The Level of Unmet Need for Family Planning and Its Predictors among HIV‐Positive Women in Ethiopia: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background. Studies indicated that the need for family planning appears to be greater for human immuno‐deficiency virus‐ (HIV‐) positive women than the general population to reduce the risk of pediatrics HIV infection and related consequences of unintended pregnancy. We aimed to assess the level of unmet need for family planning and its predictors among HIV‐positive women in Ethiopia. Methods. Online databases such as PubMed, SCOPUS, EMBASE, HINARI, Google Scholar, and digital libraries of universities were used to search for studies to be included in this systematic review and meta‐analysis. Quality assessment of included studies was conducted using the Newcastle‐Ottawa Quality Assessment Scale (NOS). Data were extracted using the format prepared on Excel workbook and analyzed by the Stata 11 software. Cochran (Q test) and I2 test statistics were used to assess the heterogeneity of studies. Similarly, the funnel plot and Egger’s regression asymmetry test were used to assess publication bias. Result. This systematic review and meta‐analysis was conducted using nine primary studies with a total of 6,154 participants. The pooled prevalence of unmet need for family planning among HIV‐positive women was found to be 25.72% (95% CI: 21.63%, 29.81%). Participants age 15‐24 years ((OR = 3.12; 95% CI: 1.59, 6.11) I2 = 27.5%; p = 0.252), being illiterate ((OR = 2.69; 95% CI: 1.69, 4.26) I2 = 0.0%; p = 0.899), failure to discuss FP with partner ((OR = 3.38; 95% CI: 2.20, 5.18) I2 = 0.0%; p = 0.861), and no access to family planning information ((OR = 4.70; 95% CI: 2.83, 7.81) I2 = 0.0%; p = 0.993) were found to be a significant predictors of unmet need for family planning among HIV‐positive women. Conclusion. The level of unmet need for family planning among HIV‐positive women was found to be high in Ethiopia. Being young age, illiteracy, failed to discuss family planning issues with a partner, and no access to family planning information were found to be the significant predictors of unmet need for family planning among HIV‐positive women in Ethiopia. Improving information access and encouraging partners’ involvement in family planning counseling and services could reduce the level of unmet need for family planning.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.037 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".