ILD umbrella terms
This article presents several umbrella terms that you are likely to encounter in the intensive longitudinal data (ILD) literature. These terms stem from different research traditions and therefore may refer to very similar—or even identical—selections of ILD collection methods. It is useful to know about these differences, although it is also important to realize that, as the field moves forward and disciplines interact with each other more, the usage of certain terms will continue to change.
Below, you can read about the following umbrella terms: 1) ecological momentary assessments; 2) ambulatory assessments; 3) real-time data capture; 4) active versus passive methods; 5) digital phenotyping; 6) e-diary assessments; and 7) mobile sensing.
1 Ecological momentary assessments (EMA)
The term ecological momentary assessment (EMA) is very popular in much of the ILD literature. It originates from health research (Stone & Shiffman, 1994), and was proposed to encompass all kinds of data collection methods that focus on assessing people in their natural setting while minimizing recall bias. EMA thus includes self-reports, but also physiological, physical, and/or environmental data.
When considering EMA based on self-report, the primary aim is to have participants “report repeatedly on their experiences in real-time, in real-world settings, over time and across contexts.” (p.3 Shiffman et al., 2008). Oftentimes, the data collection methods are described using the three categories that were distinguished by Wheeler & Reis (1991):
interval-contingent measurements, which are based on having measurement occasions that are equally spaced over time (e.g., daily diaries;
signal-contingent measurements, which are based on having random measurement occasions that are unequally spaced over time (i.e., like done in most experience sampling methodology studies);
event-contingent measurements, which are based on obtaining measurements when a specific event has taken place.
In practice the terms EMA and ESM are often used interchangeably (e.g., when people write EMA/ESM to refer to the various self-report techniques collectively). Originally, however, ESM only includes self-reports, whereas EMA also covers other data collection methods.
2 Ambulatory assessments (AA)
Another term that you are likely to encounter is ambulatory assessment (AA), which is defined as “assessment methods to study people in their natural environment, including self-report, observational, and biological/physiological/behavioral.” (p.152 Trull & Ebner-Priemer, 2013). Hence it can be considered synonymous to EMA (in its broad meaning). It places strong emphasis on measuring people in real-time and in real-life to ensure high ecological validity.
The popularity of the term AA is in part due to it being used by the Society for Ambulatory Assessment (SAA) as the collective, encompassing term for all the different branches of research that they include in their activities.
3 Real-time data capture
Real-time data capture is a term that is not that common in the literature, although it serves a rather prominent role in the title of the book edited by Stone et al. (2007): “The Science of Real-Time Data Capture: Self-Reports in Health Research”. This title suggests a focus on self-report, and many of the chapters focus indeed on self-report data. But in its closing chapter, Stone (2007) explicitly indicates that he considers real-time data capture and EMA synonyms. This implies not only self-reports, but also many other data collection methods are covered by the term real-time data capture, including ambulatory monitoring of blood pressure, glucose, heart rate, and motion.
4 Active versus passive methods
Conner & Lehman (2012) distinguish between active and passive methods in ambulatory assessment. Active measurements require participants to actively provide measurements, such as self-reports, but also some of the physiological data collection methods (e.g., obtaining saliva samples to measure cortisol levels). Another form of active measurement is formed by the cognitive tasks, which have been used to measure mental processes throughout daily life.
Passive assessment include all the data collection methods that do not require specific action by the participant at the moment of measurement. It merely requires the participant to carry a specific device (e.g., a smart watch) while they go about their daily life, or to allow researchers to access data from the devices they are already carrying and using.
As with EMA and AA described above, the terms active and passive methods tends to be specifically used for measurements obtained from everyday life. This would render it inappropriate for the collection of similar ILD in a lab setting.
5 Digital phenotyping
The term digital phenotyping was coined by Torous et al. (2016) to cover both active and passive data collection methods through wearables. Specifically, they define it as “moment-by-moment quantification of the individual-level human phenotype in-situ using data from smartphones and other personal digital devices” (p.2 Torous et al., 2016). They argue that phone use and sensors provide valuable information about social and behavioral patterns that are relevant for psychiatric and neurological diseases.
