Methodology and reporting quality of 544 studies related to ageing: a continued discussion in setting priorities for ageing research in Africa
Bibliographic record
Abstract
Background The quality assessment provides information on the overall strength of evidence and methodological quality of a research design, highlighting the level of confidence the reader should place on the findings for decision making. This paper aimed to assess the quality (methodology and quality of reporting) of ageing studies in Sub-Saharan Africa (SSA). Method This paper is the second of a Four-Part Series paper of a previous systematic mapping review of peer-reviewed literature on ageing studies conducted in SSA. We updated the literature search to include additional 32 articles, a total of 544 articles included in this paper. Downs & Black checklist, Case Report guidelines checklist, the 45-items Lundgren et al. checklist, and the Mixed Method Appraisal Tool were used to assess the methodological quality of quantitative, case reports, qualitative, and mixed-method studies. Quality assessment was piloted and conducted in pairs for each study type. Depending on the checklist, each study was classified as excellent, good, fair, or poor. Result Of the 544 articles, we performed the quality assessment of a total of 451 quantitative studies [Randomized control trials (RCTs) and pre-post (n=15), longitudinal (n=122), case-control (n=15) and cross-sectional (n=300); 4 case reports, 74 qualitative and 15 mixed-method studies. Only 20.4% (n=111) articles were of high quality [one RCT, 27 longitudinal, 4 case-control, 48 cross-sectional studies, 19 qualitative, and 12 mixed-method studies]. The remaining 433 were rated as moderate quality (n=292, 53.7%), fair quality (n = 96, 17.7%) and poor quality (n = 45, 8.2%). Most (80%) quantitative articles’ sample size is small, resulting in insufficient power to detect a clinically or significant important effect. Three-quarter (75%) of the qualitative studies did not report their research team characteristics and a reflexivity component of the 45-items Lundgren et al. checklist. Mixed-method studies with low quality did not report the qualitative studies properly. Conclusion We conclude that the methodological and quality reporting of published studies on ageing in SSA show variable quality, albeit primarily moderate quality, against high quality. Studies with a large sample size are recommended, and qualitative researchers should provide a section on research team members’ characteristics and reflexivity in their paper or as an appendix.
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 | 0.716 | 0.869 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.030 | 0.031 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".