Extreme-PGS subgroups show mostly parallel learning trajectories, with task exceptions: for N-Back the low-PGS group learned more and ultimately performed better than the high-PGS group¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2 · q2
Currency · newest study 2022 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Comparing the 15 highest and 15 lowest EAPGS participants, predicted means for most tasks followed relatively parallel trajectories, but for N-Back the low-PGS group learned more over practice and ultimately performed better than the high-PGS group. → Cherry Youn 2022 q2 i? For Word List, the low-PGS group started with an advantage but showed relatively constant performance, while the high-PGS group showed a steeper rate of learning. → Cherry Youn 2022 (2)

Evidence¶

Cherry Youn 2022¶

Cherry Youn, Andrew D. Grotzinger, Christina M. Lill, Lars Bertram, Florian Schmiedek, Martin Lövdén, Ulman Lindenberger, Michel Nivard, K. Paige Harden, Elliot M. Tucker-Drob. (2022). Genetic associations with learning over 100 days of practice. npj Science of Learning. https://doi.org/10.1038/s41539-022-00121-2

q2 · i? · associational · r2

Descriptive subgroup analysis (Fig. 5) comparing trajectories of the 15 highest and 15 lowest EAPGS participants, with outcomes scaled to day-1 distributions. The article reports "the low PGS group learning more over practice and ultimately performing better than high PGS group" for N-Back.

"Descriptive results for N-Back (Panel f) indicate that low and high PGS groups start at very similar points, with the high PGS group at a slight performance advantage relative to the low PGS group, and the low PGS group learning more over practice and ultimately performing better than high PGS group."

Cherry Youn 2022 (2)¶

Cherry Youn, Andrew D. Grotzinger, Christina M. Lill, Lars Bertram, Florian Schmiedek, Martin Lövdén, Ulman Lindenberger, Michel Nivard, K. Paige Harden, Elliot M. Tucker-Drob. (2022). Genetic associations with learning over 100 days of practice. npj Science of Learning. https://doi.org/10.1038/s41539-022-00121-2

q2 · i? · associational · r2

Same extreme-PGS descriptive analysis for the Word List task: the article reports "The low PGS group starts the practice phase with an advantage" yet stays relatively constant, while the high-PGS group shows a steeper rate of learning.

"The low PGS group starts the practice phase with an advantage, but the average performance remains relatively constant from the first to last session, with the group even showing a slight downward trend in performance starting at around session 60."

Discussion¶

Related Claims¶

• Correlations between baseline scores and practice performance follow task-specific qualitative trajectories (upward, downward, or constant) that do not cluster by cognitive ability domain — related
• Growth models show substantial variability in the shape and rate of learning, but no statistically significant EAPGS associations with that variation — reports the opposite
• Educational-attainment polygenic score associations with pre-test, post-test, and pre-to-post change scores on individual cognitive tasks are small and mostly nonsignificant after multiple-testing correction — a broader claim this one bears on
• A polygenic-score study of learning over 100 days of practice in 131 adults was too small to draw meaningful conclusions about genetic effects on baseline performance and learning — related
• Shape search and N-back tasks show no sequence position effect in session-level analysis — related