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Patient health outcomes in psychiatric mental health nursing

2009· review· en· W2037303343 on OpenAlexafffund
Phyllis Montgomery, Don Rose, L. Carter

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2009
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsToronto Metropolitan UniversityLaurentian University
FundersMcGill University Health Centre
KeywordsPsychological interventionMental healthMoodMedicineMEDLINEPsychiatryInclusion (mineral)Quality of life (healthcare)Nursing Interventions ClassificationNursingPsychology

Abstract

fetched live from OpenAlex

This integrative literature review examined evidence concerning the relationship between psychiatric mental health nursing interventions and patient-focused outcomes. Empirical studies, published between 1997 and 2007, were identified and gathered by searching relevant databases and specific data sources. Although 156 articles were critically appraised, only 25 of them met the inclusion criteria. Findings from this review showed that the most frequently used outcome instruments assessed psychiatric symptom severity. Most of the instruments targeted two symptom categories: altered thoughts/perceptions and altered mood. Other outcome instruments were categorized in the following domains: self-care, functioning, quality of life and satisfaction. The most important finding of this review is the lack of consistently strong evidence to support decisions concerning which outcome instrument or combination of instruments to recommend for routine use in practice. Based on this review, additional research to conceptualize, measure and examine the feasibility of outcome instruments sensitive to psychiatric mental health nursing interventions is recommended.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.007
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.438
Teacher spread0.399 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations19
Published2009
Admission routes2
Has abstractyes

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