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@ARTICLE{Depasquale:603118,
author = {Depasquale, Etienne-Victor and Salam, Humaira Abdul and
Davoli, Franco},
title = {{PAD}: {A} graphical and numerical enhancement of
structural coding to facilitate thematic analysis of a
literature corpus},
journal = {MethodsX},
volume = {9},
issn = {2215-0161},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {PUBDB-2024-00763},
pages = {101633},
year = {2022},
abstract = {We suggest an enhancement to structural coding through the
use of (a) causally bound codes, (b) basic constructs of
graph theory and (c) statistics. As is the norm with
structural coding, the codes are collected into categories.
The categories are represented by nodes (graph theory). The
causality is illustrated through links (graph theory)
between the nodes and the entire set of linked nodes is
collected into a single directed acyclic graph. The number
of occurrences of the nodes and the links provide the input
required to analyze relative frequency of occurrence, as
well as opening a scope for further statistical analysis.
While our raw data was a corpus of literature from a
specific discipline, this enhancement is accessible to any
qualitative analysis that recognizes causality in its
structural codes. Through our work, we claim: • To extend
the semantic potential of structural coding, where the
structural codes are causally related, and • To extend the
methodological scope of systematic review.},
cin = {IT},
ddc = {570},
cid = {I:(DE-H253)IT-20120731},
pnm = {623 - Data Management and Analysis (POF4-623)},
pid = {G:(DE-HGF)POF4-623},
experiment = {EXP:(DE-H253)TIER-II-20150101},
typ = {PUB:(DE-HGF)16},
pubmed = {35251945},
UT = {WOS:000821352600011},
doi = {10.1016/j.mex.2022.101633},
url = {https://bib-pubdb1.desy.de/record/603118},
}