直近一年間の累計
アクセス数 : ?
ダウンロード数 : ?
ID 116067
著者
キーワード
problem gambling
web-based anonymous gambler chat meetings
self-help group
change talk classifier
computerized text analysis
long-term data with dropout gamblers
recovery gradient
gradient descent method
gambling
addiction
abstinence
資料タイプ
学術雑誌論文
抄録
Background: Change and sustain talks (negative and positive comments) on gambling have been relevant for determining gamblers’ outcomes but they have not been used to clarify the abstinence process in anonymous gambler meetings.
Objective: The aim of this study was to develop a change talk model for abstinence based on data extracted from web-based anonymous gambler chat meetings by using an automatic change talk classifier.
Methods: This study used registry data from the internet. The author accessed web-based anonymous gambler chat meetings in Japan and sampled 1.63 million utterances (two-sentence texts) from 267 abstinent gamblers who have remained abstinent for at least three years and 1625 nonabstinent gamblers. The change talk classifier in this study automatically classified gamblers’ utterances into change and sustain talks.
Results: Abstinent gamblers showed higher proportions of change talks and lower probability of sustain talks compared with nonabstinent gamblers. The change talk model for abstinence, involving change and sustain talks, classified abstinent and nonabstinent gamblers through the use of a support vector machine with a radial basis kernel function. The model also indicated individual evaluation scores for abstinence and the ideal proportion of change talks for all participants according to their previous utterances.
Conclusions: Abstinence likelihood among gamblers can be increased by providing personalized evaluation values and indicating the optimal proportion of change talks. Moreover, this may help to prevent severe mental, social, and financial problems caused by the gambling disorder.
掲載誌名
Journal of Medical Internet Research
ISSN
14388871
出版者
JMIR Publications
23
6
開始ページ
e24088
発行日
2021-06-21
権利情報
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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
総合科学系