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Record W2957292207 · doi:10.1111/ijpp.12540

Promoting meaningful qualitative research in social pharmacy: moving beyond reporting guidelines

2019· editorial· en· W2957292207 on OpenAlexaff
Lisa M. Guirguis, Matthew J. Witry

Bibliographic record

VenueInternational Journal of Pharmacy Practice · 2019
Typeeditorial
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicinePharmacyQualitative researchMedical educationFamily medicineNursingSocial science

Abstract

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The application of qualitative research has expanded in the health professions and is increasingly accepted by journals and funding agencies. Similarly, the application of qualitative research methods in social pharmacy has grown exponentially. From 1970 to 1990, a total of, 48 publications studied community pharmacy using qualitative research methods. By 2017, that had doubled to 99 publications in a single year (Figure 1). The expansion of qualitative research in social pharmacy has enabled our field to move beyond characterizing practice and its impact to allow for exploration of experiences, understandings, and processes in pharmacy practice. Count of qualitative publications in community pharmacy. MEDLINE search with community pharmacy services limited to qualitative research (best balance sensitivity and specificity). The application of qualitative research in social pharmacy builds on seminal of works by qualitative research pioneers and decades of methodological, epistemological and ontological debates in the fields of sociology, anthropology, psychology and nursing. Given this lineage, researchers in social pharmacy should strive for credible research that not only makes a significant contribution to social pharmacy but also advances the field of qualitative research. We argue progress could be achieved by (1) the thoughtful application of publishing guidelines and (2) moving beyond checklists alone to consider to the generation of themes and application of theory. First, while the use of qualitative reporting guidelines does not inherently result in high-quality qualitative work, they ideally help authors provide the necessary detail so peer reviewers and eventually readers can assess the merits and rigour of a study and avoid the ‘waste’ in biomedical research due to bad reporting.[1] Dozens of reporting guidelines have been developed by experienced qualitative researchers. While each has unique elements, they have many commonalities. Most address the concepts of reflexivity, qualitative paradigms, sampling and recruitment, coding and analysis, and data presentation and discussion. One of the most widely used in health research is the COnsolidated criteria for REporting Qualitative research (COREQ).[2] This guide is a 32-item checklist that was developed from a synthesis of 22 other reporting guidelines. The criteria in the COREQ are discrete, making it a relatively simple process to examine if a study meets particular criteria. A more recent guideline is the Standards for Reporting Qualitative Research (SRQR).[3] The SRQR is more conceptual and gives overall guidance on reporting study elements, such as a general call for a description of study procedures that support trustworthiness, and a discussion that elaborates on how the findings connect to and challenge other research. Reporting guidelines are useful throughout the qualitative research process, not just in the final stages of manuscript preparation.[3] Both new and experienced researchers could use reporting guidelines in crafting their initial proposal, documenting their process and decisions while collecting data, analysing the data and in all aspects of disseminating their work. There may be a benefit to using multiple reporting guidelines, such as using the COREQ in study design and the SRQR during analysis and reporting. Journal editors and peer reviewers may employ reporting guidelines to ensure the completeness of articles and refer to them when requesting that authors provide missing information. Some journals already recommend including a completed checklist with article submission. As mentioned previously, checking off all reporting guideline elements does not inherently produce a high-quality article. Barbour[4] suggests that the unreflective application of standards may provide a false sense of quality. For example, the use of ‘grounded theory’ is too often claimed in place of methodological details and epistemological underpinnings. Lau and Traulsen[5] identified two areas where researchers may benefit from additional attention as they are not easily assessed using checklists: (1) the difference between themes and categories, and (2) the use of theory in qualitative research. The term ‘theme’ is ubiquitous in qualitative research in social pharmacy; however, themes are an important concept and may, in some cases, be inappropriately applied.[6] Morse[7] clarifies the difference between categories (i.e. the collection of similar data or codes in one place) and themes (i.e. an idea that runs through the data explains what the data are about). By differentiating these terms, we are not implying one is better than the other, but we are advocating for coherence between the methods and results. As with many scientific processes, the precise use of terminology matters. Qualitative projects that are descriptive in nature and serve to organize and summarize respondent perspectives can make a useful contribution to the literature and help build an understanding of new processes and phenomena. But just like how not every quantitative study necessitates two-stage least squares regression, not all qualitative projects necessitate the same level of qualitative analysis. Like all research, the research questions and the nature of the data should dictate the most appropriate analysis. An example of a qualitative project in social pharmacy that presents themes as the highest level of analysis is an interview study of medication use among hepatitis C patients.[8] This team used phenomenology throughout the research process and reporting to distil the medication use themes of adversity, resolution, ambiguity and irrelevance. The authors were able to identify these themes by fully embracing their theoretical framework and spending significant effort in reading the transcripts and field notes holistically. The robustness of these themes should facilitate transferability of the findings[9] to other areas of medication use and perhaps for other daily health management activities. Leutsch and Burrows[10] provide an example of using a more descriptive qualitative approach in their analysis of a motivational interviewing programme. The authors focus their analysis on how participants move from a transactional communication approach to a transformational approach. Topics raised in the interviews were coded, sorted and summarized to give the reader an easy-to-digest compilation and discussion of the qualitative data collected and how it fits into the motivational interviewing training literature. We are continuing a conversation started by Lau and Traulsen and hope our commentary stimulates others to reflect on their research process. To this end, we suggest qualitative research in social pharmacy can be bolstered through the consistent use of reporting guidelines throughout the research process, the intentional use of themes and/or categories as a product of analyses, and integrating qualitative work into existing theories and larger literature bases. It is hoped that the combination of reporting guidelines, theory and a commitment to delving deeper into the data will produce impactful work that will advance our field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.189
metaresearch head score (Gemma)0.483
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.811
Threshold uncertainty score0.997

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1890.483
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0100.007
Bibliometrics0.0140.007
Science and technology studies0.0140.023
Scholarly communication0.0410.018
Open science0.0130.009
Research integrity0.0600.058
Insufficient payload (model declined to judge)0.0120.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.846
GPT teacher head0.821
Teacher spread0.025 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainReporting
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations10
Published2019
Admission routes1
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