Qualitative Reporting

Qualitative Reporting

Qualitative research operates within a different paradigm from quantitative research — one that values depth over breadth, meaning over measurement, and context over control. Reporting qualitative research requires transparency about the research process, reflexive acknowledgment of researcher positionality, and demonstration of trustworthiness.

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Qualitative vs. Quantitative Paradigm Overview

| Dimension | Quantitative | Qualitative | |---|---|---| | Ontology | Reality is objective and measurable | Reality is socially constructed, multiple | | Epistemology | Researcher is separate from the studied | Researcher is part of the studied | | Purpose | Test hypotheses, generalise, predict | Understand meaning, explore, generate theory | | Methods | Surveys, experiments, structured observation | Interviews, focus groups, observation, documents | | Sample | Large, representative, random | Small, purposive, theoretical | | Analysis | Statistical testing | Thematic, narrative, discourse analysis | | Quality | Reliability, validity | Trustworthiness, credibility | | Reporting | CONSORT, STROBE | COREQ, SRQR |

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Reporting Guidelines

COREQ (Consolidated Criteria for Reporting Qualitative Research)

Purpose: 32-item checklist for health research.

When to use: Medical, nursing, public health, and clinical qualitative studies.

Key domains:

1. Research team and reflexivity (8 items) — researcher credentials, experience, relationship with participants
2. Study design (8 items) — methodology, sampling, sample size justification, data collection setting
3. Analysis and findings (16 items) — coding, derivation of themes, participant checking, quotations

SRQR (Standards for Reporting Qualitative Research)

Purpose: General qualitative research in social sciences.

When to use: Psychology, sociology, education, and interdisciplinary qualitative studies.

Key domains:

1. Title and abstract
2. Problem formulation
3. Purpose and research questions
4. Methods
5. Sampling and data sources
6. Data collection and analysis
7. Findings
8. Discussion
9. Ethics and trustworthiness

CASP (Critical Appraisal Skills Programme)

Purpose: Checklist for appraising qualitative research quality.

10 questions:

1. Was there a clear statement of the aims?
2. Is a qualitative methodology appropriate?
3. Was the research design appropriate?
4. Was the recruitment strategy appropriate?
5. Were the data collected in a way that addressed the research issue?
6. Has the relationship between researcher and participants been considered?
7. Have ethical issues been taken into consideration?
8. Was the data analysis sufficiently rigorous?
9. Is there a clear statement of findings?
10. How valuable is the research?

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Study Design Write-Ups

Phenomenology

Focus: The lived experience of a phenomenon.

Key reporting elements:

• Phenomenological approach (Husserl's descriptive vs. Heidegger's interpretive)
• Epoché / bracketing process
• Participant selection (those who have directly experienced the phenomenon)
• Sample size: typically 5–25
• Analysis: Colaizzi's 7 steps or van Manen's approach

Methods section example: > This study employed an interpretive phenomenological approach (Heidegger, 1927) to understand the lived experience of chronic pain in young adults. We chose interpretive phenomenology because we sought not only to describe the experience but to understand its meaning within participants' life contexts. Consistent with this approach, we conducted in-depth, semi-structured interviews (duration 45–90 minutes) with 12 participants who had experienced chronic pain for at least two years.

Grounded Theory

Focus: Developing a theory grounded in data.

Key reporting elements:

• Grounded theory approach (Glaser vs. Strauss & Corbin vs. Charmaz's constructivist)
• Theoretical sampling process
• Constant comparison method
• Saturation criteria
• Coding stages (open, axial, selective)
• Memo-writing

Methods section example: > We employed constructivist grounded theory (Charmaz, 2014) to develop a theoretical model of patient-provider communication in oncology settings. Following constructivist principles, we acknowledged that our analysis was shaped by our perspectives as healthcare researchers. We used theoretical sampling, recruiting participants who could contribute to emerging categories. Data collection and analysis proceeded iteratively until theoretical saturation was reached at 28 interviews, defined as no new categories emerging across three consecutive interviews.

Strauss & Corbin's Coding Paradigm: | Coding Stage | Purpose | Example Question | |---|---|---| | Open | Identify concepts | "What is happening here?" | | Axial | Connect categories | "What are the conditions? Consequences? Strategies?" | | Selective | Integrate around core category | "How does this relate to the central phenomenon?" |

Thematic Analysis

Focus: Identifying, analysing, and reporting patterns (themes).

