cites this paper as [9]

    In “Do They Really Work? High Availability But Low Evidence Base” (page unavailable), the paper says the time needed to conduct and publish an RCT does not align with apps’ rapid development cycle, supporting the central point. It does not address the resources required or say that the time to technological obsolescence is accelerating. (LLM, conf=0.82)

    Experimental — accuracy not yet measured
  • It is estimated that only about 3% to 4% of mental health apps are actually evidence based.

    “There is currently somewhere between 10,000 and 20,000 mental health apps [23,24], but it is estimated that only about 3% to 4% are actually evidence based.”
  • There is currently somewhere between 10,000 and 20,000 mental health apps.

    “There is currently somewhere between 10,000 and 20,000 mental health apps [23,24], but it is estimated that only about 3% to 4% are actually evidence based.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

1 of the 25 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

  1. Ben-Zeev D, Brian RM, Jonathan G, Razzano L, Pashka N, Carpenter-Song EA, Drake RE, & Schrer EA (in press). Randomized controlled trial of mHealth vs. clinic-based interventions for serious mental illness: Patient engagement, satisfaction, and clinical outcomes. Schizophrenia Bulletin.
  2. Rathner E (2017). Implementation of the mobile health app database (mHAD). Workshop presented at the 9th International for Society for Research on Internet Interventions Scientific Meeting, Berlin, Germany.

Cited by

Sorted by citations

Authors
Neary, M., & Schueller, S. M.
Affiliations
Northwestern University (US)
Corresponding author
Schueller, Stephen M.
Venue
Cognitive and Behavioral Practice
Publisher
Elsevier BV
Published
2018-11
Volume
25
Issue
4
Pages
531-537
ISSN
1077-7229 (ISSN-L)
OpenAlex
W2789479890
Cited by
247
References
25
Citations by year
2026: 19 · 2025: 30 · 2024: 28 · 2023: 44 · 2022: 39 · 2021: 37 · 2020: 24 · 2019: 18 · 2018: 7
FWCI
26.89
Type
journal article
Language
en
Open access
Locations
  • Cognitive and Behavioral Practice (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
National Institute of Mental Health (K08MH102336)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords
mental health apps, app selection, user ratings, mobile mental health

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review