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8 - Beyond Coding Interaction

New Horizons in Interaction Analysis

from Part II - Application Areas of Interaction Analysis

Published online by Cambridge University Press:  19 July 2018

By
Michael A. Rosen ,
Aaron S. Dietz  and
Sadaf Kazi
Edited by
Elisabeth Brauner ,
Margarete Boos  and
Michaela Kolbe
Elisabeth Brauner
Affiliation:
Brooklyn College, City University of New York
Margarete Boos
Affiliation:
University of Göttingen
Michaela Kolbe
Affiliation:
ETH Zürich
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The Cambridge Handbook of Group Interaction Analysis , pp. 142 - 162
Publisher: Cambridge University Press
Print publication year: 2018

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References

Arrow, H., McGrath, J. E., & Berdahl, J. L. (2000). Small groups as complex systems: Formation, coordination, development, and adaptation. Thousand Oaks, CA: Sage Publications.CrossRefGoogle Scholar
Behoora, I., & Tucker, C. S. (2015). Machine learning classification of design team members’ body language patterns for real time emotional state detection. Design Studies, 39, 100–127. http://dx.doi.org/10.1016/j.destud.2015.04.003CrossRefGoogle Scholar
Bowers, C. A., Jentsch, F., Salas, E., & Braun, C. C. (1998). Analyzing communication sequences for team training needs assessment. Human Factors, 40(4), 672–679. http://dx.doi.org/10.1518/001872098779649265CrossRefGoogle Scholar
Butts, C. T. (2008). A relational event framework for social action. Sociological Methodology, 38(1), 155–200. http://dx.doi.org/10.1111/j.1467-9531.2008.00203.xCrossRefGoogle Scholar
Cacioppo, J. T., Berntson, G. G., Sheridan, J. F., & McClintock, M. K. (2000). Multilevel integrative analyses of human behavior: Social neuroscience and the complementing nature of social and biological approaches. Psychological Bulletin, 126(6), 829–843. http://dx.doi.org/10.1037/0033-2909.126.6.829CrossRefGoogle ScholarPubMed
Chaffin, D., Heidl, R., Hollenbeck, J. R., Howe, M., Yu, A., Voorhees, C., & Calantone, R. (2017). The promise and perils of wearable sensors in organizational research. Organizational Research Methods, 20(1), 3–31. http://dx.doi.org/10.1177/1094428115617004CrossRefGoogle Scholar
Chancellor, J., Layous, K., Margolis, S., & Lyubomirsky, S. (2017, March 30). Clustering by well-being in workplace social networks: Homophily and social contagion. Emotion. Advance online publication. http://dx.doi.org/10.1037/emo0000311CrossRefGoogle Scholar
de Montjoye, Y. A., Stopczynski, A., Shmueli, E., Pentland, A., & Lehmann, S. (2014). The strength of the strongest ties in collaborative problem solving. Scientific Reports, 4, 5277. http://dx.doi.org/10.1038/srep05277CrossRefGoogle ScholarPubMed
Dietz, A. S., Pronovost, P. J., Benson, K. N., Mendez-Tellez, P. A., Dwyer, C., Wyskiel, R., & Rosen, M. A. (2014). A systematic review of behavioural marker systems in healthcare: What do we know about their attributes, validity and application? BMJ Quality & Safety, 23, 1031–1039. http://dx.doi.org/10.1136/bmjqs-2013-002457CrossRefGoogle ScholarPubMed
D’Innocenzo, L., Mathieu, J. E., & Kukenberger, M. R. (2016). A meta-analysis of different forms of shared leadership–team performance relations. Journal of Management, 42(7), 1964–1991. https://doi.org/10.1177/0149206314525205CrossRefGoogle Scholar
