Mechanism of Injury and Clinical Recovery Outcomes Following Pediatric Concussion

Abstract

Children with concussion are injured through a variety of mechanisms, but the relationship between mechanism of injury (MOI) and recovery outcomes is unclear due to small sample sizes and varied methodological designs. Our objective was to examine the association of MOI and clinical recovery in youth with concussion using a large dataset collated from a single, multisite study. We hypothesized that sport-related concussion would be related to better clinical presentation and faster recovery trajectories compared to other mechanisms of concussion. This study was a secondary analysis of data collected during the Predicting and Preventing Postconcussive Problems in Pediatrics study. Children and adolescents with concussion (n = 3056) completed the Child Sport Concussion Assessment Tool 3rd Edition and Postconcussion Symptom Inventory (PCSI) within 48 h following injury. Follow-up sessions at 1-, 2-, 4-, 8-, and 12-weeks post injury were completed using the PCSI and Pediatric Quality of Life Scale (PedsQL) scales. Acute clinical outcomes were analyzed using analysis of variances or chi-square analyses, while recovery trajectories were evaluated using linear and logistic regression. No MOI-based differences in acute clinical presentation were observed, except for balance outcomes in 13–17 year old (F _[2,1001] = 5.69, p = 0.003). Symptoms improved over time regardless of age (p < 0.05). In 8–12 and 3–17 year olds, quality of life improved over time and was significantly higher in the sports group (p < 0.05). The “other” mechanism group had higher odds of persistent symptoms at 4-week than the sports group in 8–12 year olds (OR = 2.01, 95% CI = 1.20, 3.40, p = 0.008), while this finding was reversed in the 13–17 group (OR = 0.61, 95% CI = 0.38, 0.99, p = 0.045). Sport-related concussions were generally associated with better symptom and quality of life scores in older children, but these differences were modest and unlikely to be clinically significant. Regardless of MOI, most children experienced clinical improvements across the first three months following concussion.

Introduction

The prevalence of pediatric concussion has increased over the last decade, with adolescents experiencing greater changes than preschool- and school-aged children.¹ A concussion can cause various acute deficits, including increased fatigue,² worsened cognition,³ balance and postural control difficulties,⁴ and decreased physical activity levels.⁵ While post injury symptoms typically improve within two to four weeks, approximately 30% of children with concussion experience persistent postconcussion symptoms (PPCs) lasting beyond one month.⁶ PPCs is associated with school absenteeism, declines in academic performance, poor mood, and a diminished overall quality of life.⁷

Determining predictors of prolonged concussion recovery is critical for identifying children at the highest risk of PPCs and prescribing early, targeted interventions to reduce the likelihood of chronic post injury problems.

Preexisting mental health conditions and acute symptom presentation are established predictors of worse clinical outcome and prolonged concussion recovery.^8,9 Other risk factors of extended recovery include prior concussion and age at injury, although this evidence is generally more mixed.^10

–14 Mechanism of injury (MOI) represents another factor capable of affecting recovery outcomes after concussion. The association of MOI and acute symptom presentation is varied, such that individuals concussed through motor vehicle collisions (MVCs) report increased,^15
–17 decreased,¹⁸ or similar¹⁹ post injury symptoms scores to sport-related mechanisms across various studies. Children injured in MVCs had slower symptom recovery trajectories compared to other mechanisms of concussion,¹⁸ but MOI was not predictive of PPCs in children.⁶ Women and older patients with PPCs were more commonly injured by a MVC or a fall, whilst men and younger patients with PPCs were mostly concussed through sports.²⁰ The predicting and preventing postconcussive problems in pediatrics (5P) study found no association between MOI and clinical recovery after pediatric concussion;⁶ however, the prior analysis focused only on presence of persistent symptoms at the 4-week post injury time point and did not investigate recovery trajectories over time. In addition, the original 5P study did not explore MOI by age group, which may potentially mask important associations because MOIs vary by age.²⁰

In summary, several studies have evaluated MOI as a primary independent or confounding variable, but prior analyses were limited by small sample sizes, a focus on cross-sectional designs, and exclusion of young, school-aged children. Thus, there is a continued need for more nuanced approaches that evaluate the effect of MOI on clinical recovery over time in large, age-diverse samples of pediatric concussion patients. Our primary objective was to examine the association between MOI and clinical recovery trajectories in children with concussion aged 5–17 years over the first 3 months following injury. Our secondary objective was to examine the relationship between the mechanism of concussion and acute clinical presentation. As aerobic exercise is related to improved concussion recovery and nonsport concussions are associated with higher rates of comorbid conditions (e.g., additional physical injuries, psychological trauma, etc.), we hypothesized that children injured through a sport-related mechanism would have better clinical presentation and faster recovery trajectories compared to those injured through other mechanisms of concussion.

