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Best practices for Electronically Activated Recorder (EAR) research: A practical guide to coding and processing EAR

Deanna M Kaplan1, Kelly E Rentscher2, Maximilian Lim3

  • 1Department of Psychology, University of Arizona, Tucson, AZ, USA. deannamkaplan@email.arizona.edu.

Behavior Research Methods
|January 4, 2020
PubMed
Summary
This summary is machine-generated.

The Electronically Activated Recorder (EAR) method captures daily social behavior. This article details best practices for coding EAR audio data, enhancing its use in research.

Keywords:
Ambulatory assessmentBehavioral observationEcological momentary assessmentNaturalistic observationSmartphone sensing

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Area of Science:

  • Psychology
  • Behavioral Science
  • Social Science

Background:

  • The Electronically Activated Recorder (EAR) method, established in 2001, is widely used for naturalistic observation of social behavior.
  • Prior research focused on EAR's measurement, design, and data properties, neglecting the critical audio data coding process.
  • Coding procedures for EAR data have largely been shared informally among researchers.

Purpose of the Study:

  • To document and disseminate "best practices" for processing Electronically Activated Recorder (EAR) data.
  • To provide practical guidance on the EAR data coding process, refining existing informal communication.
  • To standardize and improve the quality of quantitative behavioral data derived from EAR recordings.

Main Methods:

  • Documenting "best practices" for EAR data processing, refined through extensive research.
  • Focusing on the critical coding stage: converting ambient sounds into quantitative behavioral data.
  • Addressing key aspects of the coding workflow, from system development to data preparation.

Main Results:

  • Provides a comprehensive guide to EAR data coding, including system development and coder training.
  • Offers solutions for common coding challenges and considerations for diverse populations.
  • Establishes a framework for optimizing EAR data preparation and database management.

Conclusions:

  • Standardized coding practices are essential for maximizing the utility of the EAR method in research.
  • This article offers practical, tested guidelines to improve the reliability and validity of EAR-derived behavioral data.
  • Disseminating these best practices will enhance the application of the EAR method across various scientific disciplines.