The special issue “‘Capturing life as it is lived’—Ambulatory assessment for physical activity, sport and exercise” of the German Journal of Exercise and Sport Research aims to introduce the Ambulatory Assessment (AA) methodology into exercise, sport and movement science. In brief, AA enables to capture physical behavior data (on physical activity, sedentary behavior, and sleep) and its correlates in humans’ everyday life and in real-time, i.e., at any given moment.

AA describes a class of methods for data assessment to enable ecologically valid findings

AA is not a novel invention. Rather, the teaser of this special issue “‘Capturing life as it is lived’—Ambulatory assessment for physical activity, sport and exercise” is inspired by an pioneering AA paper published nearly 20 years ago (Bolger, Davis, & Rafaeli, 2003). Although researchers have applied AA for decades and mainly within psychological studies (e.g., Trull & Ebner-Priemer, 2013), it has just recently gained increasing interest within exercise, sport and movement science (e.g., Reichert et al., 2020b), with the association between physical activity and mood being one of the first research fields investigated by applying AA (e.g., Kanning & Schlicht, 2010; Liao, Shonkoff, & Dunton, 2015).

By definition, AA describes a class of methods for data assessment (and interventions) in near real-time and in real-world settings to enable ecologically valid findings (Society for Ambulatory Assessment, 2022). In particular, multiple data assessments across time and within subjects result in so-called intensive longitudinal data (ILD; e.g., Bolger, 2013; Conner & Mehl, 2015). For example, these data allow scientists to garner in-depth insights into within-person associations between physical behavior and behavioral, biological, physiological, as well as psychological factors in the everyday life of humans. Therefore, AA comprises methods such as physical activity monitoring (e.g., via Accelerometry; Burchartz et al., 2020; von Haaren-Mack, Bussmann, & Ebner-Priemer, 2021), physiological function assessment (e.g., via Mobile ElectroCardiogram; Ebner-Priemer & Kubiak, 2007), contextual sensing (e.g., via geolocation tracking; Tost et al., 2019), and self-reporting via e‑diaries (e.g., Ecological Momentary Assessment [EMA] and Experience Sampling Method [ESM]; Trull & Ebner-Priemer, 2009).

Translated to research practice, a prototypical AA study may therefore investigate associations between accelerometry-based physical activity and e‑diary-based self-reports. Since AA enables researchers to capture physical activity, sport and exercise “as it is” (real-time, real-life, etc.) and within a very broad range of research applications, this method is predestined to advance many subfields of exercise, sport, and movement science beyond traditional study formats. A small pretaste of the AA potential to move exercise, sport, and movement science forward is perfectly demonstrated by the various studies published in this special issue (Table 1). Therewith, the current special issue aims to provide a basis, for example, to combine expertise, to develop shared definitions and to further develop and validate AA in the field of exercise, sport, and movement science.

Table 1 Papers published in the special issue “‘Capturing life as it is lived’—Ambulatory assessment for physical activity, sport and exercise research”
Full size table

Of course, like other research methods, AA comes with challenges and limitations that, for example, comprise a time-consuming preprocessing of the ‘big data’, the need for advanced statistical methods such as multilevel models, and devices causing financial costs. However, we argue that the following AA advantages directly benefit research insights in exercise, sport, and movement science as shown by the papers published in this special issue:

  • Ecological validity of findings is increased through assessments in everyday life,

  • Biases of retrospective measurements and recall are decreased through the application of wearables such as smartphones, activity sensors and electronic diaries,

  • Within-person/intra-individual investigations across time are added to the traditional between-person/inter-individual level and can be analyzed simultaneously, for example, via multilevel modelling, and

  • Contextual factors (e.g., environmental exposures, social contexts) are considered through applying sensing methods such as geolocation-tracking

For the upcoming years, we are convinced that AA offers a huge potential for exercise, sport, and movement science even beyond the evident advantages described above. For example, AA can be combined with laboratory research to uncover (neuro)biological mechanisms (e.g., Reichert et al., 2020a), additional sensors can be embedded and advances in sensing technologies can be applied (von Haaren et al., 2016), triggered e‑diaries can help to optimize assessment strategies (Kanning, Niermann, Ebner-Primer, & Giurgiu, 2021), and ambulatory assessment interventions can enable the integration of experimental manipulation into everyday life (Heron & Smyth, 2010), just to name a few.