{"componentChunkName":"component---src-pages-background-tsx","path":"/background/","result":{"data":{"allContentfulBackgroundPage":{"edges":[{"node":{"id":"11008ed1-d01d-5285-8fce-df8116e3eb54","content":{"raw":"{\"nodeType\":\"document\",\"data\":{},\"content\":[{\"nodeType\":\"heading-2\",\"content\":[{\"nodeType\":\"text\",\"value\":\"Background\",\"marks\":[],\"data\":{}}],\"data\":{}},{\"nodeType\":\"paragraph\",\"content\":[{\"nodeType\":\"text\",\"value\":\"BiasProof have developed a mobile-enabled, easy-to-use implicit weight bias test.  BiasProof's test has been created based on the \\\"Harvard Standard\\\" Implicit Association Test (Greenwald et al., 1998).  The BiasProof test can be completed on mobile devices such as mobile phones, iPads or tablets.  It takes approximately 5 minutes to complete.  Users are presented with an array of words and/or pictures and are required to assign them to a category as quickly as possible.\",\"marks\":[],\"data\":{}}],\"data\":{}},{\"nodeType\":\"paragraph\",\"content\":[{\"nodeType\":\"text\",\"value\":\"The Implicit Association Test was created in 1998 to assess associations between concepts (e.g. thin people, people with excessive weight) and evaluations (e.g. pleasant, unpleasant) by using response latencies as part of a stimulus sorting task.  Implicit Association Tests have been used to assess implicit bias for over 20 years.\",\"marks\":[],\"data\":{}}],\"data\":{}},{\"nodeType\":\"paragraph\",\"content\":[{\"nodeType\":\"text\",\"value\":\"At the end of the test, the IAT outcome score is based on the average time it takes a person to complete the sorting task.  An implicit preference for a concept (e.g. thin people compared to people with excessive weight), would represent quicker categorization of stimuli when thin people and a positive evaluation (e.g. good) appear on the same side of the screen.  The outcomes of the test have been and continue to be used to predict cognition, emotions and behaviours (e.g. Greenwald et al., 2009).\",\"marks\":[],\"data\":{}}],\"data\":{}},{\"nodeType\":\"paragraph\",\"content\":[{\"nodeType\":\"text\",\"value\":\"References\",\"marks\":[{\"type\":\"bold\"}],\"data\":{}}],\"data\":{}},{\"nodeType\":\"paragraph\",\"content\":[{\"nodeType\":\"text\",\"value\":\"Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences inimplicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74, 1464–1480. \",\"marks\":[],\"data\":{}},{\"nodeType\":\"hyperlink\",\"content\":[{\"nodeType\":\"text\",\"value\":\"https://doi.org/10.1037/0022-3514.74.6.1464\",\"marks\":[],\"data\":{}}],\"data\":{\"uri\":\"https://doi.org/10.1037/0022-3514.74.6.1464\"}},{\"nodeType\":\"text\",\"value\":\"\\n\\nGreenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R. (2009). Understanding and using the Implicit Association Test: III. Meta- analysis of predictive validity. Journal of Personality and Social Psychology, 97, 17–41. \",\"marks\":[],\"data\":{}},{\"nodeType\":\"hyperlink\",\"content\":[{\"nodeType\":\"text\",\"value\":\"https://doi.org/10.1037/a0015575\",\"marks\":[],\"data\":{}}],\"data\":{\"uri\":\"https://doi.org/10.1037/a0015575\"}},{\"nodeType\":\"text\",\"value\":\"\",\"marks\":[],\"data\":{}}],\"data\":{}}]}"},"backButtonLabel":"Back"}}]}},"pageContext":{}},"staticQueryHashes":["1884068637"]}