Unveiling the human touch: how AI chatbots’ emotional support and human-like profiles reduce psychological reactance to promote user self-disclosure in mental health services
Aug 2026· International Journal of Advertising· Vol 45, pp. 1499 - 1523· 17 citations· ⚡ 1 influential· 79 references
TL;DR
Investigation of two dimensions of anthropomorphism in human–chatbot interactions revealed that high emotional support from a chatbot, particularly when presented with a human-like profile, effectively reduced psychological reactance, which promoted the adoption of adaptive coping strategies for managing stress.
An exploratory account of how AI use is embedded within broader emotional and relational dynamics, pointing to the need to consider AI engagement within the contexts in which social interaction is managed.
Nurashikin Salim, Ayşe Şafak, Merve Güçlü Aydoğan· Current Psychology· 0 citations
This study concludes that the evolution of human–AI communication represents the emergence of new digital communication practices that expand the role of AI from a mere technological tool to an agent participating in users’ communication experiences.
Faza An’imah, Fitriana Ulya, Luluk Ridotuljana et al.· International journal of res...· 0 citations
The findings informed the development of the Integrated Attachment–Motivation–Pedagogy (AMP) model with direct implications for designing AI in culturally sensitive pedagogical practices.
Saiful Islam Polash, Shariful Islam, Faimul Hoq· SAP Social AI· 0 citations
As AI chatbots increasingly provide conversational and emotional support, understanding emotional disclosure has become important. Yet little is known about whether accessing the same AI service through different devices shapes disclosure. Across three studies (
N
= 754), we examined whether accessing an AI chatbot through a smartphone rather than a computer shapes emotional disclosure. Study 1 found greater emotional expression in smartphone interactions through LIWC analysis of disclosures about self‐selected negative events. Study 2 replicated this pattern using disclosure choices and identified an indirect pathway in which smartphone access predicted a higher proportion of emotion‐focused choices, which was associated with lower post‐interaction negative emotions. Study 3 identified perceived portability as a mediator and showed that this indirect effect was supported under a warmth‐oriented response style but not under a competence‐oriented response style. These findings advance a media affordance account by showing how the device of access shapes emotional disclosure to AI chatbots and by providing study‐specific evidence that response style conditions this pathway.
Bingcan Li, Yi Huang, Rukun Zhang· Psychology & Marketing· 0 citations
While ChatGPT was primarily viewed as an efficient tool in a work context, the quantitative survey reveals a weakly significant correlation between psychological stress and openness toward the social-emotional use of chatbots.
Stefanie Osetrow, H. Klapperich, Dr. Alina Huldtgren· Proceedings of Mensch und Co...· 0 citations
Mental health (MH) chatbots are increasingly used to provide accessible, on-demand emotional support, yet it remains unclear how these systems linguistically construct and communicate care. This work-in-progress examines whether MH chatbots produce responses that reflect supportive value orientations and counseling-adjacent tone. We conduct an observational analysis of responses from three widely used MH chatbots (Wysa, Sintelly, and Youper) across context-aware scenario prompts and a standardized-question session. Responses are analyzed using the SemEval’23 “Adam Smith” human value detection model and LIWC’22 psycholinguistic measures, including Language Style Matching (LSM), Clout, and Authenticity. Values such as “Security: Personal” and “Benevolence: Caring” appear consistently across systems, with contextual variation in secondary value emphasis. Linguistic patterns show moderate-to-high LSM and consistently high Clout, with Authenticity varying by scenario. These findings are exploratory signals intended to inform future evaluation and design of supportive conversational mental health systems.
Maleeha Sheikh, Chao Chen, Romael Haque· Information Hiding· 0 citations