title: Visualizing risks in cancer communication: A systematic review of computer-supported visual aids.
abstract: OBJECTIVE
  Health websites are becoming important sources for cancer information. Lay users, patients and carers seek support for critical decisions, but they are prone to common biases when quantitative information is presented. Graphical representations of risk data can facilitate comprehension, and interactive visualizations are popular. This review summarizes the evidence on computer-supported graphs that present risk data and their effects on various measures.
  
  
  METHODS
  The systematic literature search was conducted in several databases, including MEDLINE, EMBASE and CINAHL. Only studies with a controlled design were included. Relevant publications were carefully selected and critically appraised by two reviewers.
  
  
  RESULTS
  Thirteen studies were included. Ten studies evaluated static graphs and three dynamic formats. Most decision scenarios were hypothetical. Static graphs could improve accuracy, comprehension, and behavioural intention. But the results were heterogeneous and inconsistent among the studies. Dynamic formats were not superior or even impaired performance compared to static formats.
  
  
  CONCLUSIONS
  Static graphs show promising but inconsistent results, while research on dynamic visualizations is scarce and must be interpreted cautiously due to methodical limitations.
  
  
  CONCLUSIONS
  Well-designed and context-specific static graphs can support web-based cancer risk communication in particular populations. The application of dynamic formats cannot be recommended and needs further research.
authors.affiliation: Deutsche Krebsgesellschaft (German Cancer Society), Kuno-Fischer-Straße 8, 14057 Berlin, Germany; Department Health Sciences, Hamburg University of Applied Sciences (HAW Hamburg), Ulmenliet 20, 21033 Hamburg, Germany; School of Engineering and Computing, University of the West of Scotland (UWS), Paisley, PA1 2BE Scotland, UK. Electronic address: stellamanns@krebsgesellschaft.de.
authors.forename: Jan
authors.initials: J
authors.lastname: Stellamanns
authors.affiliation: Deutsche Krebsgesellschaft (German Cancer Society), Kuno-Fischer-Straße 8, 14057 Berlin, Germany. Electronic address: ruetters@krebsgesellschaft.de.
authors.forename: Dana
authors.initials: D
authors.lastname: Ruetters
authors.affiliation: School of Engineering and Computing, University of the West of Scotland (UWS), Paisley, PA1 2BE Scotland, UK; Nanjing University of Information Science and Technology (NUIST), Nanjing, China. Electronic address: Keshav.Dahal@uws.ac.uk.
authors.forename: Keshav
authors.initials: K
authors.lastname: Dahal
authors.affiliation: Department Health Sciences, Hamburg University of Applied Sciences (HAW Hamburg), Ulmenliet 20, 21033 Hamburg, Germany. Electronic address: zita.schillmoeller@haw-hamburg.de.
authors.forename: Zita
authors.initials: Z
authors.lastname: Schillmoeller
authors.affiliation: Clinic for Internal Medicine 2, Department for Haematology and Internal Oncology, Jena University Hospital, Bachstraße 18, 07743 Jena, Germany. Electronic address: Jutta.Huebner@med.uni-jena.de.
authors.forename: Jutta
authors.initials: J
authors.lastname: Huebner
mesh_terms: D001296:Audiovisual Aids; D003196:Computer Graphics; D003657:Decision Making; D006801:Humans; D020407:Internet; D009369:Neoplasms / Q000628:therapy*; D012306:Risk
keywords: Cancer; Internet; Medical decision-making; Neoplasms; Risk communication; Visual aids; Visualization