Sample size
The count of collected answers. It helps show the amount of input, but it does not solve recruitment bias or unclear wording.
Methods without the jargon
Sample size is not the whole story.
When reading period surveys, sample size tells you how many answers were collected. It does not automatically tell you whether the respondents reflect the people described in the headline.
How to read the number behind the number.
Do not ask only “how many?” Ask “how were they found, who is missing, and what claim is being made from their answers?”
Representativeness
Whether the respondents reasonably reflect the group being discussed. A customer survey, for example, mainly describes people connected to that customer base.
Limitations
The honest notes that explain what the survey cannot prove. Strong reporting includes them instead of hiding them at the end.
Good limitations make content stronger, not weaker.
Limitations prevent readers from treating a narrow observation as a universal rule. In menstrual health and period product content, that matters because experiences vary and product choice is personal.
- A limitation can explain who was not included.
- A limitation can separate preference from performance.
- A limitation can stop a product claim from becoming a medical claim.
Three examples of safer wording.
From “people prefer” to “respondents in this survey preferred”.
This keeps the claim tied to the actual group that answered.
From “cups are best” to “cups are one option that collects menstrual flow”.
The NHS describes cups as products that collect flow and can be washed and reused; it does not rank a specific brand.
From “guaranteed fit” to “compare measurements and personal preferences”.
MonthlyCup’s guide advises comparing dimensions, flow and preferences; age or childbirth alone are not a size rule, and no model is guaranteed to fit everyone.