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Record W4400387382 · doi:10.1111/add.16613

Will Australia's tightened prescription system reduce nicotine vaping among young people?

2024· article· en· W4400387382 on OpenAlexafffundabout
Shannon Gravely, Geoffrey T. Fong

Bibliographic record

VenueAddiction · 2024
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsOntario Institute for Cancer ResearchUniversity of Waterloo
FundersNational Cancer InstituteCanadian Institutes of Health ResearchOntario Institute for Cancer Research
KeywordsMedical prescriptionNicotineMedicineQuit smokingYoung adultEnvironmental healthSmokeSmoking cessationYouth smokingCigarette smokingTobacco controlAdvertisingPublic healthPsychiatryGerontologyBusinessPharmacologyNursingEngineering

Abstract

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Preventing uptake of e-cigarettes by youth is a central health policy objective; however, a balanced approach to e-cigarette regulation should also support the accessibility of e-cigarettes for adults seeking to quit smoking using e-cigarettes. Australia's 2011 e-cigarette prescription-only model has not prevented many youth and young adults from vaping, according to Hall's [1] recently published article. As Hall [1] points out, few people have obtained e-cigarettes via the medical prescription route under Australia's current ban on the sale of e-cigarettes on the open consumer market, therefore, many of the two million people who vaped in 2023 used illicit products. This was further corroborated by a recently published study by Borland et al. [2] that examined the proportion of Australian adults using prescription e-cigarettes to quit smoking. The authors reported that despite a modest increase between 2018 and 2022, only 16.5% of Australian adults who used an e-cigarette during a smoking cessation attempt received a prescription. Therefore, approximately four in five of adults who tried to quit smoking and used an e-cigarette to do so, obtained their products through illegal means. Globally, e-cigarettes have been the focus of a contentious debate regarding how they should be regulated, arising from the desire to protect youth and non-smoking young adults from vaping (and addicting a new generation to nicotine) while also considering how e-cigarettes—that contain substantially fewer toxicants than combustible cigarettes [3, 4]—can offer people who smoke a less harmful alternative. Countries and jurisdictions around the world have taken very different approaches, with some completely banning e-cigarettes with nicotine, some regulating them as tobacco products, some regulating them as distinct from tobacco products (e.g. as their own product category or as general consumer products), and others not having any regulatory framework at all [5]. The public health impact of e-cigarettes will depend on their substitutability for tobacco cigarettes. Some studies have found that e-cigarettes are good substitutes for cigarettes under specific price and marketplace conditions [6, 7]. Moreover, a recent Cochrane review concluded that there is high-certainty evidence that e-cigarettes increase quit rates compared to nicotine replacement therapy [8]. However, several real-world studies have shown that many people who smoke and initiate vaping also continue dual use [9]. Therefore, public health benefits from e-cigarette use will depend on whether those who smoke and vape actually quit smoking rather than continue with long-term dual use. We agree with Hall that restrictive forms of e-cigarette regulation may result in unintended consequences. First, under Australia's prescription scenario, many healthcare professionals (HPs) are not willing to provide prescriptions [10]. Many HPs appear to have significant concerns about the safety and efficacy of e-cigarettes for smoking cessation [10] and few recommend them to their patients [11, 12]. If a majority of physicians remain unwilling to provide e-cigarette prescriptions, allowing pharmacists to do so could increase access to e-cigarettes for therapeutic purposes [13]. Additionally, considering adding e-cigarettes to clinical practice smoking cessation guidelines may help encourage HPs to recommend them if an individual is committed to quitting smoking. Second, eliminating access to e-cigarettes may result in deterring people who would otherwise continue to smoke from considering and trying to switch to a less harmful alternative. Third, if individuals who smoke want to switch to vaping, they may seek out illicit vaping products. This appears to be the reality in many countries, including Australia, which was ranked ninth among countries in Chinese exports of e-cigarettes in 2023, despite their illegality [14]. Fourth, vaping may constitute a unique harm reduction opportunity for preventing relapse among those who have quit smoking, particularly if they are heavily dependent on nicotine [15-18]; however, more research is needed. Finally, people who have switched from smoking to vaping may be deterred from the inconvenience of repeatedly filling prescriptions if they continue long-term use (vape as a permanent alternative to cigarettes rather than using e-cigarettes as a short-term cessation aid). A balanced policy approach to e-cigarette regulation that supports the accessibility of e-cigarettes to adults who smoke, while also reducing their appeal, availability and affordability to people who do not smoke is complex. While the prescription-only model is one approach, there are other avenues that could be considered as suggested by the United Kingdom Royal College of Physicians [19] and by Hall [1], including e-cigarettes being sold as consumer products by licensed adult retailers under regulations requiring plain packaging, strict regulations on advertising and promotions and imposing strict age verification at the time of purchase. Shannon Gravely: Writing—original draft (lead). Geoffrey T. Fong: Writing—review and editing (equal). G.T.F. has served as an expert witness or consultant for governments defending their country's policies or regulations in litigation. S.G. and G.T.F are funded by the United States National Cancer Institute (P01 CA200512) and the Canadian Institutes of Health Research (FDN-148477). Additional support to G.T.F. is provided by a Senior Investigator Award from the Ontario Institute for Cancer Research. The authors do not have any relationships with the nicotine industry to disclose.

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 score0.201
Threshold uncertainty score0.507

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 communication0.0000.001
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 head0.026
GPT teacher head0.289
Teacher spread0.263 · 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

Citations3
Published2024
Admission routes3
Has abstractyes

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