Determining the Prevalence and Determinants of Sleep Health in School-Age Children and Adolescent Populations
| dc.contributor | National Institutes of Health |
| dc.contributor.author | Davenport, Mattina |
| dc.contributor.other | Nationwide Children's Hospital |
| dc.date.accessioned | 2025-01-09T17:05:38Z |
| dc.description | Unearthing which patients receive certain clinical outcomes [e.g., sleep diagnosis, sleep medications, and polysomnography (PSG) evaluation] is crucial to identifying subpopulations and individuals that are historically at high risk yet not receiving equitable care. Understanding social determinants of health (SDoH) key features that influence these clinical sleep outcomes will provide more nuanced patient profiles and prompt further exploration of addressing heterogeneity in the pediatric sleep healthcare continuum. #### Study Aims 1. Quantify the robustness of models used to predict risk for patients’ receipt of a sleep diagnosis, sleep medication, or formal evaluation (e.g., PSG or MLST). 2. Develop predictions models that integrate a range of census-tract and zip code (neighborhood) level social determinants of SDoH variables as input features based on patients’ geographies to determine whether this approach shows promise in mitigating algorithmic bias. #### Study Design This is an observational study to establish and validate multivariable prediction models that can predict the risk of sleep disorders, particularly using clinical variables and neighborhood-level social determinants of health. #### Cohort Description The study sample will separately include patients diagnosed with sleep disorders, melatonin, co-occurring conditions at the date of visit, and sleep center visit. - Study period: 06/24 to 06/26 (total duration of 2 years) - Cohort entrance date 04/2020 - Follow-up window: Any follow-up visits until December 2023 - Inclusion/exclusion criteria: Age >=18 years, refers to an exclusion on the day of cohort entrance if the patient is 18 years-old or older. Sleep related encounters occurring outside of the period of 04/2020-12/2023 |
| dc.description.abstract | A study to develop prediction models (e.g., LASSO regression, random forest, patient similarity) that identify social determinants of health (SDoH) associated with clinical pediatric sleep health variables (e.g., sleep diagnoses, sleep medications, and PSG procedural codes) using multisite PEDSnet data from April 2020 - December 2023. |
| dc.identifier.uri | https://hdl.handle.net/20.500.14642/935 |
| dc.publisher | PEDSnet |
| dc.rights | a CC-BY 4.0 Attribution license. |
| dc.rights.uri | https://creativecommons.org/licenses/by-sa/4.0/ |
| dc.subject | PEDSnet Data Source |
| dc.subject | Investigator-Led Study |
| dc.subject | Observational Study |
| dc.subject | Federally-Funded Research |
| dc.subject.mesh | Sleep |
| dc.subject.mesh | Psychophysiology |
| dc.subject.mesh | Nervous System Physiological Phenomena |
| dc.subject.mesh | Psychological Phenomena |
| dc.subject.mesh | Nervous System Diseases |
| dc.title | Determining the Prevalence and Determinants of Sleep Health in School-Age Children and Adolescent Populations |
| dc.title.alternative | 2024.DAVM.NIH.NaCH |
| dspace.entity.type | Study |
| local.admin.note | The PM for this study is Colleen Byrne and the assigned data scientists and study staff include Tes Abraha, Tyler Gorham, and Joseph Sirrianni. |
| local.contributor.siteLead | Nationwide Children's Hospital |
| project.endDate | Present |
| project.startDate | 2024-03 |
| relation.isOrgUnitOfStudy | 32f633d4-ee75-467f-a1a2-24c207244346 |
| relation.isOrgUnitOfStudy.latestForDiscovery | 572f6b4e-6105-4522-b8f4-593015a44d38 |