Evidence map›Paper›PMID 23114289›Full record

ArticleBMC medical informatics and decision making2012

Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis.

Helen Cheyne, Len Dalgleish, Janet Tucker, Fiona Kane, Ashalatha Shetty, Sarah McLeod, Catherine Niven

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.7field-weighted citation impact, top 8% of its field
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

11 citing papers in PubMed, 43 citations in OpenAlex.

  1. Trial
  2. Determinants of Physicians' Referrals for Suspected Cancer Given a Risk-Prediction Algorithm: Linking Signal Detection and Fuzzy Trace Theory.Medical decision making : an international journal of the Society for Medical Decision Making · 2026
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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 at 4 institutions in 1 country.

Helen CheyneNursing, Midwifery and Allied Health Professions Research Unit, University of Stirling, Stirling, UK. h.l.cheyne@stir.ac.uk
Len Dalgleish
Janet Tucker
Fiona Kane
Ashalatha Shetty
Sarah McLeod
Catherine Niven
University of Stirling · GBAberdeen Maternity Hospital · GBNHS Highland · GBUniversity of Aberdeen · GB

Funding

Chief Scientist Office CZH/4/417Chief Scientist Office NMAHP1
6 · The paper itself

Abstract

backgroundThe importance of respecting women's wishes to give birth close to their local community is supported by policy in many developed countries. However, persistent concerns about the quality and safety of maternity care in rural communities have been expressed. Safe childbirth in rural communities depends on good risk assessment and decision making as to whether and when the transfer of a woman in labour to an obstetric led unit is required. This is a difficult decision. Wide variation in transfer rates between rural maternity units have been reported suggesting different decision making criteria may be involved; furthermore, rural midwives and family doctors report feeling isolated in making these decisions and that staff in urban centres do not understand the difficulties they face. In order to develop more evidence based decision making strategies greater understanding of the way in which maternity care providers currently make decisions is required. This study aimed to examine how midwives working in urban and rural settings and obstetricians make intrapartum transfer decisions, and describe sources of variation in decision making.

methodsThe study was conducted in three stages. 1. 20 midwives and four obstetricians described factors influencing transfer decisions. 2. Vignettes depicting an intrapartum scenario were developed based on stage one data. 3. Vignettes were presented to 122 midwives and 12 obstetricians who were asked to assess the level of risk in each case and decide whether to transfer or not. Social judgment analysis was used to identify the factors and factor weights used in assessment. Signal detection analysis was used to identify participants' ability to distinguish high and low risk cases and personal decision thresholds.

resultsWhen reviewing the same case information in vignettes midwives in different settings and obstetricians made very similar risk assessments. Despite this, a wide range of transfer decisions were still made, suggesting that the main source of variation in decision making and transfer rates is not in the assessment but the personal decision thresholds of clinicians.

conclusionsCurrently health care practice focuses on supporting or improving decision making through skills training and clinical guidelines. However, these methods alone are unlikely to be effective in improving consistency of decision making.

Indexed as

Decision MakingJudgmentPatient TransferRural Health ServicesSignal Detection, PsychologicalFemaleHumansLabor, ObstetricMidwiferyObstetric NursingPregnancyRisk AssessmentScotland

Identifiers

PMID23114289
PMCPMC3536665
OpenAlexW2009900608

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.