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Record W2989575021 · doi:10.1186/s41256-019-0123-1

A scoping review of non-communicable disease research capacity strengthening initiatives in low and middle-income countries

2019· review· en· W2989575021 on OpenAlex
Tilahun Haregu, Allison Byrnes, Kavita Singh, Thirunavukkarasu Sathish, Naanki Pasricha, Kavumpurathu Raman Thankappan, Brian Oldenburg

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Health Research and Policy · 2019
Typereview
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsPopulation Health Research Institute
FundersFogarty International CenterNational Institutes of HealthUniversity of Melbourne
KeywordsCapacity buildingNon-communicable diseaseLow and middle income countriesChecklistMedicineCapacity developmentPublic healthPolitical scienceDeveloping countryPublic relationsEconomic growthEnvironmental planningNursingPsychologyGeography

Abstract

fetched live from OpenAlex

INTRODUCTION: As the epidemic of non-communicable diseases (NCDs) is rapidly developing in low and middle-income countries (LMICs), the importance of local research capacity and the role of contextually relevant research in informing policy and practice is of paramount importance. In this regard, initiatives in research capacity strengthening (RCS) are very important. The aim of this study was to review and summarize NCD research capacity strengthening strategies that have been undertaken in LMICs. METHODS: Using both systematic and other literature search, we identified and reviewed NCD-RCS initiatives that have been implemented in LMICs and reported since 2000. Information was extracted from published papers and websites related to these initiatives using a semi-structured checklist. We extracted information on program design, stakeholders involved, and countries of focus, program duration, targeted researchers, disease focus, skill/capacity areas involved and sources of funding. The extracted information was refined through further review and then underwent a textual narrative synthesis. RESULTS: We identified a number of different strategies used by research capacity strengthening programs and in the majority of initiatives, a combination of approaches was utilized. Capacity strengthening and training approaches were variously adapted locally and tailored to fit with the identified needs of the targeted researchers and health professionals. Most initiatives focused on individual level capacity and not system level capacity, although some undoubtedly benefited the research and health systems of LMICs. For most initiatives, mid-term and long-term outcomes were not evaluated. Though these initiatives might have enhanced research capacity in the immediate term, the sustainability of the results in the long-term remains unknown. CONCLUSION: Most of NCD-RCS initiatives in LMICs focused on building individual capacity and only a few focused explicitly on institutional level capacity strengthening. Though many of the initiatives appear to have had promising short-term outcomes, evidence on their long-term impact and sustainability is lacking.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.094
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.348
GPT teacher head0.582
Teacher spread0.234 · 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