Key reporting elements:

• Approach (inductive vs. deductive; semantic vs. latent)
• Braun & Clarke's 6-phase process
• Theme development process
• Number of themes and sub-themes

Braun & Clarke's 6 Phases:

| Phase | Activity | Output | |---|---|---| | 1. Familiarisation | Read and re-read data | Immersion in data | | 2. Initial codes | Generate initial codes across dataset | Initial code list | | 3. Searching for themes | Collate codes into potential themes | Candidate themes | | 4. Reviewing themes | Check themes against coded extracts and dataset | Refined themes | | 5. Defining themes | Define and name each theme | Clear theme definitions | | 6. Writing up | Final analysis and report | Manuscript |

Methods section example: > We conducted reflexive thematic analysis (Braun & Clarke, 2022) following an inductive, semantic approach. Inductive analysis meant that our themes were data-driven rather than fitted to a pre-existing coding frame. Semantic analysis focused on the explicit content of participants' accounts. The first author coded all transcripts; themes were developed through discussion among all authors until consensus was reached.

Discourse Analysis

Focus: How language constructs meaning and power.

Key reporting elements:

• Approach (Foucauldian, critical discourse analysis, discursive psychology)
• Analytical focus (discourse, power, ideology, subject positions)
• Data type (interviews, documents, media, naturalistic conversation)
• Unit of analysis (word, phrase, turn, text)

Ethnography

Focus: Cultural patterns and social practices in natural settings.

Key reporting elements:

• Setting and duration of fieldwork
• Participant observation details
• Field note process
• Access and gatekeepers
• Researcher role (participant vs. observer)

Case Study

Focus: In-depth exploration of a bounded system.

Key reporting elements:

• Case definition and boundaries
• Case selection rationale (typical, critical, extreme, or revelatory)
• Multiple data sources (triangulation)
• Within-case and cross-case analysis (for multiple cases)

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Sample and Participant Selection

Sampling Strategies

| Strategy | When to Use | How to Report | |---|---|---| | Purposive | Select information-rich cases | "We used purposive sampling to recruit participants who..." | | Theoretical | Grounded theory; sample to develop theory | "We used theoretical sampling, with each interview informing the next recruitment..." | | Maximum variation | Capture diversity of experience | "We sought maximum variation in [characteristic] to capture a range of perspectives..." | | Homogeneous | Focus on shared experience | "We recruited participants with similar [characteristics] to enable deep exploration..." | | Convenience | Limited access; acknowledge limitations | "Due to limited access during the pandemic, we used convenience sampling, which limits transferability..." | | Snowball | Hard-to-reach populations | "Participants referred additional participants through snowball sampling..." |

Sample Size and Saturation

Reporting requirements:

1. How sample size was determined
2. Definition of saturation used
3. How saturation was assessed

Example: > We continued data collection until thematic saturation was reached, defined as no new themes emerging across three consecutive interviews (Saunders et al., 2018). This occurred at 15 interviews.

Sample size norms: | Method | Typical Range | Saturation Point | |---|---|---| | Phenomenology | 5–25 | 10–15 common | | Grounded theory | 20–40 | Theoretical saturation | | Thematic analysis | 10–30 | Theme saturation | | Ethnography | 20–50 participants + observation | Varies | | Case study | 1–10 cases | Within-case depth |

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Data Collection Reporting

Interviews

Elements to report:

• Interview type (structured, semi-structured, unstructured)
• Interview guide development process
• Duration (range)
• Mode (face-to-face, telephone, video)
• Recording method
• Transcription approach (verbatim, intelligent verbatim; notation system)
• Language of interview and translation (if applicable)

Example: > We conducted semi-structured interviews lasting 45–75 minutes (mean = 58). An interview guide was developed based on the literature and refined after two pilot interviews. All interviews were audio-recorded and transcribed verbatim, including pauses, laughter, and emphasis. Transcripts were not returned to participants for comment due to the sensitive nature of the topic.

Focus Groups

Elements to report:

• Number of focus groups
• Participants per group (typical: 4–12)
• Group composition (homogeneous vs. heterogeneous)
• Moderation approach
• Recording and transcription

Observation

Elements to report:

• Type (participant, non-participant, covert, overt)
• Duration and frequency of observation
• Field note process
• Analytic memos

Document Analysis

Elements to report:

• Document types (policy, media, organisational, personal)
• Selection criteria
• Access process
• Analysis approach

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Analysis Reporting

Coding Process

Elements to report:

• Who coded the data
• Software used (NVivo, ATLAS.ti, MAXQDA, Dedoose, or manual)
• Coding approach (deductive, inductive, hybrid)
• Inter-coder reliability (if used)
• Discrepancy resolution

Example: > Transcripts were imported into NVivo 14 (QSR International) for analysis. The first author developed an initial codebook through close reading of five transcripts. This codebook was applied to three additional transcripts by the second author; inter-coder agreement was 87%. Discrepancies were resolved through discussion, and the codebook was refined iteratively.

