Evidence map›Paper›PMID 30249221›Full record

ArticleBMC medical education2018

Developing a digital communication training tool on information-provision in oncology: uncovering learning needs and training preferences.

Sebastiaan M Stuij, Nanon H M Labrie, Sandra van Dulmen, Marie José Kersten, Noor Christoph, Robert L Hulsman, Ellen Smets, INSTRUCT project group

Abstract read
In one paragraph

Article in BMC medical education, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The promise of digital healthcare technologies.Frontiers in public health · 2023
    Review
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. 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

8 authors.

Sebastiaan M StuijDepartment of Medical Psychology, Academic Medical Centre, Amsterdam, The Netherlands.
Nanon H M LabrieDepartment of Medical Psychology, Academic Medical Centre, Amsterdam, The Netherlands.
Sandra van DulmenNIVEL (Netherlands institute for health services research), Department of Primary and Community Care, Utrecht, The Netherlands.
Marie José KerstenDepartment of Haematology, Academic Medical Center, Amsterdam, The Netherlands.
Noor ChristophCenter for Evicence Based Education, Academic Medical Centre, Amsterdam, The Netherlands.
Robert L HulsmanDepartment of Medical Psychology, Academic Medical Centre, Amsterdam, The Netherlands.
Ellen SmetsDepartment of Medical Psychology, Academic Medical Centre, Amsterdam, The Netherlands. e.m.smets@amc.uva.nl.ORCID http://orcid.org/0000-0002-8145-8595
INSTRUCT project group

Funding

KWF Kankerbestrijding AMCUVA2014-6777
6 · The paper itself

Abstract

backgroundAdequate information-provision forms a crucial component of optimal cancer care. However, information-provision is particularly challenging in an oncology setting. It is therefore imperative to help oncological health care practitioners (HCP) optimise their information-giving skills. New forms of online education, i.e. e-learning, enable safe and time and location independent ways of learning, enhancing access to continuous learning for HCP. As part of a user-centred approach to developing an e-learning to improve information-giving skills, this study aims to: 1) uncover the learning needs of oncological healthcare providers related to information- provision, and 2) explore their training preferences in the context of clinical practice.

methodsFocus groups and interviews were organised with oncological HCP (medical specialists and clinical nurse specialists) addressing participants' learning needs concerning information- provision and their training preferences with respect to a new digital training tool on this issue. All sessions were audiorecorded and transcribed verbatim. Using an inductive approach, transcripts were independently coded by three researchers and discussed to reach consensus. Main themes were summarised and discussed.

resultsFour focus group sessions (total n = 13) and three interviews were conducted. The first theme concerned the patient outcomes HCP try to achieve with their information. We found HCP to mainly strive to promote patients' understanding of information. The second theme concerned HCP reported strategies and challenges when trying to inform their patients. These entailed tailoring of information to patient characteristics, structuring of information, and dealing with patients' emotions. Regarding HCP training preferences, an e-learning should be neatly connected to clinical practice. Moreover, participants desired a digital training to allow for feedback on their own (videotaped) information-giving skills from peers, communication experts, and/or patients; to monitor their progress and to tailored the training to individual learning needs.

conclusionsAn e-learning for improvement of information-giving skills of oncological HCP should be aimed at the transfer of skills to clinical practice, rather than at enhancing knowledge. Moreover, an e-learning is probably most effective when the facilitates individual learning needs, supports feedback on competence level and improvement, and allows input from significant others (experts, peers, or patients).

Indexed as

Clinical CompetenceCommunicationEducation, DistanceAttitude of Health PersonnelFocus GroupsHumansInterviews as TopicMedical OncologyNurse-Patient RelationsOncology NursingPhysician-Patient RelationsDoctor-patient communicationE-learningFocus groupOncologyUser-centred design

Identifiers

PMID30249221
PMCPMC6154812

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.