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Record W2778221760 · doi:10.1071/ah16296

When is a medicine unwanted, how is it disposed, and how might safe disposal be promoted? Insights from the Australian population

2017· article· en· W2778221760 on OpenAlex
Emilie Bettington, Jean Spinks, Fiona Kelly, Alejandra Gallardo‐Godoy, Son Nghiem, Amanda Wheeler

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAustralian Health Review · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersAustralian Government
KeywordsDispose patternPublic healthEnvironmental healthMedicineQuarter (Canadian coin)PopulationGarbagePopulation healthDescriptive statisticsGovernment (linguistics)BusinessGeographyNursingEngineering

Abstract

fetched live from OpenAlex

Objective The aim of the present study was to explore disposal practices of unwanted medicines in a representative sample of Australian adults, compare this with previous household waste surveys and explore awareness of the National Return and Disposal of Unwanted Medicines (RUM) Project. Methods A 10-min online survey was developed, piloted and conducted with an existing research panel of adult individuals. Survey questions recorded demographics, the presence of unwanted medicines in the home, medicine disposal practices and concerns about unwanted medicines. Descriptive statistical analyses and rank-ordered logit regression were conducted. Results Sixty per cent of 4302 respondents reported having unwanted medicines in their household. Medicines were primarily kept just in case they were needed again and one-third of these medicines were expired. Two-thirds of respondents disposed of medicines with the household garbage and approximately one-quarter poured medicines down the drain. Only 17.6% of respondents had heard of the RUM Project, although, once informed, 91.7% stated that they would use it. Respondents ranked the risk of unintended ingestion as the most important public health message for future social marketing campaigns. Conclusions Respondents were largely unaware of the RUM Project, yet were willing to use it once informed. Limited awareness could lead to environmental or public health risks, and targeted information campaigns are needed. What is known about the topic? There is a growing international evidence base on how people dispose of unwanted medicines and the negative consequences, particularly the environmental effects of inappropriate disposal. Although insight into variation in disposal methods is increasing, knowledge of how people perceive risks and awareness of inappropriate disposal methods is more limited. What does this paper add? This study provides evidence of inappropriate medicines disposal and potential stockpiling of medicines in Australian households that could contribute to environmental and/or public health risks. It also reveals possible trends towards a higher frequency of inappropriate disposal practices in the Australian context. Insights into respondents' perceptions of associated risks and awareness of a national scheme for appropriate disposal of medicines have not previously been reported. What are the implications for practitioners? The findings of the present study provide important insights for all health professionals as stakeholders in the quality use of medicines. It is important for those health professionals who assist consumers to manage their medicines to have strategies in place that routinely identify potential stockpiling and inform consumers about appropriate methods of medicines disposal. Although the findings of this study are specific to the Australian context, they may usefully inform policy, public health campaigns and the individual practices of health professionals and other stakeholders in promoting the quality use of medicines nationally and internationally.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.119
GPT teacher head0.381
Teacher spread0.262 · 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