Zohreh Badiyepeymaiejahromi, Mostafa Bijani, Mahboobeh Taghizadeganzadeh, Banafsheh Tehranineshat
The effects of using the nurse self-concept mobile application on the retention of nursing students
Journal of education and health promotion
cancer therapies predispose childhood cancer survivors various treatmentrelated late effects contribute higher symptom burden chronic health conditions chcs premature mortality regular monitoring symptoms clinic visits useful timely medical consultation interventions improve quality life qol health share study aims utilize mhealth collect patientgenerated health data pghd daily symptoms momentary physical health status develop survivorspecific risk prediction scores mitigating adverse health outcomes including poor qol emergency room admissions personalized risk scores integrated hospitalbased electronic health record ehr system facilitate clinician communications survivors timely management late effects prospective study recruit 600 adult survivors childhood cancer st jude lifetime cohort study data collection include 20 daily symptoms via smartphone objective physical health data physical activity intensity sleep performance biometric data including resting heart rate heart rate variability oxygen saturation physical stress via wearable activity monitor patientreported outcomes poor qol unplanned healthcare utilization via smartphone clinically ascertained outcomes physical performance deficits onset ofworsening chcs assessed survivorship clinic participants complete health surveys physicalfunctional assessments clinic baseline 2 report daily symptoms wear activity monitor measure blood pressure home 4 months 3 complete health surveys physicalfunctional assessments clinic 1 2 years baseline sociodemographic clinical data abstracted ehr included analysis invite 20 cancer survivors investigate suitable formats display predicted risk information dashboard 10 clinicians suggest evidencebased risk management strategies adverse health outcomes machine statistical learning used prediction modeling approaches handle large number predictors including longitudinal patterns daily symptomsother pghd along cancer treatments sociodemographics individualized risk prediction scores added communications providers survivors potential improve survivorship care outcomes identifying early clinical presentations adverse events