title: Impact of graphic format on perception of change in  biological data: implications for health monitoring in  conditions such as asthma.
abstract: BACKGROUND
  Variation in graphic format can substantially influence interpretation of data. Despite a large body of literature on the  optimal design of graphs, little attention has been paid to the format of charts for health monitoring.
  
  
  OBJECTIVE
  This study assessed the effect of aspect ratio (x:y ratio) and interconnecting lines on visual identification of change in biological  data, such as during asthma exacerbations.
  
  
  METHODS
  Eighty volunteers viewed 72 sets of six consecutive blocks of unidentified biological data, recording if each block of data was  increasing, decreasing, or the same as the previous block. Three chart aspect ratios were examined (A, 5.2:1; B, 3.0:1; C, 1.1:1), with or  without lines between data points. Datasets from lung function monitoring by asthma patients included a mild/moderate/severe fall  ('exacerbation') or no exacerbation. False negative (missing true exacerbations) and false positive (identifying non-existent exacerbations)  responses were calculated.
  
  
  RESULTS
  84% of exacerbation blocks were correctly identified. There was a significant interaction between exacerbation severity and  aspect ratio (p=0.0048). The most compressed chart (C) had the fewest false negative responses. Moderate falls were missed in 24%,  12%, and 5% of trials on charts A, B, and C, respectively (C vs A: adjusted relative risk 0.19 (95% CI 0.12 to 0.30)). False positive responses  were infrequent (A, 2.5%; B, 3.8%; C, 8.3%), increasing slightly if data points were joined with lines (4.3% vs 5.1%, p=0.004) .
  
  
  CONCLUSIONS
  Compressed charts can improve the visual detection of change in biological data by up to 80%. The aspect ratio of charts  should be standardised to facilitate clinical pattern recognition.
authors.affiliation: Sydney School of Public Health, University of Sydney, New South Wales, Australia. jesse.jansen@sydney.edu.au
authors.forename: Jesse
authors.initials: J
authors.lastname: Jansen
authors.forename: Kirsten J
authors.initials: KJ
authors.lastname: McCaffery
authors.forename: Andrew
authors.initials: A
authors.lastname: Hayen
authors.forename: David
authors.initials: D
authors.lastname: Ma
authors.forename: Helen K
authors.initials: HK
authors.lastname: Reddel
mesh_terms: D000328:Adult; D001249:Asthma / Q000175:diagnosis*; D003196:Computer Graphics; D005260:Female; D006801:Humans; D008297:Male; D010364:Pattern Recognition, Visual; D010366:Peak Expiratory Flow Rate; D014796:Visual Perception