Evidence map›Paper›PMID 40903487›Full record

ArticleNpj mental health research2025

Identifying therapeutic characteristics of digital social media narratives about suicide: a mixed methods investigation.

Jessica Stubbing, Peter J Franz, David Mou, Adam C Jaroszewski, Patrick Mair, Daniel Kessler, Sara Ray, Vy Cao-Silveira, Savannah Bachman, Sarah Schuster and 3 more

Abstract read
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In one paragraph

Article in Npj mental health research, 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

13 authors.

Jessica Stubbing *Cambridge Health Alliance, Cambridge, MA, USA. jstubbing@challiance.org.
Peter J Franz *Ferkauf Graduate School of Psychology, Yeshiva University, The Bronx, NY, USA.
David MouDepartment of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
Adam C JaroszewskiHarvard Medical School, Cambridge, MA, USA.
Patrick MairHarvard University Department of Psychology, Cambridge, MA, USA.
Daniel KesslerMassachusetts Institute of Technology, Cambridge, MA, USA.
Sara RayThe Mighty, Glendale, CA, USA.
Vy Cao-SilveiraThe Mighty, Glendale, CA, USA.
Savannah BachmanThe Mighty, Glendale, CA, USA.
Sarah SchusterThe Mighty, Glendale, CA, USA.
Daniel GraupenspergerThe Mighty, Glendale, CA, USA.
Mike PorathThe Mighty, Glendale, CA, USA.
Matthew K NockDepartment of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, we found adults who received digital bibliotherapy featuring lived-experience narratives related to suicidal thoughts and behaviors reported lower suicidal thoughts, mediated by increased social connectedness and optimism. This study aimed to identify characteristics of narratives associated with decreased suicidal thinking and increased social connectedness and optimism. 1532 users of a social media platform responded to surveys before and after reading narratives. Mixed-methods content analysis and clustered multidimensional scaling tested whether clusters that shared narrative characteristics were related to suicidal thoughts, social connectedness and optimism. We identified three narrative clusters: Cluster 1: "Encouraging Readers to Live," Cluster 2: "Sharing Personal Stories," and Cluster 3: "Detailed Accounts." Clusters 2 and 3 were associated with greatest reduction in suicidal thoughts, Cluster 2 with the greatest increase in social connectedness, and Cluster 3 with the greatest increase in optimism. Results suggest the optimal narratives for reducing suicidal thoughts are personal, detailed accounts.

Identifiers

PMID40903487
PMCPMC12408815

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.