DARMA: Software for dual axis rating and media annotation

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Abstract

Continuous measurement systems provide a means of measuring dynamic behavioral and experiential processes as they play out over time. DARMA is a modernized continuous measurement system that synchronizes media playback and the continuous recording of two-dimensional measurements. These measurements can be observational or self-reported and are provided in real-time through the manipulation of a computer joystick. DARMA also provides tools for reviewing and comparing collected measurements and for customizing various settings. DARMA is a domain-independent software tool that was designed to aid researchers who are interested in gaining a deeper understanding of behavior and experience. It is especially well-suited to the study of affective and interpersonal processes, such as the perception and expression of emotional states and the communication of social signals. DARMA is open-source using the GNU General Public License (GPL) and is available for free download from http://darma.jmgirard.com.

Keywords

Research software Continuous measurement Media annotation Observational measurement Inter-rater reliability 

Notes

Acknowledgments

Research reported in this publication was supported in part by the National Institutes of Health under award number MH096951 and GM105004. The content is solely the responsibility of the authors and does not necessarily represent the views of the National Institutes of Health. Images of Matt Damon and Robin Williams from the film “Good Will Hunting” appear in several figures for demonstrative purposes only; the film was produced by Lawrence Bender Productions and distributed in the United States by Miramax Films.

References

  1. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders, 5th edn. Washington, DC: American Psychiatric Association.CrossRefGoogle Scholar
  2. Cizek, G. J. (2016). Validating test score meaning and defending test score use: Different aims, different methods. Assess. Educ. Princ. Policy Pract., 23(2), 212–225.Google Scholar
  3. Cowie, R., Douglas-Cowie, E., Savvidou, S., McMahon, E., Sawey, M., & Schröder, M. (2000). FEELtrace: An instrument for recording perceived emotion in real time, ISCA tutorial and research workshop on speech and emotion (pp. 19–24).Google Scholar
  4. Cowie, R., McKeown, G., & Douglas-Cowie, E. (2012). Tracing emotion: An overview. Int J Synth Emot, 3(1), 1–17.CrossRefGoogle Scholar
  5. Fournier, M. A., Moskowitz, D. S., & Zuroff, D. C. (2010). Origins and applications of the interpersonal circumplex. In Horowitz, L. M., & Strack, S. (Eds.), The handbook of interpersonal psychology (pp. 57–73). Hoboken, NJ: Wiley.Google Scholar
  6. Geringer, J. M., Madsen, C. K., & Gregory, D. (2004). A fifteen-year history of the continuous response digital interface: Issues relating to validity and reliability. Bulletin of the Council for Research in Music Education, 160, 1–15.Google Scholar
  7. Girard, J. M. (2014). CARMA: Software for continuous affect rating and media annotation. J Open Res Softw, 2(1), e5.Google Scholar
  8. Girard, J. M., & Cohn, J. F. (2016). A primer on observational measurement. Assess, 23(4), 404–413.CrossRefGoogle Scholar
  9. Girard, J. M., Wright, A. G. C., Stepp, S. D., & Pilkonis, P. A. (2016). Interpersonal dynamics in couples with personality pathology, Symposium conducted at the meeting of the association for psychological science.Google Scholar
  10. Gottman, J. M., & Levenson, R. W. (1985). A valid procedure for obtaining self-report of affect in marital interaction. Journal of Consulting and Clinical Psychology, 53(2), 151–160.CrossRefPubMedGoogle Scholar
  11. Gunes, H., & Schuller, B. W. (2013). Categorical and dimensional affect analysis in continuous input: Current trends and future directions. Image and Vision Computing, 31(2), 120–136.CrossRefGoogle Scholar