Elkins, A. N., Muth, E. R., Hoover, A. W., Walker, A. D., Carpenter, T. L., & Switzer, F. S. (2009). Physiological compliance and team performance. Applied Ergonomics, 40(6), 997–1003. http://dx.doi.org/10.1016/j.apergo.2009.02.002CrossRefGoogle ScholarPubMed
Funke, G. J., Knott, B. A., Salas, E., Pavlas, D., & Strang, A. J. (2012). Conceptualization and measurement of team workload: A critical need. Human Factors, 54(1), 36–51. http://dx.doi.org/10.1177/0018720811427901CrossRefGoogle ScholarPubMed
Fusaroli, R., Bjørndahl, J. S., Roepstorff, A., & Tylén, K. (2016). A heart for interaction: Shared physiological dynamics and behavioral coordination in a collective, creative construction task. Journal of Experimental Psychology: Human Perception and Performance, 42(9), 1297–1310. http://dx.doi.org/10.1037/xhp0000207Google Scholar
Gallup, A. C., Hale, J. J., Sumpter, D. J., Garnier, S., Kacelnik, A., Krebs, J. R., & Couzin, I. D. (2012). Visual attention and the acquisition of information in human crowds. Proceedings of the National Academy of Sciences, 109(19), 7245–7250. http://dx.doi.org/10.1073/pnas.1116141109CrossRefGoogle ScholarPubMed
Gorman, J. C., Hessler, E. E., Amazeen, P. G., Cooke, N. J., & Shope, S. M. (2012). Dynamical analysis in real time: Detecting perturbations to team communication. Ergonomics, 55(8), 825–839. http://dx.doi.org/10.1080/00140139.2012.679317CrossRefGoogle ScholarPubMed
Guastello, S. J. (2013). Chaos, catastrophe, and human affairs: Applications of nonlinear dynamics to work, organizations, and social evolution. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.CrossRefGoogle Scholar
Guastello, S. J. (2016). Physiological synchronization in a vigilance dual task. Nonlinear Dynamics, Psychology, and Life Sciences, 20(1), 49–80.Google Scholar
Guastello, S. J., Marra, D. E., Perna, C., Castro, J., Gomez, M., & Peressini, A. F. (2016). Physiological synchronization in emergency response teams: Subjective workload, drivers and empaths. Nonlinear Dynamics, Psychology, and Life Sciences, 20(2), 223–270.Google ScholarPubMed
Guastello, S. J., & Peressini, A. F. (2017). Development of a synchronization coefficient for biosocial interactions in groups and teams. Small Group Research, 48(1), 3–33. http://dx.doi.org/10.1177/1046496416675225CrossRefGoogle Scholar
Gully, S. M., Devine, D. J., & Whitney, D. J. (1995). A meta-analysis of cohesion and performance effects of level of analysis and task interdependence. Small Group Research, 26(4), 497–520. https://doi.org/10.1177/1046496495264003CrossRefGoogle Scholar
Hackman, J. R. (2003). Learning more by crossing levels: Evidence from airplanes, hospitals, and orchestras. Journal of Organizational Behavior, 24(8), 905–922. http://dx.doi.org/10.1002/job.226CrossRefGoogle Scholar
Halberstadt, J., Jackson, J. C., Bilkey, D., Jong, J., Whitehouse, H., McNaughton, C., & Zollmann, S. (2016). Incipient social groups: An analysis via in-vivo behavioral tracking. PloS ONE, 11(3), e0149880. http://dx.doi.org/10.1371/journal.pone.0149880CrossRefGoogle ScholarPubMed
Harrison, D. A., Mohammed, S., McGrath, J. E., Florey, A. T., & Vanderstoep, S. W. (2003). Time matters in team performance: Effects of member familiarity, entrainment, and task discontinuity on speed and quality. Personnel Psychology, 56(3), 633–669. http://dx.doi.org/10.1111/j.1744-6570.2003.tb00753.xCrossRefGoogle Scholar
Humphrey, S. E., & Aime, F. (2014). Team microdynamics: Toward an organizing approach to teamwork. Academy of Management Annals, 8(1), 443–503. http://dx.doi.org/10.1080/19416520.2014.904140CrossRefGoogle Scholar
