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. 2019 Aug 15;14(8):e0220749.
doi: 10.1371/journal.pone.0220749. eCollection 2019.

A Z-score based method for comparing the relative sensitivity of behavioral and physiological metrics including cognitive performance, mood, and hormone levels

John A Caldwell  1   2 , Philip J Niro  2 , Emily K Farina  2   3 , James P McClung  2 , Gregory R Caron  4 , Harris R Lieberman  2
Affiliations

A Z-score based method for comparing the relative sensitivity of behavioral and physiological metrics including cognitive performance, mood, and hormone levels

John A Caldwell et al. PLoS One. .

Abstract

A method for assessing the relative sensitivity of research metrics is proposed and illustrated by comparing 18 outcome measures from a published study of the cognitive, mood, and hormonal effects of four different levels of stress induced by intense military training. Research on the human response to stress often assesses multiple disparate dependent measures. Selecting the most sensitive is difficult as formal methods to compare varied dependent measures have not been developed. The method first converts the outcome measures into standard scores (z-scores) and then compares them using analysis of variance to determine whether there are differences in how they assess the impact of graded levels of exposure to stress. The analysis detected various significant interactions in several measures and suggests self-report mood questionnaires were more sensitive to the stressors present in the study than the cognitive or hormonal measures which were used. These findings support the effectiveness of the z-score based method as a useful procedure for objectively evaluating the differential sensitivity of various metrics. This method could be useful for research on other independent variables when use of multiple assessment strategies is appropriate. It could be used for evaluating studies yielding conflicting results, such as those detecting effects on one parameter but not others. In such instances, cross-metric inconsistencies may be due to differential sensitivity of measurement strategies rather than actual differences in the effects of the independent-variable on the domains under investigation.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Summary of the data transformation and analysis procedure.
Fig 2
Fig 2. Function for which each orthogonal trend-analysis contrast was tested for significance p < .05.
Fig 3
Fig 3. The number of trend-analysis contrasts that were significant p < .05.
Fig 4
Fig 4. The number of pairwise post-hoc comparisons that were significant p < .05.
Fig 5
Fig 5
Measures expected to have positive (5A) and negative (5B) trends from baseline to captivity.
Fig 6
Fig 6. The magnitude of the mean change between test sessions 1 and 2.
Fig 7
Fig 7. The magnitude of the mean change between test sessions 1 and 3.
See this image and copyright information in PMC

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