Neurocognitive Outcome and Psychological Adjustment Following Pediatric Ischemic and Hemorrhagic Stroke
Bibliographic record
Abstract
Pediatric stroke is an important cause of acquired brain injury in youth associated with neurological sequelae, including complex neurocognitive impairments. Neurocognitive deficits may impact psychological adjustment post-injury by hindering emotional and behavioural regulation, psychosocial functioning, academic advancement, quality of life, and mental health. Despite awareness of the devastating and long-term sequelae following pediatric stroke, research in this domain is lacking. Using a mixed methods approach, my doctoral dissertation contains two clinical studies that address these gaps. Study 1 used a cross-sectional design to investigate the role of eight factors identified in the literature as possible predictors of neurocognitive outcome in pediatric stroke. Ninety-two patients with a history of pediatric stroke participated in this project. Statistical analyses examined relationships between each predictor and neurocognitive outcome measures. Results indicated that large lesions, ischemic stroke, and lower socioeconomic status were associated with worse neurocognitive outcomes compared to small to medium lesions, hemorrhagic stroke, and higher socioeconomic status. Graphs showed U-shaped trends suggesting worse outcomes across most neurocognitive domains when stroke occurred at five to ten years of age. Participants with seizures had more severe executive functioning impairments than participants without seizures. We found little to no evidence of associations between the other predictors and neurocognitive outcomes. Study 2 used an inductive qualitative methodology to provide a personal lens through which to understand the day-to-day impact of neurocognitive impairments, among other sequelae, on adjustment following stroke. Fourteen adolescents and young adults with a history of childhood stroke were interviewed one-on-one to share their lived experience regarding adjustment and coping. Following thematic analysis, five overarching themes were identified: (1) Processing the Story, (2) I’ve Changed, (3) Loss and Challenges, (4) Keys to Recovery, and (5) Adjustment and Acceptance. Findings underscored a need for mental health support for survivors of stroke, as well as important strengths and sources of support drawn upon by survivors. Overall, this dissertation contributed to the advancement of developmental neuropsychology by providing novel insights into neurocognitive outcomes and adjustment following pediatric stroke. Findings should inform clinical practice and the development of services aimed at enhancing recovery and fostering optimal development for youth with stroke.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".