Follow-up visits after a concussion in the pediatric population: An integrative review
Bibliographic record
Abstract
BACKGROUND: Concussions are a significant health issue for children and youth. After a concussion diagnosis, follow-up visits with a health care provider are important for reassessment, continued management, and further education. OBJECTIVE: This review aimed to synthesize and analyse the current state of the literature on follow-up visits of children with a concussive injury and examine the factors associated with follow-up visits. METHODS: An integrative review was conducted based on Whittemore and Knafl's framework. Databases searched included PubMed, MEDLINE, CINAHL, PsycINFO, and Google Scholar. RESULTS: Twenty-four articles were reviewed. We identified follow-up visit rates, timing to a first follow-up visit, and factors associated with follow-up visits as common themes. Follow-up visit rates ranged widely, from 13.2 to 99.5%, but time to the first follow-up visit was only reported in eight studies. Three types of factors were associated with attending a follow-up visit: injury-related factors, individual factors, and health service factors. CONCLUSION: Concussed children and youth have varying rates of follow-up care after an initial concussion diagnosis, with little known about the timing of this visit. Diverse factors are associated with the first follow-up visit. Further research on follow-up visits after a concussion in this population is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".