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Jonathan Winkle, Adam Biggs, Justin Ericson, Stephen Mitroff; For better or worse: Prior trial accuracy affects current trial accuracy in visual search. Journal of Vision 2015;15(12):1371. doi: 10.1167/15.12.1371.
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© ARVO (1962-2015); The Authors (2016-present)
Life is not a series of independent events, but rather, each event is influenced by what just happened and what might happen next. However, many research studies treat any given trial as an independent and isolated event. Some research fields explicitly test trial-to-trial influences (e.g., repetition priming, task switching), but many, including visual search, largely ignore potential inter-trial effects. While trial-order effects could wash out with random presentation orders, this does not diminish their potential impact (e.g., would you want your radiologist to be negatively affected by his/her prior success in screening for cancer?). To examine biases related to prior trial performance, data were analyzed from airport security officers and Duke University participants who had completed a visual search task. Participants searched for a target “T” amongst “pseudo-L” distractors with 50% of trials containing a target. Four set sizes were used (8,16,24,32), and participants completed the search task without feedback. Inter-trial analyses revealed that accuracy for the current trial was related to the outcome of the previous trial, with trials following successful searches being approximately 10% more accurate than trials following failed searches. Pairs of target-absent or target-present trials predominantly drove this effect; specifically, accuracy on target-present trials was contingent on a previous hit or miss (i.e., other target-present trials), while accuracy on target-absent trials was contingent on a previous correct rejection or false alarm (i.e., other target-absent trials). Inter-trial effects arose in both population samples and were not driven by individual differences, as assessed by mixed-effects linear modeling. These results have both theoretical and practical implications. Theoretically, it is worth considering how to control for inter-trial variance in statistical models of behavior. Practically, characterizing the conditions that modulate inter-trial effects might help professionals searchers perform more accurately, which can have life-saving consequences.
Meeting abstract presented at VSS 2015
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