Determining factors of observance of antiretroviral treatments in Cameroon during the start-up period (2000-2002).
Bibliographic record
Abstract
OBJECTIVE: highlight the socioeconomic and environmental determining factors of long-term observance to antiretroviral treatments in developing countries. METHOD: The regularity of antiretroviral prescriptions renewal at the central pharmacy of the Yaounde Central Hospital (Cameroon) was measured through analysing the medical and pharmaceutical files of 230 patients over the 21 month start-up period. 99 patients were also interviewed during the last six months. The determining factors were analysed according to various socio-economic criteria, linked with the longitudinal study of treatment observance. RESULTS: The huge price decrease of HIV treatments during the start-up period was conducive to an increase in new treatments by a factor 5.76. In this context of an exploding demand, the paper shows that observance is firstly dependent on quality information about illness and treatment protocols, while longer term adherence is partly dependent on financial capability, and includes the strong influence of living conditions and behaviours. CONCLUSION: The paper recommends the introduction of free treatment as an objective in national sector policies and the organisation of a long term following-up of patients. In the African context of poverty and actual decentralisation of healthcare, the question of the availability of human resources is profoundly enhanced.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".