Materials and Methods

Design and settings

We conducted a secondary analysis of data collected in the 5P study. The full 5P study methods are described elsewhere.^6,21 Briefly, this prospective cohort study enrolled participants within 48 h of concussion from nine pediatric emergency departments (PEDs) in the Pediatric Emergency Research Canada Network between August 2012 and May 2015. The research ethics committees from each participating institution approved the study and written informed consent and/or assent was obtained as required. Deidentified participant data was requested and accessed through the Ontario Brain Institute’s secure neuroinformatics platform, Brain-CODE (https://www.braincode.ca/). Data for this substudy were analyzed between May 2023 and August 2023.

Study population

Children aged 5 − 17 years were eligible if they were diagnosed with a concussion (based on the Zurich Consensus Statement definition)²² and presented to a participating PED within 48 h of injury. Patients were excluded if they had a Glasgow Coma Scale score ≤13 or exhibited abnormalities on standard neuroimaging (if ordered by the treating physician). They were also excluded if they were hospitalized due to multisystem injury, had severe preexisting chronic neurological developmental delays associated with communication difficulties, or were intoxicated upon PED presentation. Additionally, patients were not included if trauma was not the primary event, they had previously enrolled in the same study, or they had a language barrier and was unable to complete the required study follow-up sessions, or if they underwent neurosurgical intervention, intubation, or admission to the intensive care unit admission.

Procedures

Acute clinical presentation outcomes were collected at the initial PED visit. Demographic information, including self-reported MOI, was collected using an electronic survey on a portable computer tablet. Age-appropriate PPCs checklists and cognition, balance, and neck examinations were completed by the children and/or the parent. Prior to leaving the PED, each family provided contact information for follow-up visits. Symptom surveys were readministered at 1, 2, 4, 8, and 12 weeks post injury, while quality of life questionnaires were completed at the 4, 8, and 12 week visits. Follow-up visits were completed online through a secure web-based platform or over the phone based on participant preference.

Outcome measures

Child sport concussion assessment tool 3rd edition

The third edition of the Child Sport Concussion Assessment Tool (Child SCAT3), the most up-to-date version at the time of testing, is a standardized concussion screening tool for children. The Child SCAT3 evaluates nine post-injury domains; only those relevant to our study are described here. Cognition was assessed using orientation, immediate memory, concentration, and delayed memory tasks from the Standardized Assessment of Concussion-Child Version. Static balance was assessed using the double leg and tandem stance conditions from the Balance Error Scoring System (BESS). A neck examination was performed, including neck range of motion, strength, and tenderness outcomes. These Child SCAT3 components were carefully selected and have been used extensively in pediatric concussion research.²³

Post concussion symptom inventory

The Post Concussion Symptom Inventory (PCSI) includes symptom ratings for preinjury and post injury time periods to account for preexisting symptoms and/or symptoms associated with other conditions as well as post injury symptoms that can be used to track clinical recovery from pediatric concussion.²⁴ Separate versions of the PCSI are available for children aged 5–7 (5 items, 3-point Guttman scale), 8–12 (17 items, 3-point Guttman scale), and 13–18 years (21 items, 7-point Guttman scale). Participants are asked to first rate their preinjury symptoms based on retrospective recall, followed by a self-report of current post injury symptoms over the last 24 h. The symptom change score (post injury minus preinjury total scores) was analyzed in the current study.

Persistent postconcussion symptoms

The presence of PPCs was established based on PCSI scores. PPCs was defined as three new or worsened post injury symptoms relative to retrospective ratings of preinjury symptoms on the PCSI at the 4 week follow-up. This definition was used in prior pediatric concussion studies, including the 5P study from which this dataset originates.⁶

Pediatric quality of life scale

The Pediatric Quality of Life Scale (PedsQL) evaluated quality of life across four domains: health, emotional, social, and school. Participants were presented with 23 questions, which they rated from 0 (never a problem) to 4 (almost always a problem). This questionnaire is reliable, valid, and has been used previously in pediatric concussion studies.²⁵ The PedsQL is transformed into an average overall score (0–100 points), with higher scores indicating better quality of life.

