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质疑社交媒体招募方式在针对使用阿片类药物的隐匿人群调查中的持续有效性。

Challenging the Continued Usefulness of Social Media Recruitment for Surveys of Hidden Populations of People Who Use Opioids.

作者信息

Nesoff Elizabeth D, Palamar Joseph J, Li Qingyue, Li Wenqian, Martins Silvia S

机构信息

Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.

Department of Population Health, NYU Langone Health, New York, NY, United States.

出版信息

J Med Internet Res. 2025 Apr 30;27:e63687. doi: 10.2196/63687.

Abstract

Historically, recruiting research participants through social media facilitated access to people who use opioids, capturing a range of drug use behaviors. The current rapidly changing online landscape, however, casts doubt on social media's continued usefulness for study recruitment. In this viewpoint paper, we assessed social media recruitment for people who use opioids and described challenges and potential solutions for effective recruitment. As part of a study on barriers to harm reduction health services, we recruited people who use opioids in New York City to complete a REDCap (Research Electronic Data Capture; Vanderbilt University) internet-based survey using Meta (Facebook and Instagram), X (formerly known as Twitter), Reddit, and Discord. Eligible participants must have reported using opioids (heroin, prescription opioids, or fentanyl) for nonprescription purposes in the past 90 days and live or work in New York City. Data collection took place from August 2023 to November 2023. Including study purpose, compensation, and inclusion criteria caused Meta's social media platforms and X to flag our ads as "discriminatory" and "spreading false information." Listing incentives increased bot traffic across all platforms despite bot prevention activities (eg, reCAPTCHA and counting items in an image). We instituted a rigorous post hoc data cleaning protocol (eg, investigating duplicate IP addresses, participants reporting use of a fictitious drug, invalid ZIP codes, and improbable drug use behaviors) to identify bot submissions and repeat participants. Participants received a US $20 gift card if still deemed eligible after post hoc data inspection. There were 2560 submissions, 93.2% (n=2387) of which were determined to be from bots or malicious responders. Of these, 23.9% (n=571) showed evidence of a duplicate IP or email address, 45.9% (n=1095) reported consuming a fictitious drug, 15.8% (n=378) provided an invalid ZIP code, and 9.4% (n=225) reported improbable drug use behaviors. The majority of responses deemed legitimate (n=173) were collected from Meta (n=79, 45.7%) and Reddit (n=48, 27.8%). X's ads were the most expensive (US $1.96/click) and yielded the fewest participants (3 completed surveys). Social media recruitment of hidden populations is challenging but not impossible. Rigorous data collection protocols and post hoc data inspection are necessary to ensure the validity of findings. These methods may counter previous best practices for researching stigmatized behaviors.

摘要

从历史上看,通过社交媒体招募研究参与者有助于接触使用阿片类药物的人群,从而获取一系列药物使用行为。然而,当前迅速变化的网络环境让人怀疑社交媒体在研究招募方面是否仍有用处。在这篇观点论文中,我们评估了针对使用阿片类药物人群的社交媒体招募情况,并描述了有效招募的挑战及潜在解决方案。作为一项关于减少伤害健康服务障碍研究的一部分,我们在纽约市招募使用阿片类药物的人群,让他们使用Meta(脸书和照片墙)、X(前身为推特)、红迪网和Discord完成一项基于网络的REDCap(研究电子数据采集;范德堡大学)调查。符合条件的参与者必须报告在过去90天内有非处方使用阿片类药物(海洛因、处方阿片类药物或芬太尼)的情况,并且居住或工作在纽约市。数据收集于2023年8月至2023年11月进行。由于包含研究目的、补偿和纳入标准,Meta的社交媒体平台和X将我们的广告标记为“歧视性”和“传播虚假信息”。尽管采取了防止机器人的措施(如使用验证码和计算图片中的项目),列出激励措施仍增加了所有平台上的机器人流量。我们制定了严格的事后数据清理协议(如调查重复的IP地址、报告使用虚构药物的参与者、无效的邮政编码和不太可能的药物使用行为)以识别机器人提交的内容和重复参与者。如果在事后数据检查后仍被认为符合条件,参与者将获得一张20美元的礼品卡。共收到2560份提交内容,其中93.2%(n = 2387)被确定来自机器人或恶意回复者。在这些当中,23.9%(n = 571)显示有重复的IP或电子邮件地址的证据,45.9%(n = 1095)报告使用虚构药物,15.8%(n = 378)提供了无效的邮政编码,9.4%(n = 225)报告了不太可能的药物使用行为。大多数被认为合法的回复(n = 173)是从Meta(n = 79,45.7%)和红迪网(n = 48,27.8%)收集到的。X的广告是最昂贵的(每次点击1.96美元),并且产生的参与者最少(3份完成的调查问卷)。对隐藏人群进行社交媒体招募具有挑战性,但并非不可能。严格的数据收集协议和事后数据检查对于确保研究结果的有效性是必要的。这些方法可能与之前研究受污名化行为的最佳实践相悖。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4adb/12079069/c3dcf20ba872/jmir_v27i1e63687_fig1.jpg

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