Evidence map›Paper›PMID 40883417›Full record

ArticleNPJ digital medicine2025

Rethinking suicide related searches and their association with suicide rates, attempts, and self harm hospitalisation.

Sandersan Onie, Matthew J Coleshill, Michelle Torok, Venkatesha, Fiona Shand, Mark E Larsen

Abstract read
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Sandersan OnieBlack Dog Institute, University of New South Wales, Sydney, NSW, Australia. s.onie@blackdog.org.au.
Matthew J ColeshillBlack Dog Institute, University of New South Wales, Sydney, NSW, Australia.
Michelle TorokBlack Dog Institute, University of New South Wales, Sydney, NSW, Australia.
VenkateshaMark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW, Australia.
Fiona ShandBlack Dog Institute, University of New South Wales, Sydney, NSW, Australia.
Mark E LarsenCentre for Big Data Research in Health, University of New South Wales, Sydney, NSW, Australia.

Funding

Australia-Indonesia Institute AII2020322National Health and Medical Research Council 2024/GNT2034904National Health and Medical Research Council APP1152952Suicide Prevention Australia Post-Doctoral Fellowship
6 · The paper itself

Abstract

This study explored the relationship between Google search volumes for suicide-related keywords and suicide, attempt, and self-harm hospitalisation rates across three investigations in Indonesia and Australia. While past research suggested a link between suicide-related searches and suicide rates, this study found no consistent association with suicide rates. However, search volumes were positively associated with suicide attempts in Indonesia and self-harm hospitalisations in Australia. Further analysis using the IMV-Model of Suicidal Behaviour showed that searches related to distress were not associated with outcomes, while ideation-related keywords were linked only to attempts. In contrast, searches related to specific suicide methods-reflecting the volitional phase of the IMV-Model-were associated with both attempts and suicides, particularly for high-lethality methods. Limitations include data quality on suicide outcomes, the representativeness of Google Trends, and a focus on only two countries. Overall, search behaviour may reflect attempt risk more than suicide risk, depending on keyword category.

Identifiers

PMID40883417
PMCPMC12397406

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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.