Evidence map›Paper›PMID 40773441›Full record

ArticlePloS one2025

Do monetary incentives encourage local communities to collect and upload mosquito sound data using smartphones? A case study in the Democratic Republic of the Congo.

Kieran E Storer, Jane P Messina, Eva Herreros-Moya, Emery Metelo, Josué Zanga, Nono M Mvuama, Soleil Muzinga, Rinita Dam, Marianne Sinka, Ivan Kiskin and 4 more

Abstract read
In one paragraph

Article in PloS one, 2025. 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

14 authors.

Kieran E StorerDepartment of Biology, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0001-9844-7174
Jane P MessinaSchool of Geography and the Environment, Oxford University Centre for the Environment, University of Oxford, Oxford, United Kingdom.
Eva Herreros-MoyaDepartment of Biology, University of Oxford, Oxford, United Kingdom.
Emery MeteloDepartment of Entomology, National Institute for Biomedical Research, Kinshasa, Democratic Republic of the Congo.
Josué ZangaKinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Nono M MvuamaKinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.ORCID https://orcid.org/0000-0003-2046-5836
Soleil MuzingaKinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Rinita DamWarwick Medical School, University of Warwick, Coventry, United Kingdom.ORCID https://orcid.org/0000-0002-4620-7088
Marianne SinkaDepartment of Biology, University of Oxford, Oxford, United Kingdom.
Ivan KiskinSurrey Institute for People-Centred AI, Centre for Vision Speech and Signal Processing, University of Surrey, Guildford, United Kingdom.
Josh EverettDepartment of Biology, University of Oxford, Oxford, United Kingdom.
Yunpeng LiCentre for Oral, Clinical, and Translational Sciences, King's College London, London, United Kingdom.
Stephen RobertsDepartment of Engineering Science, University of Oxford, Oxford, United Kingdom.
Katherine J WillisDepartment of Biology, University of Oxford, Oxford, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Malaria is one of the deadliest vector borne diseases affecting sub-Saharan Africa. A suite of systems are being used to monitor and manage malaria risk and disease incidence, with an increasing focus on technological interventions that allow private citizens to remotely record and upload data. However, data collected by citizen scientists must be standardised and consistent if it is to be used for scientific analysis. Studies that aim to improve data collection quality and quantity have often included incentivisation, providing citizen scientists with monetary or other benefits for their participation in data collection. We tested whether monetary incentives enhance participation and data collection in a study trialling an acoustic mosquito sensor. Working with the community in two health areas in the Democratic Republic of Congo, we measured data collection participation, completeness, and community responses. Our results showed mixed responses to the incentive, with more participants interested in the social status and monetary value of the technology used than the monetary incentive itself. The effect of incentives on data collection varied over the course of the trial, increasing participation in the start of the trial but with no effect in the latter half of the trial. Feedback from participants showed that opinions on technology, research objectives, and incentives varied between communities, and was associated with differences in data collection quantity and quality, suggesting that differences in community interest in data collection and the incentives may be more important than the incentive value itself. These results suggest that though there is an initial benefit, extrinsic motivations do not override differences in intrinsic motivations over time, and enhanced communication and dialogue with participants may improve citizen science participation and attitudes.

Indexed as

CulicidaeData CollectionMotivationSmartphoneAdultAnimalsDemocratic Republic of the CongoFemaleHumansMalariaMaleMiddle AgedMosquito ControlMosquito VectorsSound

Identifiers

PMID40773441
PMCPMC12331038

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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.