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Related Experiment Video

Updated: Jun 20, 2026

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

Analysis of communicative behaviour: profiling roles and activities.

Inger Dybdahl Sørby1, Øystein Nytrø

  • 1Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. inger.sorby@idi.ntnu.no

International Journal of Medical Informatics
|September 22, 2009
PubMed
Summary

This study introduces a novel method for analyzing clinician communication patterns using speech act sequences and radar graphs. The approach efficiently visualizes communicative behaviors, aiding in understanding variations and informing clinical system design.

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Assessment of Social Interaction Behaviors
06:41

Assessment of Social Interaction Behaviors

Published on: February 25, 2011

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Last Updated: Jun 20, 2026

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12:55

Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties

Published on: September 27, 2020

Assessment of Social Interaction Behaviors
06:41

Assessment of Social Interaction Behaviors

Published on: February 25, 2011

Area of Science:

  • Medical Informatics
  • Health Services Research
  • Clinical Communication Studies

Background:

  • Structured observation is crucial for understanding clinician information and communication activities.
  • Analyzing these activities can reveal patterns in healthcare settings.

Purpose of the Study:

  • To present a method for processing and visualizing clinician communication data.
  • To encode activities as speech acts and generate communicative behavior profiles.
  • To illustrate these profiles using radar graphs for analysis.

Main Methods:

  • Empirical data collected via observational study at a Norwegian university hospital.
  • A medical student observed physicians for 20 days, recording activities in various ward situations.
  • Data recorded using observation forms with codes and free-text, then post-processed into communicative act profiles and visualized as radar graphs.

Main Results:

  • Profiles of communicative behavior were generated for three individual physicians in different situations.
  • Radar graphs effectively visualized these communication patterns.
  • The method demonstrated efficiency in analyzing clinician information and communication.

Conclusions:

  • The presented approach is an efficient tool for studying clinician information and communication patterns in hospitals.
  • It can highlight variations among clinicians and compare different roles or wards.
  • Validated, this method could inform the design of new clinical information systems.