Utilizing a Matrix Approach to Analyze Qualitative Longitudinal Research: A Case Example During the COVID-19 Pandemic.

Autor: Terzis LD; School of Social Work, Tulane University, New Orleans, LA, USA., Saltzman LY; School of Social Work, Tulane University, New Orleans, LA, USA., Logan DA; School of Social Work, Tulane University, New Orleans, LA, USA., Blakey JM; School of Social Work, University of Minnesota, Minneapolis, MN, USA., Hansel TC; School of Social Work, Tulane University, New Orleans, LA, USA.
Jazyk: angličtina
Zdroj: International journal of qualitative methods [Int J Qual Methods] 2022 Sep 03; Vol. 21, pp. 16094069221123723. Date of Electronic Publication: 2022 Sep 03 (Print Publication: 2022).
DOI: 10.1177/16094069221123723
Abstrakt: Qualitative Longitudinal Research (QLR) is an evolving methodology used in understanding the rich and in-depth experiences of individuals over time. QLR is particularly conducive to pandemic or disaster-related studies, where unique and rapidly changing environments warrant fuller descriptions of the human condition. Despite QLR's usefulness, there are a limited number of articles that detail the methodology and analysis, especially in the social sciences, and specifically social work literature. As researchers adjust their focus to incorporate the impact of the COVID-19 global pandemic, there is a growing need in understanding the progression and adaptation of the pandemic on individuals' lives. This article provides a process and strategy for implementing QLR and analyzing data in online diary entries. In the provided case example, we explore a phenomenological QLR conducted with graduate level students during the COVID-19 pandemic (Saltzman et al., 2021) , and outline a matrix framework for QLR analysis. This paper provides an innovative way in which to engage in qualitative data collection and analysis for social science research.
Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
(© The Author(s) 2022.)
Databáze: MEDLINE
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