Background Adolescence is a critical developmental period to prevent and treat the emergence of mental health problems. Smartphone-based conversational agents can deliver psychologically driven intervention and support, thus increasing psychological well-being over time. Objective The objective of the study was to test the potential of an automated conversational agent named Kai.ai to deliver a self-help program based on Acceptance Commitment Therapy tools for adolescents, aimed to increase their well-being. Methods Participants were 10,387 adolescents, aged 14-18 years, who used Kai.ai on one of the top messaging apps (eg, iMessage and WhatsApp). Users’ well-being levels were assessed between 2 and 5 times using the 5-item World Health Organization Well-being Index questionnaire over their engagement with the service. Results Users engaged with the conversational agent an average of 45.39 (SD 46.77) days. The average well-being score at time point 1 was 39.28 (SD 18.17), indicating that, on average, users experienced reduced well-being. Latent growth curve modeling indicated that participants’ well-being significantly increased over time (β=2.49; P<.001) and reached a clinically acceptable well-being average score (above 50). Conclusions Mobile-based conversational agents have the potential to deliver engaging and effective Acceptance Commitment Therapy interventions.
Background Research and dissemination of smartphone apps to deliver coaching and psychological driven intervention had seen a great surge in recent years. Notably, Acceptance Commitment Therapy (ACT) protocols were shown to be uniquely effective in treating symptoms for both depression and anxiety when delivered through smartphone apps. The aim of this study is to expand on that work and test the suitability of artificial intelligence–driven interventions delivered directly through popular texting apps. Objective This study evaluated our hypothesis that using Kai.ai will result in improved well-being. Methods We performed a pragmatic retrospective analysis of 2909 users who used Kai.ai on one of the top messaging apps (iMessage, WhatsApp, Discord, Telegram, etc). Users’ well-being levels were tracked using the World Health Organization-Five Well-Being Index throughout the engagement with service. A 1-tailed paired samples t test was used to assess well-being levels before and after usage, and hierarchical linear modeling was used to examine the change in symptoms over time. Results The median well-being score at the last measurement was higher (median 52) than that at the start of the intervention (median 40), indicating a significant improvement (W=2682927; P<.001). Furthermore, HLM results showed that the improvement in well-being was linearly related to the number of daily messages a user sent (β=.029; t81.36=4; P<.001), as well as the interaction between the number of messages and unique number of days (β=–.0003; t81.36=–2.2; P=.03). Conclusions Mobile-based ACT interventions are effective means to improve individuals’ well-being. Our findings further demonstrate Kai.ai’s great promise in helping individuals improve and maintain high levels of well-being and thus improve their daily lives.
Over the last two decades, research has devoted increasing attention to the examination of empathy. Yet research examining empathic accuracy, defined as how well we judge the emotional intensity felt by another, has grown more modestly. This asymmetry may be due to the complexity of paradigms used to study empathic accuracy, as well as to the fact that the stimuli used so far are dependent upon linguistic and cultural factors. To circumvent these issues, here we present a novel paradigm that examines the ability to assess empathic accuracy in a simple and implicit manner by using stimuli that are not dependent on language and culture. To this end, we devised two sets of stimuli: (1) a painful scenario set consisting of empathy-evoking still images; and (2) a facial expression set comprising morphed intensities of emotional facial expressions. Together, these sets can be used to study the effect of the empathic experience on an individual's ability to make accurate judgments of others' emotional facial intensity, a sub-process of empathic accuracy. We contend that adopting these sets may facilitate the replicability of findings across countries and populations, which in turn will increase the number of investigations of empathic accuracy.
BACKGROUND The research and dissemination of smartphones-based apps to deliver coaching and psychological driven intervention had seen a great surge in recent years. Notably, Acceptance Commitment Therapy (ACT) protocols were shown to be uniquely effective in treating symptoms for both depression and anxiety when delivered through smartphone apps. The aim if this study to expand on that work and test the suitability of AI driven intervention delivered directly through popular texting apps. OBJECTIVE This study evaluated our hypothesis that using Kai.ai will result in improved well-being. METHODS A pragmatic retrospective analysis of 2909 users who used Kai.ai on one of the top messaging apps (iMessage, WhatsApp, Discord, Telegram, etc.) Users’ well-being levels were tracked using the WHO-5 well-being questionnaire throughout the engagement with service. Paired sample t-test was used to assess well-being levels pre and post usage, and Hierarchical Linear Modeling was used to examine the change in symptoms over time. RESULTS The median well-being score at the last measurement was better (Mdn = 52) then at the start of the intervention (Mdn = 40), indicating a significant improvement (W=2682927, p<.001, one tailed test). Furthermore, HLM results showed that the improvement in well-being was linearly related to the number of daily messages a user sent (beta =.029, t(81.36)=4, p<.001), as well as the interaction between the number of messages and unique number of days (beta = -.0003, t(81.36)=-2.2, p<.028). CONCLUSIONS mobile based Acceptance Commitment Therapy (ACT) interventions are effective means to improve individuals’ well-being. findings reported in this paper further demonstrate Kai.ai’s great promise in helping individuals improve and maintain high levels of well-being, and thus improve their daily life.
Background: Adolescence is a critical developmental period to prevent and treat the emergence of mental health problems. Smartphones-based conversational agents can deliver psychological driven intervention and support, thus increasing psychological wellbeing over time. Objective: The objective of the study was to test the potential of an automated conversational agent named Kai.ai to deliver a self-help program based on ACT tools for adolescents, aimed to increase their wellbeing. Methods: Participants were 10,387 adolescents, between the ages of 14-18 years old, who used Kai.ai in on one of the top messaging apps (e.g., iMessage, WhatsApp). Users’ well-being levels were assessed between two and five times using the WHO-5 well-being questionnaire, over their engagement with service. Results: Users engaged with the conversational agent an average of 45.39 days (SD = 46.77), in which they have sent a total average of 214.3 messages (SD = 220.24). The average wellbeing score at T1 was 39.09 (SD = 18.15), indicating that, on average, users experienced reduced wellbeing. Multilevel modeling analysis indicated that participants’ wellbeing significantly increased over time (β= 1.62, p < .0001), and reached a clinically acceptable wellbeing average score (above 50).Conclusions: Mobile based conversational agents has the potential to deliver engaging and effective way to deliver Acceptance Commitment Therapy (ACT) interventions.
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