Physiometrics in Salivary Bioscience
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SPECIAL ISSUE: SALIVARY BIOSCIENCE
Physiometrics in Salivary Bioscience Suzanne C. Segerstrom 1
# International Society of Behavioral Medicine 2020
Abstract Background Accurate estimation in statistical models depends on sample size but also, critically, reliability of the measure. Physiometrics is the equivalent of psychometrics for measures such as sex hormones, catabolic hormones, and products of the immune system. Method There are multiple ways to measure physiometrics, from simple correlation to complex generalizability theory designs. Depending on the design, these estimates can provide information about equivalency (e.g., the correlation between two measurements taken close together in time) or stability (e.g., the correlation between two measurements taken farther apart in time). Results The physiometrics of salivary measures including cortisol, α-amylase, testosterone, and cytokines range from highly stable, requiring only a single sample, to highly unstable, requiring multiple samples to achieve generalizability to longer periods of time. However, generalizability is relative to the study design, and only some designs call for stable and generalizable measures. Conclusion Both dedicated physiometric studies and more reporting of physiometrics in psychoneuroendocrinology and psychoneuroimmunology will improve the quality of salivary bioscience study designs in the future. Keywords Cortisol . Testosterone . Cytokine . Reliability . Generalizability
Introduction
Variability introduces error into behavioral studies, where stable measures are needed to characterize individual differences and changes over time. Without more information on this variability, one cannot know how many subjects to run, how many measurements to take, and when to take the measurements [1, p. 83]. Although this epigraph could apply to any number of measures, in this case, Dabbs [1] refers to the variability of salivary testosterone (T). The idea of “physiometrics” [2, 3]—the physiological equivalent of psychometrics—seems to have been around for at least 3 decades. Although the validity of physiological measures, especially salivary measures, is a major research topic (e.g., the correlation between salivary and serum * Suzanne C. Segerstrom [email protected] 1
Department of Psychology, University of Kentucky, 125 Kastle Hall, Lexington, KY 40506-0044, USA
levels), there is less attention to variability, generalizability, and measure reliability (vs. assay reliability [4]). Here, I hope to convince readers that there are good reasons that more attention to physiometrics will benefit salivary bioscience. Most important, accurate estimation depends on larger sample sizes and more reliable measurement; however, it is possible to trade off between the two [5–10]. The issue of “how many subjects to run, how many measurements to take” [1, p. 83] reflects consideration of this trade-off. When samples are small and measures are unreliable, estimates in statistical models are often substantially too large or small and/or reflect the wron
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