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Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness()
BACKGROUND: Depression impacts the lives of a large number of university students. Mobile-based therapy chatbots are increasingly being used to help young adults who suffer from depression. However, previous trials have short follow-up periods. Evidence of effectiveness in pragmatic conditions are s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760455/ https://www.ncbi.nlm.nih.gov/pubmed/35059305 http://dx.doi.org/10.1016/j.invent.2022.100495 |
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author | Liu, Hao Peng, Huaming Song, Xingyu Xu, Chenzi Zhang, Meng |
author_facet | Liu, Hao Peng, Huaming Song, Xingyu Xu, Chenzi Zhang, Meng |
author_sort | Liu, Hao |
collection | PubMed |
description | BACKGROUND: Depression impacts the lives of a large number of university students. Mobile-based therapy chatbots are increasingly being used to help young adults who suffer from depression. However, previous trials have short follow-up periods. Evidence of effectiveness in pragmatic conditions are still in lack. OBJECTIVE: This study aimed to compare chatbot therapy to bibliotherapy, which is a widely accepted and proven-useful self-help psychological intervention. The main objective of this study is to add to the evidence of effectiveness for chatbot therapy as a convenient, affordable, interactive self-help intervention for depression. METHODS: An unblinded randomized controlled trial with 83 university students was conducted. The participants were randomly assigned to either a chatbot test group (n = 41) to receive a newly developed chatbot-delivered intervention, or a bibliotherapy control group (n = 42) to receive a minimal level of bibliotherapy. A set of questionnaires was implemented as measurements of clinical variables at baseline and every 4 weeks for a period of 16 weeks, which included the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder scale (GAD-7), the Positive and Negative Affect Scale (PANAS). The Client Satisfaction Questionnaire-8 (CSQ-8) and the Working Alliance Inventory-Short Revised (WAI-SR) were used to measure satisfaction and therapeutic alliance after the intervention. Participants' self-reported adherence and feedback on the therapy chatbot were also collected. RESULTS: Participants were all university students (undergraduate students (n = 31), postgraduate students (n = 52)). They were between 19 and 28 years old (mean = 23.08, standard deviation (SD) = 1.76) and 55.42% (46/83) female. 24.07% (20/83) participants were lost to follow-up. No significant group difference was found at baseline. In the intention-to-treat analysis, individuals in the chatbot test group showed a significant reduction in the PHQ-9 scores (F = 22.89; P < 0.01) and the GAD-7 scores (F = 5.37; P = 0.02). Follow-up analysis of completers suggested that the reduction of anxiety was significant only in the first 4 weeks. The WAI-SR scores in the chatbot group were higher compared to the bibliotherapy group (t = 7.29; P < 0.01). User feedback showed that process factors were more influential than the content factors. CONCLUSIONS: The chatbot-delivered self-help depression intervention was proven to be superior to the minimal level of bibliotherapy in terms of reduction on depression, anxiety, and therapeutic alliance achieved with participants. |
format | Online Article Text |
id | pubmed-8760455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-87604552022-01-19 Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness() Liu, Hao Peng, Huaming Song, Xingyu Xu, Chenzi Zhang, Meng Internet Interv Full length Article BACKGROUND: Depression impacts the lives of a large number of university students. Mobile-based therapy chatbots are increasingly being used to help young adults who suffer from depression. However, previous trials have short follow-up periods. Evidence of effectiveness in pragmatic conditions are still in lack. OBJECTIVE: This study aimed to compare chatbot therapy to bibliotherapy, which is a widely accepted and proven-useful self-help psychological intervention. The main objective of this study is to add to the evidence of effectiveness for chatbot therapy as a convenient, affordable, interactive self-help intervention for depression. METHODS: An unblinded randomized controlled trial with 83 university students was conducted. The participants were randomly assigned to either a chatbot test group (n = 41) to receive a newly developed chatbot-delivered intervention, or a bibliotherapy control group (n = 42) to receive a minimal level of bibliotherapy. A set of questionnaires was implemented as measurements of clinical variables at baseline and every 4 weeks for a period of 16 weeks, which included the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder scale (GAD-7), the Positive and Negative Affect Scale (PANAS). The Client Satisfaction Questionnaire-8 (CSQ-8) and the Working Alliance Inventory-Short Revised (WAI-SR) were used to measure satisfaction and therapeutic alliance after the intervention. Participants' self-reported adherence and feedback on the therapy chatbot were also collected. RESULTS: Participants were all university students (undergraduate students (n = 31), postgraduate students (n = 52)). They were between 19 and 28 years old (mean = 23.08, standard deviation (SD) = 1.76) and 55.42% (46/83) female. 24.07% (20/83) participants were lost to follow-up. No significant group difference was found at baseline. In the intention-to-treat analysis, individuals in the chatbot test group showed a significant reduction in the PHQ-9 scores (F = 22.89; P < 0.01) and the GAD-7 scores (F = 5.37; P = 0.02). Follow-up analysis of completers suggested that the reduction of anxiety was significant only in the first 4 weeks. The WAI-SR scores in the chatbot group were higher compared to the bibliotherapy group (t = 7.29; P < 0.01). User feedback showed that process factors were more influential than the content factors. CONCLUSIONS: The chatbot-delivered self-help depression intervention was proven to be superior to the minimal level of bibliotherapy in terms of reduction on depression, anxiety, and therapeutic alliance achieved with participants. Elsevier 2022-01-06 /pmc/articles/PMC8760455/ /pubmed/35059305 http://dx.doi.org/10.1016/j.invent.2022.100495 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Full length Article Liu, Hao Peng, Huaming Song, Xingyu Xu, Chenzi Zhang, Meng Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness() |
title | Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness() |
title_full | Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness() |
title_fullStr | Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness() |
title_full_unstemmed | Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness() |
title_short | Using AI chatbots to provide self-help depression interventions for university students: A randomized trial of effectiveness() |
title_sort | using ai chatbots to provide self-help depression interventions for university students: a randomized trial of effectiveness() |
topic | Full length Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760455/ https://www.ncbi.nlm.nih.gov/pubmed/35059305 http://dx.doi.org/10.1016/j.invent.2022.100495 |
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