Theme Development

Elements to report:

• How codes were grouped into themes
• How themes were named and defined
• Number of themes and sub-themes
• Theme prevalence (number of participants, number of references)

Member Checking

Elements to report:

• Whether member checking was conducted
• How (summary return, participant review of themes, member checking workshop)
• Participant response and any changes made

Example: > We conducted member checking by sharing a summary of findings with all participants. Eight participants responded; all confirmed that the themes resonated with their experiences. Two participants suggested minor clarifications, which were incorporated.

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Reflexivity Statement

A reflexivity statement acknowledges the researcher's position and how it may have influenced the research.

Elements to include:

1. Researcher characteristics (gender, age, profession, cultural background)
2. Relationship to the topic
3. Assumptions and biases acknowledged
4. Strategies to manage subjectivity

Example: > As a clinician-researcher who has worked in oncology for 15 years, I brought both insights and potential biases to this study. My clinical experience provided contextual understanding, but also shaped the questions I asked and the interpretations I made. I addressed this through reflexive journaling throughout data collection and analysis, discussing emerging interpretations with non-clinical co-authors, and maintaining an audit trail of analytical decisions.

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Trustworthiness

The qualitative equivalent of reliability and validity.

| Criterion | Definition | Techniques | |---|---|---| | Credibility | Truth value — are findings accurate? | Prolonged engagement, triangulation, member checking, peer debriefing | | Transferability | Applicability to other contexts | Thick description, purposive sampling, contextual detail | | Dependability | Consistency of process | Audit trail, coding consistency, clear documentation | | Confirmability | Neutrality — are findings data-driven? | Reflexivity, audit trail, triangulation |

Trustworthiness reporting example: > To enhance credibility, we used triangulation across data sources (interviews, observation, documents) and conducted member checking. For transferability, we provide thick description of the setting and participants. Dependability was supported through an audit trail documenting analytical decisions. Confirmability was addressed through reflexive journaling and peer debriefing with colleagues outside the research team.

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Reporting Quotations

Selection Criteria

• Illustrative of the theme
• Diverse participants (don't quote the same participant repeatedly)
• Emotional range (include both expected and surprising insights)

Formatting

| Style | Format | Example | |---|---|---| | In-text | Short quotations ( Several participants described the experience of diagnosis as transformative: > > > It was like someone had pulled the rug out from under me. Everything I thought I knew about my future just... vanished. But eventually, I had to rebuild, and in some ways, I'm stronger now than before. (P11, female, 50s)

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Qualitative Software Citation

NVivo

> Data were analysed using NVivo 14 (QSR International, Melbourne, Australia).

ATLAS.ti

> Data were analysed using ATLAS.ti version 23 (ATLAS.ti Scientific Software Development GmbH, Berlin, Germany).

MAXQDA

> Data were analysed using MAXQDA 2024 (VERBI Software, Berlin, Germany).

Dedoose

> Data were analysed using Dedoose version 9.0 (SocioCultural Research Consultants, Los Angeles, CA).

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Common Mistakes Table

| Mistake | Why It's a Problem | Correction | |---|---|---| | No reflexivity statement | Qualitative research is interpretive; positionality matters | Include explicit reflexivity statement | | Generic "thematic analysis" without approach | Braun & Clarke vs. Boyatzis vs. descriptive — different rigour | Specify the approach and phases | | No saturation definition | Unclear how sample size was determined | Define and report saturation explicitly | | Treating participants as data points | Removes context and personhood | Use identifiers that preserve humanity | | Quotations without context | Reader cannot assess representativeness | Provide participant context and theme linkage | | Overclaiming transferability | Small samples cannot generalise | Use "may be relevant to" rather than "applies to" | | Ignoring power dynamics | Researcher-participant relationship shapes data | Acknowledge and discuss power dynamics | | Linear presentation of iterative process | Qualitative analysis is iterative, not linear | Describe the actual iterative process | | No mention of negative cases | Only confirming evidence reported | Actively seek and report disconfirming cases | | Methods too brief for replication | Qualitative rigour requires transparency | Use COREQ or SRQR checklist |

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Key Resources

• COREQ 32-item checklist: Tong et al. (2007), *International Journal for Quality in Health Care

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Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: muhammad1438
• Source: muhammad1438/academic-writer-skills
• License: MIT

Install and usage instructions live in the source repository linked above.