Brief Informational Intervention for COVID-19 Misinformation Prophylaxis
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 1,017
- 试验地点
- 1
- 主要终点
- Preventive behavioral intentions
研究概览
简要总结
As the coronavirus disease 2019 (COVID-19) pandemic has continued to affect life in the United States, the important role of non-pharmaceutical preventive behaviors (such as wearing a face mask) in reducing harm has become clear. In parallel to the pandemic, researchers have observed an "infodemic" of misinformed or inconsistent narratives about COVID-19. There is growing evidence that misinformed COVID-19 narratives are associated with a wide variety of undesirable behavior (e.g., burning down cell towers). Further, individuals' adherence to recommended COVID-19 preventive guidelines has been inconsistent, and such mandates have engendered opposition and controversy. Recent research suggests the possibility that trust in science and scientists may be an important thread to weave throughout these seemingly disparate components of the modern public health landscape. Thus, this paper describes the protocol for a randomized trial of a brief, digital intervention to increase trust in science.
The objective of this trial is to examine if exposure to a curated infographic can increase trust in science, reduce believability of misinformed narratives, and increase likelihood to engage in preventive behaviors.
详细描述
The investigators propose a single-stage, randomized, superiority trial with 2 parallel groups allocated with a 1:1 ratio. The comparator in this study will be a control ("placebo") infographic that is completely unrelated to science (e.g., about cats), but that is developed using the same communication and graphical style.
Subjects will be recruited using the Prolific data collection platform, which is one of two primary online crowdsourced research platforms (the other is Amazon's Mechanical Turk, or mTurk).
To be included, participants must be identified by Prolific as part of a nationally-representative sample. Participants will also be required to be age 18 or older, and to reside in the United States. Individuals who decline to digitally sign the informed consent document will be excluded and replaced. Per recent best practice recommendations for crowdsourced digital research, attention checks and screens for "bots" and international users with virtual private networks to mimic US IP addresses will be embedded within the instruments, and failure of more than one attention check, or any bot/location check will result in subject exclusion and replacement. Replacements will be drawn in such a way as to preserve the representativeness of the sample.
Missing data will be addressed using either full information maximum likelihood or Markov Chain Monte Carlo multiple imputation strategies. When there is a violation of missing at random (which is unlikely) in preliminary analyses, the investigators will incorporate strategies representing the missingness. The researchers will further explore data quality in terms of outliers, measurement error, non-normality, and variance heterogeneity. Robust methods of analysis (e.g., Huber-White robust standard errors) will be used, as appropriate. For all multi-item measures, reliability will be evaluated prior to computation of the variable.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Prevention
- 盲法
- Double (Participant, Outcomes Assessor)
盲法说明
Although this is, in practice, a double-blind study since participants will be unaware that they are randomized and all study mechanics will be processed by computer, analysts will not be blinded to the meaning of the assignment variable. However, two independent consultant analysts have been retained to verify all results and subsequent interpretation.
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •To be included, participants must be identified by Prolific as part of a nationally-representative sample. Participants will also be required to be age 18 or older, and to reside in the United States.
排除标准
- •Individuals who decline to digitally sign the informed consent document will be excluded and replaced. Per recent best practice recommendations for crowdsourced digital research, attention checks and screens for "bots" and international users with virtual private networks to mimic US internet protocol addresses will be embedded within the instruments, and failure of more than one attention check, or any bot/location check will result in subject exclusion and replacement.
研究组 & 干预措施
Brief Intervention arm
The primary intervention in this study will be an infographic that is designed to build trust in the scientific process (as described in the Intervention section). This arm will introduce the intervention and then instruct the participant to review it carefully (including a mandated pause on the infographic screen) before continuing to the remaining data collection.
干预措施: Brief informational infographic (Behavioral)
Placebo Control arm
The comparator in this study will be a control ("placebo") infographic that is completely unrelated to science (As described in the Placebo Control section). This arm will introduce the control infographic and then instruct the participant to review it carefully (including a mandated pause on the infographic screen) before continuing to the remaining data collection.
干预措施: Placebo control (non-behavioral infographic) (Behavioral)
结局指标
主要结局
Preventive behavioral intentions
时间窗: Immediately post-intervention
A series of six questions based on the US Centers for Disease Control and Prevention's recommended COVID-19 preventive behaviors. \[4\] Questions will be written according to Azjen's guide to intention questionnaires \[5\].
Change in trust in science
时间窗: Pre-intervention and immediately post-intervention
21-item scale developed by Nadelson et al \[1\] called the Trust in Science Inventory. It is scored from 1 to 5, where 1 indicates low trust and 5 indicates high trust.
Believability profiles
时间窗: Immediately post-intervention
Will be computed using latent profile analysis of believability measures. These measures were developed and first used in our recent study of COVID-19 narratives \[2\]. Response options for these measures used well-established semantic differential responses for believability of different statements (e.g., as in Herzberg et al.) \[3\] ranging from \[1: Extremely unbelievable\] to \[7: Extremely believable\]. Exact measures used to generate profiles for this study will be available in the published protocol paper (to be submitted).
次要结局
未报告次要终点
研究者
Jon Agley
Associate Professor
Indiana University