{"doi":"10.1093/jpepsy/jsad073","title":"Correlates of Longitudinal Trajectories of Depressive Symptoms in Adolescents With Traumatic Brain Injuries","abstract":"OBJECTIVE: Depression poses a significant threat to the health and well-being of adolescents with traumatic brain injury. Existing research has limitations in longitudinal follow-up period, consideration of sample heterogeneity, and outcome measurement modeling. This study aimed to address these gaps by applying the second-order growth mixture model (SO-GMM) to examine the 10-year post-injury depression trajectories in adolescents with TBI. METHODS: A total of 1,989 adolescents with TBI 16-21 years old from the Traumatic Brain Injury Model System National Data Bank were analyzed up to 10 years post-injury. Depressive symptoms were measured by Patient Health Questionnaire-9. Covariates included age, sex, race/ethnicity, employment, Functional Independence Measure Cognition, TBI severity, pre-injury disability, and substance use. Longitudinal measurement invariance was tested at the configural, metric, and scalar levels before SO-GMM was fit. Logistic regression was conducted for disparities in depression trajectories by covariates. RESULTS: A 2-class SO-GMM was identified with a low-stable group (85% of the sample) and a high-increasing group (15% of the sample) on depression levels. Older age, being a Native American, and having Hispanic origin was associated with a higher likelihood of being in the high-increasing class (odds ratios [ORs] = 1.165-4.989 and 1.609, respectively), while patients with higher education and being male were less likely to be in the high-increasing class (ORs = 0.735 and 0.557, respectively). CONCLUSIONS: This study examined the disparities in depression among two distinct longitudinal groups of adolescents with TBI 10 years post-injury. Findings of the study are informative for intervention development to improve long-term mental health in adolescents with TBI.","journal":"Journal of Pediatric Psychology","year":2023,"id":377795,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9456,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":951019,"name":"Yan Wang","orcid":"0000-0003-2237-8816","position":1,"is_corresponding":false},{"id":901674,"name":"Jiabin Shen","orcid":"0000-0001-6625-5215","position":0,"is_corresponding":true}],"reference_count":53,"raw_metadata":null,"created_at":"2026-07-19T01:16:40.346877Z","pmid":"37846151","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}