Strengthening Noncommunicable Disease Research Capacity and Chronic Disease Outcomes in Low- and Middle-Income Countries in South Asia: Implementation and Evaluation of the ASCEND Program
Bibliographic record
Abstract
This article describes the design, outcomes, challenges, and lessons learned from the ASian Collaboration for Excellence in Non-Communicable Disease (ASCEND) program, implemented between 2011 and 2015 in India, Sri Lanka, and Malaysia. The program involved a blended-delivery model, incorporating online and face-to-face training, mentoring, and supervision of trainees' research projects. Evaluation data were collected at baseline, 6, 12, 18, and 24 months. Intended outcomes, lessons, and challenges were summarized using a logic model. During the program period, 48 participants were trained over 2 cohorts in June 2011 and 2012. The trainees published 83 peer-reviewed articles between 2011 and 2015. Additionally, 154 presentations were given by trainees at national and international conferences. Underutilization of the online learning management system was an important challenge. Utilizing a combination of intensive face-to-face and online learning and mentoring of early career researchers in low- and middle-income countries has great potential to enhance the research capacity, performance, and outputs.
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How this classification was reachedexpand
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 | 0.020 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".