Open AccessMen's interpretations of graphical information in a videotape decision aid 1
Author(s) -
Pylar Jan,
Wills Celia E.,
Lillie Janet,
Rovner David R.,
KellyBlake Karen,
HolmesRovner Margaret
Publication year - 2007
Publication title -
health expectations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.314
H-Index - 74
eISSN - 1369-7625
pISSN - 1369-6513
DOI - 10.1111/j.1369-7625.2007.00443.x
Subject(s) - bar chart , interpretation (philosophy) , comprehension , meaning (existential) , psychology , graph , observational study , computer science , social psychology , mathematics , statistics , theoretical computer science , psychotherapist , programming language
Objective To examine men's interpretations of graphical information types viewed in a high‐quality, previously tested videotape decision aid (DA). Setting, participants, design A community‐dwelling sample of men >50 years of age ( N = 188) balanced by education (college/non‐college) and race (Black/White) were interviewed just following their viewing of a videotape DA. A descriptive study design was used to examine men's interpretations of a representative sample of the types of graphs that were shown in the benign prostatic hyperplasia videotape DA. Main variables studied Men provided their interpretation of graphs information presented in three formats that varied in complexity: pictograph, line and horizontal bar graph. Audiotape transcripts of men's responses were coded for meaning and content‐related interpretation statements. Results Men provided both meaning and content‐focused interpretations of the graphs. Accuracy of interpretation was lower than hypothesized on the basis of literature review (85.4% for pictograph, 65.7% for line graph, 47.8% for horizontal bar graph). Accuracy for pictograph and line graphs was associated with education level, = 3.94, P = 0.047, and = 7.55, P = 0.006, respectively. Accuracy was uncorrelated with men's reported liking of the graphs, = 2.00, P = 0.441. Conclusion While men generally liked the DA, accuracy of graphs interpretation was associated with format complexity and education level. Graphs are often recommended to improve comprehension of information in DAs. However, additional evaluation is needed in experimental and naturalistic observational settings to develop best practice standards for data representation.