Evidence map›Paper›PMID 33439888›Full record

ArticlePloS one2021

Understanding drivers of family planning in rural northern India: An integrated mixed-methods approach.

Mokshada Jain, Yael Caplan, B M Ramesh, Shajy Isac, Preeti Anand, Elisabeth Engl, Shiva Halli, Hannah Kemp, James Blanchard, Vikas Gothalwal and 3 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

13 authors.

Mokshada JainSurgo Foundation, Washington, District of Columbia, United States of America.
Yael CaplanSurgo Foundation, Washington, District of Columbia, United States of America.
B M RameshCentre for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Shajy IsacCentre for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.ORCID 0000-0002-4272-7748
Preeti AnandCentre for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Elisabeth EnglSurgo Foundation, Washington, District of Columbia, United States of America.
Shiva HalliCentre for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Hannah KempSurgo Foundation, Washington, District of Columbia, United States of America.
James BlanchardCentre for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Vikas GothalwalCentre for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Vasanthakumar NamasivayamCentre for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Pankaj KumarNational Health Mission, Government of Uttar Pradesh, Lucknow, Uttar Pradesh, India.
Sema K SgaierSurgo Foundation, Washington, District of Columbia, United States of America.ORCID 0000-0002-8311-2686

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFamily planning is a key means to achieving many of the Sustainable Development Goals. Around the world, governments and partners have prioritized investments to increase access to and uptake of family planning methods. In Uttar Pradesh, India, the government and its partners have made significant efforts to increase awareness, supply, and access to modern contraceptives. Despite progress, uptake remains stubbornly low. This calls for systematic research into understanding the 'why'-why people are or aren't using modern methods, what drives their decisions, and who influences them.

methodsWe use a mixed-methods approach, analyzing three existing quantitative data sets to identify trends and geographic variation, gaps and contextual factors associated with family planning uptake and collecting new qualitative data through in-depth immersion interviews, journey mapping, and decision games to understand systemic and individual-level barriers to family planning use, household decision making patterns and community level barriers.

resultsWe find that reasons for adoption of family planning are complex-while access and awareness are critical, they are not sufficient for increasing uptake of modern methods. Although awareness is necessary for uptake, we found a steep drop-off (59%) between high awareness of modern contraceptive methods and its intention to use, and an additional but smaller drop-off from intention to actual use (9%). While perceived access, age, education and other demographic variables partially predict modern contraceptive intention to use, the qualitative data shows that other behavioral drivers including household decision making dynamics, shame to obtain modern contraceptives, and high-risk perception around side-effects also contribute to low intention to use modern contraceptives. The data also reveals that strong norms and financial considerations by couples are the driving force behind the decision to use and when to use family planning methods.

conclusionThe finding stresses the need to shift focus towards building intention, in addition to ensuring access of trained staff, and commodities drugs and equipment, and building capacities of health care providers.

Indexed as

Contraception BehaviorFamily Planning ServicesAdolescentAdultContraceptionContraceptive AgentsFemaleHumansIndiaIntentionMaleMiddle AgedRural PopulationSex EducationSexual BehaviorYoung AdultContraceptive Agents

Identifiers

PMID33439888
PMCPMC7806122

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.