Statistical analyses

Data were analyzed in SAS (Version 9.4; SAS Institute, Inc., Cary, North Carolina) and visualized in RStudio using the ggplot2 package.²⁶ The independent variable for all analyses was MOI group. Due to small cell sizes for assault (5–7 years: n = 2; 8–12 years: n = 13; 13–17 years: n = 24) and MVC (5–7 years: n = 5; 8–12 years: n = 13; 13–17 years: n = 38) injuries, these MOIs were combined with the “other” category. Thus, MOI consisted of three levels: 1. Sport-related injuries, 2. Nonsport related falls, and 3. Other mechanisms. The PCSI has multiple versions to ensure developmental appropriateness based on age, with differences in the number of items and scoring for each version. Due to a lack of equivalency, data for 5–7, 8–12, and 13–17 year olds were analyzed separately according to the respective PCSI version.

Patient demographic and acute clinical outcomes were analyzed using analysis of variance (ANOVA) (continuous) or chi-square (categorical) analyses. Tukey post hoc analyses were performed for all significant ANOVA models. Mixed linear models examined the effects of MOI, time, and their interaction on symptom and quality of life outcomes. Logistic regression models evaluated the effect of MOI on the presence of PPCs at 4-weeks. For all regression models, univariate and multivariable models were performed, and p-values reported throughout the article adjust for multiple comparisons as appropriate. Multivariable models controlled for age, sex, pre-existing migraine history, and previous concussion with symptoms lasting ≥1 week, learning disability, anxiety, depression, and BESS tandem stance score because these variables were determined to be important predictors of recovery time in prior studies originating from this dataset. The reference level was set as sport-related concussion for all regression models.

Results

A total of 3056 participants were included. Sport-related mechanisms were most common in the 8–12 (sport: 67.6%, fall: 26.2%, other: 6.2%) and 13–17 (sport: 77.8%, fall: 12.9%, other: 9.3%) year old patients, while falls were the predominant injury mechanism in young children aged 5–7 years (sport: 45.5%, fall: 46.5%, other: 8.1%). Most (n = 1921, [62.9%]) participants completed all six study visits, while 2390 (78.2%) completed five or more visits. Loss to follow-up did not differ by MOI group for 5–7 (p = 0.43), 8–12 (p = 0.12), or 13–18 year olds (p = 0.26). Patient characteristics, presented separately for each age group, are found in Tables 1–3.

Table 1.

Patient Characteristics for the 5–7-Year-Old Group

	Sport(n = 241)	Fall(n = 247)	Other(n = 43)	Overall(n = 531)	p-value
Age (years)	6.7 (0.8)	6.5 (0.8)	6.3 (0.8)	6.6 (0.8)	0.02
Sex
Female	80 (33.2%)	102 (41.3%)	20 (46.5%)	202 (38.0%)	0.09
Male	161 (66.8%)	145 (58.7%)	23 (53.5%)	329 (62.0%)
Prior concussion
0	215 (89.2%)	218 (88.3%)	41 (95.3%)	474 (89.3%)	0.31
1+	22 (9.1%)	29 (11.7%)	2 (4.7%)	53 (10.0%)
Time to ED (hours)	6.4 (9.4)	6.6 (9.4)	6.1 (7.4)	6.5 (9.2)	0.91
Lose consciousness	18 (7.5%)	17 (6.9%)	2 (4.7%)	37 (7.0%)	0.78
Amnesia	32 (13.3%)	32 (13.0%)	5 (11.6%)	69 (13.0%)	0.96
ADHD	17 (7.1%)	7 (2.8%)	2 (4.7%)	26 (4.9%)	0.09
Anxiety	8 (3.3%)	3 (1.2%)	2 (4.7%)	13 (2.4%)	0.20
Depression	0 (0%)	0 (0%)	0 (0%)	0 (0%)	—
Developmental disorder	7 (2.9%)	10 (4.0%)	2 (4.7%)	19 (3.6%)	0.77
Learning disability	11 (4.6%)	10 (4.0%)	1 (2.3%)	22 (4.1%)	0.78
Migraine (Personal Hx)	11 (4.6%)	12 (4.9%)	2 (4.7%)	25 (4.7%)	0.99
Migraine (Family Hx)	116 (48.1%)	117 (47.4%)	16 (37.2%)	249 (46.9%)	0.44
Psychiatric disorder	2 (0.8%)	1 (0.4%)	0 (0%)	3 (0.6%)	0.72
Sleep disorder	4 (1.7%)	1 (0.4%)	0 (0%)	5 (0.9%)	0.28

Age and time to emergency department are presented as mean (standard deviation). All other variables are presented as frequency (percentage). For injury characteristics and preexisting health conditions (from “lose consciousness” to “sleep disorder”), only the number of patients reporting “yes” are displayed.

