Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".