MétaCan
Menu
Back to cohort
Record W2106625803 · doi:10.1177/1087054715587098

Inattention Symptoms Are Associated With Academic Achievement Mostly Through Variance Shared With Intrinsic Motivation and Behavioral Engagement

2015· article· en· W2106625803 on OpenAlexaff
André Plamondon, Rhonda Martinussen

Bibliographic record

VenueJournal of Attention Disorders · 2015
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of TorontoUniversité Laval
Fundersnot available
KeywordsPsychologyIntrinsic motivationVariance (accounting)Association (psychology)Academic achievementReading (process)Student engagementDevelopmental psychologyGoal theoryClinical psychologySocial psychologyMathematics education

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.071
GPT teacher head0.330
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Attention DisordersSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207