TEAM-UP: mixed-methods data for understanding traditional and modern contraceptive use dynamics in four sub-Saharan African countries

This Data Article describes a novel dataset from the “Re-Examining Traditional Method Use” (TEAM-UP) project, which systematically collected data on the measurement of and motivations for use of non-modern (traditional and folkloric) contraceptive methods and/or modern methods, in four sub-Saharan African countries: the Democratic Republic of Congo, Ghana, Kenya, and Nigeria. TEAM-UP comprises four datasets (two quantitative and two qualitative), enabling comprehensive analyses of: 1) the impact of methodological innovations on reporting of modern and non-modern method use, and prevalence estimates, 2) motivations for, and user experiences related to traditional and folkloric methods, and 3) contraceptive use dynamics across all methods and method types, including non-use. Data collection was conducted in four stages: qualitative (Stage 1; 54 focus group discussions and 81 key informant interviews) and quantitative (Stage 2; n=918) pilots, followed by women’s surveys (Stage 3; n=13,625) and follow-up qualitative in-depth interviews (Stage 4; 469 interviews). The main TEAM-UP survey data are publicly available, with both the pilot and follow-up in-depth qualitative data available upon vetted request.

Authors

Publication Details

Journal
London School of Economics and Political Science Research Online (London School of Economics and Political Science)
Published
2026-01-21
Primary Topic
Global Maternal and Child Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

TEAM-UP: mixed-methods data for understanding traditional and modern contraceptive use dynamics in four sub-Saharan African countries

Jacques Emina, Eliya M. Zulu, John Mushomi, Saseendran Pallikadavath et al.
London School of Economics and Political Science Research Online (London School of Economics and Political Science)
Global Maternal and Child Health
article

TEAM-UP: mixed-methods data for understanding traditional and modern contraceptive use dynamics in four sub-Saharan African countries

Jacques Emina, Eliya M. Zulu, John Mushomi, Saseendran Pallikadavath, Elizabeth Omoluabi, Themba Mzembe, Maame Peterson, Ernestina Coast, Funmilola M. OlaOlorun, Jamaica Corker, Nurudeen Alhassan, Naa Dodua Dodoo, Nyovani Janet Madise, F. Nii-Amoo Dodoo
article en

Abstract

This Data Article describes a novel dataset from the “Re-Examining Traditional Method Use” (TEAM-UP) project, which systematically collected data on the measurement of and motivations for use of non-modern (traditional and folkloric) contraceptive methods and/or modern methods, in four sub-Saharan African countries: the Democratic Republic of Congo, Ghana, Kenya, and Nigeria. TEAM-UP comprises four datasets (two quantitative and two qualitative), enabling comprehensive analyses of: 1) the impact of methodological innovations on reporting of modern and non-modern method use, and prevalence estimates, 2) motivations for, and user experiences related to traditional and folkloric methods, and 3) contraceptive use dynamics across all methods and method types, including non-use. Data collection was conducted in four stages: qualitative (Stage 1; 54 focus group discussions and 81 key informant interviews) and quantitative (Stage 2; n=918) pilots, followed by women’s surveys (Stage 3; n=13,625) and follow-up qualitative in-depth interviews (Stage 4; 469 interviews). The main TEAM-UP survey data are publicly available, with both the pilot and follow-up in-depth qualitative data available upon vetted request.

London School of Economics and Political Science Research Online (London School of Economics and Political Science)
Good health and well-being
Openalex Percentile: Top 71%
Global Maternal and Child Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.