Provide an example of bias in a community health survey and how to minimize it.

• A. Nonresponse bias; minimize with follow-ups, incentives, multiple contact modes, and weighting to reflect population
• B. Measurement bias; minimize by using a single method
• C. Selection bias; minimize by excluding nonrespondents
• D. Recall bias; minimize by longer recall period

Answer: (A)

Nonresponse bias occurs when the people who participate in a survey differ in important ways from those who don’t respond, so the results don’t accurately reflect the whole population. In a community health survey, if younger people, people with busier schedules, or those with limited access are less likely to respond, the collected data may overrepresent other groups and misrepresent true health patterns.

To minimize this bias, use follow-ups to reach nonrespondents, offer incentives to participate, employ multiple contact methods (phone, mail, online) to reach diverse segments, and apply weighting so the respondent sample matches the population on key characteristics. These approaches help both increase participation and adjust for remaining differences.

Why the other ideas don’t fit as well: measurement bias comes from errors in how data are collected, not from who responds, and one method alone isn’t the reliable fix; selection bias would worsen if you excluded nonrespondents rather than include them; recall bias typically increases with longer recall periods, so a longer recall window would often worsen it rather than minimize it.