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Attrition Rate in Infant fNIRS Research: A Meta-Analysis

View ORCID ProfileSori Baek, Sabrina Marques, Kennedy Casey, View ORCID ProfileMeghan Testerman, Felicia McGill, View ORCID ProfileLauren Emberson
doi: https://doi.org/10.1101/2021.06.15.448526
Sori Baek
1Psychology Department, Princeton University, Peretsman, Princeton, NJ 08540, USA
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  • For correspondence: srbaek@princeton.edu
Sabrina Marques
1Psychology Department, Princeton University, Peretsman, Princeton, NJ 08540, USA
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Kennedy Casey
1Psychology Department, Princeton University, Peretsman, Princeton, NJ 08540, USA
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Meghan Testerman
1Psychology Department, Princeton University, Peretsman, Princeton, NJ 08540, USA
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Felicia McGill
1Psychology Department, Princeton University, Peretsman, Princeton, NJ 08540, USA
2Psychology Department, University of South Carolina, Columbia, SC 29208, USA
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Lauren Emberson
1Psychology Department, Princeton University, Peretsman, Princeton, NJ 08540, USA
3Psychology Department, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
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Abstract

Understanding the trends and predictors of attrition rate, or the proportion of collected data that is excluded from the final analyses, is important for accurate research planning, assessing data integrity, and ensuring generalizability. In this pre-registered meta-analysis, we reviewed 182 publications in infant (0-24 months) functional near-infrared spectroscopy (fNIRS) research published from 1998 to April 9, 2020 and investigated the trends and predictors of attrition. The average attrition rate was 34.23% among 272 experiments across all 182 publications. Among a subset of 136 experiments which reported the specific reasons of subject exclusion, 21.50% of the attrition were infant-driven while 14.21% were signal-driven. Subject characteristics (e.g., age) and study design (e.g., fNIRS cap configuration, block/trial design, and stimulus type) predicted the total and subject-driven attrition rates, suggesting that modifying the recruitment pool or the study design can meaningfully reduce the attrition rate in infant fNIRS research. Based on the findings, we established guidelines on reporting the attrition rate for scientific transparency and made recommendations to minimize the attrition rates. We also launched an attrition rate calculator (LINK) to aid with research planning. This research can facilitate developmental cognitive neuroscientists in their quest toward increasingly rigorous and representative research.

Highlights

  • Average attrition rate in infant fNIRS research is 34.23%

  • 21.50% of the attrition are infant-driven (e.g., inattentiveness) while 14.21% are signal-driven (e.g., poor optical contact)

  • Subject characteristics (e.g., age) and study design (e.g., fNIRS cap configuration, block/trial design, and stimulus type) predict the total and infant-driven attrition rates

  • Modifying the recruitment pool or the study design can meaningfully reduce the attrition rate in infant fNIRS research

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Conflict of interest statement: The authors declare no competing financial interests.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 16, 2021.
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Attrition Rate in Infant fNIRS Research: A Meta-Analysis
Sori Baek, Sabrina Marques, Kennedy Casey, Meghan Testerman, Felicia McGill, Lauren Emberson
bioRxiv 2021.06.15.448526; doi: https://doi.org/10.1101/2021.06.15.448526
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Attrition Rate in Infant fNIRS Research: A Meta-Analysis
Sori Baek, Sabrina Marques, Kennedy Casey, Meghan Testerman, Felicia McGill, Lauren Emberson
bioRxiv 2021.06.15.448526; doi: https://doi.org/10.1101/2021.06.15.448526

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