Cited by 242Qualitative Research Methods and ApplicationsQualitative Research Methods and EthicsComputational and Text Analysis Methods

Increasing rigor and reducing bias in qualitative research: a document analysis of parliamentary debates using applied thematic analysis

Mackieson, Penny, Shlonsky, Aron, Connolly, Marie·2019·Qualitative Social Work

Abstract

Qualitative research methods have traditionally been criticised for lacking rigor, and impressionistic and biased results. Subsequently, as qualitative methods have been increasingly used in social work inquiry, efforts to address these criticisms have also increased. Applied thematic analysis provides structure and integrates reflexivity in qualitative research using textual data. In this article, we describe how applied thematic analysis was operationalised in a document analysis of the official records of parliamentary debates in the Australian State of Victoria relating to the introduction of Permanent Care Orders, an alternative to adoption for children residing out-of-home and unable to be safely reunified with their parents. We present this example to extend the knowledge base regarding applied thematic analysis and to demonstrate how step-by-step implementation of a purposeful methodology using trustworthy documentary data can effectively increase rigor and transparency, thereby reducing potential bias, in a qualitative analysis. First, we clarify key terms; then discuss the challenges of analysing textual data; consider the value of parliamentary debates as a textual data source; and provide a detailed description of the processes undertaken in the document analysis. Finally, we reflect on the application of applied thematic analysis in our study, highlighting its value in strengthening qualitative social work research using document analysis.

Integrity signals

Registry

Crossref · 10.1177/1473325018786996

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Mackieson, P., Shlonsky, A., & Connolly, M.
Affiliations
The University of Melbourne (AU)
Corresponding author
Mackieson, Penny
Venue
Qualitative Social Work
Published
2018-07-10
Volume
18
Issue
6
Pages
965-980
ISSN
  • 1473-3250 (ISSN-L)
  • 1741-3117
OpenAlex
W2859271408
Cited by
242
References
27
Citations by year
2026: 31 · 2025: 56 · 2024: 48 · 2023: 38 · 2022: 36 · 2021: 19 · 2020: 9 · 2019: 4 · 2018: 1
FWCI
26.81
Type
journal article
Language
en
Open access
closed
Locations
Qualitative Social Work (publishedVersion)
Topics
  • Social Sciences › Education › Qualitative Research Methods and Applications
  • Social Sciences › Sociology and Political Science › Qualitative Research Methods and Ethics
  • Social Sciences › General Social Sciences › Computational and Text Analysis Methods
Keywords
document analysis, qualitative research rigor, reflexivity, research bias, parliamentary debate, out-of-home care, social work research methods, textual data analysis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review