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Record W1499044887

Barriers and facilitators to implementation of a metabolic monitoring protocol in hospital and community settings for second-generation antipsychotic-treated youth.

2011· article· en· W1499044887 on OpenAlexaff
Rebecca Ronsley, K.S. Raghuram, Jana Davidson, Constadina Panagiotopoulos

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsBC Children's HospitalUniversity of Toronto
Fundersnot available
KeywordsProtocol (science)MedicineNursingAntipsychoticConfidence intervalFamily medicineHealth professionalsMental healthHealth careMedical emergencyPsychiatrySchizophrenia (object-oriented programming)Alternative medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: 1) Assess perceived barriers associated with metabolic monitoring in second-generation antipsychotic (SGA)-treated youth; and 2) Propose a metabolic monitoring protocol (MMP) and implementation strategies. METHOD: Online surveys were created for community mental health teams (CMHTs) and BC Children's Hospital (BCCH) with questions designed to evaluate knowledge of physical health care, confidence, communication with primary care, and practical issues. RESULTS: 26/50 (52%) of CMHT and 44/111 (40%) of BCCH surveys were completed. While both groups agreed that monitoring is their responsibility, 26% of CMHTs and 35% of BCCH professionals agreed that providing information about SGA side-effects would influence medication adherence. CMHTs reported lower overall confidence and more practical issues as monitoring barriers. While higher overall confidence was reported at BCCH, there was still a substantial proportion (23%) of hospital professionals who reported not knowing what parameters to monitor and how frequently. Communication with primary care, including inadequate systems for sharing results and identifying responsibility for acting on abnormal results, appear to be common barriers shared by both settings. CONCLUSIONS: Barriers to metabolic monitoring were more frequently reported by CMHTs who had limited access to nursing staff. We propose hands-on training, educational resources, pre-printed orders, and regular quality assurance evaluation as facilitators to promote MMP uptake.

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)0.000
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 score0.067
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.064
GPT teacher head0.328
Teacher spread0.265 · 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

Citations17
Published2011
Admission routes1
Has abstractyes

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