PLoS ONE (Jan 2013)

Time perception and depressive realism: judgment type, psychophysical functions and bias.

  • Diana E Kornbrot,
  • Rachel M Msetfi,
  • Melvyn J Grimwood

DOI
https://doi.org/10.1371/journal.pone.0071585
Journal volume & issue
Vol. 8, no. 8
p. e71585

Abstract

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The effect of mild depression on time estimation and production was investigated. Participants made both magnitude estimation and magnitude production judgments for five time intervals (specified in seconds) from 3 sec to 65 sec. The parameters of the best fitting psychophysical function (power law exponent, intercept, and threshold) were determined individually for each participant in every condition. There were no significant effects of mood (high BDI, low BDI) or judgment (estimation, production) on the mean exponent, n = .98, 95% confidence interval (.96-1.04) or on the threshold. However, the intercept showed a 'depressive realism' effect, where high BDI participants had a smaller deviation from accuracy and a smaller difference between estimation and judgment than low BDI participants. Accuracy bias was assessed using three measures of accuracy: difference, defined as psychological time minus physical time, ratio, defined as psychological time divided by physical time, and a new logarithmic accuracy measure defined as ln (ratio). The ln (ratio) measure was shown to have approximately normal residuals when subjected to a mixed ANOVA with mood as a between groups explanatory factor and judgment and time category as repeated measures explanatory factors. The residuals of the other two accuracy measures flagrantly violated normality. The mixed ANOVAs of accuracy also showed a strong depressive realism effect, just like the intercepts of the psychophysical functions. There was also a strong negative correlation between estimation and production judgments. Taken together these findings support a clock model of time estimation, combined with additional cognitive mechanisms to account for the depressive realism effect. The findings also suggest strong methodological recommendations.