CoChat
Sign Up
Cited by 289Suicide and Self-Harm StudiesDigital Mental Health InterventionsMobile Health and mHealth Applications

The DOI matches its Crossref record; 23 of the 24 references it cites were found in a registry or an index.

A Systematic Assessment of Smartphone Tools for Suicide Prevention

Open access
Larsen, Mark Erik, Nicholas, Jennifer, Christensen, Helen·2016·PLoS ONE
DOI 10.1371/journal.pone.0152285PMC PMC4830444
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: Suicide is a leading cause of death globally, and there has been a rapid growth in the use of new technologies such as mobile health applications (apps) to help identify and support those at risk. However, it is not known whether these apps are evidence-based, or indeed contain potentially harmful content. This review examines the concordance of features in publicly available apps with current scientific evidence of effective suicide prevention strategies. METHODS: Apps referring to suicide or deliberate self-harm (DSH) were identified on the Android and iOS app stores. Systematic review methodology was employed to screen and review app content. App features were labelled using a coding scheme that reflected the broad range of evidence-based medical and population-based suicide prevention interventions. Best-practice for suicide prevention was based upon a World Health Organization report and supplemented by other reviews of the literature. RESULTS: One hundred and twenty-three apps referring to suicide were identified and downloaded for full review, 49 of which were found to contain at least one interactive suicide prevention feature. Most apps focused on obtaining support from friends and family (n = 27) and safety planning (n = 14). Of the different suicide prevention strategies contained within the apps, the strongest evidence in the literature was found for facilitating access to crisis support (n = 13). All reviewed apps contained at least one strategy that was broadly consistent with the evidence base or best-practice guidelines. Apps tended to focus on a single suicide prevention strategy (mean = 1.1), although safety plan apps provided the opportunity to provide a greater number of techniques (mean = 3.9). Potentially harmful content, such as listing lethal access to means or encouraging risky behaviour in a crisis, was also identified. DISCUSSION: Many suicide prevention apps are available, some of which provide elements of best practice, but none that provide comprehensive evidence-based support. Apps with potentially harmful content were also identified. Despite the number of apps available, and their varied purposes, there is a clear need to develop useful, pragmatic, and multifaceted mobile resources for this population. Clinicians should be wary in recommending apps, especially as potentially harmful content can be presented as helpful. Currently safety plan apps are the most comprehensive and evidence-informed, for example, "Safety Net" and "Mood-Tools--Depression Aid".

Overview

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 · 10.1371/journal.pone.0152285

Cites

23 of 23 references verified0 citation errors · 0 not checkable

Statistics

Verification

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?

Self-check

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

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

Citations

Cites

Flagged first, then by citations

Show all 24 references

1 of the 24 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Leitner M, Barr W, Hobby L. Effectiveness of Interventions to Prevent Suicide and Suicidal Behaviour: A Systematic Review. 2008.

Cited by

Sorted by citations

Items 201–283 of 283

Related

See all

Metadata

Authors
Larsen, M. E., Nicholas, J., & Christensen, H.
Affiliations
Black Dog Institute (AU)
Corresponding author
Larsen, Mark Erik
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2016-04-13
Volume
11
Issue
4
Pages
e0152285
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0152285
PMC
PMC4830444
OpenAlex
W2339369942
Semantic Scholar
b05c1f3c05d39e26892368ea8fceb6ea0ef29bf3
Cited by
289
References
24
Citations by year
2026: 15 · 2025: 31 · 2024: 24 · 2023: 25 · 2022: 24 · 2021: 41 · 2020: 31 · 2019: 28 · 2018: 43 · 2017: 22 · 2016: 5
FWCI
4.64
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • Medical Research Council
  • National Health and Medical Research Council (1042580, 1056964)
Topics
  • Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
suicide prevention, mobile health apps, mobile application, self-harm, crisis support, evidence-based interventions, app reviews, suicide risk
MeSH terms
Smartphone, Suicide Prevention, Humans, Self Care, Suicide, Telemedicine, Mobile Applications

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