Cited by 359Digital Mental Health InterventionsMobile Health and mHealth ApplicationsMental Health Research Topics

Do mental health mobile apps work: evidence and recommendations for designing high-efficacy mental health mobile apps

Open access
Chandrashekar, Pooja·2018·mHealth

Abstract

Smartphone-based mental health apps represent a unique opportunity to expand the availability and quality of mental health treatment. The number of mobile health (mHealth) apps focused on mental health has rapidly increased; a 2015 World Health Organization (WHO) survey of 15,000 mHealth apps revealed that 29% focus on mental health diagnosis, treatment, or support (1).

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 · 10.21037/mhealth.2018.03.02

Cites

22 of 22 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?

  • Smartphone-delivered interventions differ in their design, content presentation, usability, and other user experience aspects.

    “Smartphone-delivered interventions also differ in their design, content presentation (e.g., text- or video-based), usability, and other user experience aspects (cf. Chandrashekar, 2018).”

    From Smartphone-delivered mental health care interventions for refugees: A systematic review of the literature (2023) · cites this paper as Chandrashekar, 2018

    The “Why apps: the utility of mental health apps for psychological treatment” section says mental health apps vary in design and functionality. “Simple user interface (UI) and experience” discusses interface design and pictures versus text, supporting variation in presentation and user experience, but our copy does not substantiate the specific text-versus-video example. (LLM, conf=0.82)

    Experimental — accuracy not yet measured
  • When an application was combined with face-to-face or internet-based therapy, the effect was even greater.

    “When the application was combined with face-to-face or internet-based therapy, the effect was even greater [15].”
  • Mobile health technology has been growing in popularity to minimize some barriers to traditional mental healthcare.

    “Mobile health (mHealth) technology has been growing in popularity to minimize some barriers to traditional mental healthcare [8,9].”
  • Synthesizing a standard systematic review typically takes significant time and fails to capture emerging issues.

    “Synthesizing a standard systematic review, which is best suited to assess well-established topics, typically takes significant time to evaluate and analyze at least ten years of literature; therefore, fails to capture emerging issues.”

    From Analysis of Mobile App-Based Mental Health Solutions for College Students: A Rapid Review (2023) · cites this paper as [9]

    The section ‘Do they work: evidence for using mental health apps for treatment’ discusses gaps in evidence about app efficacy, and the References list includes a systematic review. Neither addresses how long a standard systematic review takes, a ten-year literature window, or whether such reviews miss emerging issues; searches for those terms found no supporting passage in our copy. (LLM, conf=0.75)

    Experimental — accuracy not yet measured
  • A rapid review speeds up the systematic review process by omitting stages, making it less rigorous and precise.

    “A rapid review speeds up the systematic review process by omitting stages of the systematic review making it less rigorous and precise [8,9].”

    From Analysis of Mobile App-Based Mental Health Solutions for College Students: A Rapid Review (2023) · cites this paper as [9]

    The section ‘Do they work: evidence for using mental health apps for treatment’ discusses evidence for mental health apps, not rapid-review methods. Searches for rapid reviews, omitted systematic-review stages, and reduced rigor or precision found no passage in our copy addressing the claim. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

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

Cited by

Sorted by citations

Authors
Chandrashekar, P.
Affiliations
Harvard University (US)
Corresponding author
Chandrashekar, Pooja
Venue
mHealth
Published
2018-03
Volume
4
Pages
6-6
ISSN
2306-9740 (ISSN-L)
OpenAlex
W2792516940
Cited by
359
References
22
Citations by year
2026: 27 · 2025: 41 · 2024: 53 · 2023: 43 · 2022: 70 · 2021: 58 · 2020: 42 · 2019: 24 · 2018: 1
FWCI
39.41
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • mHealth (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
Keywords
mental health apps, mobile health, mobile application, app efficacy, mobile application design, digital mental health interventions, access to mental health care

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