Thoughts on experience sampling and I/O Psychology

Best Practices for Experience Sampling Methodology

By Dr. Louis Tay

Fields across academia, employee engagement, customer experience, product innovation, healthcare, and beyond are all trending toward understanding the everyday experiences of people. Literature on capturing experience data, or Experience Sampling Methodology (ESM), has grown exponentially over the past years. The volume of information out there today can be overwhelming! There are key questions that should be considered when considering experience sampling research:

  • What are the practical issues and considerations when conducting an ESM or EMA study?
  • What are some of the trends in ESM and EMA?
  • How should one analyze ESM and EMA data?
  • How can platforms, such as Expimetrics, be used to implement an ESM or EMA study?
  • What is the history of Experience Sampling Methodology (ESM) or Ecological Momentary Assessment (EMA)?

In this video webinar, I provide answers to all these key questions and more. The goal is to show how to effectively apply ESM and EMA and generate more meaningful insights!

The Experience Sampling Method (ESM) in the Social Sciences

By Dr. Louis Tay

The Experience Sampling Method (ESM) was introduced in the late 1970s by Mihalyi Csikszentmihalyi and colleagues [1]. It is a systematic approach for capturing experiences and activities of individuals in their ecological context. The ESM was groundbreaking. Social scientists have since recognized the importance of the ESM because much of what makes scientific principles generalizable and applicable is through examining and evaluating it in our day-to-day lives.

Tremendous Growth.

Not surprisingly then, there has been a surge of Experience Sampling methodology and design in the social sciences. A quick search on Google Scholar on this topic (“experience sampling”) reveals an exponential increase in the numbers of papers referencing ESM. There has been roughly a five-to-six fold increase in the numbers of academic papers using ESM every decade.

1980-1990: 280 papers

1991-2000: 1,190 papers

2001-2010: 7,810 papers

2010-2016: 16,000 papers

Research Applications.

What types of research questions can be examined using ESM and extensions of ESM? The following represents only a small but fascinating sample of research topics that are now enabled by ESM.

  • Education: There is a growing interest in understanding student experiences in and outside of the classroom. ESM can serve to understand flipped classroom experiences, along with daily activities experienced at home, etc.
  • Clinical: Researchers seek to track daily feelings/behaviors and understand the situational triggers that may affect feelings/behaviors.
  • Marketing: Researchers wish to determine how individuals interact with the product even after the point of purchase over multiple occasions.
  • Organizations: Researchers are keen on examining mean levels and variability of emotions of employees as it can have an impact on job performance and motivation.
  • Politics: Researchers can be enabled to determine how political attitudes and choices change over time in an election cycle.
Practical Applications.

Technology-enabled ESM is exciting because we can not only gather information for research purposes but also immediate information that can be used to make practical key decisions within an educational institution, political campaign, or an organization. Further, such a platform can serve to provide feedback to respondents in a timely fashion. Here are some potential applications.

  • Education: As educators have become increasingly interested in formative assessments, the ESM can be also harnessed to provide quick and immediate feedback to students to build skills, habits, and character.
  • Clinical: Through ESM technology, clinicians can not only track the feelings and behaviors of clients but also provide insights and feedback to clients throughout the week.
  • Marketing: Instead of bringing product testers on-site which is expensive, companies can test products in-situ and capture how clients interact with products over time in their environment.
  • Organizations: Human resources and managers can obtain a regular pulse of their employees on different dimensions such as engagement, stress, burnout; these can also be examined as a function of new company policies.
  • Politics: The ESM can not only examine how voters react to political speeches but track intentions and behaviors (other social media mobile apps) over time.
New Frontiers.

Past ESM used pen-and-paper methods; these provide important information. However, with Expimetrics, we are now providing a seamless integration between web (survey creators) and mobile (participants) apps. This enables us to gather new insights, enhance interactivity between survey creators and participants, and promote a more rigorous approach to science and practice. There are new frontiers of technology-enabled ESM that I am pursuing with Expimetrics that will open new doors for research and practice.

  • Including multimedia data (voice, video, location) into our research designs and analysis
  • Using location-enabled surveys
  • Locating participants that fit a demographic criterion
  • Integrating with health information (e.g., fitbit)
  • Ongoing push notifications from survey creators
  • Proprietary HR tools for business

I hope that more social scientists will see the value of ESM and join Expimetrics in using and refining this exciting method. Please feel free to contact me at should you be interested or have any questions.


1. Csikszentmihalyi M, Larson R, Prescott S: The ecology of adolescent activity and experience. Journal of Youth and Adolescence 1977, 6:281-294.

Differences between Experience Sampling Methodology (ESM) and Ecological Momentary Assessment (EMA)

By Dr. Louis Tay

Aspects of Ecological Validity Focus on Representativeness

Representative Activities

Representative Subjective Experience
Focus on Momentariness

Momentary Activities

Momentary Subjective Experience
Analytic Focus Frequencies of activities

General psychological levels across and within activities (e.g., motivation, mood)
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)
When are surveys taken? Representativeness-focus; general activities and experiences over the day and days

Time-contingent (i.e., regular timed surveys)

Signal-contingent (i.e., whenever a notification is sent)
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)
Mode of Data/ReportingSelf-reported experience-related surveysGenerally any type of self-reported surveys; also includes health data, physical data, etc.

Researchers often use the terms ESM and EMA interchangeably, referring to studies where survey data (and other types of data) are collected on multiple occasions within the day and over time. However, there are also subtle, if not substantial, differences when we examine the historical motivations behind ESM and EMA.


One of the goals of psychology historically has been to advance the understanding of people in their everyday contexts. Donald Fiske (1971) described how one of the major goals of psychology is 'to measure ... the ways a person usually behaves, the regularities in perceptions, feelings, and actions'

Out of this motivation to capture representative activities and experiences, ESM was developed. One of the first applications of this method was on an adolescent sample by Mihaly Csikzentmihalyi, Reed Larson, and Suzanne Prescott. Interestingly, the goal was to understand 'What do adolescents do all day long?', 'What motivates them to engage in these activities?', and 'What are their psychological responses to these activities?'

ESM grew out of this tradition and the focus has primarily been on representativeness of activities and experiences in a population of interest in their natural environments.


As developed by Arthur Stone and colleagues, EMA developed later and grew from the tradition of clinical and health psychology. In the former, this was motivated by behavior therapy and self-monitoring, where the goal was to have participants actively monitor their a specific set of behaviors in a repeated fashion. This included aspects such as addictive behaviors (e.g., smoking) or dysfunctional behaviors (e.g., conflict) in order to address them. In the latter, it was inspired by ambulatory assessments within health settings (e.g., blood pressure monitoring).

Therefore, while ESM focuses on representativeness, EMA focuses on the dynamic unfolding of behaviors in natural environments.


At Expimetrics, we use the term ESM for the historical flavor, reflecting early studies seeking to capture repeated survey data within participants using the aid of technology. However, we use this to refer to all types of ESM and EMA studies, and broadly different types of longitudinal studies.

To aid researchers, I am providing a summary Table seen above which organizes and delineates the differences between ESM and EMA.

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