“停止大麻”移动应用程序用户使用大麻的动机和改变的意愿:聚类分析。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES
Milena Wegener, Stéphane Rothen, Elise Dan-Glauser, Tania Lecomte, Stéphane Potvin, Lucien Rochat, Marissa Sjöblom, Germano Vera Cruz, Jean-François Etter, Yasser Khazaal
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引用次数: 0

摘要

背景:大麻的使用是广泛的,并由多种动机驱动,从娱乐目的到应对心理困扰。了解大麻使用的潜在原因,它们在不同大麻使用者亚群体中的分布,以及它们与可能的行为改变之间的关系,对于制定有效的预防和干预策略至关重要,例如旨在支持改变的智能手机应用程序。目的:该研究的主要目的是确定分析“停止大麻”应用程序(瑞士日内瓦大学全球卫生研究所)上的资料是否可以揭示基于大麻使用动机和改变意愿的亚群体。第二个目标是在有问题的使用和其他变化准备指标方面探索这些子组之间的差异。方法:本研究分析了2578名使用“停止大麻应用程序”的个人数据,这是瑞士开发的一款移动应用程序,旨在支持那些寻求管理大麻使用的人。参与者完成了有效的问卷调查,评估使用动机(大麻动机测量[MMM]),改变的准备(改变准备和治疗渴望量表[SOCRATES]),以及有问题使用的风险(酒精,吸烟和物质介入筛选测试[ASSIST])。他们还对自己的“行动准备情况”、“改变的重要性”和“对自己改变能力的信心”进行了自我评估。这些评估是应用程序干预模型的一部分,根据参与者的反应提供个性化反馈;没有提供外部激励。采用聚类分析来确定基于MMM和SOCRATES分数的亚组。结果:共有3种不同的用户类型:“个体应对用户”(ICU)、“社交和应对用户”(SCU)和“寻求增强用户”(ESU)。根据苏格拉底的测量,ICU和SCU在应对动机上的得分高于ESU,同时也有更大的矛盾心理和更强的问题使用意识。他们在ASSIST上的得分也更高(表明使用大麻的风险更高),更重视改变行为,但对自己实施这些改变的能力的信心较低。相比之下,ESU主要出于娱乐原因使用大麻,尽管风险适中,但对问题使用的认识较低。结论:这项研究强调,虽然使用大麻的动机各不相同,而且每个人都有细微差别,但可以确定不同的亚群体,每个群体都有特定的挑战。这些发现与先前强调应对动机在行为改变中的重要性的研究相一致。定制应用程序内容以反映每个子群体的独特概况和需求可能会改善干预结果。例如,SCU和ICU可能受益于针对情绪调节和替代性应对机制的策略,而ESU可能对简短的动机反馈和减少伤害的策略有更好的反应。这种量身定制的方法可以提高数字工具在促进有意义和长期的行为改变方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Motives for Cannabis Use and Readiness to Change Among Users of the "Stop-Cannabis" Mobile App: Cluster Analysis.

Motives for Cannabis Use and Readiness to Change Among Users of the "Stop-Cannabis" Mobile App: Cluster Analysis.

Motives for Cannabis Use and Readiness to Change Among Users of the "Stop-Cannabis" Mobile App: Cluster Analysis.

Background: Cannabis use is widespread and driven by diverse motives, ranging from recreational purposes to coping with psychological distress. Understanding the underlying reasons for cannabis use, their distribution across different subgroups of people who use cannabis, and how they relate to possible behavior change is essential for developing effective prevention and intervention strategies such as smartphone apps designed to support change.

Objective: The primary objective of the study was to determine whether analyzing profiles on the "Stop-cannabis" app (Institute of Global Health, University of Geneva, Switzerland) could reveal subgroups based on motives for cannabis use and readiness to change. A secondary objective was to explore differences among these subgroups in terms of problematic use and other indicators of change readiness.

Methods: This study analyzed data from 2578 individuals using the "Stop-cannabis app", a mobile app developed in Switzerland to support those seeking to manage their cannabis use. Participants completed validated questionnaires assessing motives for use (Marijuana Motives Measure [MMM]), readiness to change (Stages of Change Readiness and Treatment Eagerness Scale [SOCRATES]), and risk of problematic use (Alcohol, Smoking, and Substance Involvement Screening Test [ASSIST]). They also self-rated their "readiness for action," the "importance of change," and their "confidence in their ability to change." These assessments were part of the app's intervention model, with personalized feedback delivered based on participants' responses; no external incentives were offered. Cluster analysis was conducted to identify subgroups based on MMM and SOCRATES scores.

Results: In total, 3 distinct profiles emerged: the "individually coping users" (ICU), the "social and coping users" (SCU), and the "enhancement-seeking users" (ESU). ICU and SCU scored higher on coping motives compared with ESU, along with greater ambivalence and stronger recognition of problematic use, as measured by SOCRATES. They also scored higher on the ASSIST (indicating greater risk of problematic cannabis use), placed more importance on making behavioral changes, yet reported lower confidence in their ability to enact those changes. By contrast, ESU primarily used cannabis for recreational reasons and had low recognition of problematic use, despite being at moderate risk.

Conclusions: This research highlights that while motives for cannabis use are varied and individually nuanced, distinct subgroups can be identified, each with specific challenges. The findings align with previous research emphasizing the importance of coping motives in behavior change. Tailoring app content to reflect the unique profiles and needs of each subgroup may improve intervention outcomes. For instance, SCU and ICU may benefit from strategies targeting emotion regulation and alternative coping mechanisms, whereas ESU may respond better to brief motivational feedback and harm reduction strategies. Such tailored approaches can enhance the effectiveness of digital tools in promoting meaningful and long-term behavior change.

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来源期刊
JMIR Formative Research
JMIR Formative Research Medicine-Medicine (miscellaneous)
CiteScore
2.70
自引率
9.10%
发文量
579
审稿时长
12 weeks
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