Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

Conversational Artificial Intelligence and Human Loneliness: An Explanatory Sequential Mixed-Methods Study of an Eight-Week Chatbot Interaction Program

Document Type : Original Article

Authors
A. Sharma 1
R. Mehta 2
1 Department of Psychology, University of Delhi, Delhi, India.
2 Department of Psychology, Jawaharlal Nehru University, New Delhi, India.
10.22034/tdas.2026.255849
Abstract
Background. Loneliness is a prevalent public-health problem, and conversational artificial intelligence (AI) is increasingly used for companionship, but controlled evidence outside Western settings is scarce. Objective. To examine the effect of regular interaction with a conversational AI chatbot on loneliness and psychological well-being among lonely adults in Delhi, India, and to explore how users experienced it. Method. In an explanatory sequential mixed-methods design, 132 adults aged 20–45 years with UCLA Loneliness Scale scores above 45 were randomized (1:1, concealed allocation) to eight weeks of chatbot interaction (at least 15 minutes a day, five days a week) or a waitlist control; 120 completed the posttest. Loneliness and well-being (Ryff, 42-item version) were measured before and after the intervention in both groups. Fifteen participants were then interviewed, and the transcripts were analysed thematically. Results. Adjusting for pretest scores, posttest loneliness was 15.0 points lower in the intervention group (95% CI [12.9, 17.1]; F(1, 117) = 197.9, p < .001, partial η² = .63); the effect remained in the intention-to-treat analysis (difference 13.5 points). After Holm correction, 4 of the six well-being dimensions improved more than in the control group (self-acceptance, positive relations, purpose in life, personal growth), whereas autonomy and environmental mastery did not. Attachment to the chatbot correlated with loneliness reduction (r = .34, 95% CI [.09, .55]). Interviews revealed two beneficial themes (non-judgmental reflection, constant companionship) and two risk themes (illusion of intimacy, diminished motivation for human connection). Conclusions. Conversational AI may provide short-term relief from loneliness, but the emotional bond that drives the benefit also carries a risk of dependence; the unusually large effect needs replication against an active control.
Keywords
Conversational Artificial Intelligence
Chatbot
Loneliness
Psychological Well-Being
Technology Attachment
Digital Mental-Health Intervention
Mixed Methods
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Transactions on Data Analysis in Social Science
Volume 8, Issue 1
Winter 2026
Pages 59-73

  • Receive Date 05 December 2025
  • Revise Date 26 January 2026
  • Accept Date 03 March 2026