One of the challenges with traditional, laboratory research is that it does not translate data to real-world contexts, including times of day, geography, and other variables that impact human subjects’ lives. Therefore, there are limitations to how meaningful that data can be.
Fortunately, there is a research method that recognizes data provides better insights when it’s relevant to the day-to-day lives of the subjects.
The experience sampling method (ESM), or ecological momentary assessments (EMA), is the “real-time data collection of momentary experiences (thoughts, behaviors, emotions, contexts, events) that are typically expected to change in natural environments.”
The use of ESM for social science, workplace, and health research is growing at an incredible rate. More journals are publishing ESM and EMA studies. Many researchers in the social sciences and health sciences seek to apply this method in their research. And many are even seeking to replace regular one-off online surveys with this method.
Why is there such an interest in ESM?
Experience sampling overcomes survey problems.
ESM provides a great counterpoint to the issues many researchers face in utilizing online surveys, which ultimately improves the quality of the data they gather.
The Nobel Laureate Daniel Kahneman found that people’s positive or negative recollections of their experiences are affected by the peak intensity of the experience and the end of the experience (i.e., peak-end rule). People do not evaluate the whole of the experience or the duration, only the moments that stand out the most.
Therefore, asking people about their past experiences through online surveys will likely fail to capture their moment-to-moment information as experienced in real-time. On the other hand, ESM is designed to capture these experiences through thin slices of daily life.
Another problem is that researchers seek to study all aspects of a phenomenon so that they can analyze all variables that impact it. When this approach informs online survey development, it leads to unhelpfully long surveys. (Yes—we want to capture all the nuances of the experience regardless of the cost!)
Yet, long online surveys are known to cause survey fatigue, inattention, and even prompt participants to log out before completion. In the end, researchers obtain poor-quality data when participants are unable to fully engage with the survey.
ESM enables researchers to utilize micro-surveys over time to overcome trying to do it all in a single sitting making it a much easier experience for participants to give their full participation and attention.
Without understanding how behaviors, emotions, and self-perceptions interface with each other as well as how they evolve over time—temporal dynamics—researchers are unable to create a complete picture of the phenomena they study. The wonderful dynamic processes of human behaviors can only truly be understood through the use of experience sampling.
One-off online surveys do not reflect temporal dynamics and the unfolding of behaviors. Yes, researchers can ask questions about happiness and health in surveys. But how do they know if experiences of happiness occur before health behaviors or after?
By capturing these experiences in daily life through ESM, researchers can begin to understand the temporal dynamics of phenomena. In other words, we can learn how experiences change over time in the lives of people.
And importantly, we can understand it as they occur in everyday life; in people’s natural environments—where they live, where they work, who they interact with. For example, ESM is used to understand the experiences of hotel employees on a day-to-day basis providing valuable insights into employee turnover in a high-movement industry.
The fascinating thing about many psychological and medical interventions is that ongoing engagement by participants—consistency—leads to better outcomes.
Think of somebody brushing their teeth. They reap the benefits of the intervention when they continually engage in it in their daily life.
More researchers are recognizing this and pairing the use of experience sampling with daily momentary nudges. These small reminders help move people toward engaging in habits and behaviors that are helpful for them. Think of a portal for a medical practice that sends an email link to update insurance information ahead of an appointment.
Beyond nudges, ESM can enable context-awareness sensing to help prevent or promote behaviors. For example, sending reminders to individuals when they reach their homes to exercise.
With the proliferation of big data and data science approaches in the social sciences and health research, more researchers are seeking to integrate methods like passive sensing technologies into their data collection to enrich their understanding of participants.
With ESM technology, researchers can combine both passive sensed information (e.g. location, accelerometer data) and self-reported experiences throughout the day to validate data.
ESM self-reports can be used to interpret and validate the types of passively sensed behaviors.
For example, ESM technology may record vigorous movement from the accelerometer, but the individual could be exercising, arguing, or vacuuming. Researchers need timely self-report information from participants to understand the passively sensed behaviors and to build their next machine learning algorithm to track or predict behavior.
I developed the ESM platform ExpiWell to improve the experience for participants and researchers in order to enhance insights from behavioral and social research. ESM is the future of data collection because it has more expansive capabilities than one-off online surveys and positions data in everyday life, where it matters most.
Yet, there are many barriers for researchers conducting ESM, making it difficult for them to reap the many benefits of this innovative type of data collection.
For example, many researchers still rely on disjointed, inefficient systems to conduct ESM. Their research process may look like this:
With ExpiWell, ESM is a streamlined, user-friendly experience:
And through the free ExpiWell mobile app, researchers can have participants provide video, photo, and voice data while enabling geolocation data, capturing experiences immersively.
ExpiWell is a platform designed by social scientists, for social scientists.
Through the use of ExpiWell, ESM can reach its highest potential providing researchers with valid and rigorous data into the lived experiences of their human subjects.
Ready to learn more? Sign up to explore ExpiWell for free today!