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Record W2166754231 · doi:10.3109/14659891.2013.790497

Survey of Ontario health professionals’ knowledge, attitudes and beliefs of alcohol-related harms: key findings

2013· article· en· W2166754231 on OpenAlexaffabout
Elizabeth Manafò, Norman Giesbrecht, Romilla Gupta

Bibliographic record

VenueJournal of Substance Use · 2013
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsToronto Public HealthCentre for Addiction and Mental HealthToronto Metropolitan University
Fundersnot available
KeywordsHarmHealth professionalsHealth promotionMedicineHealth careHarm reductionNursingPublic healthAlcohol consumptionHealth educationEnvironmental healthFamily medicinePsychologyAlcoholSocial psychology

Abstract

fetched live from OpenAlex

Introduction: The purpose of this study is to explore the knowledge, attitudes and beliefs among health and health care professionals in Ontario of the risks associated with excessive alcohol use to strengthen attention on alcohol as a key modifiable risk factor for cancer and other health harms.Methods: This study used an online survey to answer the following research questions: (1) What is the level of awareness of excessive alcohol use as a risk factor for injuries, cancer and chronic diseases among health and health care professionals? (2) How do you address alcohol consumption and alcohol-related harm reduction in practice? and (3) What opportunities and barriers exist for health care professionals in addressing alcohol-related harm in practice?Results: Five hundred and eight-one participants responded to the online survey. The majority of respondents were Dietitians, Public Health Nurses, Nurses, Health Promotion Consultants and Health Educators. Results include participant’s attitudes, opinions and knowledge on the identified research questions.Discussion & Conclusion: Results from this survey will be disseminated to promote health and health care professionals awareness surrounding issues of alcohol consumption and alcohol-related harm, with emphasis on physicians and other Allied Health Professionals (including Registered Dietitians and Public Health Nurses). Several knowledge exchange areas are identified.

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 score0.033
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.069
GPT teacher head0.336
Teacher spread0.267 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

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