Evidence map›Paper›PMID 42621628›Full record

ArticleInternet interventions2026

Disseminating brief video-based mental health interventions on Instagram: Reach, engagement, and real-world implementation.

Shilat Haim-Nachum, Andrés Martin, Doron Amsalem

Abstract read
In one paragraph

Article in Internet interventions, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Shilat Haim-NachumSchool of Social Work, Tel Aviv University, Tel Aviv, Israel.
Andrés MartinYale Child Study Center, Yale School of Medicine, New Haven, CT, USA.
Doron AmsalemDepartment of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Childhood trauma (CT) profoundly impacts mental health. Negative attitudes and stigma surrounding mental health and trauma often deter survivors from seeking help. Previous research demonstrated that a brief video intervention significantly reduced stigma and enhanced openness to treatment among CT survivors. Given social media's pervasive role in young people's lives, Instagram offers a promising avenue for delivering evidence-based interventions. This study aimed to test the feasibility and acceptability of disseminating this intervention via Instagram. Methods: Two consecutive campaigns targeted U.S. youth aged 18-24. The first campaign featured a human-narrated personal story video shown to reduce stigma among CT survivors, alongside a psychoeducational control video without social-contact elements. The second campaign aimed to replicate these findings and explore the feasibility of additional videos, including artificial intelligence (AI)-generated videos. We assessed key engagement metrics: impressions (total views), reach (unique viewers), link clicks (engagement with treatment resources), and cost-per-click (CPC) for recruitment. Results: The campaigns generated approximately 997,000 impressions, reaching 387,068 Instagram users, resulting in 6417 link clicks. Using click-through rate (CTR), compared via two-proportion z-tests, as the primary comparative metric, the human-narrated intervention significantly outperformed the control videos on a per-impression basis in both campaigns, and on a per-reach basis against the 'About Me' control in Campaign 2, but not on a per-reach basis in Campaign 1 or against the psychoeducational control in Campaign 2. AI-generated videos showed significantly higher per-reach CTR than the human-narrated intervention in Campaign 2. Conclusion: These findings suggest Instagram's potential to disseminate cost-effective interventions previously shown to reduce negative attitudes toward CT and encourage youth to seek help. Future studies should examine long-term effects on treatment-seeking behaviors in different populations.Clinical trial number: not applicable.

Indexed as

Childhood traumaHelp-seekingSocial mediaStigmaVideo-intervention

Identifiers

PMID42621628
PMCPMC13488557

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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.