  12. Gurtman, M. B. (1994). The circumplex as a tool for studying normal and abnormal personality: A methodological primer. In Strack, S., & Lorr, M. (Eds.), Differentiating normal and abnormal personality (pp. 243–263). New York, NY: Springer.Google Scholar
  13. Heck, R. H. (1999). Multilevel modeling with SEM. In Thomas, S. L., & Heck, R. H. (Eds.), Introduction to multilevel modeling techniques (pp. 89–127). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  14. Horowitz, L. M., Wilson, K. R., Turan, B., Zolotsev, P., Constantino, M. J., & Henderson, L. (2006). How interpersonal motives clarify the meaning of interpersonal behavior: A revised circumplex model. Personality and Social Psychology Review, 10(1), 67–86.CrossRefPubMedGoogle Scholar
  15. Juslin, P. N., & Sloboda, J. A. (eds.) (2011). Handbook of music and emotion: Theory, research, applications. Oxford University Press.Google Scholar
  16. Kiesler, D. J. (1983). The 1982 interpersonal circle: A taxonomy for complementarity in human transactions. Psychological Review, 90, 185–214.CrossRefGoogle Scholar
  17. LeBreton, J. M., Burgess, J. R. D., Kaiser, R. B., Atchley, E. K., & James, L. R. (2003). The restriction of variance hypothesis and interrater reliability and agreement: Are ratings from multiple sources really dissimilar? Organizational Research Methods, 6(1), 80–128.CrossRefGoogle Scholar
  18. Lizdek, I., Sadler, P., Woody, E., Ethier, N., & Malet, G. (2012). Capturing the stream of behavior: A computer-joystick method for coding interpersonal behavior continuously over time. Social Science Computer Review, 30(4), 513–521.CrossRefGoogle Scholar
  19. Markey, P., Lowmaster, S., & Eichler, W. (2010). A real-time assessment of interpersonal complementarity. Personal Relationships, 17(1), 13–25.CrossRefGoogle Scholar
  20. McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1(1), 30–46.CrossRefGoogle Scholar
  21. Messinger, D. S., Cassel, T. D., Acosta, S. I., Ambadar, Z., & Cohn, J. F. (2008). Infant smiling dynamics and perceived positive emotion. Journal of Nonverbal Behavior, 32(3), 133–155.CrossRefPubMedPubMedCentralGoogle Scholar
  22. Nagel, F., Kopiez, R., Grewe, O., & Altenmuller, E. (2007). EMujoy: Software for continuous measurement. Behavior Research Methods, 39(2), 283–290.CrossRefPubMedGoogle Scholar
  23. Ross, J. M., Girard, J. M., Wright, A. G. C., Beeney, J. E., Scott, L. N., Hallquist, M. N., ..., & Pilkonis, P. A. (2017). Momentary patterns of covariation between specific affects and interpersonal behavior: Linking relationship science and personality assessment. Psychological Assessment, 29(2), 123–134.CrossRefPubMedGoogle Scholar
  24. Ruef, A. M., & Levenson, R. W. (2007). Continuous measurement of emotion: The affect rating dial. In Coan, J. A., & Allen, J. J. B. (Eds.), Handbook of emotion elicitation and assessment (pp. 286–297). New York, NY, US: Oxford University Press.Google Scholar
  25. Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161.CrossRefGoogle Scholar
  26. Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110 (1), 145–172.CrossRefPubMedGoogle Scholar
  27. Sadler, P., Ethier, N., Gunn, G. R., Duong, D., & Woody, E. (2009). Are we on the same wavelength? Interpersonal complementarity as shared cyclical patterns during interactions. Journal of Personality and Social Psychology, 97(6), 1005– 1020.CrossRefPubMedGoogle Scholar
  28. Schubert, E. (1999). Measuring emotion continuously: Validity and reliability of the two-dimensional emotion-space. Australian Journal of Psychology, 51(3), 154–165.CrossRefGoogle Scholar
  29. Schubert, E. (2007). Real time cognitive response recording., In Proceedings of the international conference on music communication science (pp. 139–142).Google Scholar
  30. Tracey, T. J. G., Bludworth, J., & Glidden-Tracey, C. E. (2012). Are there parallel processes in psychotherapy supervision? An empirical examination. Psychotheraphy, 49(3), 330–343.CrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2017

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of PittsburghPittsburghUSA

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