Impact of Adverse Childhood Experiences on Resilience and School Success in Individuals With Autism Spectrum Disorder and Attention-Deficit Hyperactivity Disorder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Adolescents with emotional and behavioral disorders face known academic challenges and poor life outcomes. It was imperative to explore and find if the new diagnostic criterion for diagnosing autism profoundly affects educational outcomes and resilience in individuals diagnosed with co-occurring autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). The literature is robust on the impact of adverse childhood experiences (ACEs) on educational outcomes and resilience in adolescents with no history of disability. Still, there remains a dearth of literature explaining, with no ambiguity, the complex relationships between ACEs and resilience, school engagement, and success in individuals with co-occurring ASD and ADHD. This study reviews the existing scholarships on the topic. The significance of this review is that it informs healthcare providers, rehabilitation counselors, and educators about the need for early identification of individuals with ASD and ADHD with a background in ACEs. This will enable interventions early enough to ensure they are more resilient and can obtain improved success in school-related and outside-school activities and eventually improved quality of life.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it