EXperienceS and aTtitudes towards Agitated behaviours in Traumatic brain injury in the Intensive Care unit patients (EXSTATIC): a protocol for an interprofessional mixed-method study
Bibliographic record
Abstract
INTRODUCTION: Agitation and violent behaviours are common conditions developed by patients with acute traumatic brain injury (TBI) in intensive care units (ICUs). Healthcare professionals caring for these patients have various tools to manage these behaviours, but lack of a formal protocol to assess and manage them makes caring for these patients a challenge. Moreover, safety may often be compromised for both ICU professionals and patients encountering such situations. The EXperienceS and aTtitudes towards Agitated behaviours in Traumatic brain injury in the Intensive Care unit patients (EXSTATIC) study aims to explore the experiences and attitudes of ICU nurses and other ICU healthcare professionals on the management of agitated behaviours in patients with acute TBI. METHODS AND ANALYSIS: EXSTATIC is a multicenter mixed methods convergent study exploring experiences and attitudes of ICU healthcare professionals caring of agitated patients with TBI. The study includes three qualitative methods (observation, semistructured interviews and focus groups) and one quantitative method (retrospective cohort). The integration of the different methods will be done using sequential steps of the research and by the integration of results for each step. Qualitative data will be evaluated following a thematic analysis derived from a grounded theory approach. Quantitative data will be analysed using descriptive statistics. Qualitative and quantitative results will be combined in a convergent interactive interpretative design. Gender and race perspective will be integrated in collection, analysis and interpretation of data. ETHICS AND DISSEMINATION: This study has been approved by the Centre intégré universitaire de santé et de services sociaux du nord de l'île de Montréal (CIUSSS-NÎM) Research Ethics Board. The findings will be disseminated locally with ICU staff and health managers, international peer-reviewed journals, a PhD dissertation, and national and international conferences. The knowledge derived from this study is key in the development of clinical protocols to manage agitation and related behaviours in patients with TBI and designing further interventional studies targeting this specific problematic. TRIAL REGISTRATION NUMBER: NCT04741399.
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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 | 0.048 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".