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Color-encoding visualizations as a tool to assist a nonliterate population in completing health survey responses.

Maichou Lor
Published in: Informatics for health & social care (2018)
Visual representations of data have increasingly included color-encodings to help engage participants in health research. However, there is limited information on the way in which participants interpret color or on the influence of embedded cultural interpretations of color on survey responses. This study examines the interpretation of color-encodings used to indicate survey response options and their impact on participants' responses. Using a descriptive, cross-sectional design, interviews were conducted with 30 older Hmong adults from one Midwestern city in the United States. A survey data collection method was developed using: (a) an Audio-Computer-Assisted Self-Interviewing tool with (b) text-based and color-encoded response options and (c) assistance from a familiar helper. We analyzed the responses using directed content analysis. Findings reveal that some colors (red, black, and white) have strong cultural connotations; such colors were strongly correlated with specific emotions, while others (green, blue, purple, and pink) had no cultural meaning. Early in the survey, some older Hmong were distracted by response options indicated in red and black, influencing their response choices. However, with repeated instructions from the helpers, all participants overcame the color-related distractions and completed the survey. The findings highlight the importance of using colors cautiously and purposively in visualization development.
Keyphrases
  • cross sectional
  • healthcare
  • electronic health record
  • big data
  • machine learning
  • palliative care
  • single cell
  • smoking cessation
  • community dwelling
  • artificial intelligence
  • drug induced
  • health information