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Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328790/ https://www.ncbi.nlm.nih.gov/pubmed/35598216 http://dx.doi.org/10.2196/36018 |
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author | Naor, Navot Frenkel, Alex Winsberg, Mirène |
author_facet | Naor, Navot Frenkel, Alex Winsberg, Mirène |
author_sort | Naor, Navot |
collection | PubMed |
description | 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; t(81.36)=4; P<.001), as well as the interaction between the number of messages and unique number of days (β=–.0003; t(81.36)=–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. |
format | Online Article Text |
id | pubmed-9328790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-93287902022-07-28 Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study Naor, Navot Frenkel, Alex Winsberg, Mirène JMIR Form Res Original Paper 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; t(81.36)=4; P<.001), as well as the interaction between the number of messages and unique number of days (β=–.0003; t(81.36)=–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. JMIR Publications 2022-07-12 /pmc/articles/PMC9328790/ /pubmed/35598216 http://dx.doi.org/10.2196/36018 Text en ©Navot Naor, Alex Frenkel, Mirène Winsberg. Originally published in JMIR Formative Research (https://formative.jmir.org), 12.07.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Naor, Navot Frenkel, Alex Winsberg, Mirène Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study |
title | Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study |
title_full | Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study |
title_fullStr | Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study |
title_full_unstemmed | Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study |
title_short | Improving Well-being With a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Pragmatic Retrospective Study |
title_sort | improving well-being with a mobile artificial intelligence–powered acceptance commitment therapy tool: pragmatic retrospective study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328790/ https://www.ncbi.nlm.nih.gov/pubmed/35598216 http://dx.doi.org/10.2196/36018 |
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