Introducing Novel Methods to Identify Fraudulent Responses (Sampling With Sisyphus): Web-Based LGBTQ2S+ Mixed-Methods Study.

IF 6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Internet Research Pub Date : 2025-03-17 DOI:10.2196/63252
Kinnon Ross MacKinnon, Naail Khan, Katherine M Newman, Wren Ariel Gould, Gin Marshall, Travis Salway, Annie Pullen Sansfaçon, Hannah Kia, June Sh Lam
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Abstract

Background: The myth of Sisyphus teaches about resilience in the face of life challenges. Detransition after an initial gender transition is an emerging experience that requires sensitive and community-driven research. However, there are significant complexities and costs that researchers must confront to collect reliable data to better understand this phenomenon, including the lack of a uniform definition and challenges with recruitment.

Objective: This paper presents the sampling and recruitment methods of a new study on detransition-related phenomena among lesbian, gay, bisexual, transgender, queer, and 2-spirit (LGBTQ2S+) populations. It introduces a novel protocol for identifying and removing bot, scam, and ineligible responses from survey datasets and presents preliminary descriptive sociodemographic results of the sample. This analysis does not present gender-affirming health care outcomes.

Methods: To attract a large and heterogeneous sample, 3 different study flyers were created in English, French, and Spanish. Between December 1, 2023, and May 1, 2024, these flyers were distributed to >615 sexual and gender minority organizations and gender care providers in the United States and Canada, and paid advertisements totaling >CAD $7400 (US $5551) were promoted on 5 different social media platforms. Although many social media promotions were rejected or removed, the advertisements reached >7.7 million accounts. Study website visitors were directed from 35 different traffic sources, with the top 5 being Facebook (3,577,520/7,777,218, 46%), direct link (2,255,393/7,777,218, 29%), Reddit (1,011,038/7,777,218, 13%), Instagram (466,633/7,777,218, 6%), and X (formerly known as Twitter; 233,317/7,777,218, 3%). A systematic protocol was developed to identify scam, nonsense, and ineligible responses and to conduct web-based Zoom video platform screening with select participants.

Results: Of the 1377 completed survey responses, 957 (69.5%) were deemed eligible and included in the analytic dataset after applying the exclusion protocol and conducting 113 virtual screenings. The mean age of the sample was 25.87 (SD 7.77; median 24, IQR 21-29 years). A majority of the participants were White (Canadian, American, or of European descent; 748/950, 78.7%), living in the United States (704/957, 73.6%), and assigned female at birth (754/953, 79.1%). Many participants reported having a sexual minority identity, with more than half the sample (543/955, 56.8%) indicating plurisexual orientations, such as bisexual or pansexual identities. A minority of participants (108/955, 11.3%) identified as straight or heterosexual. When asked about their gender-diverse identities after stopping or reversing gender transition, 33.2% (318/957) reported being nonbinary, 43.2% (413/957) transgender, and 40.5% (388/957) identified as detransitioned.

Conclusions: Despite challenges encountered during the study promotion and data collection phases, a heterogeneous sample of >950 eligible participants was obtained, presenting opportunities for future analyses to better understand these LGBTQ2S+ experiences. This study is among the first to introduce an innovative strategy to sample a hard-to-reach and equity-deserving group, and to present an approach to remove fraudulent responses.

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引入新方法识别欺诈反应(西西弗斯抽样):基于网络的LGBTQ2S+混合方法研究。
背景:西西弗斯的神话告诉我们在面对生活挑战时要有适应力。最初的性别转换后的去变性是一种新兴的经验,需要敏感和社区驱动的研究。然而,为了更好地理解这一现象,研究人员必须面对收集可靠数据的巨大复杂性和成本,包括缺乏统一的定义和招聘方面的挑战。目的:介绍一项针对女同性恋、男同性恋、双性恋、跨性别、酷儿和双性恋(LGBTQ2S+)人群中变性相关现象的新研究的抽样和招募方法。它引入了一种新的协议,用于从调查数据集中识别和删除机器人、骗局和不合格的回答,并提出了样本的初步描述性社会人口统计结果。这一分析没有提出性别肯定的卫生保健结果。方法:为了吸引大量的异质样本,用英语、法语和西班牙语制作了3种不同的研究传单。在2023年12月1日至2024年5月1日期间,这些传单分发给了美国和加拿大的615个性和性别少数群体组织和性别护理提供者,并在5个不同的社交媒体平台上推广了总计7400亿加元(5551美元)的付费广告。尽管许多社交媒体宣传被拒绝或删除,但这些广告仍达到了770万账户。研究网站的访问者来自35个不同的流量来源,前5名是Facebook(3,577,520/7,777,218, 46%),直接链接(2,255,393/7,777,218,29%),Reddit (1,011,038/7,777,218, 13%), Instagram(466,633/7,777,218, 6%)和X(以前称为Twitter;233317/7777218, 3%)。我们制定了一个系统的协议来识别骗局、废话和不合格的回复,并对选定的参与者进行基于网络的Zoom视频平台筛选。结果:在完成的1377份调查问卷中,采用排除方案并进行113次虚拟筛选后,957份(69.5%)被认为符合条件并纳入分析数据集。样本的平均年龄为25.87岁(SD 7.77;中位24岁,IQR 21-29岁)。大多数参与者是白人(加拿大人、美国人或欧洲血统;748/950, 78.7%),居住在美国(704/957,73.6%),出生时被指定为女性(754/953,79.1%)。许多参与者报告自己的性少数身份,超过一半的样本(543/955,56.8%)表明多元性取向,如双性恋或泛性恋身份。少数参与者(108/955,11.3%)认为自己是异性恋或异性恋。当被问及停止或逆转性别转换后的性别多样性认同时,33.2%(318/957)报告为非二元性,43.2%(413/957)报告为跨性别,40.5%(388/957)报告为变性。结论:尽管在研究推广和数据收集阶段遇到了挑战,但我们获得了一个由bbb950名符合条件的参与者组成的异质样本,为未来的分析提供了机会,以更好地了解这些LGBTQ2S+的经历。这项研究首次引入了一种创新策略,对一个难以接触到的、理应获得公平待遇的群体进行抽样,并提出了一种消除欺诈性回复的方法。
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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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