ADHD, attention deficit/hyperactivity disorder; ED, Emergency Department; Hx, history.

Table 2.

Patient Characteristics for the 8–12-Year-Old Group

	Sport(n = 866)	Fall(n = 335)	Other(n = 79)	Overall(n = 1280)	p-value
Age (years)	10.8 (1.4)	10.5 (1.4)	10.8 (1.4)	10.7 (1.4)	0.03
Sex
Female	276 (31.9%)	141 (42.1%)	27 (34.2%)	444 (34.7%)	0.004
Male	590 (68.1%)	194 (57.9%)	52 (65.8%)	836 (65.3%)
Prior concussion
0	700 (80.8%)	280 (83.6%)	70 (88.6%)	1050 (82.0%)	0.23
1+	159 (18.4%)	55 (16.4%)	9 (11.4%)	223 (17.4%)
Time to ED (hours)	7.6 (11.1)	8.5 (12.9)	9.4 (12.3)	7.9 (11.7)	0.27
Lose consciousness	95 (11.0%)	54 (16.1%)	9 (11.4%)	158 (12.3%)	0.06
Amnesia	116 (13.4%)	47 (14.0%)	9 (11.4%)	172 (13.4%)	0.84
ADHD	77 (8.9%)	30 (9.0%)	6 (7.6%)	113 (8.8%)	0.91
Anxiety	51 (5.9%)	25 (7.5%)	5 (6.3%)	81 (6.3%)	0.63
Depression	9 (1.0%)	3 (0.9%)	2 (2.5%)	14 (1.1%)	0.44
Developmental disorder	34 (3.9%)	15 (4.5%)	4 (5.1%)	53 (4.1%)	0.85
Learning disability	65 (7.5%)	28 (8.4%)	10 (12.7%)	103 (8.0%)	0.28
Migraine (Personal Hx)	80 (9.2%)	40 (11.9%)	10 (12.7%)	130 (10.2%)	0.31
Migraine (Family Hx)	401 (46.3%)	165 (49.3%)	40 (50.6%)	606 (47.3%)	0.49
Psychiatric disorder	5 (0.6%)	2 (0.6%)	2 (2.5%)	9 (0.7%)	0.14
Sleep disorder	8 (0.9%)	5 (1.5%)	3 (3.8%)	16 (1.3%)	0.08

ADHD, attention deficit/hyperactivity disorder; ED, Emergency Department; Hx, history.

Table 3.

Patient Characteristics for the 13–17-Year-Old Group

	Sport(n = 968)	Fall(n = 161)	Other(n = 116)	Overall(n = 1245)	p-value
Age (years)	15.1 (1.3)	15.0 (1.3)	15.5 (1.5)	15.2 (1.3)	0.02
Sex
Female	410 (42.4%)	86 (53.4%)	61 (52.6%)	557 (44.7%)	0.006
Male	558 (57.6%)	74 (46.0%)	55 (47.4%)	687 (55.2%)
Prior concussion
0	625 (64.6%)	112 (69.6%)	82 (70.7%)	819 (65.8%)	0.24
1+	335 (34.6%)	48 (29.8%)	33 (28.4%)	416 (33.4%)
Time to ED (hours)	10.0 (12.4)	12.6 (14.2)	9.3 (11.4)	10.3 (12.6)	0.04
Lose consciousness	154 (15.9%)	24 (14.9%)	21 (18.1%)	199 (16.0%)	0.74
Amnesia	199 (20.6%)	20 (12.4%)	15 (12.9%)	234 (18.8%)	0.01
ADHD	90 (9.3%)	21 (13.0%)	18 (15.5%)	129 (10.4%)	0.045
Anxiety	92 (9.5%)	28 (17.4%)	23 (19.8%)	143 (11.5%)	<0.001
Depression	49 (5.1%)	10 (6.2%)	14 (12.1%)	73 (5.9%)	0.009
Developmental disorder	32 (3.3%)	9 (5.6%)	9 (7.8%)	50 (4.0%)	0.04
Learning disability	78 (8.1%)	23 (14.3%)	17 (14.7%)	118 (9.5%)	0.004
Migraine (Personal Hx)	169 (17.5%)	39 (24.2%)	27 (23.3%)	235 (18.9%)	0.06
Migraine (Family Hx)	442 (45.7%)	75 (46.6%)	58 (50.0%)	575 (46.2%)	0.55
Psychiatric disorder	13 (1.3%)	3 (1.9%)	4 (3.4%)	20 (1.6%)	0.21
Sleep disorder	28 (2.9%)	6 (3.7%)	7 (6.0%)	41 (3.3%)	0.19