Digital phenotyping is a slightly more narrow term than the terms EMA, AA, and real-time data capture, because it is restricted to measurements obtained through a person’s own digital device, typically a smartphone. Hence paper and pencil questionnaires or saliva measures would not be considered part of digital phenotyping. Yet, collecting data with a wearable device (e.g., a smartwatch) that is temporarily provided to participants for the duration of the study, is currently considered a form of digital phenotyping (Siepe et al., 2025).
6 e-Diary assessments
The term e-diary assessment has been coined for self-reports (Ebner-Priemer & Santangelo, 2024). The term e-diary emphasizes that the diaries are administered and recorded using some kind of electronic device, such as a smartphone. This implies that paper versions—which are nowadays mostly outdated anyway—are not covered by this term.
7 Mobile sensing
Harari et al. (2023) define the term mobile sensing as: “[…] a methodological approach that leverages digital devices and platforms to collect data about human behavior.” (p.3). Behaviors that are measured through mobile sensing may include social interactions a person engages in, their phone use, their physical activity levels, or their location and movement. The focus tends to be on objective aspects of behaviors (e.g., number of social interactions, number of hours spent sleeping), rather than the subjective aspects of these behaviors (e.g., quality of a social interaction or sleep).
The book Mobile Sensing in Psychology: Methods and Applications edited by Mehl et al. (2024) also includes chapters on physiological data (e.g., heart rate and other features of the autonomous nervous system; see de Geus & Gevonden (2024)), as well as environmental features (e.g., location, sound, and light). Hence, the term is used more broadly than the definition provided by Harari et al. (2023). While mobile sensing can be combined with self-report techniques to investigate the relation between these objective measurements and subjective thoughts and feelings, the self-reports themselves are not considered part of mobile sensing (Ebner-Priemer & Santangelo, 2024).
8 Think more about
From the above, you can see that many of the umbrella terms tend to overlap. This is because these terms have emerged from different fields, which have overlapping foci.
The majority of the umbrella terms focus exclusively on data collection methods that are applied in a natural setting: It stresses an interest in measuring people in real-time and in real-life, in their natural habitat, or “in situ”. Although many of these methods tend to result in a large number of repeated measurements per person, this is not necessarily the case; hence, these terms may also be used occasionally to refer to data that would not be considered ILD.
You can use the umbrella term ILD collection methods to emphasize the practical outcome of the data collection technique that is chosen: Data that are characterized by repeated measures from one or more cases across many occasions. Whether such data are obtained with passive or active assessments, whether the measurements are objective or subjective, and whether the observations are obtained from people in their natural habitat or in a controlled lab setting, can be considered important features of such data, but these are not used as in- or exclusion criterion.
9 Takeaway
When you read in the ILD literature, you are likely to encounter various terms that point to specific forms of data and data collection methods. Some of the names are synonyms stemming from different research traditions, whereas other names only partly overlap. It is useful to have some knowledge about this terminology and how specific terms relate to each other, as it helps to see what others are referring to.
It is good to keep in mind that the umbrella terms presented in this article are not an exhaustive list of all currently available ILD umbrella terms. Moreover, with ongoing advancements in data collection techniques, the terminology is likely to expand further.
10 Further reading
We have collected various topics for you to read more about below.
- ILD collection methods
- [Ecological momentary assessment versus ecological retrospective assessment]
- [Active versus passive sensing]
- [Retrospective, ecological retrospective, and ecological momentary assessment]
- [Remembering versus experiencing self]
- [Designing a measurement instrument to target between-person or within-person variance]
- [Measurement burst designs]
- [Event contingent bursts]
Acknowledgments
This work was supported by the European Research Council (ERC) Consolidator Grant awarded to E. L. Hamaker (ERC-2019-COG-865468).
References
Citation
@article{hamaker2026,
author = {Hamaker, Ellen L. and Hoekstra, Ria H. A.},
title = {ILD Umbrella Terms},
journal = {MATILDA Preprints},
number = {2026-06-05},
date = {2026-06-05},
url = {https://matilda.fss.uu.nl/articles/ild-umbrella-terms.html},
langid = {en}
}