Evidence map›Paper›PMID 37932759›Full record

Trial reportBMC medical informatics and decision making2023

Assessment of a venous thromboembolism prophylaxis shared decision-making intervention (DASH-TOP) using the decisional conflict scale: a mixed-method study.

Montserrat León-García, Brittany Humphries, Pablo Roca Morales, Derek Gravholt, Mark H Eckman, Shannon M Bates, Nataly R Espinoza Suárez, Feng Xie, Lilisbeth Perestelo-Pérez, Pablo Alonso-Coello

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC medical informatics and decision making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Montserrat León-GarcíaIberoamerican Cochrane Center, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain. mleong@santpau.cat.
Brittany HumphriesDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
Pablo Roca MoralesFaculty of Health Sciences, Universidad Villanueva, Madrid, Spain.
Derek GravholtIberoamerican Cochrane Center, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain.
Mark H EckmanDivision of General Internal Medicine and Center for Clinical Effectiveness, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Shannon M BatesDepartment of Medicine, McMaster University, Hamilton, ON, Canada.
Nataly R Espinoza SuárezKnowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
Feng XieDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
Lilisbeth Perestelo-PérezEvaluation Unit (SESCS), Canary Islands Health Service (SCS), Tenerife, Spain.
Pablo Alonso-CoelloIberoamerican Cochrane Center, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain.

Funding

CIHR GSD-152327
6 · The paper itself

Abstract

backgroundVenous thromboembolism (VTE) in pregnancy is a major cause of maternal morbidity and death. The use of low-molecular-weight heparin (LMWH), despite being the standard of care to prevent VTE, comes with some challenges. Shared decision-making (SDM) interventions are recommended to support patients and clinicians in making preference-sensitive decisions. The quality of the SDM process has been widely assessed with the decisional conflict scale (DCS). Our aim is to report participants' perspectives of each of the components of an SDM intervention (DASH-TOP) in relation to the different subscales of the DCS.

methodsDesign: A convergent, parallel, mixed-methods design.

participantsThe sample consisted of 22 health care professionals, students of an Applied Clinical Research in Health Sciences (ICACS) master program.

interventionWe randomly divided the participants in three groups: Group 1 received one component (evidence -based information), Group 2 received two components (first component and value elicitation exercises), and Group 3 received all three components (the first two and a decision analysis recommendation) of the SDM intervention. ANALYSIS: For the quantitative strand, we used a non-parametric test to analyze the differences in the DCS subscales between the three groups. For the qualitative strand, we conducted a content analysis using the decisional conflict domains to deductively categorize the responses.

resultsGroups that received more intervention components experienced less conflict and better decision-making quality, although the differences between groups were not statistically significant. The decision analysis recommendation improved the efficacy with the decision-making process, however there are some challenges when implementing it in clinical practice. The uncertainty subscale showed a high decisional conflict for all three groups; contributing factors included low certainty of the evidence-based information provided and a perceived small effect of the drug to reduce the risk of a VTE event.

conclusionsThe DASH-TOP intervention reduced decisional conflict in the decision -making process, with decision analysis being the most effective component to improve the quality of the decision. There is a need for more implementation research to improve the delivery of SDM interventions in the clinical encounter.

Indexed as

Decision MakingVenous ThromboembolismConflict, PsychologicalFemaleHeparin, Low-Molecular-WeightHumansPregnancyUncertaintyHeparin, Low-Molecular-WeightDecision aidsDecisional conflictInformed decision choicesShared decision-makingValues and preferences and decision analysis

Identifiers

PMID37932759
PMCPMC10629184

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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.