Background: Health knowledge and literacy are among the main determinants of health. Assessment of these issues via Web-based surveys is growing continuously. Research has suggested that approximately one-fifth of respondents submit cribbed answers, or cheat, on factual knowledge items, which may lead to measurement error. However, little is known about methods of discouraging cheating in Web-based surveys on health knowledge. Objective: This study aimed at exploring the usefulness of imposing a survey time limit to prevent help-seeking and cheating. Methods: On the basis of sample size estimation, 94 undergraduate students were randomly assigned in a 1:1 ratio to complete a Web-based survey on nutrition knowledge, with or without a time limit of 15 minutes (30 seconds per item); the topic of nutrition was chosen because of its particular relevance to public health. The questionnaire consisted of two parts. The first was the validated consumer-oriented nutrition knowledge scale (CoNKS) consisting of 20 true/false items; the second was an ad hoc questionnaire (AHQ) containing 10 questions that would be very difficult for people without health care qualifications to answer correctly. It therefore aimed at measuring cribbing and not nutrition knowledge. AHQ items were somewhat encyclopedic and amenable to Web searching, while CoNKS items had more complex wording, so that simple copying/pasting of a question in a search string would not produce an immediate correct answer. Results: A total of 72 of the 94 subjects started the survey. Dropout rates were similar in both groups (11%, 4/35 and 14%, 5/37 in the untimed and timed groups, respectively). Most participants completed the survey from portable devices, such as mobile phones and tablets. To complete the survey, participants in the untimed group took a median 2.3 minutes longer than those in the timed group; the effect size was small (Cohen’s r=.29). Subjects in the untimed group scored significantly higher on CoNKS (mean difference of 1.2 points, P=.008) and the effect size was medium (Cohen’s d=0.67). By contrast, no significant between-group difference in AHQ scores was documented. Unexpectedly high AHQ scores were recorded in 23% (7/31) and 19% (6/32) untimed and timed respondents, respectively, very probably owing to “e-cheating”. Conclusions: Cribbing answers to health knowledge items in researcher-uncontrolled conditions is likely to lead to overestimation of people’s knowledge; this should be considered during the design and implementation of Web-based surveys. Setting a time limit alone may not completely prevent cheating, as some cheats may be very fast in Web searching. More complex and contextualized wording of items and checking for the “findability” properties of items before implementing a Web-based health knowledge survey may discourage help-seeking, thus reducing measurement error. Studies with larger sample sizes and diverse populations are needed to confirm our results.