ADHD, attention deficit/hyperactivity disorder; ED, Emergency Department; Hx, history.

Acute clinical presentation

For children aged 5–7 and 8–12 years, no significant differences were observed across MOI group for any acute clinical presentation outcomes collected in the PED (Supplementary Tables S1 and S2). A significant effect of MOI was found for the BESS tandem stance in the 13–17 years-old sample (F _(2,1001)=5.69, p = 0.003, Supplementary Table S3). Post hoc testing revealed that the sport-related MOI group had significantly better balance performance than the fall group (mean difference: −0.94, 95% confidence interval [CI]: −1.62, −0.26, p = 0.004). No other differences in acute clinical outcomes were found between MOI groups in the 13–17-years-old sample.

Longitudinal clinical recovery trajectories

In univariate models, the main effect of time (F _(1,2684) = 195.1, p < 0.001) was significant for symptom scores in the 5–7 years old, with symptoms decreasing over time. No main effect of MOI (F _(2,16) = 1.6, p = 0.23) or interaction effects (F _(2,2684) = 0.84, p = 0.43) were observed. These results held in the multivariable model, with symptom scores continuing to decrease over time (F _(1,2677) = 198.7, p < 0.001). In the 8–12-years-old sample, the main effects of time (F _(1,6498) = 577.7, p < 0.001) and MOI (F _(2,16) = 3.78, p = 0.05) were significant in univariate models. Symptoms scores decreased over time and the other mechanism group reported significantly higher symptoms compared to the sport concussion group (t = 2.75, p = 0.01). However, only the main effect of time (F _(1,6490) = 493.4, p < 0.001) was retained in the multivariable model. For the 13–17-years-old sample, univariate models revealed significant main effects of time (F _(1,6191) = 502.8, p < 0.001) only. However, the main effects of time (F _(1,6191) = 531.4, p < 0.001) and MOI (F _(2,16) = 4.29, p = 0.03) were significant in the multivariable model, with symptoms decreasing over time and the fall group having fewer symptoms than the sport group (t = −2.91, p = 0.01).

For PedsQL outcomes, no significant effects of MOI, time, or their interaction were observed for 5–7 year olds in univariate or multivariable models (p > 0.05). For 8–12 year olds, univariate models revealed significant main effects of time (F _(1,3025) = 26.7, p < 0.001) and MOI (F _(2,16) = 8.74, p = 0.003). The sport concussion group had significantly higher quality of life than both the fall (t = −3.19, p = 0.006) and other mechanism (t = −3.17, p = 0.006) groups, but quality of life generally increased over time regardless of MOI. In the multivariable models, both the main effects of time (F _(1,3017) = 25.1, p < 0.001) and MOI (F _(2,16) = 6.43, p = 0.009) remained significant. The 13–17-year-old sample had nearly identical findings. Univariate models revealed main effects of time (F _(1,2835) = 19.2, p < 0.001) and MOI (F _(2,16) = 7.3, p = 0.006), with quality of life increasing over time and the sport group having higher quality of life than the other MOI group (t = 3.71, p = 0.002). Those results were retained in the multivariable model (time: F _(1,2835) = 22.5, p < 0.001; MOI: F _(2,16) = 4.0, p = 0.04, Fig. 1).

FIG. 1.

Symptom (Panels A–C) and quality of life (Panels D–F) trajectories presented separately for each age group. Symptom scores generally decreased over time, but few differences relating to MOI were observed. Quality of life scores increased over time and were higher in the sport-related concussion group in 8–12 and 13–17year olds only. MOI, mechanism of injury.

