Online surveys are a popular tool in sex research and it is vital to understand participation bias in these surveys to improve inferences. However, research on this topic is limited and out of date given the increase in online survey methodology and changes in sexual attitudes. This study examined whether demographics and sexual abuse and assault history predict opting into online survey questions about sex. The sample was recruited for a longitudinal mental health study using a probability-based sampling panel developed to represent the US household population. Participants were masked to the inclusion of sexual content and given a choice to opt into sex questions. Analyses were run on raw and weighted responses to adjust for sampling bias. Of the total sample (n = 476, 62.6% female), 69% opted into sex questions. Raw analysis showed that participants were more likely to be younger, have higher education and income, and have a history of sexual abuse or assault. No racial, gender, relationship status, or regional differences were found. After weighting, effect sizes were reduced for most predictor variables, and only a history of sexual abuse or assault still significantly predicted participation. Results suggest that key demographic features do not have a strong association with participation in sex survey questions. Reasons for participation bias stemming from sexual abuse or assault history should be examined further. This study demonstrates how researchers should continue to monitor participation bias in sex survey research as online methodologies and sexual attitudes evolve over time.

在线调查是性研究中的一种流行工具，了解这些调查中的参与偏差对于改善推论至关重要。然而，鉴于在线调查方法的增加和性态度的变化，关于这一主题的研究有限且过时。这项研究调查了人口统计数据、性虐待和性侵犯历史是否预示着人们会选择有关性的在线调查问题。使用代表美国家庭人口的基于概率的抽样小组招募样本进行纵向心理健康研究。参与者被蒙蔽，不知道是否包含性内容，并可以选择回答性问题。对原始响应和加权响应进行分析，以调整抽样偏差。总样本中（n = 476，62.6% 为女性），69% 选择了性问题。原始分析显示，参与者更有可能更年轻、受过高等教育、收入更高、有性虐待或性侵犯史。没有发现种族、性别、关系状况或地区差异。加权后，大多数预测变量的效应大小都减少了，只有性虐待或性侵犯的历史仍然可以显着预测参与。结果表明，关键人口特征与性别调查问题的参与程度没有很强的关联。应进一步审查因性虐待或性侵犯历史而产生的参与偏见的原因。这项研究表明，随着在线方法和性态度随着时间的推移而演变，研究人员应如何继续监测性调查研究中的参与偏差。