Optimizing an online motivational tobacco cessation program

优化在线激励戒烟计划

基本信息

批准号：
8206743
负责人：
JENNIFER B MCCLURE
金额：
$ 48.82万
依托单位：
KAISER FOUNDATION HEALTH PLAN OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-03-01 至 2013-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8206743
关键词：
Abstinence Address Adult American Area Automobile Driving Cause of Death Centers for Disease Control and Prevention (U.S.)Characteristics Communication Communication Research Computers Country Effectiveness Future Generic Drugs Health Health Planning Health Priorities Health behavior change Individual Individual Differences Internet Intervention Investigation Learning Life Mediating Modeling Motivation Outcome Participant Phase Population Randomized Recruitment Activity Reporting Research Risk Science Screening procedure Self Efficacy Series Smoke Smoker Smoking Specific qualifier value Testing The Sun Time To specify Tobacco Use Cessation Treatment outcome United States Dept. of Health and Human Services Withholding Treatment Work base design disability enhancing factor help-seeking behavior motivational enhancement therapy motivational intervention next generation outreach programs psychosocial research study smoking cessation smoking prevalence social cognitive theory theories therapy design treatment program uptake

项目摘要

DESCRIPTION (provided by applicant): Smoking is the leading cause of death and disability in the U.S. Despite this, 21% of U.S. adults continue to smoke on a regular basis and less than about 20% are ready to quit smoking or taking action to quit at any given time. In other words, about 80% or more of smokers are not sufficiently motivated and ready to quit smoking, even though they may want to quit someday. Interventions are critically needed which can reach these people, enhance their motivation for quitting, promote uptake of existing empirically-validated treatments, and ultimately enhance abstinence rates on a population level. Motivational interventions delivered via the Internet can be easily tailored to the needs of individual smokers. There is now a large body of research demonstrating that computer-tailored health behavior change interventions can be more effective than generic interventions, particularly for smoking cessation, but it is less clear what specific content and presentation factors will be most effective and for whom when tailoring an online motivational intervention. The current study will test the effectiveness of five potentially important tailoring factors (decisional framework, message framing, self-efficacy, navigation autonomy, and proactive outreach). Factor choice was largely informed by the principles of Motivational Interviewing, Social Cognitive Theory, Prospect Theory, and the Transtheoretical Model. In addition to examining whether each factor is important for treatment outcome, we will also examine for whom each factor is most important by exploring the influence of relevant individual characteristics which may mediate or moderate outcomes. This level of understanding is important for designing future tailored programs. Participants in this study will be recruited from a large, regional U.S. health plan. Using a fractional factorial design to screen for important main effects and 2-way interactions, participants will be randomized to receive one of 16 different experimental factor combinations and followed for one year to assess program impact on smokers' motivation for quitting, use of empirically-validated cessation treatment, and abstinence. The proposed research is a natural extension of our collaborative team's work in tailoring, developing motivational and action oriented programs for smoking cessation, health risk communications research, and creating online health behavior change programs. Information learned from this study will advance the science of tailoring health risk communications, as well as inform how to best design an online motivational intervention for smoking cessation. This is the first study we are aware of to address this important issue. PUBLIC HEALTH RELEVANCE: Reducing smoking prevalence in the U.S. will require motivational interventions which are both effective at promoting abstinence and can be easily disseminated on a population level. Computer-tailored programs delivered over the Internet hold great potential for this purpose, but research in this area must move beyond simply comparing tailored to non-tailored programs and begin to specify which content and presentation factors enhance tailoring effectiveness and for whom. The proposed study is the first we are aware of to examine this issue in the context of an online motivational intervention for smoking cessation. Information learned from this study will advance the science of tailoring health risk communications, as well as inform how to best design an online motivational intervention for smoking cessation.

描述（由申请人提供）：吸烟是美国死亡和残疾的主要原因。尽管如此，21% 的美国成年人仍然定期吸烟，只有不到 20% 的人准备戒烟或采取行动戒烟在任何给定时间。换句话说，大约 80% 或更多的吸烟者没有足够的动力和准备戒烟，即使他们有一天可能想戒烟。迫切需要采取干预措施来接触这些人，增强他们的戒烟动机，促进对现有经经验验证的治疗方法的采用，并最终提高人口水平的戒烟率。通过互联网提供的激励干预措施可以轻松地根据个体吸烟者的需求进行定制。现在有大量研究表明，计算机定制的健康行为改变干预措施比一般干预措施更有效，特别是在戒烟方面，但尚不清楚哪些具体内容和呈现因素最有效，以及定制时对谁最有效在线动机干预。当前的研究将测试五个潜在重要的定制因素（决策框架、信息框架、自我效能、导航自主性和主动外展）的有效性。因素选择很大程度上取决于动机访谈、社会认知理论、前景理论和跨理论模型的原则。除了检查每个因素是否对治疗结果重要外，我们还将通过探索可能介导或调节结果的相关个体特征的影响来检查每个因素对谁最重要。这种程度的理解对于设计未来的定制项目非常重要。这项研究的参与者将从美国大型地区健康计划中招募。使用部分因子设计来筛选重要的主效应和双向交互作用，参与者将被随机接受 16 种不同实验因素组合中的一种，并跟踪一年，以评估项目对吸烟者戒烟动机的影响，使用经验-经验证的戒烟治疗和禁欲。拟议的研究是我们合作团队在定制、开发激励性和行动导向的戒烟计划、健康风险沟通研究以及创建在线健康行为改变计划方面工作的自然延伸。从这项研究中获得的信息将推进定制健康风险沟通的科学，并告知如何最好地设计在线戒烟动机干预措施。这是我们所知的第一项解决这一重要问题的研究。公共卫生相关性：降低美国的吸烟率需要激励干预措施，这些干预措施既能有效促进戒烟，又能在人群层面上轻松传播。通过互联网提供的计算机定制程序在这方面具有巨大的潜力，但该领域的研究必须超越简单地比较定制程序与非定制程序，并开始指定哪些内容和呈现因素可以增强定制效果以及为谁增强定制效果。这项拟议的研究是我们所知的第一个在在线戒烟动机干预背景下研究这个问题的研究。从这项研究中获得的信息将推进定制健康风险沟通的科学，并告知如何最好地设计在线戒烟动机干预措施。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Blockade of SARS-CoV-2 spike protein-mediated cell-cell fusion using COVID-19 convalescent plasma.

DOI：
10.1038/s41598-021-84840-3
发表时间：
2021-03-10
期刊：
Scientific reports
影响因子：
4.6
作者：
Wang L;Zhao J;Nguyen LNT;Adkins JL;Schank M;Khanal S;Nguyen LN;Dang X;Cao D;Thakuri BKC;Lu Z;Zhang J;Zhang Y;Wu XY;El Gazzar M;Ning S;Moorman JP;Yao ZQ
通讯作者：
Yao ZQ

Using multiple imputations to accommodate time-outs in online interventions.

使用多重插补来适应在线干预中的超时。