Suppr超能文献

基于特征的戒烟移动应用程序定性评估

A feature-based qualitative assessment of smoking cessation mobile applications.

作者信息

Tesfaye Lydia, Wakeman Michael, Baskin Gunnar, Gruse Greg, Gregory Tim, Leahy Erin, Kendrick Brandon, El-Toukhy Sherine

机构信息

Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Rockville, Maryland, United States of America.

ICF, Reston, Virginia, United States of America.

出版信息

PLOS Digit Health. 2024 Nov 21;3(11):e0000658. doi: 10.1371/journal.pdig.0000658. eCollection 2024 Nov.

Abstract

Understanding users' acceptance of smoking cessation interventions features is a precursor to mobile cessation apps' uptake and use. We gauged perceptions of three features of smoking cessation mobile interventions (self-monitoring, tailored feedback and support, educational content) and their design in two smoking cessation apps, Quit Journey and QuitGuide, among young adults with low socioeconomic status (SES) who smoke. A convenience sample of 38 current cigarette smokers 18-29-years-old who wanted to quit and were non-college-educated nor currently enrolled in a four-year college participated in 12 semi-structured virtual focus group discussions on GoTo Meeting. Discussions were audio recorded, transcribed verbatim, and coded using the second Unified Theory of Acceptance and Use of Technology (UTAUT2) constructs (i.e., performance and effort expectancies, hedonic motivation, facilitating conditions, social influence), sentiment (i.e., positive, neutral, negative), and app features following a deductive thematic analysis approach. Participants (52.63% female, 42.10% non-Hispanic White) expressed positive sentiment toward self-monitoring (73.02%), tailored feedback and support (70.53%) and educational content (64.58%). Across both apps, performance expectancy was the dominant theme discussed in relation to feature acceptance (47.43%). Features' perceived usefulness centered on the reliability of apps in tracking smoking triggers over time, accommodating within- and between-person differences, and availability of on-demand cessation-related information. Skepticism about features' usefulness included the possibility of unintended consequences of self-monitoring, burden associated with user-input and effectiveness of tailored support given the unpredictable timing of cravings, and repetitiveness of cessation information. All features were perceived as easy to use. Other technology acceptance themes (e.g., social influence) were minimally discussed. Acceptance of features common to smoking cessation mobile applications among low socioeconomic young adult smokers was owed primarily to their perceived usefulness and ease of use. To increase user acceptance, developers should maximize integration within app features and across other apps and mobile devices.

摘要

了解用户对戒烟干预功能的接受程度是移动戒烟应用程序被采用和使用的前提。我们评估了低收入社会经济地位(SES)的吸烟青年成年人对两款戒烟应用程序Quit Journey和QuitGuide中戒烟移动干预的三个功能(自我监测、个性化反馈与支持、教育内容)及其设计的看法。一个由38名年龄在18至29岁、想要戒烟、未受过大学教育且未就读于四年制大学的当前吸烟者组成的便利样本,参加了在GoTo Meeting上进行的12次半结构化虚拟焦点小组讨论。讨论进行了录音,逐字转录,并采用第二次技术接受与使用统一理论(UTAUT2)结构(即绩效期望和努力期望、享乐动机、促进条件、社会影响)、情感(即积极、中性、消极)以及应用程序功能,按照演绎主题分析方法进行编码。参与者(52.63%为女性,42.10%为非西班牙裔白人)对自我监测(73.02%)、个性化反馈与支持(70.53%)和教育内容(64.58%)表达了积极的情感。在这两款应用程序中,绩效期望是与功能接受度相关讨论的主导主题(47.43%)。功能的感知有用性集中在应用程序随时间跟踪吸烟触发因素的可靠性、适应个体内部和个体之间的差异以及随时提供戒烟相关信息的可用性上。对功能有用性的怀疑包括自我监测可能产生意外后果、与用户输入相关的负担以及鉴于渴望时机不可预测而提供的个性化支持的有效性,以及戒烟信息的重复性。所有功能都被认为易于使用。其他技术接受主题(如社会影响)讨论较少。低收入社会经济地位的年轻成年吸烟者对戒烟移动应用程序常见功能的接受主要归因于其感知的有用性和易用性。为了提高用户接受度,开发者应最大限度地在应用程序功能内部以及与其他应用程序和移动设备之间进行整合。

相似文献

1
A feature-based qualitative assessment of smoking cessation mobile applications.基于特征的戒烟移动应用程序定性评估
PLOS Digit Health. 2024 Nov 21;3(11):e0000658. doi: 10.1371/journal.pdig.0000658. eCollection 2024 Nov.

本文引用的文献

4
Smokers' user experience of smoking cessation apps: A systematic review.烟民使用戒烟应用程序的体验:系统评价。
Int J Med Inform. 2023 Jul;175:105069. doi: 10.1016/j.ijmedinf.2023.105069. Epub 2023 Apr 15.
6
Social desirability bias in qualitative health research.定性健康研究中的社会期望偏差。
Rev Saude Publica. 2022 Dec 9;56:101. doi: 10.11606/s1518-8787.2022056004164. eCollection 2022.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验