Evidence map›Paper›PMID 41267003›Full record

ArticleBMC psychiatry2025

Temporal analysis of posts on a Japanese online message board for suicide risk monitoring.

Takahiro Arai, Hiroyuki Shinkai, Keita Yamauchi

Abstract read
In one paragraph

Article in BMC psychiatry, 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

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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

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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. Observational
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.

Takahiro AraiSchool of Management and Information Sciences, Tama University, 4-1-1 Hijirigaoka, Tama-Shi, Tokyo, 206-0022, Japan. arai.t@keio.jp.
Hiroyuki ShinkaiFaculty of Law, Kanagawa University, Kanagawa, Japan.
Keita YamauchiGraduate School of Health Management, Keio University, Kanagawa, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSuicide prevention can be significantly enhanced by time-sensitive surveillance using digital data sources like online message board. To inform more effective suicide prevention strategies, this study analyzes the temporal patterns of posts on a Japanese mental health message board—NHK’s “Facing Suicide” website—that may aid in early risk detection.

methodsWe analyzed 63,046 posts from Japan’s national broadcaster (NHK) message board (1 Jan, 2008–31 Mar, 2025), stratified by gender and age (≤19, 20s, 30s, ≥40). Generalized additive models were used to model hourly, weekly, and monthly variations, with time of day included as a spline term. Results are presented as incidence rate ratios (IRRs) with 95% confidence intervals (CIs).

resultsFemales contributed 75.5% of posts, and the 20–29 age group was the most active (32.4%). Posting activity consistently peaked around 23:00 across all subgroups. A marked increase was observed among adolescents (≤19 years) in August (males: IRR = 1.30, 95% CI [1.05–1.61]; females: IRR = 1.55, 95% CI [1.43–1.69]), while adults showed decreases in January–February. Weekly patterns varied by subgroup; for instance, males aged 20–29 posted more on Mondays and Tuesdays (IRR = 1.17, 95% CI [1.05–1.30]).

conclusionsOnline message board activity displays predictable temporal cycles with demographic-specific patterns. These findings provide an essential baseline for real-time monitoring systems to detect deviations that may signal elevated suicide risk. The August peak in adolescent posts aligns with back-to-school distress, and the late-night peaks underscore the need to provide 24-hour support services and implement automated multi-layered online intervention strategies directly within message boards. These insights can guide the development of targeted, time-sensitive suicide prevention strategies.

Indexed as

InternetSuicide PreventionAdolescentAdultEast Asian PeopleFemaleHumansJapanMaleSuicideTime FactorsYoung AdultDiurnal variationGeneralized additive modelJapanMental healthOnline message boardSuicidal ideationSuicideTemporal patterns

Identifiers

PMID41267003
PMCPMC12632057

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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.