Ilgen, D. R., Hollenbeck, J. R., Johnson, M., & Jundt, D. (2005). Teams in organizations: From input-process-output models to IMOI models. Annual Review of Psychology, 56, 517–543. http://dx.doi.org/10.1146/annurev.psych.56.091103.070250CrossRefGoogle ScholarPubMed
Isella, L., Romano, M., Barrat, A., Cattuto, C., Colizza, V., Van den Broeck, W., … Tozzi, A. E. (2011). Close encounters in a pediatric ward: Measuring face-to-face proximity and mixing patterns with wearable sensors. PloS ONE, 6(2), e17144. http://dx.doi.org/10.1371/journal.pone.0017144CrossRefGoogle Scholar
Knight, A. P., Kennedy, D. M., & McComb, S. A. (2016). Using recurrence analysis to examine group dynamics. Group Dynamics: Theory, Research, and Practice, 20 (3), 223–241. http://dx.doi.org/10.1037/gdn0000046CrossRefGoogle Scholar
Kozlowski, S. W. (2015). Advancing research on team process dynamics: Theoretical, methodological, and measurement considerations. Organizational Psychology Review, 5(4), 270–299. http://dx.doi.org/10.1177/2041386614533586CrossRefGoogle Scholar
Kozlowski, S. W., Chao, G. T., Chang, C. H., & Fernandez, R. (2015). Team dynamics: Using ‘‘big data’’ to advance the science of team effectiveness. Big data at work: The data science revolution and organizational psychology. New York, NY: Routledge Academic.Google Scholar
Kozlowski, S. W., Chao, G. T., Grand, J. A., Braun, M. T., & Kuljanin, G. (2013). Advancing multilevel research design: Capturing the dynamics of emergence. Organizational Research Methods, 16(4), 581–615. http://dx.doi.org/10.1177/1094428113493119CrossRefGoogle Scholar
Kozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to theory and research in organizations: Contextual, temporal, and emergent processes. In Klein, K. J. & Kozlowski, S. W. J. (Eds.), Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions (pp. 3–90). San Francisco, CA: Jossey-Bass.Google Scholar
Lazega, E., & Snijders, T. A. B. (Eds.). (2015). Multilevel network analysis for the social sciences: Theory, methods and applications (Vol. 12). New York, NY: Springer International Publishing.Google Scholar
Leenders, R. T. A., Contractor, N. S., & DeChurch, L. A. (2016). Once upon a time: Understanding team processes as relational event networks. Organizational Psychology Review, 6(1), 92–115. http://dx.doi.org/10.1177/2041386615578312CrossRefGoogle Scholar
LePine, J. A., Piccolo, R. F., Jackson, C. L., Mathieu, J. E., & Saul, J. R. (2008). A meta‐analysis of teamwork processes: Tests of a multidimensional model and relationships with team effectiveness criteria. Personnel Psychology, 61(2), 273–307. http://dx.doi.org/10.1111/j.1744-6570.2008.00114.xCrossRefGoogle Scholar
Levenson, R. W., & Gottman, J. M. (1983). Marital interaction: Physiological linkage and affective exchange. Journal of Personality and Social Psychology, 45(3), 587–597. http://dx.doi.org/10.1037/0022-3514.45.3.587CrossRefGoogle ScholarPubMed
Marks, M. A., Mathieu, J. E., & Zaccaro, S. J. (2001). A temporally based framework and taxonomy of team processes. Academy of Management Review, 26(3), 356–376. http://dx.doi.org/10.2307/259182CrossRefGoogle Scholar
McGrath, J. E. (1964). Social psychology: A brief introduction. New York, NY: Holt, Rinehart, and Winston.Google Scholar
Mehl, R. M. & Conner, T. S. (Eds.) (2012). Handbook of research methods for studying daily life. New York, NY: The Guilford Press.Google Scholar
