Reading difficulties and socio-emotional adjustment: internalizing patterns depend on age of identification
Bibliographic record
Abstract
Children with reading difficulty experience stress in school and may develop negative socio-emotional adjustment. It is unclear what influences some students to experience externalizing patterns and others internalizing patterns. This study investigated the influence of the age of identification of reading difficulties on coping strategies and socio-emotional adjustment. 36 children (ages 9-12) from Winnipeg Schools and Child-Care centres completed measures of coping strategy and socio-emotional adjustment and their parents/guardians reported age of initial reading difficulty. Conditional processing analyses, using percentile bootstrapping, were used to examine mediating effects of coping strategies in the relationship between age-of-identification and socio-emotional adjustment. Results showed children who were identified with reading difficulties in Grade 2 or later were more likely to report using disengagement coping strategies but children identified with reading difficulties before Grade 2 were more likely to report higher internalizing patterns. Evidence for expected mediation by coping strategy was not found. These findings suggest that prolonged experience of reading difficulties is associated with greater risk of developing internalizing problems. Clarifying how age of identification of reading difficulty influences socio-emotional adjustment will help resolve theoretical debates and will help educators/clinicians to better serve students learning to read, and promote struggling readers’ healthy socio-emotional adjustment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".