Longitudinal trajectories of post-concussive and depressive symptoms in adolescents with prolonged recovery from concussion

ABSTRACT

Primary Objective: To investigate the symptom trajectories of depressive and post-concussive symptoms (PCS) in slow-to-recover adolescents to understand how the two sets of symptoms are related.

Research Design: We used data from a randomized clinical trial of a collaborative care intervention for post-concussive symptoms to better understand how these two sets of symptoms change in parallel over 6 months.

Methods and Procedure: PCS and depressive symptom scores for 49 adolescents (ages 11–17) were measured at enrolment and after 1, 3, and 6 months. Latent growth curve modelling for parallel processes was used to simultaneously examine change in PCS and depressive symptoms over time and to evaluate the influence of one change process on the other.

Main Outcomes and Results: On average, patients enrolled 66 days following injury (Interquartile range (IQR) 43.5, 88.5). PCS and depressive symptoms were significantly associated at enrolment and over time, and both decreased over the course of 6 months. Higher PCS at enrolment predicted a greater decrease in depressive symptoms over time.

Conclusions: Our results suggest that clinicians should screen for and treat depressive symptoms in patients with high post-concussive symptoms one month following injury.

KEYWORDS:

• concussion
• pediatric
• post-concussive symptoms
• depression
• traumatic brain injury

Declaration of interest

The authors report no conflicts of interest.

Funding

This study was supported by a legacy gift from the Satterberg Foundation. Study data were collected and managed using REDCap electronic data capture tools hosted at the Institute of Translational Health Sciences. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources. REDCap at ITHS is supported by the National Center For Advancing Translational Sciences of the National Institutes of Health under Award Number UL1 TR002319.

Additional information

Funding

This study was supported by a legacy gift from the Satterberg Foundation. Study data were collected and managed using REDCap electronic data capture tools hosted at the Institute of Translational Health Sciences. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources. REDCap at ITHS is supported by the National Center For Advancing Translational Sciences of the National Institutes of Health under Award Number UL1 TR002319.