Dataset of physiological, behavioral, and self-report measures from a group decision-making lab study

Area of Science:

• Psychology
• Social Psychology
• Human Behavior

Background:

• Group decision-making tasks are crucial for understanding social dynamics.
• Multimodal data collection offers a comprehensive approach to studying group interactions.

Purpose of the Study:

• To present a multimodal dataset integrating physiological, behavioral, and self-report measures from group decision-making.
• To facilitate future research, verification, and replication of group dynamics studies.

Main Methods:

• Sixty participants were organized into twenty groups of three for a "desert survival task."
• Physiological data (electrocardiogram, respiration, electrodermal activity) were collected simultaneously.
• Video recordings of group interactions were coded for positive affective behaviors; self-report measures (trait anxiety, social phobia) were also collected.

Main Results:

• The study successfully collected synchronized physiological, behavioral, and self-report data from groups.
• The dataset provides a rich resource for analyzing the interplay between individual differences and group performance.

Conclusions:

• This multimodal dataset is valuable for advancing the understanding of group dynamics.
• The integrated data allows for novel analyses and robust verification of findings in social psychology research.