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Record W4400781981 · doi:10.4314/ahs.v24i2.6

Prevalence of unmet need for family planning and unintended pregnancies among women of reproductive age living with HIV in sub-Saharan Africa: a systematic review and meta-analysis

2024· review· en· W4400781981 on OpenAlexaff
Hafidha Mhando Bakari, Oluwafemi David Alo, Mariam Salim Mbwana, Swalehe Mustafa Salim, Emilie Ludeman, Taylor Lascko, Habib O. Ramadhani

Bibliographic record

VenueAfrican Health Sciences · 2024
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsScience World at Telus World of Science
Fundersnot available
KeywordsMedicineUnintended pregnancyPregnancyFamily planningConfidence intervalMeta-analysisEnvironmental healthDemographyReproductive healthLimitingPopulationResearch methodology

Abstract

fetched live from OpenAlex

Introduction: Family planning is an effective intervention for women living with HIV who do not desire to have children to reduce vertical transmission and infant- and pregnancy-related mortality. Objectives: We aimed to evaluate the prevalence of unmet need for family planning (UFP) and unintended pregnancies among women living with HIV in sub-Saharan Africa. Methods: This was a systematic review that searched databases from March 2007 to December 2021. UFP was defined as women who were sexually active and did not desire to have additional children (unmet need for limiting), or who delayed their next pregnancy (unmet need for spacing) but were not using any contraception. Unintended pregnancies were defined as women who reported that their last pregnancy was unintended. Forest plots were used to present the pooled prevalence with a 95% confidence interval (CI). Results: Total of 35 articles were included. Overall, the pooled prevalence of UFP was 30.1% (95%CI, 26.4-33.9). The pooled prevalence of unmet need for spacing was 11.9% and 14.2% for limiting.. The pooled prevalence of unintended pregnancy was 16.5% (95%CI, 9.4-25.1). Conclusion: Three in ten women of reproductive age living with HIV in Africa have UFP. Efforts to prevent unsafe abortions from unintended pregnancies are needed to minimize the UFP.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.242
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.148
GPT teacher head0.415
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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