Inattention Symptoms Are Associated With Academic Achievement Mostly Through Variance Shared With Intrinsic Motivation and Behavioral Engagement
Bibliographic record
Abstract
Objective: The main goal of the current study is to investigate whether intrinsic motivation and behavioral engagement mediate the association between inattention symptoms and academic achievement (reading, writing, and mathematics), as well as to document the extent to which inattention symptoms contribute to academic achievement due to variance overlapping with intrinsic motivation and behavioral engagement. Method: Participants were 92 children (Grades 1-4). Data were gathered using a combination of parent and teacher reports as well as objective assessments. Results: Results did not support the mediating role of intrinsic motivation and behavioral engagement. A commonality analysis showed that 77.44% to 82.10% of the variance explained in each academic achievement domains was due to variance shared by inattention symptoms, intrinsic motivation, and behavioral engagement. Conclusion: These results suggest more commonality than differences between inattention symptoms, intrinsic motivation, and behavioral engagement with regard to their association with academic achievement. The implications of these findings are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".