IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-031-13064-9_19.html
   My bibliography  Save this book chapter

Collecting Longitudinal Psychophysiological Data in Remote Settings: A Feasibility Study

In: Information Systems and Neuroscience

Author

Listed:
  • Sara-Maude Poirier

    (HEC Montréal)

  • Félix Giroux

    (HEC Montréal)

  • Pierre-Majorique Léger

    (HEC Montréal)

  • Frédérique Bouvier

    (HEC Montréal)

  • David Brieugne

    (HEC Montréal)

  • Shang-Lin Chen

    (HEC Montréal)

  • Sylvain Sénécal

    (HEC Montréal)

Abstract

Research methods to better understand the habituation process of individuals’ repeated task performance are constantly improving. However, data collection methods from a longitudinal perspective have been overlooked. Thus, the aim of this study is to explore the feasibility of collecting psychophysiological data remotely over several days. Through a five-days longitudinal study, behavioral data, facial emotions, and electrodermal activity were collected remotely. Behavioral results revealed that consumers tend to improve their performance in executing the tasks over time, regardless of their difficulty levels. Psychophysiological data showed that negative emotions were experienced by participants on Day 3 and tend to decrease on Day 5. Thus, it is possible that the novelty of the first remote session on Day 1 prevented participants from expressing negatives emotions even if they found the tasks difficult. This study highlights potential limitations of cross-sectional studies investigating the habituation process and validates the feasibility of conducting longitudinal psychophysiological data collection remotely in a naturalistic setting.

Suggested Citation

  • Sara-Maude Poirier & Félix Giroux & Pierre-Majorique Léger & Frédérique Bouvier & David Brieugne & Shang-Lin Chen & Sylvain Sénécal, 2022. "Collecting Longitudinal Psychophysiological Data in Remote Settings: A Feasibility Study," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Gernot (ed.), Information Systems and Neuroscience, pages 179-186, Springer.
    • Handle: RePEc:spr:lnichp:978-3-031-13064-9_19
    DOI: 10.1007/978-3-031-13064-9_19
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:lnichp:978-3-031-13064-9_19. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.