Absent a perceived motive for deception, people will infer that a message source is honest. As a consequence, confessions should be believed more often than denials, true confessions will be correctly judged as honest, and false confessions will be misjudged. In the first experiment, participants judged true and false confessions and denials. As predicted, confessions were judged as honest more frequently than denials. Subsequent experiments replicated these results with an independent groups design and with a sample of professional investigators. Together, these three experiments document an important exception to the 50%+ accuracy conclusion, provide evidence consistent with a projected motive explanation of deception detection, and highlight the importance of the content-in-context in judgmental processes.
This study provided the first empirical test of point predictions made by the Park-Levine probability model of deception detection accuracy. Participants viewed a series of interviews containing truthful answers, unsanctioned, high-stakes lies, or some combination of both. One randomly selected set of participants (n0/50) made judgments where the probability that each message was honest was P(H)0/.50. Accuracy judgments in this condition were used to generate point predictions generated from the model and tested against the results from a second set of data (n 0/413). Participants were randomly assigned to one of eight base-rate conditions where the probability that a message was honest systematically varied from 0.00 to 1.00. Consistent with the veracity effect, participants in P(H)0/.50 condition were significantly more likely to judge messages as truths than as lies, and consequently truths (67%) were identified with greater accuracy than lies (34%). As predicted by the model, overall accuracy was a linear function of message veracity base-rate, the base-rate induction explained 24% of the variance in accuracy scores, and, on average, raw accuracy scores for specific conditions were predicted to within approximately9/2.6%. The findings show that specific deception detection accuracy scores can be precisely predicted with the Park-Levine model.
The current paper reexamines how suspicion affects deception detection accuracy. McCornack and Levine's (1990) nonlinear ''optimal level'' hypothesis is contrasted with an ''opposing effects'' hypothesis. Three different levels of suspicion were experimentally induced and participants (N ¼ 91) made veracity judgments of videotaped interviews involving denials of cheating. The results were more consistent with the opposing effects hypotheses than the optimal level hypotheses.
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