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Reducing alcohol‐related damage in populations: rethinking the roles of education and persuasion interventions

2007· review· en· W2005861891 on OpenAlexaff
Norman Giesbrecht

Bibliographic record

VenueAddiction · 2007
Typereview
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsPersuasionPsychological interventionCognitive reframingEnvironmental healthAlcohol educationPopulationAlcohol consumptionConsumption (sociology)MedicinePublic healthPsychologyPublic economicsSocial psychologyAlcoholPsychiatryNursingEconomicsSociology

Abstract

fetched live from OpenAlex

AIM: In order to potentially enhance the impact of most effective policies and interventions in reducing the population level damage from alcohol, a new perspective with regard to education and persuasion interventions is offered. METHODS: Recent studies were examined on the global burden of alcohol and also those focusing on the links between overall consumption and high-risk drinking, on one hand, and drinking-related damage on the other hand. A synopsis of main findings from reviews and other analysis provides the basis for conclusions about the impacts of education and persuasion interventions. RESULTS: There is a relative absence of evidence of the effectiveness of education and persuasion in reducing consumption, curtailing high-risk drinking or reducing damage from alcohol. This is in contrast to the rising levels of damage from alcohol, and also to the demonstrated effectiveness of certain alcohol policies and interventions, as summarized in Babor et al. CONCLUSIONS: Given that only a small fraction of education and persuasion interventions have any positive impact, generating 'more of the same' is not an impact-effective and cost-efficient approach. Therefore, interventions that have not been shown to be effective need to be phased out and those most effective and of widest scope should receive more attention and enhanced resources. A reframing of the roles and foci of persuasion interventions is advised, including, for example, focusing on informing policy-makers, and stimulating public discussions about the rationale of alcohol policies and the roles that citizens can play in promoting and supporting these policies.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.143
GPT teacher head0.422
Teacher spread0.279 · 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 designOther design
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

Citations44
Published2007
Admission routes1
Has abstractyes

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