ArticlePharmacy practice
Preferences based interventions to address the use of antibiotics without prescription: A discrete choice experiment.
Article in Pharmacy practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 2 syntheses or guidelines pooled it, 6 citations in OpenAlex.
- The Evolving Landscape of Discrete Choice Experiments in Health Economics: A Systematic Review.PharmacoEconomics · 2025Pooled it
- Eliciting parents' decision-making to antibiotic use for upper respiratory tract infections: A discrete choice experiment.Journal of global health · 2024Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn many countries, concerns have arisen over the population using antibiotics without consulting a physician. This practice can place patients at risk and increase antibiotic resistance in the community.
objectiveTo evaluate individuals' preferences regarding the use of antibiotics. The study also assessed the likely effectiveness of interventions aimed at reducing inappropriate use of antibiotics.
methodsA discrete choice experiment (DCE) was conducted in Bogotá, Colombia. The attributes were determined by a systematic literature review and four focus group sessions. The DCE included nine factors - cost, time to get attention, level of symptoms, efficacy, safety, among others- and one label -using or not antibiotics. Data analysis was carried out using a generalized multinomial logit (GMNL) model. Marginal probabilities of different sets of attributes' levels were compared to estimate the likely effectiveness of interventions.
resultsThe survey was administered to 222 participants from diverse socioeconomic backgrounds. The results suggest that participants preferred not taking antibiotics and having a physician as an advisor, but the probability of inappropriate antibiotic use increased as the waiting time or the cost of receiving advice rose. The pharmacy was the preferred source of antibiotics, and participants chose the pharmacy worker (nonprofessional) as an advisor over the nurse on the phone. In the absence of any interventions aimed at reducing the use of antibiotics, approximately 47.3% of people would misuse antibiotics. This reduces to 26.5% when people perceive the efficacy of the antibiotics as low and the potential risks of self-medicating as high. An alternative model using a nursing service would likely lower inappropriate use of antibiotics.
conclusionsEven though people prefer not using antibiotics or visiting a physician in case of disease rather than self-medicating, current access conditions might discourage them from appropriately use antibiotics. The results suggest that interventions that informing people about the risks of self-medication and the low efficacy might significantly reduce inappropriate use of antibiotics. Our results also suggest that programs that empower other health professionals to provide access to antibiotics would likely further lower inappropriate use.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.