Evidence map›Paper›PMID 25547513›Full record

Trial reportBMC medical education2014

Identifying and enhancing risk thresholds in the detection of elder financial abuse: a signal detection analysis of professionals' decision making.

Priscilla Harries, Huiqin Yang, Miranda Davies, Mary Gilhooly, Kenneth Gilhooly, Carl Thompson

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC medical education, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Referral Decision Making of General Practitioners: A Signal Detection Study.Medical decision making : an international journal of the Society for Medical Decision Making · 2019
    Article
  6. Person-centered dementia care: current perspectives.Clinical interventions in aging · 2016
    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

6 authors.

Priscilla HarriesDepartment of Clinical Sciences, Brunel University, Mary Seacole Building, Uxbridge, Middlesex, England, UB8 3PH, UK. priscilla.harries@brunel.ac.uk.
Huiqin YangCRD, The University of York, Seebohm Rowntree Building, York, YO10 5DD, UK. huiqin.yang@york.ac.uk.
Miranda DaviesDepartment of Clinical Sciences, Brunel University, Mary Seacole Building, Uxbridge, Middlesex, England, UB8 3PH, UK. Miranda.Davies@brunel.ac.uk.
Mary GilhoolyBrunel Institute for Ageing Studies, Department of Clinical Sciences, Brunel University, Mary Seacole Building, Uxbridge, Middlesex, England, UB8 3PH, UK. mary.gilhooly@brunel.ac.uk.
Kenneth GilhoolyDepartment of Clinical Sciences, Brunel University, Mary Seacole Building, Uxbridge, Middlesex, England, UB8 3PH, UK. kenneth.gilhooly@brunel.ac.uk.
Carl ThompsonHealth Services Research, Department of Health Sciences, The University of York, Seebohm Rowntree Building, Heslington, York, YO10 5DD, UK. carl.thompson@york.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFinancial abuse of elders is an under acknowledged problem and professionals' judgements contribute to both the prevalence of abuse and the ability to prevent and intervene. In the absence of a definitive "gold standard" for the judgement, it is desirable to try and bring novice professionals' judgemental risk thresholds to the level of competent professionals as quickly and effectively as possible. This study aimed to test if a training intervention was able to bring novices' risk thresholds for financial abuse in line with expert opinion.

methodsA signal detection analysis, within a randomised controlled trial of an educational intervention, was undertaken to examine the effect on the ability of novices to efficiently detect financial abuse. Novices (n = 154) and experts (n = 33) judged "certainty of risk" across 43 scenarios; whether a scenario constituted a case of financial abuse or not was a function of expert opinion. Novices (n = 154) were randomised to receive either an on-line educational intervention to improve financial abuse detection (n = 78) or a control group (no on-line educational intervention, n = 76). Both groups examined 28 scenarios of abuse (11 "signal" scenarios of risk and 17 "noise" scenarios of no risk). After the intervention group had received the on-line training, both groups then examined 15 further scenarios (5 "signal" and 10 "noise" scenarios).

resultsExperts were more certain than the novices, pre (Mean 70.61 vs. 58.04) and post intervention (Mean 70.84 vs. 63.04); and more consistent. The intervention group (mean 64.64) were more certain of abuse post-intervention than the control group (mean 61.41, p = 0.02). Signal detection analysis of sensitivity (A´) and bias (C) revealed that this was due to the intervention shifting the novices' tendency towards saying "at risk" (C post intervention -.34) and away from their pre intervention levels of bias (C-.12). Receiver operating curves revealed more efficient judgments in the intervention group.

conclusionAn educational intervention can improve judgements of financial abuse amongst novice professionals.

Indexed as

Financial ManagementProfessional CompetenceAgedDiagnosis, Computer-AssistedElder AbuseHealth PersonnelHumansRisk AssessmentSignal Detection, Psychological

Identifiers

PMID25547513
PMCPMC4322548

What OpenQuestion holds

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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.