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Record W2442921303 · doi:10.1080/10376178.2016.1194726

Perceived training needs of nurses working with mentally ill patients

2016· article· en· W2442921303 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueContemporary Nurse · 2016
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsBrandon UniversityUniversity of Manitoba
Fundersnot available
KeywordsMental healthCompetence (human resources)PsychosocialNursingMedicineMentally illHealth carePsychologyPsychiatryMental illness

Abstract

fetched live from OpenAlex

Introductio n: In Malaysia, nurses form a significant part of the clinical mental health team, but the current level of training in mental health results in suboptimal nursing care delivery. METHODS: For this study 220 registered nurses and medical assistants working with the mentally ill completed a structured questionnaire. The purpose of this study was to explore perceived competence in mental healthcare and the training needs of nurses working with mentally ill patients in inpatient mental healthcare facilities. RESULTS: The skills perceived as important for practicing in mental health varied among the nurse participants. Post basic training in mental health was significantly related to perceived competence in patient mental state assessment (p=0.036), risk assessment for suicide (p=0.024), violence (p=0.044) and self-harm (p=0.013). CONCLUSION: There is little emphasis on psychosocial skills in current post basic mental health training in Malaysia.

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.

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 score0.249
Threshold uncertainty score0.946

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)0.0010.000

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 head0.077
GPT teacher head0.333
Teacher spread0.256 · 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