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Record W2118911163 · doi:10.1108/14717794200800005

An exploratory study of nurses' knowledge of antipsychotic drug use with older persons

2008· article· en· W2118911163 on OpenAlexaff
Christopher Armstrong-Esther, Brad Hagen, Christine Smith, Sherrill Snelgrove

Bibliographic record

VenueQuality in Ageing and Older Adults · 2008
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsAntipsychoticExploratory researchDescriptive statisticsMedicineNursingDescriptive researchNursing staffPsychiatryFamily medicineSchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

Aim: Previous research has documented the widespread use of antipsychotic drugs by nursing staff with older persons, although less is known about the knowledge that nurses actually have about these drugs. The purpose of this exploratory, descriptive study was to survey a sample of UK gerontological nurses from different work settings on their knowledge of antipsychotic drugs.Methods: An exploratory descriptive study design was utilised, whereby a sample of nursing staff was given a questionnaire developed to determine knowledge about antipsychotic drugs and their use with older persons. Questionnaires were distributed to 100 nursing staff, including registered general nurses, registered mental nurses, state enrolled nurses, nursing assistants and care assistants. Of the 100 questionnaires distributed, 62 were returned and 57 were completed substantially enough for data analysis.Results: Descriptive statistics including frequencies and means were calculated for demographic variables and the questionnaire responses. Results indicated that the use of antipsychotic drugs within the psychiatric hospital setting was substantial, with 43.7% of patients receiving antipsychotic drugs, for an average length of time of 1.8 years. Conclusions: Nursing staff participants from all three work settings revealed a number of significant knowledge gaps, particularly with regard to appropriate indications for antipsychotic drugs with older persons and the side-effects of antipsychotic drugs. Summary: This paper adds new information regarding the use of antipsychotic drugs in the nursing care of older people.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.159
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.049
GPT teacher head0.357
Teacher spread0.308 · 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

Citations16
Published2008
Admission routes1
Has abstractyes

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