How lay people understand and make sense of personalized disease risk information

Olga C Damman, Nina M M Bogaerts, Maaike J van den Haak, Danielle R M Timmermans

Research output: Contribution to JournalArticleAcademicpeer-review


BACKGROUND: Disease risk calculators are increasingly web-based, but previous studies have shown that risk information often poses problems for lay users.

OBJECTIVE: To examine how lay people understand the result derived from an online cardiometabolic risk calculator.

DESIGN: A qualitative study was performed, using the risk calculator in the Dutch National Prevention Program for cardiometabolic diseases. The study consisted of three parts: (i) attention: completion of the risk calculator while an eye tracker registered eye movements; (ii) recall: completion of a recall task; and (iii) interpretation: participation in a semi-structured interview.

SETTING AND PARTICIPANTS: We recruited people from the target population through an advertisement in a local newspaper; 16 people participated in the study, which took place in our university laboratory.

RESULTS: Eye-tracking data showed that participants looked most extensively at numerical risk information. Percentages were recalled well, whereas natural frequencies and verbal labels were remembered less well. Five qualitative themes were derived from the interview data: (i) numerical information does not really sink in; (ii) the verbal categorical label made no real impact on people; (iii) people relied heavily on existing knowledge and beliefs; (iv) people zoomed in on risk factors, especially family history of diseases; and (v) people often compared their situation to that of their peers.

DISCUSSION AND CONCLUSION: Although people paid attention to and recalled the risk information to a certain extent, they seemed to have difficulty in properly using this information for interpreting their risk.

Original languageEnglish
Article number20 (5)
Pages (from-to)973-983
Number of pages10
JournalHealth Expectations
Issue number5
Publication statusPublished - Oct 2017


  • risk information
  • user research


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