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Record W4415623342 · doi:10.12968/bjnn.2024.0044

Evaluation of the transition experience of nurses and healthcare assistants to a neurology research role in a clinical research facility

2025· article· en· W4415623342 on OpenAlexaff
Carlito Adan, Alexandra Pone Lameirinhas, Maria Cristina G. Bautista, Daniele Giacoppo, Ana Marie Laxa, Euphrasia Ngum

Bibliographic record

VenueBritish Journal of Neuroscience Nursing · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsCanadian Nurses Association
Fundersnot available
KeywordsCLARITYClinical researchHealth careHealthcare deliveryHealth professionalsWork (physics)Patient care

Abstract

fetched live from OpenAlex

Background: Clinical staff experience challenges and barriers transitioning to a research role, despite it being a popular professional pathway. Aim: To understand the experiences of clinical staff transitioning to research that will assist in developing strategies to support them. Method: A questionnaire to was distributed to clinical research nurses and research healthcare assistants at a clinical research facility specialising in neurology in a large London hospital. Results: Findings showed that challenges resulted from unfamiliarity with the research role, while a lack of clarity about the roles and responsibilities, managing expectations and providing a conducive working environment were considered barriers. Overall, clinical research nurses and research healthcare assistants felt supported and believed that they had made the right career choice. Conclusion: Facilitating a smooth transition from clinical to research work will ensure a positive experience for staff and reinforce the best research delivery and outcomes at the research facility they have joined.

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)0.054
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0540.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.556
GPT teacher head0.676
Teacher spread0.119 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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