Co-author Dr Belén López-Pérez, Lecturer in Psychology at The University of Manchester, said: “Our findings suggest that what makes emotional support effective is less about who provides it, and more about how it is delivered. Providing people with specific, actionable steps, rather than general reassurance, is a key ingredient for effective support, whether that comes from a person or a chatbot.
She added: “While a human might typically suggest going for a walk or making a cup of tea, an AI chatbot tends to go further, for example acknowledging the person’s feelings and offering step-by-step strategies such as breathing techniques or specific ways to reframe a thought. Training human supporters – whether professionals or members of the public – to provide this kind of structured, actionable guidance could meaningfully improve the quality of everyday emotional support.”
Co-author Yuhui Chen, a PhD researcher at The University of Manchester, said: “We found that AI can emulate the supportive strategies that humans use, and at times even outperform human supporters in improving a person’s emotional state – though this is not universal. The effect depends on the type of emotion and what outcome you are looking at.”
She added: “We are not saying that humans should or can be replaced by AI. But our findings do show that when people choose to use AI for emotional support, it can be genuinely helpful, and understanding why it works can help us improve how both humans and AI provide that support.”
The research comes amid growing public interest in AI as an emotional resource. Recent surveys suggest that 66% of 25- to 34-year-olds in the UK have turned to AI chatbots instead of loved ones to discuss emotional problems, and in the US, 20% of young adults aged 18–21 have used ChatGPT to manage their emotions, with 92.7% of those users finding the advice helpful.
Dr Sarah Walker, co-author of the study from Durham University’s School of Education, said: “What’s key here is that we’re not suggesting AI should replace human support. But when people do turn to it, it can help, and understanding why tells us something useful. Concrete, actionable steps work better than general reassurance, and that is something all of us can get better at offering. However, we also need to think about the human cost of actionable support as well.
“When AI suggests a walk or a breathing exercise, the suggestion is where its involvement ends. When a person offers the same thing, it usually comes with their presence as well. We don’t just suggest the walk, we go on it. That kind of support takes real time and effort, and the people closest to us are often stretched thin. So to me, this work is less about AI replacing us and more of a reminder that what we want from each other in hard moments is often more than the people we love can give.”
- “A Digital Shoulder to Cry On: Understanding Why Large Language Models Can Be Effective in Extrinsic Interpersonal Emotion Regulation is published in the journal Emotion. DOI
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