PPCs at 4 weeks

Only 76 (16.8%) children aged 5–7 years experienced PPCs at 4-weeks (Sport: n = 39, 18.3%, Fall: n = 33, 16.2%, Other: n = 4, 11.8%). No MOI-based differences in PPCs were observed in univariate (p = 0.59) or multivariable (p = 0.48) models. For 8–12 year olds, 281 (25.5%) participants experienced PPCs. Univariate logistic regressions revealed that other MOIs (n = 175, 23.6%) were related to increased PPCs than sport concussions (n = 28, 39.4%, odd ratio [OR] = 2.11, 95% CI = 1.28, 3.50, p = 0.004). This finding was retained in the multivariable model (OR = 2.01, 95% CI = 1.20, 3.40, p = 0.008). In adolescents aged 13–17 years, the overall proportion of patients experiencing PPCs was 41.9% (Sport: n = 337, 41.4%; Fall: n = 66, 50.0%; Other: n = 32, 34.4%, Fig. 2). Compared to sport concussions, univariate models revealed no significant differences in PPCs between the fall (OR = 1.42, 95% CI = 0.98, 2.05, p = 0.06) or other mechanism (OR = 0.74, 95% CI = 0.47, 1.16, p = 0.19) groups. However, in the multivariable model, patients in the other group were significantly less likely to experience PPCs compared to the sport group (OR = 0.61, 95% CI = 0.38, 0.99, p = 0.05).

FIG. 2.

Proportion of patients meeting the study definition of PPCs by MOI for each group. Significant findings in univariate models were observed only for the 8–12 year old group, where patients injured through sport-related mechanisms were significantly less likely to experience PPCs than “other” mechanisms of concussion. PPC, persistent postconcussion symptom; MOI, mechanism of injury.

Discussion

MOI was not associated with any recovery outcomes in children aged 5–7 years. In children and adolescents aged 8–17 years, sport-related concussions were generally associated with slightly more favorable outcomes on select assessments compared to falls and other MOIs, partially supporting our initial hypothesis. However, findings were somewhat mixed, and the mean differences of significant findings are small and unlikely to be clinically significant.

For acute clinical outcomes obtained in the PED, one significant difference was observed. Adolescents aged 13–17 years with a sport-related concussion had significantly better balance compared to children injured during falls. This agrees with prior literature suggesting youth concussed through nonsport mechanisms have worse post injury postural control.²⁷ Healthy athletes have better balance performance than nonathletes;^28
–30 which may contribute to better postconcussion balance performance. We observed no significant findings for acute symptom, mental status, and neck examination outcomes, while prior investigations report mixed results. Studies suggest that acute PPCs are unaffected by MOI,^19,31 which is consistent with our results. However, other studies suggest acute symptom scores are higher in patients injured through MVC and other mechanisms.^15
–17 Mixed findings are also present for cognitive outcomes, with one study reporting worse visual memory scores in association with MOI¹⁹ while another study reports no such differences.¹⁵ Future research should continue to consider the effect of MOI on acute clinical presentation in pediatric populations to provide more concrete conclusions on findings.

A key novel aspect of this study was the investigation of potential associations between MOI and clinical recovery trajectories over time. For longitudinal symptom outcomes, the main effect of time (symptoms improve further out from injury) was observed for all age groups, but no differences between MOI groups were observed. This finding agrees with prior literature, including other investigations using the 5P study dataset.^18,32,33 Collegiate athletes with nonsport concussions had more days lost to injury compared to those injured through sport mechanisms,¹⁷ which indirectly suggests that symptoms improved faster in the sport injury group and disagrees with our findings. However, participants in that study are older and the nonsports concussion group took longer to seek care, which may explain the differences between our results and prior findings. When looking at persistent symptoms at the 4-week assessment specifically, sports-related concussion was related to lower rates of PPCs in 8–12-year-old group only. Compared to the 8–12 year olds, older adolescents (13–18 years) were more likely to be female, have prior concussions, and self-report preexisting mental health conditions, which are all related to slower concussion recovery^8,9,13 and may contribute to a lack of significant finding in this age group. Additionally, neither preinjury physical fitness nor post injury exercise were measured in this study. It is possible that the sports-related concussion group was not more fit or physically active then the other MOI groups and, thus, did not confer any positive benefits of exercise/fitness for their concussion recovery.

