Evidence map›Paper›PMID 34253221›Full record

ArticleBMC medical education2021

Development of the Feedback Quality Instrument: a guide for health professional educators in fostering learner-centred discussions.

Christina E Johnson, Jennifer L Keating, Michelle Leech, Peter Congdon, Fiona Kent, Melanie K Farlie, Elizabeth K Molloy

Abstract read
In one paragraph

Article in BMC medical education, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Christina E JohnsonDepartment of Medical Education, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia. christina.johnson@monashhealth.org.ORCID https://orcid.org/0000-0002-4209-8419
Jennifer L KeatingDepartment of Physiotherapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0003-3161-4964
Michelle LeechFaculty of Medicine, Nursing and Health Sciences, Monash University, Monash Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-7226-7121
Peter CongdonRoyal Australian and New Zealand College of Psychiatrists, Melbourne, Victoria, Australia.
Fiona KentFaculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia.
Melanie K FarlieFaculty of Medicine, Nursing and Health Sciences, Monash University, Monash Health, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-6820-1496
Elizabeth K MolloyDepartment of Medical Education, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0001-9457-9348

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFace-to-face feedback plays an important role in health professionals' workplace learning. The literature describes guiding principles regarding effective feedback but it is not clear how to enact these. We aimed to create a Feedback Quality Instrument (FQI), underpinned by a social constructivist perspective, to assist educators in collaborating with learners to support learner-centred feedback interactions. In earlier research, we developed a set of observable educator behaviours designed to promote beneficial learner outcomes, supported by published research and expert consensus. This research focused on analysing and refining this provisional instrument, to create the FQI ready-to-use.

methodsWe collected videos of authentic face-to-face feedback discussions, involving educators (senior clinicians) and learners (clinicians or students), during routine clinical practice across a major metropolitan hospital network. Quantitative and qualitative analyses of the video data were used to refine the provisional instrument. Raters administered the provisional instrument to systematically analyse educators' feedback practice seen in the videos. This enabled usability testing and resulted in ratings data for psychometric analysis involving multifaceted Rasch model analysis and exploratory factor analysis. Parallel qualitative research of the video transcripts focused on two under-researched areas, psychological safety and evaluative judgement, to provide practical insights for item refinement. The provisional instrument was revised, using an iterative process, incorporating findings from usability testing, psychometric testing and parallel qualitative research and foundational research.

resultsThirty-six videos involved diverse health professionals across medicine, nursing and physiotherapy. Administering the provisional instrument generated 174 data sets. Following refinements, the FQI contained 25 items, clustered into five domains characterising core concepts underpinning quality feedback: set the scene, analyse performance, plan improvements, foster learner agency, and foster psychological safety.

conclusionsThe FQI describes practical, empirically-informed ways for educators to foster quality, learner-centred feedback discussions. The explicit descriptions offer guidance for educators and provide a foundation for the systematic analysis of the influence of specific educator behaviours on learner outcomes.

Indexed as

Clinical CompetenceEducational PersonnelFeedbackHealth PersonnelHumansLearningEffective feedbackFactor analysisFeedbackFeedback instrumentHealth professional educationInstrument developmentMFRMProfessional developmentPsychometric evaluationScale developmentWorkplace learning

Identifiers

PMID34253221
PMCPMC8276464

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.