The long-term stability and predictive validity of trait measures of affect.
Abstract
This study examined the long-term temporal stability and predictive utility of trait Positive Affect and Negative Affect scales. Participants were assessed initially as undergraduates: They rated how they felt generally (general sample) or during the past year (year sample). They were retested on a general affect measure and on scales assessing current depression and anxiety approximately 6 (general sample) or 7 (year sample) years later. By this time, all of them had graduated from college and most were working full-time. Negative Affect scores declined significantly over the study. Nevertheless, the Negative and Positive Affect scales both displayed a significant, moderate level of stability. Moreover, initial scores on both scales correlated significantly with measures of current symptoms that were completed several years later. Thus, trait affect scales were substantially stable--and maintained significant predictive power--even across extended time spans.
Cites (9)
- Validation of the five-factor model of personality across instruments and observers.McCrae, Robert R., Costa, Paul T. · 1987 · Journal of Personality and Social Psychology
- Negative affectivity: the disposition to experience aversive emotional statesWatson, David, Clark, Lee A. · 1984 · Psychological Bulletin
- Tripartite model of anxiety and depression: psychometric evidence and taxonomic implicationsClark, Lee Anna, Watson, David · 1991 · Journal of Abnormal Psychology
- Health complaints, stress, and distress: Exploring the central role of negative affectivity.Watson, David, Pennebaker, James W. · 1989 · Psychological Review
- Temperament, personality, and the mood and anxiety disorders.Clark, Lee Anna, Watson, David, Mineka, Susan · 1994 · Journal of Abnormal Psychology
- A contrarian view of the five-factor approach to personality description.Block, Jack · 1995 · Psychological Bulletin
- Mood and the mundane: Relations between daily life events and self-reported mood.Clark, Lee Anna, Watson, David · 1988 · Journal of Personality and Social Psychology
- Environmental and dispositional influences on well‐being: Longitudinal follow‐up of an American national sampleCosta, Paul T., McCrae, Robert R., Zonderman, Alan B. · 1987 · British Journal of Psychology
- Personality change in women from college to midlife.Helson, Ravenna, Moane, Geraldine · 1987 · Journal of Personality and Social Psychology
Cited by (31)
- Patterns of mean-level change in personality traits across the life course: A meta-analysis of longitudinal studies.Roberts, Brent W., Walton, Kate E., Viechtbauer, Wolfgang · 2006 · Psychological Bulletin
- Affect and Creativity at WorkAmabile, Teresa M., Barsade, Sigal G., Mueller, Jennifer S., Staw, Barry M. · 2005 · Administrative Science Quarterly
- Rethinking the mood and anxiety disorders: A quantitative hierarchical model for DSM-V.Watson, David · 2005 · Journal of Abnormal Psychology
- Developing a model for adult temperamentEvans, David E., Rothbart, Mary K. · 2007 · Journal of Research in Personality
- The Affective Underpinnings of Job Perceptions and Attitudes: A Meta-Analytic Review and Integration.Thoresen, Carl J., Kaplan, Seth A., Barsky, Adam P., Warren, Christopher R., de Chermont, Kelly · 2003 · Psychological Bulletin
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The long-term stability and predictive validity of trait measures of affect. https://app.cochat.ai/papers/10.1037//0022-3514.70.3.567
- The paper
- Watson, D., & Walker, L. M. (1996). The long-term stability and predictive validity of trait measures of affect. Journal of Personality and Social Psychology. https://doi.org/10.1037//0022-3514.70.3.567
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.