Self-concept among youth with a chronic illness: A meta-analytic review.
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to use meta-analytic techniques to compare self-concept between children and adolescents (abbreviated to youth) with a chronic illness versus healthy controls, and to examine methodological influences on effect sizes. METHOD: Databases were searched for asthma, cerebral palsy, diabetes, epilepsy, and juvenile arthritis. Inclusion criteria were: 1) original research studies in English; 2) youth <18 years; 3) the inclusion of self-reported self-concept; and 4) data available to estimate effect sizes. Study quality was assessed with a modified Quality Index. Effect sizes were calculated as Hedges' g using a random effects model. RESULTS: A total of 60 studies were analyzed. On average, youth with a chronic illness had compromised self-concept, d = -0.17 [-0.27, -0.07]. However, type of control group exerted a moderating influence that resulted in discrepant findings. Studies based on normative data reported higher self-concept in youth with a chronic illness, d = 0.27 [0.06, 0.47], whereas studies that recruited healthy controls reported lower self-concept in youth with a chronic illness, d = -0.25 [-0.34, -0.15]. CONCLUSIONS: Self-concept is compromised in youth with a chronic illness; however, the effect size may be underestimated because of methodological weaknesses and systematic biases in existing studies. Future research should avoid the use of normative data and employ rigorous methods to ensure representative sampling and control of confounding variables to better appreciate the impact of chronic illness on youths' self-concept.
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.025 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".