Pain Management Strategies After Orthopaedic Trauma: A Mixed-Methods Study with a View to Optimizing Practices
Bibliographic record
Abstract
Sonia Grzelak,1,2 Mélanie Bérubé,1,2 Marc-Aurèle Gagnon,1 Caroline Côté,1,2 Valérie Turcotte,3 Stéphane Pelet,4 Ãtienne Belzile4 1Population Health and Optimal Practices Research Unit (Trauma - Emergency - Critical Care Medicine), Laval University Research Center (Hôpital de lâEnfant-Jésus), Quebec City, QC, Canada; 2Faculty of Nursing, Laval University, Quebec City, QC, Canada; 3Nursing Department, CIUSSS du Nord-de-lâÃle-de-Montréal, Hôpital du Sacré-Coeur de Montréal, Montréal, QC, Canada; 4Department of Orthopedic Surgery, CHU de Québec-Université Laval (Hôpital de lâEnfant-Jésus), Quebec City, QC, CanadaCorrespondence: Sonia GrzelakPopulation Health and Optimal Practices Research Unit, Laval University Research Center (Hôpital de lâEnfant-Jésus), 1401, 18 e rue, Quebec City, QC, G1V 1Z4, Canada, Tel +1 418 649-0252, ext 66600, Fax +1 418-649-5733, Email sonia.grzelak.1@ulaval.caPurpose: To examine 1) pain management strategies within the care trajectory of orthopaedic trauma patients and patientsâ perception of their effectiveness, 2) adverse effects (AEs) associated with pharmacological treatments, particularly opioids and cannabis, and 3) patientsâ perceptions of strategies that should be applied after an orthopaedic trauma and support that they should obtain from health professionals for their use.Patients and Methods: This study was conducted with orthopaedic trauma patients in a level 1 trauma center. A convergent mixed-methods design was used. Data on pain experience, pain management strategies used and AEs were collected with self-administered questionnaires at hospital discharge (T1) and at 3 months after injury (T2). Patientsâ preferences about the pain management strategies used, the required support and AEs were further examined through semi-structured individual interviews at the same time measures. Descriptive statistics and thematic analyses were performed.Results: Seventy-one patients were recruited and 30 individual interviews were undertaken. Pharmacological pain management strategies used at T1 and T2 were mainly opioids (95.8%; 20.8%) and acetaminophen (91.5%; 37.5%). The most frequently applied non-pharmacological strategies were sleep (95.6%) and physical positioning (89.7%) at T1 and massage (46.3%) and relaxation (32.5%) at T2. Findings from quantitative and qualitative analyses highlighted that non-pharmacological strategies, such as comfort, massage, distraction, and physical therapy, were perceived as the most effective by participants. Most common AEs related to opioids were dry mouth (78.8%) and fatigue (66.1%) at T1 and insomnia (30.0%) and fatigue (20.0%) at T2. Dry mouth (28.6%) and drowsiness (14.3%) were the most reported AEs by patients using recreational cannabis. An important need for information at hospital discharge and for a personalized follow-up was identified by participants during interviews.Conclusion: Despite its AEs, we found that opioids are still the leading pain management strategy after an orthopaedic trauma and that more efforts are needed to implement non-pharmacological strategies. Cannabis was taken for recreational purposes but patients also used it for pain relief. Support from health professionals is needed to promote the adequate use of these strategies.Keywords: orthopaedic trauma, pain, pharmacological strategies, non-pharmacological strategies, opioids, cannabis
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".