In older children, quality of life improved over time and was significantly greater in the sport-concussion group overall. Average quality of life scores reported in our study are similar to or higher than reported in prior concussion studies^34,35 and align with normative values in healthy children.³⁶ Physical activity has numerous positive benefits on physical and mental health,^37

–40 which may contribute to generally higher quality of life in the sport-concussion group. Furthermore, other mechanisms of concussion (e.g., motor vehicle crash, intentional assault) may be related to additional physical injuries or psychological trauma,^41,42 which may further reduce quality of life in this cohort.⁴³

Strengths

While several prior studies have investigated the association between MOI and clinical presentation in concussion patients, limitations prevented firm conclusions. Our study largely accounts for these shortcomings using a large, age-diverse, longitudinal dataset of pediatric concussion patients. We analyzed three different age ranges (5–7, 8–12, and 13–17 year olds), an important consideration given the different MOIs and developmental changes present across childhood. The wide age range of participants overall and broad recruitment are major strengths for having a large and generalizable sample of injured youth who present to PEDs. Our inclusion of young, school-aged children (5–12 years) is particularly noteworthy, as younger children are understudied and findings in adolescent samples may not generalize to younger patients. This study included longitudinal follow-ups across the first three months after concussion, whereas most prior studies investigating the relationship between MOI and clinical outcomes are cross-sectional in nature. Furthermore, follow-up visits were completed online or via telephone; this reduced barriers to participation and promoted retention throughout the study period.

Limitations

Some MOIs were uncommon in our sample. To avoid issues with small cell sizes, we combined these mechanisms into an “other” category. This limits our ability to determine how each mechanism is uniquely associated with clinical recovery. Although the PCSI is a developmentally appropriate tool with strong psychometric characteristics, there is a lack of equivalency between the various PCSI versions. Thus, age groups were analyzed separately based on the cut-offs used for this scale, which limits our ability to either combine age groups or select other age ranges for analysis. Although virtual and phone visits reduced the burden of participation, loss to follow-up was still present. Reasons for loss to follow-up was not available in the requested 5P dataset, but the proportion of patients lost did not differ by MOI group. Symptom and quality of life forms differed by age to ensure developmental appropriateness, but this limits our ability to make direct comparisons between age groups. There is no definitive biomarker of concussion currently available. Thus, concussion diagnosis can be challenging and often relies on the judgement of the treating health care provider and self-reported symptoms by the patient. No intervention was provided through this study, but patients may have independently sought treatment. Future studies should gather information on treatment received by participants and adjust for this potential confounding variable as appropriate.

Clinical significance

Our results suggest that MOI does not alter concussion recovery trajectories in clinically significant ways, indicating that children with concussion likely do not require unique clinical management approaches based on their MOI alone. However, group-based analyses may obscure important individual differences. For example, assault patients may present with associated psychological trauma⁴⁴ and MVC patients may have comorbid injuries which may be associated with poorer clinical outcome after concussion.^45
–47 Thus, while our results suggest that MOI alone does not generally confer increased risk of worse clinical outcomes, clinicians must consider MOI-specific comorbid injuries and illnesses that may affect concussion recovery trajectories. Thus, concussion management should continue to be based on individualized post injury symptoms and problems, as recommended by current best practice approaches.⁴⁸ MOI may also be an important consideration when providing patient education, which is recommended for all children with concussion.⁴⁸ Regardless of MOI, all children with concussion should have access to appropriate health care providers and age-appropriate rehabilitation programs to ensure positive recovery outcomes. Children with sport-related concussions, particularly elite adolescent athletes, may have access to athletic therapists, physiotherapists, or other professionals who can help facilitate recovery,⁴⁹ whereas children concussed through other MOIs may need assistance to access these resources. All children, particularly those at high risk for PPCs, should be referred to interdisciplinary concussion specialists independent of MOI if symptoms have not resolved in 2–4 weeks after injury.⁵⁰

Conclusions

Few significant associations between MOI and clinical outcomes were observed in our study. No differences in acute clinical presentation or recovery trajectories were found based on MOI for young children. For the 8–12 and 13–17-year-old groups, sport-related concussion was related to slightly reduced symptom presentation and higher quality of life compared to other MOIs. However, observed differences are minor and unlikely to be clinically significant. Regardless of MOI, most children experience reduced symptom burden and improved quality of life across the first 3 months following concussion. Referrals to specialty pediatric concussion providers should be considered for youth at higher risk of prolonged recovery and any child not independently achieving clinical recovery within 2–4 weeks.

