Evidence map›Paper›PMID 27073900›Full record

SynthesisPloS one2016

A Systematic Assessment of Smartphone Tools for Suicide Prevention.

Mark Erik Larsen, Jennifer Nicholas, Helen Christensen

Registry-linked trialAbstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04414774 (Assessing the Effectiveness of a CBT-based App in Reducing Suicidal Ideation), which is not on this map. Cited by 137 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed, 7 pooled it
–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.

NCT04414774 nacompletednot on this mapstarted 2020, after this paper: background citation

Assessing the Effectiveness of a CBT-based App in Reducing Suicidal Ideation: An Open Randomized Study

TypeinterventionalSponsorShahak YarivRan2020 to 2021Enrolled128ConditionsSuicide IdeationArmsGG-Suicide-Ideation
3 · Its place in the literature

Who cites it

137 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Article
  13. Diving into the Regulatory Landscape of Digital Therapeutics.Therapeutic innovation & regulatory science · 2026
    Review
  14. Article
  15. Reducing the 'Silence Between Sessions': A Qualitative Study on Youth and Professionals' Perspectives on Digital Tools for Suicide Prevention.Health expectations : an international journal of public participation in health care and health policy · 2026
    Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article

77 more citing papers are in PubMed but not listed here.

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.

Mark Erik LarsenBlack Dog Institute, University of New South Wales, Sydney, New South Wales, Australia.
Jennifer NicholasBlack Dog Institute, University of New South Wales, Sydney, New South Wales, Australia.
Helen ChristensenBlack Dog Institute, University of New South Wales, Sydney, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSuicide 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.

methodsApps 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.

resultsOne 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".

Indexed as

SmartphoneSuicide PreventionHumansMobile ApplicationsSelf CareSuicideTelemedicine

Identifiers

PMID27073900
PMCPMC4830444

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.