A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study.

A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study.
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DOI:
10.2196/mhealth.5787
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发表时间:
2016-09-16
影响因子:
5
通讯作者:
Sutton S
Sutton S
中科院分区:
医学2区
文献类型:
--
作者:
Naughton F;Hopewell S;Lathia N;Schalbroeck R;Brown C;Mascolo C;McEwen A;Sutton S

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在戒烟尝试中,吸烟者的直接环境引发的渴望是吸烟失败和复发的主要原因。为了帮助吸烟者在尝试戒烟时解决这些暗示诱导的渴望,我们开发了一款情境感知戒烟应用程序Q Sense,该应用程序使用结合位置传感和地理围栏的吸烟事件报告系统来定制支持内容并真实的触发支持交付。我们试图(1)评估吸烟者是否遵守真实的吸烟报告并确定不遵守的原因,(2)评估该应用程序在识别用户特定的吸烟高风险位置方面的准确性,(3)探索地理围栏触发支持的可行性和用户观点,以及(4)确定任何技术问题或隐私问题。使用了解释性顺序混合方法设计,其中应用程序收集的数据通知半结构化访谈。参与者是拥有Android移动的手机并愿意在一个月内设定戒烟日期的吸烟者(N=15)。应用程序数据包括带有上下文信息和地理位置的吸烟报告、吸烟信念和行为的一天结束(EoD)调查、支持消息评级和应用程序交互数据。访谈进行了主题分析(N=13)。定量和定性数据分别进行了分析,并按顺序列出了结果。在15名参与者中,3名(20%)过早停止使用该应用程序。戒烟前,收到的吸烟报告的平均数量为37.8(SD 21.2)/参与者,或2.0(SD 2.2)/参与者/天。EoD调查显示,参与者至少有56.2%的时间少报吸烟。在97.0%的吸烟报告中收集了地理位置,平均准确度为31.6(SD 16.8)米。9名合格参与者中共有5名(56%)获得了地理围栏触发的支持。交互数据表明,50.0%(137/274)的地理围栏触发的消息通知在生成后30分钟内被点击,导致发送支持消息,78.2%(158/202)的已发送消息由参与者评级。定性研究结果确定了多种原因不遵守报告吸烟,最显着的是由于环境的限制和遗忘。参与者验证了应用程序对他们吸烟位置的识别,对地理围栏触发支持的价值基本持肯定态度,并且对应用程序收集的数据没有隐私问题。用户发起的自我报告对于培训戒烟应用程序了解个人吸烟行为是可行的,尽管可能会漏报。地理围栏是一种可靠和准确的识别吸烟地点的方法,参与者对地理围栏触发的支持持积极态度。
A major cause of lapse and relapse to smoking during a quit attempt is craving triggered by cues from a smoker's immediate environment. To help smokers address these cue-induced cravings when attempting to quit, we have developed a context-aware smoking cessation app, Q Sense, which uses a smoking episode-reporting system combined with location sensing and geofencing to tailor support content and trigger support delivery in real time. We sought to (1) assess smokers’ compliance with reporting their smoking in real time and identify reasons for noncompliance, (2) assess the app's accuracy in identifying user-specific high-risk locations for smoking, (3) explore the feasibility and user perspective of geofence-triggered support, and (4) identify any technological issues or privacy concerns. An explanatory sequential mixed-methods design was used, where data collected by the app informed semistructured interviews. Participants were smokers who owned an Android mobile phone and were willing to set a quit date within one month (N=15). App data included smoking reports with context information and geolocation, end-of-day (EoD) surveys of smoking beliefs and behavior, support message ratings, and app interaction data. Interviews were undertaken and analyzed thematically (N=13). Quantitative and qualitative data were analyzed separately and findings presented sequentially. Out of 15 participants, 3 (20%) discontinued use of the app prematurely. Pre-quit date, the mean number of smoking reports received was 37.8 (SD 21.2) per participant, or 2.0 (SD 2.2) per day per participant. EoD surveys indicated that participants underreported smoking on at least 56.2% of days. Geolocation was collected in 97.0% of smoking reports with a mean accuracy of 31.6 (SD 16.8) meters. A total of 5 out of 9 (56%) eligible participants received geofence-triggered support. Interaction data indicated that 50.0% (137/274) of geofence-triggered message notifications were tapped within 30 minutes of being generated, resulting in delivery of a support message, and 78.2% (158/202) of delivered messages were rated by participants. Qualitative findings identified multiple reasons for noncompliance in reporting smoking, most notably due to environmental constraints and forgetting. Participants verified the app’s identification of their smoking locations, were largely positive about the value of geofence-triggered support, and had no privacy concerns about the data collected by the app. User-initiated self-report is feasible for training a cessation app about an individual’s smoking behavior, although underreporting is likely. Geofencing was a reliable and accurate method of identifying smoking locations, and geofence-triggered support was regarded positively by participants.
DOI: 10.1007/s00213-013-3429-6
发表时间: 2014-07-01
期刊: PSYCHOPHARMACOLOGY
影响因子: 3.4
作者:
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通讯作者: Shiffman, Saul
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发表时间: 2012-12-15
期刊: LANCET
影响因子: 168.9
作者:
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DOI: 10.1016/s0140-6736(11)60701-0
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期刊: LANCET
影响因子: 168.9
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发表时间: 1994-02-23
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通讯作者: BAKER, TB
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发表时间: 2011-08-12
影响因子: 7.4
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通讯作者: Mohr DC