Transparency, Rigor, and Reproducibility Summary

This study is a secondary analysis of a preexisting dataset and was not preregistered. However, the original study from which this dataset originates was registered on ClinicalTrials.gov (#NCT01873287). The analysis plan for the current study was not formally preregistered, but the team member responsible for data analysis certifies that the executed statistical plan matches the proposed analysis plan detailed in the protocol submitted for ethics review. This secondary analysis used all available participants in the study dataset. A formal sample size calculation was performed for the original study and the necessary number of participants was obtained. All patients (and their parents as appropriate) in the original study consented (or assented) to participation, with data collection performed by investigators aware of relevant participant characteristics. A separate ethics application was submitted and approved to obtain access to the existing study dataset. The inclusion/exclusion criteria and primary outcomes measures used in both the current project and the original 5P study are common clinical outcomes used in pediatric concussion research and clinical care. Deidentified data related to the 5P study are held in a controlled repository hosted by Brain-Code, a secure neuroinformatics platform for data management, sharing and analysis. Interested individuals can request access to this data at https://www.braincode.ca/content/controlled-data-releases. The authors agree to provide the full content of the article on request by contacting the corresponding author.

Footnotes

Acknowledgments

We would like to acknowledge the individuals and organizations that made the data used for this research available, including the Ontario Brain Institute, the Brain-CODE platform, the Government of Ontario, and 5P study team.

Authors’ Contributions

A.G. and S.G.I.: Assisted with data analysis, drafted the initial article, and critically reviewed and revised the article. I.S.G., G.L.I., and N.E.C.: Conceptualized and designed the study and critically reviewed and revised the article for important intellectual content. I.S.G.: Additionally assisted in securing the dataset from the repository in which it is held. R.Z.: Conceptualized and designed the study, secured study financing, and oversaw data collection for the larger study from which this dataset results. R.Z.: Critically reviewed and revised the article for important intellectual content. E.F.T.: Assisted in securing the study dataset, conceptualized and designed the current study, assisted with data analysis, provided student supervision, and critically reviewed and revised the article for important intellectual content.

Author Disclosure Statement

G.L.I. has a clinical practice in forensic neuropsychology, including expert testimony involving individuals with mild traumatic brain injury (TBIs). He has received research support from the Harvard Integrated Program to Protect and Improve the Health of National Football League Player's Association (NFLPA) Members, and a grant from the National Football League. He serves as a scientific advisor for NanoDx™, Sway Medical, Inc., and Highmark, Inc. N.E.C. has a clinical practice in forensic neuropsychology, including expert testimony involving individuals with mild TBIs. R.Z. sits on the board of directors for North American Brain Injury Society which is a volunteer (unpaid) role. He is a founding partner and a minority shareholder of 360 Concussion Care (a learning health system and network of interdisciplinary concussion clinics in Ontario); no proceeds have been transferred to him.

Funding Information

This is a secondary analysis of data collected in the Predicting and Preventing Postconcussive Problems in Pediatrics (5P) study. The original 5P study was funded through the Canadian Institutes of Health Research (operating grant #126197, planning grant #119829) and the Canadian Institutes of Health Research–Ontario Neurotrauma Foundation Mild Traumatic Brain Injury Team (TM1#127047). G.L.I. acknowledges unrestricted philanthropic support from the Mooney-Reed Charitable Foundation, Heinz Family Foundation, Boston Bolts, ImPACT Applications, Inc., National Rugby League, and the Schoen Adams Research Institute at Spaulding Rehabilitation. R.Z.’s program of research has received financial support through competitively funded research grants from Canadian Institutes of Health Research, Ontario Neurotrauma Foundation, Physician Services Incorporated Foundation, Children's Hospital of Eastern Ontario (CHEO) Foundation, University of Ottawa Brain and Mind Research Institute, Ontario Brain Institute, National Football League, Ontario Ministry of Health, Public Health Agency of Canada, Health Canada, Parachute Canada and Ontario SPOR Support Unit. He is supported by a Tier 1 Clinical Research Chair in Pediatric Concussion from the University of Ottawa. All grant funding goes directly to the institution. There is no direct funding related to the secondary analysis presented in this article. The above entities were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.

Supplementary Material

Supplementary Table S1

Supplementary Table S2

Supplementary Table S3

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