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Alberta Healthcare Professionals’ Perceptions of Prescription Drug Misuse

2016· article· en· W3016861993 on OpenAlexaffvenueabout
Opal A. McInnis, Paula Robeson, Sheena A. Gereghty, Amy J. Porath-Waller

Bibliographic record

VenueThe Canadian Journal of Addiction · 2016
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsCanadian Centre on Substance Use and Addiction
Fundersnot available
KeywordsMedical prescriptionHealth professionalsMedicineNursingHealth carePublic healthLimitingFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Background: The harms associated with the use of psychoactive prescription drugs are a serious public health problem. Healthcare professionals play an important part in addressing this problem; however, there is limited research examining their role in identifying and preventing prescription drug misuse (PDM). Methods: The perceptions of 1,063 Canadian healthcare professionals (HCPs) (physicians, registered nurses and nurse practitioners, pharmacists, and dentists) regarding PDM were collected using an anonymous online survey. Results: Findings revealed that only 27.7% of HCPs felt adequately supported in addressing PDM. HCPs did not feel overly effective in preventing or addressing PDM; they indicated several barriers such as inadequate knowledge and training, as well as those related to communication issues with fellow HCPs. Interpretation: This study supports the need to increase the capacity of HCPs to identify and address PDM among patients. This could be accomplished through clearer protocols and training on the clinical signs of PDM, as well as strategies aimed at facilitating better communication among healthcare providers. By limiting some of the existing barriers, HCPs will be better prepared to address this public health crisis. Contexte: Les méfaits associés à l'utilisation de substances psychoactives disponibles sous prescription sont un problème sérieux de santé publique. Les professionnels de la santé ont un rôle important à jouer pour faire face à ce problème, mais peu d’études se sont penchées sur leur rôle dans l'identification et la prévention de l'abus de médicaments prescrits (AMP). Méthodes: La perception de 1 063 professionnels canadiens de la santé (PS) (médecins, infirmières, infirmières cliniciennes, pharmaciens et dentistes) a été recueilli au sujet de l'AMP à l'aide d'un sondage anonyme en ligne. Résultats: Les données révèlent que seulement 27,7% des PS se sentent adéquatement supportés pour aborder l'AMP. Les PS ne se sont pas sentis trop efficaces à prévenir et à faire face à l'AMP; ils ont rapporté plusieurs obstacles tels que les connaissances et la formation inadéquates et les obstacles reliés aux problèmes de communication avec les collègues. Interprétation: Cette étude réitère le besoin d'améliorer les capacités des PS à identifier et faire face à l'AMP parmi leurs patients. Ceci pourrait être atteint avec des protocoles plus clairs et des formations sur les signes cliniques de l'AMP, ainsi qu'avec des stratégies visant à faciliter de meilleures communications entre les PS. En minimisant quelques-unes des barrières existantes, les PS seront mieux outillés pour s'attaquer à cette crise de santé publique.

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 score0.121
Threshold uncertainty score0.993

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 head0.067
GPT teacher head0.372
Teacher spread0.305 · 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

Citations2
Published2016
Admission routes3
Has abstractyes

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