A systematic review of Demographic and Health Surveys: data availability and utilization for research
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.
Bibliographic record
Abstract
OBJECTIVE: To systematically review the public health literature to assess trends in the use of Demographic and Health Survey (DHS) data for research from 1984 to 2010 and to describe the relationship between data availability and data utilization. METHODS: The MEASURE DHS web site was searched for information on all population-based surveys completed under the DHS project between 1984 and 2010. The information collected included the country, type of survey, survey design, fieldwork period and certain special features, such as inclusion of biomarkers. A search of PubMed was also conducted to identify peer-reviewed articles published during 2010 that analysed DHS data and included an English-language abstract. Trends in data availability and in the use of DHS data for research were assessed through descriptive, graphical and bivariate linear regression analyses. FINDINGS: In total, 236 household surveys under the DHS project were completed across 84 countries during 2010. The number of surveys per year has remained constant, although the scope of the survey questions has expanded. The inclusion criteria were met by 1117 peer-reviewed publications. The number of publications has increased progressively over the last quarter century, with an average annual increment of 4.3 (95% confidence interval, CI: 3.2-5.3) publications. Trends in the number of peer-reviewed publications based on the use of DHS data were highly correlated with trends in funding for health by the Government of the United States of America and globally. CONCLUSION: Published peer-reviewed articles analysing DHS data, which have increased progressively in number over the last quarter century, have made a substantial contribution to the public health evidence base in developing countries.
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 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 | 0.335 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it