Evidence map›Paper›PMID 36371177›Full record

ArticleBMC medical education2022

Adaptability and learning Intraprofessional collaboration of residents during the COVID-19 pandemic.

C L Bus, R van der Gulden, M Bolk, J de Graaf, M van den Hurk, N N D Scherpbier-de Haan, C R M G Fluit, W Kuijer-Siebelink, N Looman

Abstract read
In one paragraph

Article in BMC medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Social Cohesion and COVID-19: Integrative Review.Interactive journal of medical research · 2024
    Review
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

9 authors.

C L BusRadboudumc Health Academy, Department of Research on Learning and Education, Radboud University Medical Centre, Nijmegen, the Netherlands. Lotte.Bus@radboudumc.nl.
R van der GuldenRadboud Institute for Health Sciences, Department of Primary and Community Care, Radboud University Medical Center, Nijmegen, the Netherlands.
M BolkDutch Association of Medical Specialists, Utrecht, the Netherlands.
J de GraafRadboudumc Health Academy, Division of Post Graduate Medical Education, Radboud University Medical Centre, Nijmegen, the Netherlands.
M van den HurkDepartment of Educational Sciences, Faculty of Social Sciences, Radboud University, Nijmegen, the Netherlands.
N N D Scherpbier-de HaanDepartment of General Practice and Elderly Care Medicine, University Medical Centre Groningen, Groningen, the Netherlands.
C R M G FluitRadboudumc Health Academy, Department of Research on Learning and Education, Radboud University Medical Centre, Nijmegen, the Netherlands.
W Kuijer-SiebelinkRadboudumc Health Academy, Department of Research on Learning and Education, Radboud University Medical Centre, Nijmegen, the Netherlands.
N LoomanRadboud Institute for Health Sciences, Department of Primary and Community Care, Radboud University Medical Center, Nijmegen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextThe COVID-19 pandemic created a worldwide public health emergency, in which hospitals created new COVID departments and doctors from different disciplines had to work together. In the Netherlands, a large proportion of doctors in these departments were residents. With knowledge of the disease developing only gradually, the influx of COVID-19 patients called for adaptability, innovative work behavior, and intraprofessional collaboration (intraPC) between residents and between residents and medical specialists. RESEARCH GOAL: This study investigates how the delivery of COVID-19 care in hospital settings altered the way residents develop their sense of adaptability and intraPC during their training.

methodsSixteen semi-structured interviews were conducted with residents and medical specialists from various disciplines who worked at a COVID department or Intensive Care Unit (ICU) during the COVID pandemic in the Netherlands, focusing on adaptability and intraPC learning. Transcripts were analyzed using (thematic) template analysis.

resultsFour themes that influenced learning during COVID care were identified: collective uncertainty, social cohesion and a sense of safety, the need for adaptive performance and intraPC learning. During the first wave, collective uncertainty about the unknown disease and the continuation of the crisis urged residents to adapt in order to take care of patients with a disease that was as yet unknown. The combination of collective uncertainty, social cohesion and a sense of safety, and the presence of different disciplines in one department promoted residents' intraPC learning. However, intraPC learning was not always the matter of course due to the scope of the crisis and the huge numbers of new patients.

conclusionCollective uncertainty affected the residents' adaptability. The combination of collective uncertainty, social cohesion, and the presence of different disciplines in one department promoted the residents' intraPC learning. An important facilitating factor for both adaptability and intraPC learning is a high level of social cohesion and safety. The physical and psychological proximity of supervisors is an important factor contributing to a safe learning environment. This study provides implications for practice for learning during postgraduate training in non-crisis settings.

Indexed as

COVID-19Internship and ResidencyEducation, Medical, GraduateHumansLearningPandemicsAdaptabilityCollective uncertaintyCrisis(learning) intraprofessional collaborationPandemicPostgraduate trainingResidentSocial cohesionSupervision

Identifiers

PMID36371177
PMCPMC9652594

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.