CHERRIES Checklist: Reporting E-Surveys

CHERRIES — the Checklist for Reporting Results of Internet E-Surveys — is a reporting standard for web-based survey research, published by Gunther Eysenbach in the Journal of Medical Internet Research in 2004 (J Med Internet Res 2004;6(3):e34). It was built on the same logic as the CONSORT statement for randomized trials and the QUORUM statement (the predecessor to PRISMA) for systematic reviews: give authors a fixed set of items to report, so a reader can judge sample selection and methodology from the paper itself instead of having to take the response rate on faith. CHERRIES is now listed as a reporting guideline by the EQUATOR Network, the body that maintains CONSORT, PRISMA, and STROBE, and it is routinely required or recommended by journal instructions for authors covering online survey studies.

It has no live page on this site yet despite steady, if modest, direct search demand — researchers preparing a methods section, or reviewers checking one, search for it by name. This guide covers all eight CHERRIES categories, then goes deeper on the one section that produces the most reporting errors in practice: the three response-rate definitions, which a documented erratum shows even survey-methods specialists get backwards.

What CHERRIES Covers, Category by Category

The checklist is organized into eight item categories, covering the full lifecycle of an internet survey from design through analysis:

Design. The survey design itself, the target population, and the sampling frame — including whether the sample is a convenience sample rather than a probability sample.
IRB approval and informed consent. Whether ethics review was obtained, how consent was presented, and how data protection/storage was described to participants.
Development and pre-testing. How the questionnaire was built and tested before fielding — expert review, pilot testing, usability testing.
Recruitment process and sample description. Whether the survey was open or closed (see below), how participants were contacted, and how the survey was advertised.
Survey administration. Web vs. email delivery, the context/platform, whether participation was mandatory or voluntary, incentives offered, the fielding window, item/questionnaire randomization, adaptive questioning, item and screen counts, and whether a completeness check or a final review step was built in.
Response rates. Unique site visitors, view rate, participation rate, and completion rate — the section covered in depth below.
Preventing multiple entries from the same respondent. Cookies, IP-address checks, log-file analysis, or registration gating.
Analysis. How incomplete responses were handled, whether submissions with an atypical timestamp were flagged, and whether any statistical correction was applied for non-response or sample bias.

None of these items is exotic on its own — most methods sections already gesture at several of them. CHERRIES’ actual value is forcing all eight into one place, in a fixed order, so a reviewer doesn’t have to reconstruct the sampling logic from scattered sentences.

Response Rates: The Section Authors Get Wrong Most Often

CHERRIES defines three distinct rates, each with a different denominator, and each answering a different question about where respondents were lost:

View rate — unique visitors who reached the survey’s first page, divided by unique visitors to the site overall. This measures how much of your general site traffic actually encountered the survey.
Participation rate — unique visitors who agreed to participate (typically, submitted the first substantive page), divided by unique visitors to that first survey page. This measures how many people who saw the invitation actually started.
Completion rate — respondents who finished the survey (submitted the last page), divided by respondents who agreed to participate. This measures attrition after the survey was started.

Multiplied together, these three ratios decompose total yield into three separate failure points — low visibility, a weak invitation, and mid-survey drop-off — rather than collapsing them into one undifferentiated “response rate” that can’t tell a reader which stage actually cost the sample size.

Worked illustrative example (invented numbers, not a real study, to show the arithmetic): a site had 10,000 unique visitors during the fielding window. 2,000 of them reached the survey’s first page — a 20% view rate. Of those 2,000, 1,500 agreed to participate and submitted the first substantive page — a 75% participation rate. Of those 1,500 participants, 1,200 completed every page through submission — an 80% completion rate. A single blended “response rate” computed as 1,200/10,000 (12%) would look like a weak survey; the three-rate breakdown shows the survey instrument itself performed well once someone started it (80% completion) — the real bottleneck was visibility (only 20% of site traffic ever saw it).

This is also the section with a documented history of getting misreported even in CHERRIES’ own primary source: the original 2004 table’s ratio wording was corrected in a formal erratum published January 4, 2012, after the numerator/denominator phrasing for these three rates had been presented ambiguously enough that some downstream summaries inverted it. The definitions above reflect the corrected 2012 wording. If you’re citing or reproducing a CHERRIES ratio table from a source that predates 2012, or from a source that copied the pre-correction phrasing, verify it against the corrected version rather than assuming it’s right.

