Predicting Adolescent Depression and Suicide Risk based on Preadolescent Behavioral Health Screening in Primary Care DOI Creative Commons
Jason D. Jones, Molly Davis, Sara Reagan

и другие.

Academic Pediatrics, Год журнала: 2025, Номер unknown, С. 102833 - 102833

Опубликована: Апрель 1, 2025

To examine the degree to which a broadband behavioral health screener administered in preadolescence primary care (PC) could serve as an early risk indicator for depression and suicide adolescence. Participants included 9,329 patients who attended well visits at 9 years old 12 large pediatric PC network. The sample was 49% female, 64% White, 18% Black, 4% Asian, 14% other races, 6% Hispanic/Latinx. Caregivers completed Pediatric Symptom Checklist (PSC-17) about their child age 9; youth Patient Health Questionnaire-9 Modified Teens (PHQ-9-M) 12. After adjusting demographic covariates, scoring above cutoffs on PSC-17 total scale subscales (internalizing, externalizing, attention) had significantly greater odds of elevated and/or PHQ-9-M (odds ratios: 2.41 4.23, ps<.001). Approximately one-third with (sensitivity: 37.1%) or 33.3%) were identified 9. Results suggest that PSC-17, well-researched widely used pediatrics, has moderate predictive value respect during More research is needed feasibility potential benefits screening promote identification prevention efforts.

Язык: Английский

Estimation and Validation of the “c” Factor for Overall Cerebral Functioning in the Philadelphia Neurodevelopmental Cohort DOI Creative Commons
Tyler M. Moore, Monica E. Calkins, Daniel H. Wolf

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(4), С. 1697 - 1697

Опубликована: Фев. 7, 2025

While both psychopathology and cognitive deficits manifest in mental health disorders, the nature of their relationship remains poorly understood. Recent research suggests a potential common factor underlying domains. Using data from Philadelphia Neurodevelopmental Cohort (N = 9494, ages 8–21), we estimated validated “c” representing overall cerebral functioning through structural model combining indicators. The incorporated general factors (“p”) ability (“g”), along with specific sub-domain factors. We evaluated model’s criterion validity using external measures, including parent education, neighborhood socioeconomic status, global functioning, intracranial volume, assessed its predictive utility for longitudinal psychosis outcomes. demonstrated acceptable fit (CFI 0.98, RMSEA 0.021, SRMR 0.030), this showed stronger associations education (r 0.43), SES 0.47), volume 0.39) than “p” “g” alone. Additionally, baseline scores significantly predicted spectrum outcomes at follow-up (d 0.30–0.57). These findings support capturing function across domains, implications understanding brain function, improving clinical assessment, optimally focusing interventions.

Язык: Английский

Процитировано

0
Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health DOI Creative Commons
Golia Shafiei, Nathália Bianchini Esper, Max Hoffmann

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Фев. 26, 2025

Major mental disorders are increasingly understood as of brain development. Large and heterogeneous samples required to define generalizable links between development psychopathology. To this end, we introduce the Reproducible Brain Charts (RBC), an open data resource that integrates from 5 large studies in youth three continents ( N =6,346; 45% Female). Confirmatory bifactor models were used create harmonized psychiatric phenotypes capture major dimensions Following rigorous quality assurance, neuroimaging carefully curated processed using consistent pipelines a reproducible manner with DataLad, Configurable Pipeline for Analysis Connectomes (C-PAC), FreeSurfer. Initial analyses RBC emphasize benefit careful assurance harmonization delineating developmental effects associations Critically, all - including phenotypes, unprocessed images, fully imaging derivatives openly shared without use agreement via International Neuroimaging Data-sharing Initiative. Together, facilitates large-scale, reproducible, research neuroscience.

Язык: Английский

Процитировано

0
Prediction of mental health risk in adolescents DOI
Elliot D. Hill,

Pratik Kashyap,

Elizabeth Raffanello

и другие.

Nature Medicine, Год журнала: 2025, Номер unknown

Опубликована: Март 5, 2025

Язык: Английский

Процитировано

0
Predicting Adolescent Depression and Suicide Risk based on Preadolescent Behavioral Health Screening in Primary Care DOI Creative Commons
Jason D. Jones, Molly Davis, Sara Reagan

и другие.

Academic Pediatrics, Год журнала: 2025, Номер unknown, С. 102833 - 102833

Опубликована: Апрель 1, 2025

To examine the degree to which a broadband behavioral health screener administered in preadolescence primary care (PC) could serve as an early risk indicator for depression and suicide adolescence. Participants included 9,329 patients who attended well visits at 9 years old 12 large pediatric PC network. The sample was 49% female, 64% White, 18% Black, 4% Asian, 14% other races, 6% Hispanic/Latinx. Caregivers completed Pediatric Symptom Checklist (PSC-17) about their child age 9; youth Patient Health Questionnaire-9 Modified Teens (PHQ-9-M) 12. After adjusting demographic covariates, scoring above cutoffs on PSC-17 total scale subscales (internalizing, externalizing, attention) had significantly greater odds of elevated and/or PHQ-9-M (odds ratios: 2.41 4.23, ps<.001). Approximately one-third with (sensitivity: 37.1%) or 33.3%) were identified 9. Results suggest that PSC-17, well-researched widely used pediatrics, has moderate predictive value respect during More research is needed feasibility potential benefits screening promote identification prevention efforts.

Язык: Английский

Процитировано

0