Evidence map›Paper›PMID 36969539›Full record

ArticleUltrasound (Leeds, England)2022

Exploring the use of knobology for image optimisation in final year sonography students.

Samantha Mallard, Narelle Kennedy, Afrooz Najafzadeh Abriz, Ann Quinton

Abstract read
In one paragraph

Article in Ultrasound (Leeds, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Samantha MallardXray and Imaging, Maleny, Qld, Australia.
Narelle KennedyDiscipline of Obstetrics, Gynaecology and Neonatology, Sydney Medical School Nepean, University of Sydney, Nepean Hospital, Penrith, NSW, Australia.ORCID https://orcid.org/0000-0003-0801-6317
Afrooz Najafzadeh AbrizMedical Sonography School of Health, Medical and Applied Science, Central Queensland University, Perth, WA, Australia.
Ann QuintonMedical Sonography School of Health, Medical and Applied Science, Central Queensland University, Perth, WA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Image optimisation is essential for acquisition of quality images in ultrasound and critical to the diagnostic ability of the examination. These skills are taught to sonography students early in their education, but research has found that retention of non-rehearsed knowledge decreases significantly after a year. The aim of this study was to determine which optimisation tools (knobology) final year sonography students use, how often and why they chose to adjust parameters and assess barriers to optimisation of knobology tools. Methods: A prospective study using data from an anonymous online survey of 34 final year sonography students. Results: Survey results showed that 19/34 (55%) of students "frequently" optimise all Doppler settings and 23/34 (67%) of students "frequently" optimise basic parameter settings (depth, focus, time gain compensation). Time constraints (24/34 (70%)) and loss of gained knowledge of sonography principles and instrumentation (17/34 (50%)) were the major barriers to the use of knobology. The majority 28/34 (82%) believed they would benefit from further training. Conclusion: This study demonstrates that although most students are optimising settings to improve image quality, sonography principles and instrumentation knowledge loss and time constraints prevent students from maximising machine capabilities. This study supports the need for further training prior to final year clinical placement.

Indexed as

imaging qualityInstrumentationphysicssonographic equipmentultrasound

Identifiers

PMID36969539
PMCPMC10034655

What OpenQuestion holds

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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.