ArticleFrontiers in public health2026
Loneliness to consumption intention: emotional bonding and escapism in AI emotional companion app use.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
With the diffusion of generative AI, AI emotional companion apps have emerged as a new domain of digital consumption in which users may pay to extend relationship-like experiences. This study examines how loneliness and actual-ideal self-discrepancy are associated with experience-enhancing consumption intention and continuance intention through two competing pathways: emotional bonding with the AI (relational compensation) and escapism (avoidant compensation). The emotional bond with the AI is modeled as a second-order construct comprising anthropomorphism, emotional responsiveness, and parasocial intimacy. Data were collected from 393 adult users in China who used AI emotional companion apps at least twice per week and were analyzed using structural equation modeling. Loneliness and actual-ideal self-discrepancy were positively associated with both emotional bonding and escapism. However, significant indirect associations with experience-enhancing consumption intention and continuance intention emerged only through the emotional-bond pathway. Direct comparisons further showed that the relational indirect effects were significantly stronger than the avoidant indirect effects across all antecedent-outcome combinations. Escapism was significantly associated with both outcomes when modeled alone but became nonsignificant when emotional bonding was included, suggesting that its association with consumer responses largely overlaps with the relational pathway. A partial-mediation analysis further showed that actual-ideal self-discrepancy retained a significant direct association with continuance intention. These findings suggest that relational compensation, rather than avoidant compensation, is more closely associated with willingness to pay for experience enhancement and intention to continue using AI companions. The study extends compensatory-use, self-discrepancy, and parasocial-interaction perspectives to the AI-companion context by linking psychological vulnerability to experience-enhancing consumption intention and continuance intention, while highlighting implications for responsible relational design and user protection.
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