Miller, G. (2012). The smartphone psychology manifesto. Perspectives on Psychological Science, 7(3), 221–237. http://dx.doi.org/10.1177/1745691612441215CrossRefGoogle ScholarPubMed
Mosier, K. L., & Chidester, T. R. (1991). Situation assessment and situation awareness in a team setting. In Queinnec, Y. and Daniellou, F. (Eds.), Designing for Everyone (pp. 798–800). London, UK: Taylor & Francis.Google Scholar
Moya‐Albiol, L., Andrés‐García, D., Sanchis‐Calatayud, M. V., Sariñana‐González, P., Ruiz‐Robledillo, N., Romero‐Martínez, Á., & González‐Bono, E. (2013). Psychophysiological responses to cooperation: The role of outcome and gender. International Journal of Psychology, 48(4), 542–550. http://dx.doi.org/10.1080/00207594.2012.666552CrossRefGoogle ScholarPubMed
Nowak, A., & Vallacher, R. R. (1998). Dynamical social psychology (Vol. 647). New York, NY: Guilford Press.Google Scholar
Olguín Olguín, D., Waber, B. N., Kim, T., Mohan, A., Ara, K., & Pentland, A. (2009). Sensible organizations: Technology and methodology for automatically measuring organizational behavior. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 39(1), 43–55. http://dx.doi.org/10.1109/TSMCB.2008.2006638CrossRefGoogle ScholarPubMed
Onnela, J. P., Waber, B. N., Pentland, A., Schnorf, S., & Lazer, D. (2014). Using sociometers to quantify social interaction patterns. Scientific Reports, 4, 5604. http://dx.doi.org/10.1038/srep05604Google Scholar
Orlitzky, M., & Hirokawa, R. Y. (2001). To err is human, to correct for it divine: A meta-analysis of research testing the functional theory of group decision-making effectiveness. Small Group Research, 32(3), 313–341. http://dx.doi.org/10.1177/104649640103200303CrossRefGoogle Scholar
Palumbo, R. V., Marraccini, M. E., Weyandt, L. L., Wilder-Smith, O., McGee, H. A., Liu, S., & Goodwin, M. S. (2017). Interpersonal autonomic physiology: A systematic review of the literature. Personality and Social Psychology Review, 21(2), 99–141. http://dx.doi.org/10.1177/1088868316628405CrossRefGoogle ScholarPubMed
Pentland, A., & Heibeck, T. (2010). Honest signals: How they shape our world. Cambridge, MA: MIT Press.Google Scholar
Robins, G., Snijders, T. A. B., Wang, P., Handcock, M., & Pattison, P. (2007). Recent developments in exponential random graph (p*) models for social networks. Social Networks, 29(2), 192–215. http://dx.doi.org/10.1016/j.socnet.2006.08.003CrossRefGoogle Scholar
Rosen, M. A., Dietz, A., Yang, T., Priebe, C. E., & Pronovost, P. J. (2015). An integrative framework for sensor-based measurement of teamwork in healthcare. Journal of the American Medical Informatics Association, 22(1), 11–18. http://dx.doi.org/10.1136/amiajnl-2013-002606CrossRefGoogle ScholarPubMed
Rosen, M. A., Schiebel, N., Salas, E., Wu, T., Silvestri, S., & King, H. (2012). How can team performance be measured, assessed, and diagnosed? In Salas, E. & Frush, K. (Eds.), Improving patient safety through teamwork and team training (pp. 59–79). New York, NY: Oxford University Press.Google Scholar
Salas, E., Dickinson, T. L., Converse, S. A., & Tannenbaum, S. I. (1992). Toward an understanding of team performance and training. In Swezey, R. W. & Salas, E. (Eds.), Teams: Their training and performance (pp. 3–29). Westport, CT: Ablex Publishing.Google Scholar
Schaubroeck, J., Lam, S. S., & Cha, S. E. (2007). Embracing transformational leadership: team values and the impact of leader behavior on team performance. Journal of Applied Psychology, 92(4), 1020. http://dx.doi.org/10.1037/0021-9010.92.4.1020CrossRefGoogle ScholarPubMed
