正在下雨的机器人:如何更容易获得互联网调查创造了完美的风暴。

IF 1.3 Q4 HEALTH CARE SCIENCES & SERVICES
Isabelle Caven, Zhenxiao Yang, Karen Okrainec
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引用次数: 0

摘要

在线调查是一种越来越普遍的向公众收集数据的方式,通常使用社交媒体和财务激励(如礼品卡)来提高参与率。匿名性、易于回应以及接触不同人口统计数据的潜力也促成了在线调查的流行。卫生服务研究受益于基于在线调查的数据收集提供的更多可访问性;然而,欺诈性回复令人担忧。下面的文章描述了我们的团队在加拿大医疗保健提供者的全国性调查中被欺诈性回复泛滥的经验,以及确保调查数据有效性的方法。我们为研究团队就如何最好地设计调查、与他们的机构合作在调查平台内实施保障措施以及筛选完成的回复提供建议。我们还描述了欺诈性的开放文本响应,我们认为这些响应是在人工智能的帮助下产生的,并为其他研究人员敲响了警钟,让他们意识到这种对数据完整性的潜在威胁。通过分享的经验教训,研究人员和研究机构可以更好地预防和筛选欺诈性回应,继续成功地让公众参与在线研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
It's raining bots: how easier access to internet surveys has created the perfect storm.

Online surveys are an increasingly common way to collect data from the public, with social media and financial incentives (e.g. gift cards) commonly used to increase participation rates. Anonymity, ease of response, and the potential to reach diverse demographics have also contributed to the popularity of online surveys. Health services research benefits from the increased accessibility that online survey-based data collection provides; however, fraudulent responses are of concern. The following article describes our team's experience with a national survey of Canadian healthcare providers being overrun with fraudulent responses and approach to ensure the validity of our survey data. We provide recommendations for research teams on how best to design their surveys, work with their institutions to implement safeguards within survey platforms, and screen completed responses. We also describe fraudulent open-text responses that we believe to have been produced with the help of artificial intelligence and are sounding the alarm for other researchers to be aware of this potential threat to data integrity. Informed by the learnings shared, researchers and research institutions can be better equipped to prevent and screen fraudulent responses to continue successfully engage the public in online research.

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来源期刊
BMJ Open Quality
BMJ Open Quality Nursing-Leadership and Management
CiteScore
2.20
自引率
0.00%
发文量
226
审稿时长
20 weeks
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