ArticleRoyal Society open science2023
Exploring the use of AI text-to-image generation to downregulate negative emotions in an expressive writing application.
Article in Royal Society open science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Beyond traditional stimuli: Validating AI-generated images for eliciting negative emotions in affect research.PloS one · 2026Article
- Fostering adolescent engagement in generative AI art therapy: a dual SEM-ANN analysis of emotional.Frontiers in psychology · 2025Article
- Generative AI for Diagnostic Medical Imaging: A Review.Current medical imaging · 2025Review
- Debate and Dilemmas Regarding Generative AI in Mental Health Care: Scoping Review.Interactive journal of medical research · 2024Article
- Behavioral health and generative AI: a perspective on future of therapies and patient care.Npj mental health research · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conventional writing therapies are versatile, accessible and easy to facilitate online, but often require participants to self-disclose traumatic experiences. To make expressive writing therapies safer for online, unsupervised environments, we explored the use of text-to-image generation as a means to downregulate negative emotions during a fictional writing exercise. We developed a writing tool, StoryWriter, that uses Generative Adversarial Network models to generate artwork from users' narratives in real time. These images were intended to positively distract users from their negative emotions throughout the writing task. In this paper, we report the outcomes of two user studies: Study 1 (
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