Evidence map›Paper›PMID 39759213›Full record

ReviewIranian journal of public health2024

Unmet Need for Family Planning in Spatial Analysis: A Systematic Review.

Musafaah Musafaah, Hadrianti Haji Darise Lasari, Martya Rahmaniati Makful, Tris Eryando

Abstract readReview
In one paragraph

Review in Iranian journal of public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Musafaah MusafaahPublic Health Study Program, Faculty of Medicine and Health Sciences, Lambung Mangkurat University, Banjarbaru, South Kalimantan 70714, Indonesia.
Hadrianti Haji Darise LasariPublic Health Study Program, Faculty of Medicine and Health Sciences, Lambung Mangkurat University, Banjarbaru, South Kalimantan 70714, Indonesia.
Martya Rahmaniati MakfulDepartment of Biostatistics and Population Studies, Faculty of Public Health, Universitas Indonesia, Indonesia.
Tris EryandoDepartment of Biostatistics and Population Studies, Faculty of Public Health, Universitas Indonesia, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The unmet need for family planning is an indicator in monitoring and evaluating family planning programs in the decentralization era. Spatial analysis is an analytical tool that can understand the existence of family planning disparities among regions. This study aimed to conduct a systematic review of the application of spatial analysis in research related to the unmet need for family planning and to review its results. Methods: The databases used in the literature search are PubMed, Scopus, and SpringerLink. The keywords used in the search were: "unmet need for family planning" OR "unmet need for contraception" AND (spatial OR geographic). Full-text articles from 2013 to 2022 were included. Results: Of the 334 identified articles, 3 (three) articles were reviewed. The three studies used spatial analysis at the level of spatial data exploration by using global and local Moran Index tests, Getis-Ord Gi* local statistics, and natural break spatial techniques. Conclusion: The use of advanced spatial analysis such as GWR and other regression analyzes is needed to investigate factors associated with regionally specific unmet need for family planning so that policy makers can allocate resources effectively.

Indexed as

Family planningRegionalSpatial analysisSystematic reviewUnmet need

Identifiers

PMID39759213
PMCPMC11693811

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.