Recalled Emotion Regulation in Matched Human and LLM Chatbot Support Episodes
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: People increasingly turn to LLM chatbots for emotional support, but little research compares thatsupport with human support in the same framework. We distinguish cognitive-symbolic support(articulation, validation, reframing), which a language model can deliver, fromembodied-relational support (reciprocal presence, co-regulation, being understood by a realother), which it cannot, and predicted similar outcomes on the first and a human advantage onthe second. In a preregistered within-subject retrospective study (osf.io/pesrh), 583 Prolificparticipants who had talked to both a person and an LLM chatbot about the same or acomparable personal topic in the past week reported both episodes in randomized order.Outcomes were recalled distress change, perceived attunement, emotional expression andprocessing, and help-seeking. Both episode types were associated with large recalled distressreductions (AI dz = 1.22; human dz = 1.00), and the difference between them met thepreregistered equivalence criterion (dz = 0.20; pTOST = .009). Contrary to prediction,attunement, expression, processing, and same-source help-seeking intention showed nodetectable difference by source, with 95 percent confidence intervals within dz = ±0.12.Conclusions held when the 479 excluded cases were restored and when topic domain wascovaried. Felt closeness to the source, higher for humans, predicted attunement in both episodetypes, processing in human episodes, and distress reduction in AI episodes. A reflexive thematicanalysis of 619 topic descriptions identified four needs that participants brought to both sources.Among recent dual-source users, recalled support outcomes were strikingly similar for a personand a chatbot. Whether the underlying relational processes or longer-term outcomes are similarremains untested.
Source: PsyArXiv (OSF Preprints)
Authors: Luigi Maruani, June Thompson, Maahir Uttam
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7212317537