Social adjustment in children diagnosed with sickle cell disease: A retrospective study
Bibliographic record
Abstract
BACKGROUND: Children with sickle cell disease (SCD) are at risk for physical, psychological, and social adjustment challenges. This study sought to investigate social adjustment and related factors in children living with SCD. METHODS: Data from 32 children (50% male, mean age = 10.32 years, SD = 3.27) were retrospectively collected from a neuropsychology clinic at a tertiary care pediatric hospital. Social adjustment was measured using the Behavior Assessment System for Children (BASC-3) parent-proxy, withdrawal subscale, and the Pediatric Quality of Life Inventory (PedsQL) Generic Module Social Functioning self- and parent-proxy subscales. Other measures captured executive functioning (i.e., Behavior Rating Inventory of Executive Function, Second Edition (BRIEF-2) Parent Form) and non-disease-related associations with social adjustment, including number of years in Canada and family functioning (i.e., PedsQL Family Impact Module). RESULTS: Sixteen percent of patients reported elevated social adjustment difficulties. Multiple linear regression found better family functioning [B = .48, t = 2.65, p = .016], and higher executive functioning [B = -.43, t = -2.39, p = .028] were related to higher scores on the PedsQL parent-proxy ratings of social adjustment [F(4,18) = 5.88, p = .003]. Male sex [B = .54, t = 3.08, p = .005], and having lived more years in Canada [B = .55, t = 2.81, p = .009], were related to higher PedsQL self-reported social adjustment [F(4,23) = 3.75, p = .017]. The model examining the BASC-3 withdrawal subscale was not statistically significant [F(4,16) = 1.63, p = .22]. IMPLICATIONS: Social adjustment in children diagnosed with SCD warrants future research to understand the influence of executive function, and non-disease-related factors, particularly focusing on sociocultural factors.
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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 | 0.001 | 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 | 0.001 | 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".