Sensemaking about HRV data of high performing individuals: Crafting a mixed methods study

Nathalie Mitev, Stefan Klein and Stefan Schellhammer
Additional contact information
Nathalie Mitev: DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Stefan Klein: DLR Institut für Materialphysik im Weltraum - DLR - Deutsches Zentrum für Luft- und Raumfahrt [Köln], BIG - Biomedical Imaging Group [Rotterdam] - Erasmus MC - Erasmus University Medical Center [Rotterdam]

Post-Print from HAL

Abstract: In collaboration with the HR team of a large IT service provider, we have studied 50 individuals, who have been identified as high performers by their employer. We have been looking for indicators and patterns of sustainable high performance and asked the study participants as an introductory question: "In your own opinion: will you be able to keep your current pace of work for the next five years?" Our research design consisted of initial interviews at a virtual day, attendance of 2.5 day off-site coaching workshops and > 60 min follow-up interviews. During the workshop days, we collected 24h heart rate variability (HRV) measurements, a well-established biomarker of wellbeing, strain and recovery. As HRV data are difficult to analyse without contextual information, we combined interviews, focus-group sessions, participatory observation and debriefing interviews in order to contextualize the quantitative measurements and involve the participants in the interpretation and sensemaking of the findings. The methodological goal of this paper is to demonstrate that and how orchestrating, improvising and performing a mixed-method study has been essential to validate, augment and complement quantitative data. The study results depend on the ability of the researchers to skilfully and empathetically engage with the interviewees and to engage them as participants in the interpretation of their data and thus as co-producers of meaning.

Keywords: Mixed method; Algorithmic data analysis; Qualitative sense-making; Salutogenesis; High performance work (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Published in The Cambridge Handbook of Qualitative Digital Research, Cambridge University Press, pp.229-246, 2023, 9781009106436. ⟨10.1017/9781009106436.019⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04222837

DOI: 10.1017/9781009106436.019

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().