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Record W3106767188 · doi:10.1002/nop2.688

A rapid review exploring nurse‐led memory clinics

2020· review· en· W3106767188 on OpenAlexaff
Kerrie E. Luck, Shelley Doucet

Bibliographic record

VenueNursing Open · 2020
Typereview
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsSaint John Regional HospitalUniversity of New Brunswick
Fundersnot available
KeywordsCINAHLChecklistMEDLINENursingInclusion (mineral)MedicineNurse practitionersFamily medicinePsychologyHealth carePsychological intervention

Abstract

fetched live from OpenAlex

AIMS: To systematically explore the structures, functions, outcomes, roles and nursing credentials of memory clinics where nurses autonomously lead diagnosis and postdiagnostic care. DESIGN: A systematic rapid review was conducted. DATA SOURCES: MEDLINE (Ovid), CINAHL Full-Text (EBSCO) and EMBASE were systematically searched in December 2019 with no timeframe limitations imposed. REVIEW METHODS: The modified PRISMA checklist was used as a guide to facilitate the review. Articles identified were screened and assessed for inclusion criteria, and screening of reference lists of included studies was also completed. RESULTS: Six articles, published between 2011-2019, including two case studies, two descriptive reports, one qualitative study and one programme evaluation were included in the review. Nurse-led memory clinics were situated in community centres, on university campuses, hospitals and in general practitioners' offices. The services offered included assessment, diagnosis and treatment/postdiagnostic care. Nurse credentials included advanced practice nurses and a community psychiatric nurse who was a non-medical prescriber. Overall, there was low quantity and quality of evidence to evaluate outcomes.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.250
GPT teacher head0.469
Teacher spread0.219 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations7
Published2020
Admission routes1
Has abstractyes

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