Journal of Global Public Health and Healthcare Innovation

(Annual (One issue per year))

ABSTRACT

Artificial-intelligence (AI) chatbots are increasingly proposed as low-threshold instruments for supporting people with depressive symptoms, yet it remains unclear whether their acceptance is governed by users’ psychological need or by instrumental appraisal. Drawing on the Technology Acceptance Model, the present study reports original empirical data from a cross-sectional online survey that examined whether the acceptance of AI chatbots for depressive support is predicted by perceived usefulness, by psychological well-being, and by prior therapy experience. A non-probabilistic, self-selected sample of 99 adults (M = 36.56 years, SD = 10.36) was recruited through topic-relevant communities on the social-media platform Reddit and completed three-item Likert scales assessing well-being, perceived usefulness, and acceptance. Perceived usefulness correlated strongly with acceptance, r = .77, p < .001, whereas well-being was unrelated to acceptance, r = -.00, p = .989. A multiple regression explained a substantial proportion of the variance in acceptance, R² = .60, adjusted R² = .59, F(2, 96) = 72.45, p < .001, with perceived usefulness emerging as the sole significant predictor, β = .78, p < .001, while well-being did not contribute, β = .05, p = .55. Acceptance did not differ between participants with and without prior therapy experience, t(97) = 0.32, p = .748. These findings indicate that the acceptance of AI chatbots for depressive support follows an instrumental rather than a need-based logic: it is driven almost entirely by perceived usefulness, whereas current well-being and prior therapy experience play no discernible role. Implications for the design and framing of digital mental-health tools are discussed.

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