Evidence map›Paper›PMID 33795368›Full record

ArticleGlobal health, science and practice2021

Remote Interviewer Training for COVID-19 Data Collection: Challenges and Lessons Learned From 3 Countries in Sub-Saharan Africa.

Shani Turke, Sarah Nehrling, Samuel Olanipekun Adebayo, Pierre Akilimali, Ivan Idiodi, Anthony Mwangi, Elizabeth Larson, Caroline Moreau, Philip Anglewicz

Abstract read
In one paragraph

Article in Global health, science and practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

9 authors.

Shani TurkeBill & Melinda Gates Institute for Population and Reproductive Health, Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. sturke1@jh.edu.
Sarah NehrlingGarabam Consulting, Cambridge, MA, USA.
Samuel Olanipekun AdebayoCentre for Research, Evaluation Resources and Development, Abuja, Nigeria.
Pierre AkilimaliKinshasa School of Public Health, Kinshasa, Democratic Republic of the Congo.
Ivan IdiodiCentre for Research, Evaluation Resources and Development, Abuja, Nigeria.
Anthony MwangiInternational Centre for Reproductive Health, Mombasa, Kenya.
Elizabeth LarsonBill & Melinda Gates Institute for Population and Reproductive Health, Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Caroline MoreauDepartment of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Philip AnglewiczBill & Melinda Gates Institute for Population and Reproductive Health, Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is an urgent need for data to inform coronavirus disease (COVID-19) pandemic response efforts. At the same time, the pandemic has created challenges for data collection, one of which is interviewer training in the context of social distancing. In sub-Saharan Africa, in-person interviewer training and face-to-face data collection remain the norm, requiring researchers to think creatively about transitioning to remote settings to allow for safer data collection that respects government guidelines. Performance Monitoring for Action (PMA, formerly PMA2020) has collected both cross-sectional and longitudinal data on key reproductive health measures in Africa and Asia since 2013. Relying on partnerships with in-country research institutes and cadres of female interviewers recruited from sampled communities, the project was well-positioned to transition to collecting data on COVID-19 from the onset of the pandemic. This article presents PMA's development of a remote training system for COVID-19 surveys in the Democratic Republic of the Congo, Kenya, and Nigeria, including challenges faced and lessons learned. We demonstrate that remote interviewer training can be a viable approach when data are critically needed and in-person learning is not possible. We also argue against systematic replacement of in-person trainings with remote learning, instead recommending consideration of local context and a project's individual circumstances when contemplating a transition to remote interviewer training.

Indexed as

COVID-19Data CollectionEducation, DistancePandemicsAdolescentAdultAfrica South of the SaharaCommunicable Disease ControlDemocratic Republic of the CongoEducation, ProfessionalFemaleHumansInternetKenyaNigeriaPhysical Distancing

Identifiers

PMID33795368
PMCPMC8087422

What OpenQuestion holds

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LicenceCC BY
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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.