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使用人工标注和自然语言处理技术对Reddit上有关丁丙诺啡-纳洛酮内容的主题分析

Thematic Analysis of Reddit Content About Buprenorphine-naloxone Using Manual Annotation and Natural Language Processing Techniques.

作者信息

Graves Rachel Lynn, Perrone Jeanmarie, Al-Garadi Mohammed Ali, Yang Yuan-Chi, Love Jennifers, O'Connor Karen, Gonzalez-Hernandez Graciela, Sarker Abeed

机构信息

From the Department of Emergency Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA (RLG, JP); Department of Biomedical Informatics, Emory University School of Medicine, Woodruff Memorial Research Building, Atlanta, GA, USA (MAA-G, Y-CY, AS); Department of Emergency Medicine, School of Medicine, Oregon Health and Science University, Portland, OR, USA (JSL); Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (KC, GG-H); Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA (AS).

出版信息

J Addict Med. 2022;16(4):454-460. doi: 10.1097/ADM.0000000000000940. Epub 2021 Dec 23.

DOI:10.1097/ADM.0000000000000940
PMID:34864788
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9365256/
Abstract

BACKGROUND

Opioid use disorder (OUD) is a major public health crisis for which buprenorphine-naloxone is an effective evidence-based treatment. Analysis of Reddit data yields detailed information about firsthand experiences with buprenorphine-naloxone that has the potential to inform treatment of OUD.

METHODS

We conducted a thematic analysis of posts about buprenorphine-naloxone from a Reddit forum in which Reddit users anonymously discuss topics related to opioid use. We used an application programming interface to retrieve posts about buprenorphine-naloxone, then applied natural language processing to generate meta-information and curate samples of salient posts. We manually categorized posts according to their content and conducted natural language processing-aided analysis of posts about buprenorphine tapering strategies, withdrawal symptoms, and adjunctive substances/behaviors useful in the tapering process.

RESULTS

A total of 16,146 posts from 1933 redditors were retrieved from the /r/suboxone subreddit. Thematic analysis of sample posts (N = 200) revealed descriptions of personal experiences (74%), nonpersonal accounts (24%), and other content (2%). Among redditors who reported tapering to termination (N = 40), 0.063 mg and 0.125 mg were the most common termination doses. Fatigue, gastrointestinal disturbance, and mood disturbance were the most frequent adverse effects, and loperamide and vitamins/dietary supplements the most frequently discussed adverse effects adjunctive substances/behaviors respectively.

CONCLUSIONS

Discussions on Reddit are rich in information about buprenorphine-naloxone. Information derived from analysis of Reddit posts about buprenorphine-naloxone may not be available elsewhere and may help providers improve treatment of people with OUD through better understanding of the experiences of people who have used buprenorphine-naloxone.

摘要

背景

阿片类物质使用障碍(OUD)是一场重大的公共卫生危机,丁丙诺啡 - 纳洛酮是一种基于证据的有效治疗方法。对Reddit数据的分析可得出有关丁丙诺啡 - 纳洛酮第一手经验的详细信息,这些信息有可能为OUD的治疗提供参考。

方法

我们对一个Reddit论坛中关于丁丙诺啡 - 纳洛酮的帖子进行了主题分析,在这个论坛上,Reddit用户匿名讨论与阿片类物质使用相关的话题。我们使用应用程序编程接口检索关于丁丙诺啡 - 纳洛酮的帖子,然后应用自然语言处理来生成元信息并策划突出帖子的样本。我们根据帖子内容进行手动分类,并对关于丁丙诺啡减药策略、戒断症状以及在减药过程中有用的辅助物质/行为的帖子进行自然语言处理辅助分析。

结果

从/r/suboxone子版块中检索到了来自1933名Reddit用户的总共16146个帖子。对样本帖子(N = 200)的主题分析显示,个人经历描述占74%,非个人记录占24%,其他内容占2%。在报告减药至停药的Reddit用户(N = 40)中,0.063毫克和0.125毫克是最常见的停药剂量。疲劳、胃肠道不适和情绪紊乱是最常见的不良反应,洛哌丁胺和维生素/膳食补充剂分别是讨论最多的辅助物质/行为。

结论

Reddit上的讨论包含了丰富的关于丁丙诺啡 - 纳洛酮的信息。从对Reddit上关于丁丙诺啡 - 纳洛酮的帖子分析中获得的信息可能在其他地方无法获取,并且可能有助于医疗服务提供者通过更好地了解使用丁丙诺啡 - 纳洛酮的人的经历来改善对OUD患者的治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7abd/9365256/af84fabbfab1/jam-16-454-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7abd/9365256/9adf91ee5e80/jam-16-454-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7abd/9365256/af84fabbfab1/jam-16-454-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7abd/9365256/9adf91ee5e80/jam-16-454-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7abd/9365256/af84fabbfab1/jam-16-454-g002.jpg

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