survey

The Experience Sampling Method on Mobile Devices

Authors:

Niels van Berkel,

Denzil Ferreira,

Vassilis KostakosAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 50, Issue 6

Article No.: 93, Pages 1 - 40

https://doi.org/10.1145/3123988

Published: 06 December 2017 Publication History

Abstract

The Experience Sampling Method (ESM) is used by scientists from various disciplines to gather insights into the intra-psychic elements of human life. Researchers have used the ESM in a wide variety of studies, with the method seeing increased popularity. Mobile technologies have enabled new possibilities for the use of the ESM, while simultaneously leading to new conceptual, methodological, and technological challenges. In this survey, we provide an overview of the history of the ESM, usage of this methodology in the computer science discipline, as well as its evolution over time. Next, we identify and discuss important considerations for ESM studies on mobile devices, and analyse the particular methodological parameters scientists should consider in their study design. We reflect on the existing tools that support the ESM methodology and discuss the future development of such tools. Finally, we discuss the effect of future technological developments on the use of the ESM and identify areas requiring further investigation.

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McFerran KKrause AOsborne M(2025)Exploring the feasibility of collecting music and wellbeing data to examine intentional listening using a mobile-ESM applicationFrontiers in Psychology10.3389/fpsyg.2025.150592916Online publication date: 28-Feb-2025
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Index Terms

The Experience Sampling Method on Mobile Devices
1. General and reference
  1. Document types
    1. Surveys and overviews
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. Field studies
      2. User studies
  2. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing design and evaluation methods
    2. Ubiquitous and mobile devices

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 50, Issue 6

November 2018

752 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3161158

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Sartaj Sahni
Department of Computer and Information Science and Engineering / University of Florida / Gainesville, FL

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Published: 06 December 2017

Accepted: 01 July 2017

Revised: 01 June 2017

Received: 01 September 2016

Published in CSUR Volume 50, Issue 6

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https://doi.org/10.3389/fpsyg.2025.1505929
Klein Haneveld LDekkers TBouman YScholten HWeerdmeester JKelders SKip H(2025)The Effect of the Virtual Reality–Based Biofeedback Intervention DEEP on Stress, Emotional Tension, and Anger in Forensic Psychiatric Inpatients: Mixed Methods Single-Case Experimental DesignJMIR Formative Research10.2196/652069(e65206)Online publication date: 12-Feb-2025
https://doi.org/10.2196/65206
Poppe LDe Paepe ADeforche BVan Dyck DLoeys TVan Cauwenberg J(2025)Experience sampling method studies in physical activity research: the relevance of causal reasoningInternational Journal of Behavioral Nutrition and Physical Activity10.1186/s12966-025-01723-w22:1Online publication date: 5-Mar-2025
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Volsa SLewetz DMlakic VBertagnoli CHochstöger SRechl MSertic HBatinic BStieger S(2024)Development of an open-source solution to facilitate the use of one-button wearables in experience sampling designsBehavior Research Methods10.3758/s13428-023-02322-y56:6(5876-5899)Online publication date: 17-Jan-2024
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Schetter ESchwinger M(2024)What Triggers Mental Disorders? Examining the Role of Increasing Relationships between Self-Regulatory Efficacy Expectations and Behavioral IntensityPsychiatry International10.3390/psychiatryint50400485:4(672-696)Online publication date: 9-Oct-2024
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