In real-time data collection research, the terms Experience Sampling Method (ESM) and Ecological Momentary Assessment (EMA) are often used interchangeably. These methodologies involve collecting survey data—and other data types—multiple times throughout the day and across different days.
Despite their similarities, nuanced distinctions are rooted in their historical development and primary objectives. Comparing ESM and EMA methodologies for research studies can empower researchers to choose the appropriate method for their study objectives.
1) The experience sampling method (ESM) focuses on capturing typical behaviors and experiences in natural settings that stem from its roots in traditional psychology. At the same time, ecological momentary assessment (EMA) is more concerned with the real-time monitoring and adjustment of specific behaviors originating from clinical and health psychology contexts.
2) The experience sampling method (ESM) aims to provide a representative overview of a population's everyday activities and psychological states, making it suitable for broad behavioral studies. In contrast, EMA targets the dynamic tracking of behaviors and psychological conditions, ideal for more focused clinical assessments.
3) Methodologically, The experience sampling method (ESM) typically employs self-reported experience-related surveys. At the same time, EMA can include various data types, such as health metrics and event-triggered responses, offering a more granular view of subjects' states and actions.
Historically, the discipline of psychology has sought to comprehend human behavior within everyday contexts. Donald Fiske (1971) emphasized the importance of measuring individuals' typical behaviors, perceptions, and actions. Emerging from this ambition to encapsulate real-life experiences, ESM was conceptualized.
Pioneers such as Mihaly Csikszentmihalyi, Reed Larson, and Suzanne Prescott applied ESM in their adolescent studies to answer pressing questions about their daily activities, motivations, and psychological responses to these activities. ESM is rooted in the aim to represent activities and experiences authentically within a target population's natural setting.
Developed by Arthur Stone and his colleagues, EMA originated from clinical and health psychology. Behavior therapy and the practice of self-monitoring were significant motivators, aiming to help participants consistently track specific behaviors—such as addictive or dysfunctional actions—with the intent to modify them.
Health psychology contributed through the practice of ambulatory assessments (e.g., blood pressure monitoring) to capture the dynamic nature of behaviors as they unfold naturally.
Hence, while ESM is centered on representativeness, EMA experience is more concerned with the real-time evolution of behaviors in natural environments.
In summary, while both methods gather real-time data, ESM seeks to document life as it happens. In contrast, EMA aims to monitor and influence specific behaviors for research and clinical purposes.
READ MORE: EMA Strategies: Boosting Accuracy in Behavioral Science Research
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At ExpiWell, we prefer the term experience sampling method to honor the methodology's historical roots. This term reflects the initial studies that utilized technology to capture repeated survey data within participants.
Nonetheless, this term encompasses a broader range of studies, including all variations of ESM and EMA, as well as diverse longitudinal research.
There are some key differentiators and four dimensions that can help you differentiate Experience Sampling Method vs Ecological Momentary Assessment in research.
ESM: Focuses on representativeness, representative activities, representative subjective experiences
EMA: Focus on momentariness, momentary activities, momentary subjective experiences
ESM: Frequencies of activities; general psychological levels across and within activities (e.g., motivation, mood)
EMA: Trajectories of psychological phenomena; dispersion of psychological phenomena over time (e.g., positivity spirals); dynamics of psychological phenomena (i.e., how one dimension relates to another over time)
ESM: Representativeness-focus; general activities and experiences over the days and weeks; time-contingent (i.e., regular timed surveys); signal-contingent (i.e., whenever a notification is sent)
EMA: Phenomenon-focus; measuring appropriate intervals to assess changes in psychological phenomena; time-contingent (i.e., regular timed surveys); signal-contingent (i.e., whenever a notification is sent); event-contingent (i.e., whenever an event occurs)
ESM: Self-reported experience-related surveys
EMA: Generally, any type of self-reported survey includes health data, physical data, relational data, work data, etc.
To assist researchers in easily distinguishing between these two methodologies, we provide a summary table below that outlines their differences. This resource is designed to help clarify which method may be best suited for various research objectives.
With the four dimensions above, you can also think of it this way:
So, using as this guide, how would you know if ESM or EMA experience is the right research method for your study?
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Here are the five practical scenarios to help you differentiate the difference between ESM and EMA and how you can use to make your data collection more efficient.
Method: ESM
Goal: You want to understand typical emotions and daily routines of college students, including their average happiness or stress. If this is the case, you can use ESM to monitor your participant’s natural behavior in natural setting.
Study Example: Analysis On The Association Between Well-Being And Disclosure Transformations Among College Students Post-Pandemic.
This study investigates how social disclosures (i.e., how students share personal information and connect with others) changed before, during, and after the COVID-19 pandemic, and whether these changes affected well-being and feelings of connection.
Method: EMA
If your goal is tracking how anxiety changes day-to-day, EMA is ideal because it allows tracking immediate changes and responses over time.
Study Example: Eco-anxiety in daily life: Relationships with well-being and pro-environmental behavior.
This study examines eco-anxiety (anxiety and worry about environmental issues) and how it fluctuates in daily life while influencing well-being (happiness, meaning in life) and pro-environmental behavior (actions taken to help the environment).
Method: ESM
For broadly understanding everyday job satisfaction, ESM is the most appropriate method as it aims to represent typical experiences and behaviors.
Study Sample: Subjective Experience, Job Satisfaction, and Professional Actions of Music Teachers as a Predictor of Flow State.
This study investigates how job satisfaction and preparedness influence flow states (a psychological state of being fully immersed in an activity) among music teachers. It applies Csikszentmihalyi’s theory of flow, which describes different mental states based on the balance between challenge and skill (e.g., optimal flow, stress/anxiety, relaxation, boredom).
Method: EMA
When the focus is on a specific behavior (like smoking) and its triggers or patterns, EMA is best since you can capture events and their immediate contexts.
This pilot study explores the feasibility of using Ecological Momentary Assessment (EMA) via smartphones to track how often Canadian adolescents are exposed to cannabis marketing, their reactions to these exposures, and the context in which these exposures occur in real life.
Method: ESM
If your goal is to understand common human behavior like mind wandering without focusing on a specific intervention, ESM would provide the most representative insights.
This study investigates mind wandering—the experience of thoughts drifting away from the current task—in the daily lives of working adults (ages 25–50) across the U.S. Unlike previous research that mostly focused on university students in lab settings, this study explores real-world mind-wandering experiences using the Experience Sampling Method (ESM).
You can use these five examples to help you learn the difference between ESM and EMA for better research method understanding.
Understanding the differences between ESM and EMA can significantly impact the design and outcomes of research studies. By choosing the correct method, researchers can obtain more accurate and representative data, leading to more effective interventions and understanding of behaviors in real-world contexts.
ExpiWell’s real-time data collection tool utilizes ESM best practices to understand your audience better.
Please feel free to contact sales@expiwell.com should you be interested or have any questions. Also, if you need help with your EMA research, visit Expiwell to learn more about how you can utilize it. You can also email sales@expiwell.com for a FREE consultation.
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