Capturing lived experiences remotely: exploring the potential of audio diaries as an innovative qualitative data collection method in crisis contexts

Background: The COVID-19 pandemic disrupted traditional qualitative research methods, necessitating innovative approaches to data collection that avoided physical contact. Aim: To introduce and reflect upon audio diaries as a novel qualitative technique for capturing healthcare workers' lived experiences in crisis contexts. Methods: Healthcare professionals in Barcelona, Spain, recorded their thoughts, reflections, and concerns using WhatsApp audio notes. The study was conducted in two phases: the first during the initial pandemic wave (March-July 2020) and the second during a less restrictive period. Results: In the first phase, seven healthcare professionals provided 147 audio entries (2-10 minutes each). In the second phase, five professionals submitted 12 entries (26 seconds to 23 minutes). Audio diaries demonstrated several strengths, including efficiency, authenticity promotion, establishment of an informal therapeutic space, and the capturing of emotional content through voice tonality. Conclusion: Audio diaries offer a valuable alternative for collecting rich, transferable data in situations where traditional face-to-face techniques are not feasible, particularly in crisis contexts. This methodological innovation has implications for future qualitative research, especially in challenging or restricted environments.

Authors

Publication Details

Journal
Kontakt
Published
2025-02-05
DOI
https://doi.org/10.32725/kont.2025.005
Primary Topic
Qualitative Research Methods and Ethics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Capturing lived experiences remotely: exploring the potential of audio diaries as an innovative qualitative data collection method in crisis contexts

Serena Brigidi, Juan M. Leyva‐Moral
Kontakt
Qualitative Research Methods and Ethics
article

Capturing lived experiences remotely: exploring the potential of audio diaries as an innovative qualitative data collection method in crisis contexts

Serena Brigidi, Juan M. Leyva‐Moral
article en

Abstract

Background: The COVID-19 pandemic disrupted traditional qualitative research methods, necessitating innovative approaches to data collection that avoided physical contact. Aim: To introduce and reflect upon audio diaries as a novel qualitative technique for capturing healthcare workers' lived experiences in crisis contexts. Methods: Healthcare professionals in Barcelona, Spain, recorded their thoughts, reflections, and concerns using WhatsApp audio notes. The study was conducted in two phases: the first during the initial pandemic wave (March-July 2020) and the second during a less restrictive period. Results: In the first phase, seven healthcare professionals provided 147 audio entries (2-10 minutes each). In the second phase, five professionals submitted 12 entries (26 seconds to 23 minutes). Audio diaries demonstrated several strengths, including efficiency, authenticity promotion, establishment of an informal therapeutic space, and the capturing of emotional content through voice tonality. Conclusion: Audio diaries offer a valuable alternative for collecting rich, transferable data in situations where traditional face-to-face techniques are not feasible, particularly in crisis contexts. This methodological innovation has implications for future qualitative research, especially in challenging or restricted environments.

KontaktVol. 27(2)
Openalex Percentile: Top 97%
Qualitative Research Methods and Ethics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.