13 Mood Measurement: Current Status and Future Directions

Research Methods in Psychology


  1. David Watson PhD1,
  2. Jatin G. Vaidya PhD2

Published Online: 26 SEP 2012

DOI: 10.1002/9781118133880.hop202013

Handbook of Psychology, Second Edition

Handbook of Psychology, Second Edition

How to Cite

Watson, D. and Vaidya, J. G. 2012. Mood Measurement: Current Status and Future Directions. Handbook of Psychology, Second Edition. 2:III:13.

Author Information

  1. 1

    University of Notre Dame, Department of Psychology, Iowa City, Iowa, USA

  2. 2

    University of Iowa, Department of Psychiatry, Iowa City, Iowa, USA

Publication History

  1. Published Online: 26 SEP 2012


We examine the measurement of mood in the context of prevailing hierarchical models of affect. We begin by discussing contemporary thinking and research regarding the underlying hierarchical structure of mood. We then evaluate the most important and widely used measures in this domain. Our review of the higher order level of the hierarchy establishes the existence of reliable and valid scales to assess the general dimensions of pleasantness, positive affect, and negative affect. In contrast, we currently lack good measures of the proposed higher order dimension of activation/arousal or engagement. In addition, although researchers have access to several widely used multiaffect inventories (including the POMS, the MAACL-R, and the PANAS-X), it is difficult to evaluate these instruments properly in the absence of (a) comparative psychometric studies and (b) a consensual taxonomic model that captures the specific affects occupying the lower level of the hierarchy. Next, we review the role of both random and systematic (i.e., social desirability and acquiescence bias) measurement errors in the assessment of mood, noting conditions under which they may be particularly problematic. Finally, we discuss the strengths and weaknesses associated with various approaches to the assessment of trait affect. Our review of the existing evidence indicates that we can improve the reliability and construct validity of trait affect measures by moving to a sentence-based approach.


  • mood measurement;
  • positive affect;
  • negative affect;
  • pleasantness;
  • measurement error