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Enregistrement W2896681288 · doi:10.1111/medu.13739

Medical education research approaches

2018· editorial· en· W2896681288 sur OpenAlexaff
Kevin W. Eva

Notice bibliographique

RevueMedical Education · 2018
Typeeditorial
Langueen
DomaineMedicine
ThématiqueInnovations in Medical Education
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedical educationMEDLINEMedical researchMedicinePsychologyPolitical sciencePathology

Résumé

récupéré en direct d'OpenAlex

“Anything goes” is not a “principle” I hold … but the terrified exclamation of a rationalist who takes a closer look at history.1,p.vii Anyone who has had the misfortune of attending a ‘research methods’ workshop I have offered soon discovers that in most circumstances, it takes a long time to get around to talking about actual research methods. I try to offer participants fair warning, but it is not something for which I can readily apologise because (if you will pardon the pun) there is a method to the madness. Most often, when people start talking about new research ideas (regardless of experience level), it is the concepts and assumptions embedded in the research question (including whether or not one can justify its importance in relation to what is already known) that must take centre stage before worrying about just how the study will be conducted. The only way to sensibly reason through choices about one's methods, after all, is through reference to how contextual factors influence one's abilities to achieve meaningful advances by conducting the project in a particular way. For the uninitiated, especially those accustomed to thinking in terms of evidence hierarchies,2 it is the need to make choices, the absence of a simple set of methodological recipe cards and the context-driven demands for adaptation that can be particularly unsettling. In fact, it is that constant need for adaptation that leads me, in general, to align with Feyerabend's view (expressed in the opening quote) that the only universal methodological rule is that there are no universal rules. In offering a number of historical case studies, he argued that ‘One can show the following: Given any rule, however “fundamental” or “necessary” for science, there are always circumstances when it is advisable not only to ignore the rule, but to adopt its opposite.’1,p.23 It would be a mistake to assume that everyone in health professional education shares this view, but I know of no field that includes a group of investigators who better exemplify the ‘epistemological anarchy’ he promotes. There have certainly been historical norms and dominant voices surrounding particular issues,3 but there is no perspective, lens or view of health professional education that is insusceptible to just critique.4 Nor need there be. The very nature of the expertise the field exists to understand and nurture is embedded in complexity.5 Health professionals must make practice adjustments to accommodate the context (environmental, personal, social, etc.) that surrounds them.6 Educators make similar adjustments,7 and researchers are no different. As a result, to paraphrase Lambert Schuwirth (personal communication [by email], 2018), one's methods should be seen as an accumulation of choices (large and small) that need to be justified if our scientific efforts are to offer meaningful and insight-producing information to be gathered. This view of the world creates a particular challenge for those of us charged with training newcomers to health professional education research; those of us striving to not be completely blinded by the methodologies with which we are most comfortable; and for those of us who seek to examine whether or not conceptual barriers are created within the field by limitations inherent in the most commonly applied methods. The ability to nuance one's research approach appropriately and convincingly, altering general principles to the specifics of the situation, requires judgement ideally guided by knowledge and experience. With so many distinct methods, methodologies and epistemologies influencing the rich tapestry we call the field of health professional education it is not possible to be aware of, let alone experience, all of the options one might consider. Nor could one be expected to review comprehensive manifestos of every potentially relevant research approach during initial explorations of which approaches might be most useful to apply to a given situation. To help, the editors of Medical Education have been contemplating how we might use the journal to create a series of access points: articles that problematise some aspect of health professional education research to critically question taken-for-granted practices or that introduce the field to approaches of which we are not taking sufficient advantage. In this way, the series might be conceived of as a methodological analogue of ‘The Cross-Cutting Edge’ series, which began exactly a decade ago,8 in that both are aimed at scholarly exploration of knowledge that is under-represented in our field's efforts at scholarship by sharing ‘cutting-edge’ ideas that ‘cross-cut’ disciplinary boundaries. Although this is a new ‘series’ in the sense that it is a first effort to systematically identify, define and promote these types of articles, there are many good examples already published that can help orient potential authors to the type of work we hope to encourage. In fact, this effort is meant to build on the success of our January 2017 ‘State of the Science’ issue in which a variety of authors offered guidance on research approaches, including conducting ‘practical trials’,9 promoting rigour in qualitative methods,10 and overcoming challenges encountered when studying visual expertise.11 The first paper to be published under the banner of ‘Research Approaches’, included in this issue, provides another example as Cleland et al.12 offer a critical examination of what discrete choice experiments, commonly used in the field of economics, have to offer the field of health professional education. We have called this new section of the journal ‘Research Approaches’ to reflect that it is expected to flexibly cover a breadth of issues that will focus at varying degrees of granularity ranging from specific aspects of sampling or analysis through to the type of knowledge that might be gained (robustly) from adoption of a particular class of methodologies. These papers are not intended to offer a simple description of ‘how to’ conduct different types of research. There are countless textbooks for such purposes that offer more suitable outlets given the number of words required to cover the relevant issues in sufficient detail. Rather, editorial priority will be given to manuscripts that offer compelling claims regarding how the effort can help the field think better about some aspects of our research enterprise. Given the philosophy used to open this editorial, it should be no surprise that we think it is antithetical to force authors writing for the ‘Research Approaches’ section to follow a set algorithmic structure. However, we expect all successful submissions, in one way or another, to cover three things: (i) a brief and critical summary of the background from where the approach was derived; (ii) more extensive guidance regarding the process through which one can determine whether it is effectively applied, and (iii) practical pearls of wisdom for those who are new to the approach. The description of seminal examples, guidance regarding what issues and problems arise from its application, and pointers to more detailed information, will be considered an asset. As a self-test of whether or not each section has been covered adequately, authors should consider whether or not they have addressed the following, non-comprehensive and non-mandatory, list of guiding questions about the research approach focused upon. Background Process Pearls For formatting details and current instructions, please see the Author Guidelines posted on our website by clicking ‘write’ at www.mededuc.com. The deputy editors and I look forward to reading your submissions. Let the anarchy ensue.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,012
score de la tête « metaresearch » (Gemma)0,253
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesIntégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,273
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0120,253
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0010,002
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0060,008
Charge utile insuffisante (le modèle a refusé de juger)0,0170,002

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.

Tête enseignante Opus0,054
Tête enseignante GPT0,463
Écart entre enseignants0,409 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations8
Publié2018
Routes d'admission1
Résumé présentoui

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