Schmid Mast, M., Gatica-Perez, D., Frauendorfer, D., Nguyen, L., & Choudhury, T. (2015). Social sensing for psychology: Automated interpersonal behavior assessment. Current Directions in Psychological Science, 24(2), 154–160. http://dx.doi.org/10.1177/0963721414560811CrossRefGoogle Scholar
Schuller, B., & Batliner, A. (2013). Computational paralinguistics: Emotion, affect and personality in speech and language processing. West Sussex, UK: John Wiley & Sons.CrossRefGoogle Scholar
Smith-Jentsch, K. A., Cannon-Bowers, J. A., Tannenbaum, S. I., & Salas, E. (2008). Guided team self-correction: Impacts on team mental models, processes, and effectiveness. Small Group Research, 39(3), 303–327. http://dx.doi.org/10.1177/1046496408317794CrossRefGoogle Scholar
Stevens, R. H., Galloway, T., & Berka, C. (2007). EEG-related changes in cognitive workload, engagement and distraction as students acquire problem solving skills. In Conati, C., McCoy, K. & Paliouras, G. (Eds.), User modeling 2007. UM 2007. Lecture Notes in Computer Science, Vol. 4511. Berlin, Germany: Springer. https://doi.org/10.1007/978-3-540-73078-1_22Google Scholar
Stevens, R. H., Galloway, T. L., Wang, P., & Berka, C. (2012). Cognitive neurophysiological synchronies: What can they contribute to the study of teamwork? Human Factors, 54(4), 489–502. https://doi.org/10.1177/0018720811427296CrossRefGoogle Scholar
Stevens, R., Gorman, J. C., Amazeen, P., Likens, A., & Galloway, T. (2013). The organizational neurodynamics of teams. Nonlinear Dynamics, Psychology, and Life Sciences, 17(1), 67–86.Google ScholarPubMed
Strang, A. J., Funke, G. J., Russell, S. M., Dukes, A. W., & Middendorf, M. S. (2014). Physio-behavioral coupling in a cooperative team task: Contributors and relations. Journal of Experimental Psychology: Human Perception and Performance, 40(1), 145–158. http://dx.doi.org/10.1037/a0033125Google Scholar
Tesluk, P., Mathieu, J. E., Zaccaro, S. J., & Marks, M. (1997). Task and aggregation issues in the analysis and assessment of team performance. In Brannick, M. T., Salas, E., & Prince, C. W. (Eds.). Team performance assessment and measurement: Theory, methods, and applications (pp. 197–224). New York, NY: Taylor & Francis.Google Scholar
Tschan, F. (2002). Ideal cycles of communication (or cognitions) in triads, dyads, and individuals. Small Group Research, 33(6), 615–643. http://dx.doi.org/10.1177/1046496402238618CrossRefGoogle Scholar
Vinciarelli, A., Pantic, M., & Bourlard, H. (2009). Social signal processing: Survey of an emerging domain. Image and Vision Computing, 27(12), 1743–1759. http://dx.doi.org/10.1016/j.imavis.2008.11.007CrossRefGoogle Scholar
Walker, A. D., Muth, E. R., Switzer, F. S., & Rosopa, P. J. (2013). Predicting team performance in a dynamic environment: A team psychophysiological approach to measuring cognitive readiness. Journal of Cognitive Engineering and Decision Making, 7(1), 69–82. http://dx.doi.org/10.1177/1555343412444733CrossRefGoogle Scholar
Wild, J. (2017, February 28). Wearables in the workplace and the dangers of staff surveillance. Financial Times. Retrieved February 16, 2018, from https://www.ft.com/content/089c0d00-d739-11e6-944b-e7eb37a6aa8eGoogle Scholar
Woltman, H., Feldstain, A., MacKay, J. C., & Rocchi, M. (2012). An introduction to hierarchical linear modeling. Tutorials in Quantitative Methods for Psychology, 8(1), 52–69. http://dx.doi.org/10.20982/tqmp.08.1.p052CrossRefGoogle Scholar

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