Setting priorities for ageing research in Africa:A systematic mapping review of 512 studies from sub-Saharan Africa
Bibliographic record
Abstract
Background In 2040, the older population’s growth rate in sub-Saharan Africa (SSA) will be faster than those experienced by developed nations since 1950. In preparation for this growth, the National Institute on Aging commissioned the National Academies’ Committee on Population to organize a workshop on advancing aging research in Africa. This meeting provided a platform for discussing some areas requiring improvement in aging research in SSA regions. We believed that conducting a systematic review of peer-reviewed articles to set priorities for aging research in SSA is warranted. Therefore, this article is the first in a Four-Part series that summaries the types and trends of peer-reviewed studies in SSA. Methods This systematic mapping review followed the Search-Appraisal-Synthesis-Analysis Framework. We systematically searched multiple databases from inception till February 2021 and included peer-reviewed articles conducted with/for older adults residing in SSA. Conventional content analysis was employed to categorize studies into subject-related areas. Results We included 512 studies (quantitative = 426, qualitative = 71 and mixed-method = 15). Studies were conducted in 32 countries. Quantitative studies included were observational studies: cross-sectional (n = 250, 59%), longitudinal (n = 126, 30%), and case-control (n = 12, 3%); and experimental studies: pre-post design (n = 4, 1%), randomized control trial (RCT, n = 12, 3%); and not reported (n = 21, 5%). Fifteen qualitative studies did not state their study design; where stated, study design ranged from descriptive (n = 14, 20%), ethnography (n = 12, 17%), grounded theory (n = 7, 10%), narrative (n = 5, 7%), phenomenology (n = 10, 14%), interpretative exploratory (n = 4, 6%), case studies (n = 4, 6%). Of the 15 mixed-method studies, seven did not state their mixed-method design. Where stated, design includes concurrent (n = 1), convergent (n = 1), cross-sectional (n = 3), informative (n = 1), sequential exploratory (n = 1) and retrospective (n = 2). Studies were classified into 30 (for quantitative studies) and seven (for qualitative and mixed-method) subject-related areas. HIV/AIDs-related and non-communicable diseases-related studies were the most predominant subject-related areas. No studies explored the transdisciplinary co-production of interventions. Conclusions There are glaring gaps in ageing research in SSA, especially mixed-methods and RCTs. A large number of studies focused on HIV/AIDs and non-communicable disease-related studies. National and international funding agencies should set up priority funding competitions for transdisciplinary collaborations in ageing 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 | 0.055 | 0.163 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.050 | 0.039 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 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".