AI-Mediated Mental Health Support: The Role of Attachment Orientation and Psychological Distress

General-purpose generative AI (GenAI) models are increasingly serving as quasi-social agents, representing a novel form of informal AI-mediated help-seeking. This study examined associations between adult attachment orientations (Experiences in Close Relationships-Relationship Structures questionnaire), psychological distress (Depression Anxiety Stress Scales–21), and the use of GenAI for mental health support. In a nonprobability sample of 584 Israeli adult GenAI users, 29.3 percent reported having turned to these models at least once for emotional support, coping advice, or mental health assistance; the proportion reached 47.0 percent among those reporting severe distress. These self-reported figures reflect any such contact, from a single exchange to sustained use. Hierarchical logistic regression identified distress as the strongest psychological correlate of use. Younger age and female gender predicted use. Attachment anxiety was associated with use, but this association did not remain significant once distress was included, a pattern consistent with the shared variance between the two constructs. Attachment avoidance was negatively but nonsignificantly associated with use. Findings position general-purpose GenAI as an accessible, low-barrier resource disproportionately used by distressed individuals. The high uptake among severely distressed users (47.0 percent) points to potential safety concerns and to a need for systematic evaluation of the safety, crisis-response quality, and clinical-displacement risks of consumer-facing AI use.