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Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing
BACKGROUND: The delivery of education on pain neuroscience and the evidence for different treatment approaches has become a key component of contemporary persistent pain management. Chatbots, or more formally conversation agents, are increasingly being used in health care settings due to their versa...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589833/ https://www.ncbi.nlm.nih.gov/pubmed/37801342 http://dx.doi.org/10.2196/47267 |
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author | Andrews, Nicole Emma Ireland, David Vijayakumar, Pranavie Burvill, Lyza Hay, Elizabeth Westerman, Daria Rose, Tanya Schlumpf, Mikaela Strong, Jenny Claus, Andrew |
author_facet | Andrews, Nicole Emma Ireland, David Vijayakumar, Pranavie Burvill, Lyza Hay, Elizabeth Westerman, Daria Rose, Tanya Schlumpf, Mikaela Strong, Jenny Claus, Andrew |
author_sort | Andrews, Nicole Emma |
collection | PubMed |
description | BACKGROUND: The delivery of education on pain neuroscience and the evidence for different treatment approaches has become a key component of contemporary persistent pain management. Chatbots, or more formally conversation agents, are increasingly being used in health care settings due to their versatility in providing interactive and individualized approaches to both capture and deliver information. Research focused on the acceptability of diverse chatbot formats can assist in developing a better understanding of the educational needs of target populations. OBJECTIVE: This study aims to detail the development and initial pilot testing of a multimodality pain education chatbot (Dolores) that can be used across different age groups and investigate whether acceptability and feedback were comparable across age groups following pilot testing. METHODS: Following an initial design phase involving software engineers (n=2) and expert clinicians (n=6), a total of 60 individuals with chronic pain who attended an outpatient clinic at 1 of 2 pain centers in Australia were recruited for pilot testing. The 60 individuals consisted of 20 (33%) adolescents (aged 10-18 years), 20 (33%) young adults (aged 19-35 years), and 20 (33%) adults (aged >35 years) with persistent pain. Participants spent 20 to 30 minutes completing interactive chatbot activities that enabled the Dolores app to gather a pain history and provide education about pain and pain treatments. After the chatbot activities, participants completed a custom-made feedback questionnaire measuring the acceptability constructs pertaining to health education chatbots. To determine the effect of age group on the acceptability ratings and feedback provided, a series of binomial logistic regression models and cumulative odds ordinal logistic regression models with proportional odds were generated. RESULTS: Overall, acceptability was high for the following constructs: engagement, perceived value, usability, accuracy, responsiveness, adoption intention, esthetics, and overall quality. The effect of age group on all acceptability ratings was small and not statistically significant. An analysis of open-ended question responses revealed that major frustrations with the app were related to Dolores’ speech, which was explored further through a comparative analysis. With respect to providing negative feedback about Dolores’ speech, a logistic regression model showed that the effect of age group was statistically significant (χ(2)(2)=11.7; P=.003) and explained 27.1% of the variance (Nagelkerke R(2)). Adults and young adults were less likely to comment on Dolores’ speech compared with adolescent participants (odds ratio 0.20, 95% CI 0.05-0.84 and odds ratio 0.05, 95% CI 0.01-0.43, respectively). Comments were related to both speech rate (too slow) and quality (unpleasant and robotic). CONCLUSIONS: This study provides support for the acceptability of pain history and education chatbots across different age groups. Chatbot acceptability for adolescent cohorts may be improved by enabling the self-selection of speech characteristics such as rate and personable tone. |
format | Online Article Text |
id | pubmed-10589833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-105898332023-10-22 Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing Andrews, Nicole Emma Ireland, David Vijayakumar, Pranavie Burvill, Lyza Hay, Elizabeth Westerman, Daria Rose, Tanya Schlumpf, Mikaela Strong, Jenny Claus, Andrew JMIR Form Res Original Paper BACKGROUND: The delivery of education on pain neuroscience and the evidence for different treatment approaches has become a key component of contemporary persistent pain management. Chatbots, or more formally conversation agents, are increasingly being used in health care settings due to their versatility in providing interactive and individualized approaches to both capture and deliver information. Research focused on the acceptability of diverse chatbot formats can assist in developing a better understanding of the educational needs of target populations. OBJECTIVE: This study aims to detail the development and initial pilot testing of a multimodality pain education chatbot (Dolores) that can be used across different age groups and investigate whether acceptability and feedback were comparable across age groups following pilot testing. METHODS: Following an initial design phase involving software engineers (n=2) and expert clinicians (n=6), a total of 60 individuals with chronic pain who attended an outpatient clinic at 1 of 2 pain centers in Australia were recruited for pilot testing. The 60 individuals consisted of 20 (33%) adolescents (aged 10-18 years), 20 (33%) young adults (aged 19-35 years), and 20 (33%) adults (aged >35 years) with persistent pain. Participants spent 20 to 30 minutes completing interactive chatbot activities that enabled the Dolores app to gather a pain history and provide education about pain and pain treatments. After the chatbot activities, participants completed a custom-made feedback questionnaire measuring the acceptability constructs pertaining to health education chatbots. To determine the effect of age group on the acceptability ratings and feedback provided, a series of binomial logistic regression models and cumulative odds ordinal logistic regression models with proportional odds were generated. RESULTS: Overall, acceptability was high for the following constructs: engagement, perceived value, usability, accuracy, responsiveness, adoption intention, esthetics, and overall quality. The effect of age group on all acceptability ratings was small and not statistically significant. An analysis of open-ended question responses revealed that major frustrations with the app were related to Dolores’ speech, which was explored further through a comparative analysis. With respect to providing negative feedback about Dolores’ speech, a logistic regression model showed that the effect of age group was statistically significant (χ(2)(2)=11.7; P=.003) and explained 27.1% of the variance (Nagelkerke R(2)). Adults and young adults were less likely to comment on Dolores’ speech compared with adolescent participants (odds ratio 0.20, 95% CI 0.05-0.84 and odds ratio 0.05, 95% CI 0.01-0.43, respectively). Comments were related to both speech rate (too slow) and quality (unpleasant and robotic). CONCLUSIONS: This study provides support for the acceptability of pain history and education chatbots across different age groups. Chatbot acceptability for adolescent cohorts may be improved by enabling the self-selection of speech characteristics such as rate and personable tone. JMIR Publications 2023-10-06 /pmc/articles/PMC10589833/ /pubmed/37801342 http://dx.doi.org/10.2196/47267 Text en ©Nicole Emma Andrews, David Ireland, Pranavie Vijayakumar, Lyza Burvill, Elizabeth Hay, Daria Westerman, Tanya Rose, Mikaela Schlumpf, Jenny Strong, Andrew Claus. Originally published in JMIR Formative Research (https://formative.jmir.org), 06.10.2023. 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 Andrews, Nicole Emma Ireland, David Vijayakumar, Pranavie Burvill, Lyza Hay, Elizabeth Westerman, Daria Rose, Tanya Schlumpf, Mikaela Strong, Jenny Claus, Andrew Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing |
title | Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing |
title_full | Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing |
title_fullStr | Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing |
title_full_unstemmed | Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing |
title_short | Acceptability of a Pain History Assessment and Education Chatbot (Dolores) Across Age Groups in Populations With Chronic Pain: Development and Pilot Testing |
title_sort | acceptability of a pain history assessment and education chatbot (dolores) across age groups in populations with chronic pain: development and pilot testing |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589833/ https://www.ncbi.nlm.nih.gov/pubmed/37801342 http://dx.doi.org/10.2196/47267 |
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