Effectiveness of a community-based intervention (Konga model) to address the factors contributing to viral load suppression among children living with HIV in Tanzania: a cluster-randomized clinical trial protocol
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This study aims to test the effectiveness of a community-based intervention (Konga model) to improve viral-load suppression in children living with human immunodeficiency virus (HIV) and enrolled in care and treatment centers in Tanzania mainland. The study will be a cluster-randomized clinical trial study designed with both intervention and control arms. The study will involve 268 children with a viral load of >1000 copies/ml who are aged between 2 and 14 years. The children will be randomly allocated into the intervention and control arms. The intervention will include three distinct activities: adherence and retention counseling, psychosocial support, and comorbidity screening (i.e. tuberculosis). The outcome of the study will be assessment of the success of the intervention to increase medication adherence with the immediate result of reducing the viral load below 1000 copies/ml. Descriptive statistics will be used to calculate the mean, median, standard deviation, and interquartile range of continuous data. We will use frequencies and percentages to summarize categorical data. As for the primary outcome (proportion of HIV-infected children with viral suppression), we will compare the proportion of successful participants in the intervention and control arms. Proportions and tests for different proportions will be used as a measure of improvement. All statistical tests will be two-sided and P < 0.05 will be considered statistically significant.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.047 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it