关键词: chatbot conversational agent digital intervention eating disorder mHealth mental health treatment optimization screening

来  源:   DOI:10.1002/eat.24260

Abstract:
OBJECTIVE: Few individuals with eating disorders (EDs) receive treatment. Innovations are needed to identify individuals with EDs and address care barriers. We developed a chatbot for promoting services uptake that could be paired with online screening. However, it is not yet known which components drive effects. This study estimated individual and combined contributions of four chatbot components on mental health services use (primary), chatbot helpfulness, and attitudes toward changing eating/shape/weight concerns (\"change attitudes,\" with higher scores indicating greater importance/readiness).
METHODS: Two hundred five individuals screening with an ED but not in treatment were randomized in an optimization randomized controlled trial to receive up to four chatbot components: psychoeducation, motivational interviewing, personalized service recommendations, and repeated administration (follow-up check-ins/reminders). Assessments were at baseline and 2, 6, and 14 weeks.
RESULTS: Participants who received repeated administration were more likely to report mental health services use, with no significant effects of other components on services use. Repeated administration slowed the decline in change attitudes participants experienced over time. Participants who received motivational interviewing found the chatbot more helpful, but this component was also associated with larger declines in change attitudes. Participants who received personalized recommendations found the chatbot more helpful, and receiving this component on its own was associated with the most favorable change attitude time trend. Psychoeducation showed no effects.
CONCLUSIONS: Results indicated important effects of components on outcomes; findings will be used to finalize decision making about the optimized intervention package. The chatbot shows high potential for addressing the treatment gap for EDs.
摘要:
目的:很少有进食障碍(ED)患者接受治疗。需要创新来识别患有ED的个人并解决护理障碍。我们开发了一个聊天机器人,用于促进服务的吸收,可以与在线筛选配对。然而,尚不知道哪些组件驱动效果。这项研究估计了四个聊天机器人组件对心理健康服务使用(主要)的个人和综合贡献,聊天机器人乐于助人,以及对改变饮食/形状/体重问题的态度(“改变态度,“分数越高,表明重要性/准备程度越高)。
方法:在一项优化的随机对照试验中,随机选择了250名接受ED筛查但未接受治疗的个体,以接受多达四个聊天机器人组件:心理教育,动机性面试,个性化服务推荐,和重复给药(随访检查/提醒)。在基线和第2、6和14周进行评估。
结果:接受重复给药的参与者更有可能报告使用精神卫生服务,其他组件对服务使用没有显著影响。重复管理减缓了参与者随着时间的推移所经历的态度变化的下降。接受激励面试的参与者发现聊天机器人更有帮助,但这一因素也与改变态度的更大下降有关。收到个性化推荐的参与者发现聊天机器人更有帮助,并且自己接收该组件与最有利的改变态度时间趋势有关。心理教育没有效果。
结论:结果表明各组成部分对结果的重要影响;研究结果将用于最终确定有关优化干预方案的决策。聊天机器人显示出解决ED治疗差距的巨大潜力。
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