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Automated Reinforcement Management System (ARMS): focused phase I provider feedback

BACKGROUND: Alcohol use increases risk for morbidity and mortality and is associated with over 3 million annual deaths worldwide. Contingency Management (CM) is one of the most effective interventions for substance use disorders, and has recently been coupled with technologies to promote novel treat...

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Autores principales: Smith, Crystal L., Rodin, Nicole M., Hwang, Julie Y., Miguel, André Q. C., Johnson, Kim, McDonell, Michael G., McPherson, Sterling M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962143/
https://www.ncbi.nlm.nih.gov/pubmed/35346358
http://dx.doi.org/10.1186/s13722-022-00301-w
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author Smith, Crystal L.
Rodin, Nicole M.
Hwang, Julie Y.
Miguel, André Q. C.
Johnson, Kim
McDonell, Michael G.
McPherson, Sterling M.
author_facet Smith, Crystal L.
Rodin, Nicole M.
Hwang, Julie Y.
Miguel, André Q. C.
Johnson, Kim
McDonell, Michael G.
McPherson, Sterling M.
author_sort Smith, Crystal L.
collection PubMed
description BACKGROUND: Alcohol use increases risk for morbidity and mortality and is associated with over 3 million annual deaths worldwide. Contingency Management (CM) is one of the most effective interventions for substance use disorders, and has recently been coupled with technologies to promote novel treatments for alcohol use disorders (AUD). Leveraging these technological advances, we are developing the Automated Reinforcement Management System (ARMS), an integrated CM system designed to enable CM treatment as a component of a digital therapeutic or adjunct therapy remotely to anyone with a smartphone. OBJECTIVE: To collect detailed provider feedback on ARMS and determine the need for modifications to make the system most feasible, acceptable, and useful to providers. METHODS: Seven providers completed one-hour structured interviews/focus groups wherein we described the ARMS system and its application to clinical care. Providers viewed screen shots of the ARMS provider facing and patient facing systems. Providers gave feedback on their current AUD treatment practices, preferences for the functionality and appearance of the system, preferences for receipt of information on their patients, why they and their patients would or would not use the system, suggestions for improvement, and the proposed intervention overall. To analyze the qualitative data gathered, we used a qualitative descriptive approach with content analysis methods. RESULTS: The overarching theme of Individualized Treatment emerged throughout the interviews. This sentiment supports use of ARMS, as it is intended to supplement provider communication and intervention as an adjunctive and customizable tool with the ability to reach rural patients, not a stand-alone option. Themes of Accountability and Objective Assessment arose during discussions of why people would use the system. Themes within provider obstacles included, Information Overload and Clinical Relevance, and in patient obstacles, Sustained Engagement and Security Concerns. Two themes emerged regarding suggestions for improvement: Increasing Accessibility and Bi-directional Communication. DISCUSSION: Themes from provider input are being used to modify ARMS to make it more user friendly, time saving, and relevant to treatment of AUD. If successful, ARMS will provide effective, individualized-digital therapeutic for those needing adjunctive treatment or those living in rural remote areas needing better connected care.
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spelling pubmed-89621432022-03-30 Automated Reinforcement Management System (ARMS): focused phase I provider feedback Smith, Crystal L. Rodin, Nicole M. Hwang, Julie Y. Miguel, André Q. C. Johnson, Kim McDonell, Michael G. McPherson, Sterling M. Addict Sci Clin Pract Research BACKGROUND: Alcohol use increases risk for morbidity and mortality and is associated with over 3 million annual deaths worldwide. Contingency Management (CM) is one of the most effective interventions for substance use disorders, and has recently been coupled with technologies to promote novel treatments for alcohol use disorders (AUD). Leveraging these technological advances, we are developing the Automated Reinforcement Management System (ARMS), an integrated CM system designed to enable CM treatment as a component of a digital therapeutic or adjunct therapy remotely to anyone with a smartphone. OBJECTIVE: To collect detailed provider feedback on ARMS and determine the need for modifications to make the system most feasible, acceptable, and useful to providers. METHODS: Seven providers completed one-hour structured interviews/focus groups wherein we described the ARMS system and its application to clinical care. Providers viewed screen shots of the ARMS provider facing and patient facing systems. Providers gave feedback on their current AUD treatment practices, preferences for the functionality and appearance of the system, preferences for receipt of information on their patients, why they and their patients would or would not use the system, suggestions for improvement, and the proposed intervention overall. To analyze the qualitative data gathered, we used a qualitative descriptive approach with content analysis methods. RESULTS: The overarching theme of Individualized Treatment emerged throughout the interviews. This sentiment supports use of ARMS, as it is intended to supplement provider communication and intervention as an adjunctive and customizable tool with the ability to reach rural patients, not a stand-alone option. Themes of Accountability and Objective Assessment arose during discussions of why people would use the system. Themes within provider obstacles included, Information Overload and Clinical Relevance, and in patient obstacles, Sustained Engagement and Security Concerns. Two themes emerged regarding suggestions for improvement: Increasing Accessibility and Bi-directional Communication. DISCUSSION: Themes from provider input are being used to modify ARMS to make it more user friendly, time saving, and relevant to treatment of AUD. If successful, ARMS will provide effective, individualized-digital therapeutic for those needing adjunctive treatment or those living in rural remote areas needing better connected care. BioMed Central 2022-03-26 2022 /pmc/articles/PMC8962143/ /pubmed/35346358 http://dx.doi.org/10.1186/s13722-022-00301-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Smith, Crystal L.
Rodin, Nicole M.
Hwang, Julie Y.
Miguel, André Q. C.
Johnson, Kim
McDonell, Michael G.
McPherson, Sterling M.
Automated Reinforcement Management System (ARMS): focused phase I provider feedback
title Automated Reinforcement Management System (ARMS): focused phase I provider feedback
title_full Automated Reinforcement Management System (ARMS): focused phase I provider feedback
title_fullStr Automated Reinforcement Management System (ARMS): focused phase I provider feedback
title_full_unstemmed Automated Reinforcement Management System (ARMS): focused phase I provider feedback
title_short Automated Reinforcement Management System (ARMS): focused phase I provider feedback
title_sort automated reinforcement management system (arms): focused phase i provider feedback
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962143/
https://www.ncbi.nlm.nih.gov/pubmed/35346358
http://dx.doi.org/10.1186/s13722-022-00301-w
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