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Record W4392130948 · doi:10.1016/j.jmir.2024.02.005

Research activity among diagnostic and therapeutic radiographers: An international survey

2024· article· en· W4392130948 on OpenAlexaff
Marcus Oliveira, Peter Hogg, Lisa Di Prospero, Stephen Lacey, Samar El-Farra, Safora Johansen

Bibliographic record

VenueJournal of medical imaging and radiation sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMentorshipMedical educationMedicineSurvey researchClinical PracticeData collectionVariety (cybernetics)PsychologyFamily medicineSociology

Abstract

fetched live from OpenAlex

INTRODUCTION: Various national solutions have been considered and implemented to address the factors which limit radiographer engagement in conducting research. Nevertheless, national literature continues to suggest that radiographer engagement in research remains low. The aim of this study was to extend the existing evidence base by conducting an international survey to assess diagnostic radiographers and therapeutic radiographers involvement with, barriers to and support mechanisms for research. METHODS: Data collection was obtained via an online questionnaire which was distributed by the International Society of Radiographers and Radiologic Technologists (ISRRT). The study population included an international sample of qualified diagnostic radiographers and therapeutic radiographers across clinical and academic contexts in a variety of different roles such as clinical practice, management, education and research. RESULTS: In total, 420 diagnostic radiographers and therapeutic radiographers completed the survey. Multiple reasons were identified that were considered to inhibit respondents from conducting research. 69.3% indicated a combination of reasons for lack of engagement with research, rather than one single issue. Examples of reasons include: lack of time, insufficient research funding, limited research expertise, and lack of a suitable mentorship scheme. CONCLUSION: A minor segment of survey respondents indicated involvement in research activity. Lack of dedicated time to research, mentors, and funding were among the main barriers to conduct research. Further research is required to explore what solutions are available to overcoming the barriers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.098
GPT teacher head0.485
Teacher spread0.387 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2024
Admission routes1
Has abstractyes

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