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The problem
Intervention: Identification of risk factors for impaired health using patient-reported outcomes measurement to enable targeted intervention
Who it was tested with: 127 youth (mean age 10.59 years) who were survivors of pediatric brain tumors (4.45 years post-diagnosis).
Experience from people who deliver programmes: stories, case studies and lessons learned. Valuable for understanding how and why, and for spotting what to test next, but not a measure of effect.
"Univariate and logistic regression analyses examined potential demographic, medical, and psychosocial factors (e.g., age, race, diagnosis, treatment) related to poor global health." The study uses statistical association to identify modifiable risk factors, but without a prospective design or intervention evaluation, it cannot determine whether addressing these factors causally improves health.
Cross-sectional design cannot establish causation. Uses parent-proxy reporting rather than youth self-report. No control or comparison group. Does not evaluate whether targeting identified risk factors improves outcomes.
Across countries and designs
1 study · 1 country
Classified by the Hub's AI
Not yet reviewed by a person. Model output is not AICS's view until reviewed.
claude-haiku-4-5-20251001 · synth-v1
