Scholarlink

<p>Young adults aged 18–35 years increasingly engage with conversational artificial intelligence (C-AI) in everyday contexts in which they may perceive emotional relief, cognitive clarification, and psychological support. However, the mechanisms through which C-AI interactions are associated with users’ perceived psychological health support remain insufficiently understood. Drawing on an extended stimulus-organism-response (S-O-R) framework, this mixed-methods study examined the associations among Conversational AI Perceived Trust (C-AIPT), Conversational AI Perceived Warmth (C-AIPW), Technology Healthy Use (THU), and Perceived Psychological Health Support (PHS). In this study, PHS was conceptualized as users’ subjective appraisal of psychological support arising from everyday C-AI interactions, rather than as mental health-specific use or clinically verified improvement in mental health symptoms. THU was conceptualized not as objectively observed use behavior or usage frequency, but as a self-regulatory orientation toward C-AI engagement encompassing moderate use, reflective judgment, goal orientation, and boundary awareness. Survey data from 1,006 participants with prior C-AI use experience, collected between July and August 2025, were analyzed using partial least squares structural equation modeling (PLS-SEM) with 5,000 bootstrap resamples. These quantitative analyses were complemented by asynchronous in-depth interviews with 50 experienced C-AI users. The results showed that C-AIPT significantly predicted both C-AIPW (β = 0.774, <i>P</i> &lt; 0.001) and THU (β = 0.409, <i>P</i> &lt; 0.001), whereas only THU was directly associated with PHS (β = 0.382, <i>P</i> &lt; 0.001). Mediation analyses identified THU as the primary self-regulatory pathway linking C-AIPT to PHS. In addition, AI autonomy (AIAu) weakened the association between C-AIPT and THU, whereas AI attachment (AIAt) weakened the association between THU and PHS. Qualitative findings further suggest that perceived warmth primarily functions as an interactional cue rather than a direct therapeutic mechanism. Overall, the findings suggest that perceived psychological health support in everyday C-AI use is more closely related to goal-oriented, self-regulated, and boundary-aware healthy engagement than to emotional warmth alone.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Trust-driven healthy engagement with conversational AI for mental health support in young adults: a mixed methods study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月23日

查看全文
  • Yanling Lan,
  • Sihang Liu,
  • Chao Liu,
  • Hao Chen

摘要

Young adults aged 18–35 years increasingly engage with conversational artificial intelligence (C-AI) in everyday contexts in which they may perceive emotional relief, cognitive clarification, and psychological support. However, the mechanisms through which C-AI interactions are associated with users’ perceived psychological health support remain insufficiently understood. Drawing on an extended stimulus-organism-response (S-O-R) framework, this mixed-methods study examined the associations among Conversational AI Perceived Trust (C-AIPT), Conversational AI Perceived Warmth (C-AIPW), Technology Healthy Use (THU), and Perceived Psychological Health Support (PHS). In this study, PHS was conceptualized as users’ subjective appraisal of psychological support arising from everyday C-AI interactions, rather than as mental health-specific use or clinically verified improvement in mental health symptoms. THU was conceptualized not as objectively observed use behavior or usage frequency, but as a self-regulatory orientation toward C-AI engagement encompassing moderate use, reflective judgment, goal orientation, and boundary awareness. Survey data from 1,006 participants with prior C-AI use experience, collected between July and August 2025, were analyzed using partial least squares structural equation modeling (PLS-SEM) with 5,000 bootstrap resamples. These quantitative analyses were complemented by asynchronous in-depth interviews with 50 experienced C-AI users. The results showed that C-AIPT significantly predicted both C-AIPW (β = 0.774, P < 0.001) and THU (β = 0.409, P < 0.001), whereas only THU was directly associated with PHS (β = 0.382, P < 0.001). Mediation analyses identified THU as the primary self-regulatory pathway linking C-AIPT to PHS. In addition, AI autonomy (AIAu) weakened the association between C-AIPT and THU, whereas AI attachment (AIAt) weakened the association between THU and PHS. Qualitative findings further suggest that perceived warmth primarily functions as an interactional cue rather than a direct therapeutic mechanism. Overall, the findings suggest that perceived psychological health support in everyday C-AI use is more closely related to goal-oriented, self-regulated, and boundary-aware healthy engagement than to emotional warmth alone.