Promoting meaningful qualitative research in social pharmacy: moving beyond reporting guidelines
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,189 | 0,483 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,010 | 0,007 |
| Bibliométrie | 0,014 | 0,007 |
| Études des sciences et des technologies | 0,014 | 0,023 |
| Communication savante | 0,041 | 0,018 |
| Science ouverte | 0,013 | 0,009 |
| Intégrité de la recherche | 0,060 | 0,058 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,009 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».