TY  - JOUR
AU  - Vertsberger, Dana
AU  - Naor, Navot
AU  - Winsberg, Mirène
PY  - 2022
DA  - 2022/11/29
TI  - Adolescents’ Well-being While Using a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Evidence From a Longitudinal Study
JO  - JMIR AI
SP  - e38171
VL  - 1
IS  - 1
KW  - well-being
KW  - adolescents
KW  - chatbots
KW  - conversational agents
KW  - mental health
KW  - mobile mental health
KW  - automated
KW  - support
KW  - self-management
KW  - self-help
KW  - smartphone
KW  - psychology
KW  - intervention
KW  - psychological
KW  - therapy
KW  - acceptance
KW  - commitment
KW  - engagement
AB  - 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. 
SN  - 2817-1705
UR  - https://ai.jmir.org/2022/1/e38171
UR  - https://doi.org/10.2196/38171
DO  - 10.2196/38171
ID  - info:doi/10.2196/38171
ER  -