A systematic review on academic research productivity of postgraduate students in low- and middle-income countries
Bibliographic record
Abstract
BACKGROUND: While several individual studies addressing research productivity of post-graduate students are available, a synthesis of effective strategies to increase productivity and the determinants of productivity in low-income countries has not been undertaken. Further, whether or not this research from post-graduate students' projects was applied in evidence-informed decision-making was unknown. Therefore, we conducted a systematic review of literature to identify and assess the effectiveness of approaches that increase productivity (proportion published) or the application (proportion cited) of post-graduate students' research, as well as to assess the determinants of post-graduate students' research productivity and use. METHODS: We conducted a systematic review as per our a priori published protocol, also registered in PROSPERO (CRD42016042819). We searched for published articles in PubMed/MEDLINE and the ERIC databases through to July 2017. We performed duplicate assessments for included primary studies and resolved discrepancies by consensus. Thereafter, we completed a structured narrative synthesis and, for a subset of studies, we performed a meta-analysis of the findings using both fixed and random effects approaches. We aligned our results to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. RESULTS: We found 5080 articles in the PubMed (n = 3848) and ERIC (n = 1232) databases. After excluding duplicates (n = 33), we screened 5047 articles, of which 5012 were excluded. We then retrieved 44 full texts and synthesised 14, of which 4 had a high risk of bias. We did not find any studies assessing effectiveness of strategies for increasing publication nor citations of post-graduate research projects. We found an average publication proportion of 7% (95% CI 7-8%, Higgins I-squared 0.0% and Cochran's Q p < 0.01) and 23% (95% CI 17-29%, Higgins I-squared of 98.4% and Cochran's Q, p < 0.01) using fixed effects and random effects models, respectively. Two studies reported on the citation of post-graduate students' studies, at 17% (95% CI 15-19%) in Uganda and a median citation of 1 study in Turkey (IQR 0.6-2.3). Only one included study reported on the determinants of productivity or use of post-graduate students' research, suggesting that younger students were more likely to publish and cohort studies were more likely to be published. CONCLUSIONS: We report on the low productivity of post-graduate students' research in low- and middle-income countries, including the citation of post-graduate students' research in evidence-informed health policy in low- and middle-income countries. Secondly, we did not find a single study that assessed strategies to increase productivity and use of post-graduate students' research in evidence-informed health policy, a subject for future research.
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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 | 0.052 | 0.205 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.026 | 0.029 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".