Utilization of the Progressive Return to Activity Following Acute Concussion Clinical Recommendations
Bibliographic record
Abstract
Purpose:\nSince 2000, almost 300,000 concussions have been reported in the military population. Concussions were labeled the signature injury of the wars in Iraq and Afghanistan. Prevalence of concussions and implications for service members prompted the Defense Centers of Excellence (DCoE) for Psychological Health and Traumatic Brain Injury to introduce the Progressive Return to Activity Progression Following Acute Concussion/Mild Traumatic Brain Injury clinical recommendations in 2014 to guide cognitive and physical rehabilitation of concussion. The purpose of this study was to identify utilization rates of the DCoE clinical practice recommendations and to identify barriers to implementation that affect clinician adherence. Subjects:\nSubjects included military healthcare providers at Joint Base-Lewis McChord, WA and Fort Wainwright, AK who treat patients with concussions. 79 survey responses were received.\nMethods:\nPrimary service line providers who treat concussion in service members at Joint Base-Lewis McChord, WA and Fort Wainwright, AK were sent an online survey.\nThe survey examined utilization of the clinical recommendations, ease of use, barriers to implementation, recommendations for increased adherence, and use of other return to activity protocols.\nResults:\nWhile 76% of respondents treat service members with concussions and 70% are familiar with the DCOE clinical recommendations, only 31% reported unwavering adherence to the recommendations. Primary reasons for deviating from the protocol included patient compliance (30%) and need to individualize treatment (35%). No significant correlations were found between provider type or experience and protocol use. Significant differences were found between provider and PT/OT rating of the protocol.\nConclusions:\nResponses suggest that the DCOE recommendations are underutilized. Utilization of the protocols could be improved through factors including provider education, ease of application, a more interdisciplinary approach, and the ability to individualize treatment within the parameters of the protocol. Clinical Relevance:\nThe results may inform recommendations to commanders or the Defense and Veteran’s Brain Injury Center for procedural or educational changes to facilitate improved adherence to the clinical recommendations. The study identifies areas for potential protocol modification based on provider feedback and may improve post-concussion outcomes.\nReferences:\n1. DoD Worldwide Numbers for TBI | DVBIC. http://dvbic.dcoe.mil/dod-worldwide-numbers-tbi. Accessed September 11, 2017.\n2. Snell FI, Halter MJ. A signature wound of war: mild traumatic brain injury. J Psychosoc Nurs Ment Health Serv. 2010;48(2):22-28 7p. doi:10.3928/02793695-20100108-02.\n3. McCulloch KL, Goldman S, Lowe L, et al. Development of clinical recommendations for progressive return to activity after military mild traumatic brain injury: guidance for rehabilitation providers. J Head Trauma Rehabil. 2015;30(1):56-67. doi:10.1097/HTR.0000000000000104.\n4. http://www.dtic.mil/dtic/tr/fulltext/u2/a592497.pdf. Accessed September 15, 2017.\n5. http://www.dtic.mil/dtic/tr/fulltext/u2/a592691.pdf. Accessed September 15, 2017.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".