Characterizing low effort responding among young African adults recruited via Facebook advertising.

Emmanuel Olawale Olamijuwon,Zhifeng Gao

doi:10.1371/journal.pone.0250303

Emmanuel Olawale Olamijuwon, Zhifeng Gao

Open Access

https://doi.org/10.1371/journal.pone.0250303

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Journal: PloS one	Publication Date: May 14, 2021
Citations: 3	License type: CC BY 4.0

Affiliation: University of Eswatini, University of the Witwatersrand

Abstract

Multiple studies have successfully used Facebook’s advertising platform to recruit study participants. However, very limited methodological discussion exists regarding the magnitude of low effort responses from participants recruited via Facebook and African samples. This study describes a quasi-random study that identified and enrolled young adults in Kenya, Nigeria, and South Africa between 22 May and 6 June 2020, based on an advertisement budget of 9,000.00 ZAR (US $521.44). The advertisements attracted over 900,000 views, 11,711‬ unique clicks, 1190 survey responses, and a total of 978 completed responses from young adults in the three countries during the period. Competition rates on key demographic characteristics ranged from 82% among those who attempted the survey to about 94% among eligible participants. The average cost of the advertisements was 7.56 ZAR (US $0.43) per survey participant, 8.68 ZAR (US $0.50) per eligible response, and 9.20 ZAR (US $0.53) per complete response. The passage rate on the attention checks varied from about 50% on the first question to as high as 76% on the third attention check question. About 59% of the sample passed all the attention checks, while 30% passed none of the attention checks. Results from a truncated Poisson regression model suggest that passage of attention checks was significantly associated with demographically relevant characteristics such as age and sex. Overall, the findings contribute to the growing body of literature describing the strengths and limitations of online sample frames, especially in developing countries.

Highlights

BackgroundEvidence of the use of Facebook as a sampling frame for studying population processes continues to emerge
The cloglog model is frequently used when the probability of an event is very small or very large. Model fit indices such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) index provided evidence that the cloglog model was significantly better than other link functions
Over two weeks (22 May-6 June 2020), the advertisement campaign reached over 900,000 young adults in Kenya, Nigeria, and South Africa based on an advertisement cost of about 9,000.00 ZAR (US $521.44)

Summary

Introduction

BackgroundEvidence of the use of Facebook as a sampling frame for studying population processes continues to emerge. [11] during the outbreak of diseases These studies, among others, have demonstrated that this method of sampling study participants is moderately successful at collecting representative samples at a relatively low cost [4,12,13,14,15] and with non-significant biases [16,17]. Data from online samples can provide insights into the broader issues faced by people online and offline [16]. Most of these studies are focused mainly on participants in developed countries. A bulk of web-based studies in African countries have recruited participants mostly through snowball samples of university students [18,19,20,21] and men who have sex with men [22]. The recruitment group was comprised of medical practitioners such as physicians [23,24] and public health officials [25]

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Discussion

Conclusion