New developments in experience sampling methodology

Area of Science:

• Psychological Science
• Behavioral Science
• Methodology

Background:

• Experience Sampling Methodology (ESM) is a powerful tool for studying real-life experiences.
• Its widespread adoption necessitates methodological updates.
• Recent advancements focus on improving data collection and analysis in ESM studies.

Purpose of the Study:

• To provide a comprehensive overview of recent methodological advancements in ESM.
• To discuss innovations in ESM design, statistical analysis, and implementation.
• To highlight the application of these advancements in studying affect in daily life.

Main Methods:

• Review of recent literature on ESM design, statistical analysis, and implementation.
• Discussion of self-report measures, mobile sensing, burst designs, and sample size planning.
• Exploration of non-linear models, survival analysis, real-time monitoring, open science, and data preprocessing.

Main Results:

• Recent ESM developments enhance the reliability and validity of collected data.
• Advanced statistical techniques offer deeper insights into time-series and time-to-event data.
• Improved implementation strategies facilitate open science and efficient data handling.

Conclusions:

• Methodological advancements are crucial for maximizing the potential of ESM.
• These innovations support more robust and insightful research into daily life phenomena.
• The discussed methods are broadly applicable, with a focus on affect research.