Open Survey vs. Closed Survey

CHERRIES asks authors to state explicitly whether the survey was open or closed, because this single fact changes what the response-rate figures above can and can’t tell a reader:

Open survey — anyone who encounters it (via a public link, social media, or a site visit) can respond; there is no defined sampling frame, and “unique site visitors” is the closest available denominator, not a true population count.
Closed survey — distributed to a known, enumerable list (a class roster, a membership database, a random sample drawn from a registry), typically via unique invitation links or access codes, so a true response rate against a known denominator is calculable.

An open survey’s view/participation/completion rates describe funnel performance, not representativeness — a high completion rate says nothing about whether the people who found the link resemble the population the authors want to generalize to. That distinction is exactly why CHERRIES pairs the response-rate section with a separate, explicit design item asking authors to name their sampling frame and disclose a convenience sample as such.

Design, Ethics, and Pre-Testing: The Sections Before Administration

The three categories that precede fielding are shorter individually but load-bearing for interpretation:

Design asks for the survey’s actual design (cross-sectional, longitudinal panel, etc.), the target population, and the sampling frame used to reach it. IRB approval and informed consent asks whether ethics review occurred, and how consent, data storage, and investigator contact information were presented to respondents — standard practice for any human-subjects data collection regardless of mode. Development and pre-testing asks how the instrument itself was built and vetted before fielding: expert review, cognitive pre-testing, or a pilot run, the same instrument-development questions any well-designed questionnaire needs to answer, applied specifically to the web delivery context.

Preventing Multiple Entries and Handling the Analysis

Internet surveys carry a failure mode paper surveys don’t: the same person submitting more than once, whether by accident (a browser back-button resubmission) or deliberately (gaming an incentive). CHERRIES asks authors to state which of the standard technical controls were used — cookies, IP-address checks, log-file analysis for duplicate patterns, or a registration/login requirement — and, in the final Analysis category, how incomplete questionnaires were handled, whether submissions with an implausible or atypical timestamp were flagged, and whether any statistical correction was applied for non-response.

Using CHERRIES With a Modern Survey Platform

The checklist predates the current generation of survey tools, but every item maps cleanly onto features most platforms already log: Qualtrics, REDCap, and Alcher/LimeSurvey-style tools all record unique-visit timestamps (view rate), partial-response starts (participation rate), and completed submissions (completion rate) in their response export, and most support the cookie- or login-based duplicate controls CHERRIES asks about. The gap is almost never data availability — it’s that authors don’t pull the three separate counts out of the platform’s export before writing the methods section, and default instead to reporting a single “completion percentage” the software surfaces on its dashboard, which is usually the completion rate alone, not the full three-rate picture.

Related CASRAI Resources

Frequently Asked Questions

What does CHERRIES stand for?

Checklist for Reporting Results of Internet E-Surveys. It was introduced by Gunther Eysenbach in the Journal of Medical Internet Research in 2004.

Is CHERRIES required by journals?

It isn’t a universal mandate the way CONSORT is for some trial registries, but many journals that publish online-survey studies list it in their instructions for authors, and it’s registered as a reporting guideline with the EQUATOR Network alongside CONSORT, PRISMA, and STROBE. Check the specific journal’s author guidelines for online-survey submissions before assuming it is or isn’t required.

What’s the difference between view rate and participation rate?

View rate measures how many of your overall site visitors ever reached the survey’s first page. Participation rate measures how many of the people who reached that first page actually agreed to start — a completely separate question from whether they saw it at all. A survey can have a high participation rate among the people who found it, and still reach almost nobody, if the view rate is low.

Does CHERRIES apply to surveys run in Qualtrics, REDCap, or similar platforms?

Yes — CHERRIES is a reporting standard, not a platform-specific requirement, so it applies to any internet-delivered survey regardless of the tool used to build and field it. The relevant counts (unique visits, partial starts, completions) are standard exports on essentially every modern survey platform.

Do I need to report all eight CHERRIES categories even for a short survey?

The checklist doesn’t have a length exemption built in — a short survey still has a sampling frame, a consent process, and a completion rate worth stating. In practice, several items (e.g., informed consent, incentives) can often be covered in a single sentence each; the goal is that a reader can find every item somewhere in the methods section, not that each item needs its own paragraph.

CHERRIES Checklist: Reporting Results of Internet E-Surveys

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