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Record W4407177647 · doi:10.1080/16549716.2025.2458935

Irrational medicine use and its associated factors in conflict-affected areas in Mali: a cross-sectional study

2025· article· en· W4407177647 on OpenAlexaff
Mohamed Ali Ag Ahmed, Alassane Seydou, Issa Coulibaly, Karina Kielmann, Raffaella Ravinetto

Bibliographic record

VenueGlobal Health Action · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCross-sectional studyIrrational numberMedicineGeographyPsychologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Rational use of essential medicines is a critical step towards prevention and treatment of many illnesses. However, it represents a significant challenge worldwide, and particularly for under-resourced health systems in conflict-affected areas. OBJECTIVE: To assess barriers to rational use of essential medicines at primary healthcare level in conflict-affected areas of Mali. METHODS: We conducted a cross-sectional study in twenty randomly selected community health centres (CHCs) in four health districts, by applying the World Health Organisation and International Network on Rational Use of Drugs core forms for the rational use of medicines. Seven hundred eighty-nine (789) prescriptions were retrospectively selected and analysed; four hundred forty-three (443) patients were interviewed: and health facility-related indicators were collected prospectively from the 20 CHCs. RESULTS: The average number of medicines per prescription was 3.89 ± 1.83; out of these, 94.0% were prescribed by generic name, and 91.0% belonged to Mali's National List of Essential Medicines. Overall, 68% of the assessed prescriptions included antibiotics; 58% included injectables; and 75.79% were characterized by polypharmacy, i.e. more than two medicines per prescription. In multivariate analysis, the study area and prescriber's sex were significantly associated with polypharmacy; prescriber's seniority and training were associated with antibiotic overprescription; the study area, prescriber's sex and seniority were associated with overprescription of injectables. Moreover, the average price of prescriptions was high in relation to average local income, likely making these unaffordable for many households. CONCLUSION: Excessive polypharmacy and overprescription of antibiotics and injectables undermine the performance of the local health system and the achievement of intended therapeutic outcomes. Our findings provide a solid basis for more targeted and multidisciplinary research, to further inform relevant stakeholders on how best to mitigate the impact of conflict on the rational use of medicines.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.385
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes1
Has abstractyes

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