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Record W4403270698 · doi:10.2196/54389

Pulmonary and Physical Virtual Reality Exercises for Patients With Blunt Chest Trauma: Randomized Clinical Trial

2024· article· en· W4403270698 on OpenAlexvenueno aff
Tjitske D Groenveld, Indy Smits, Naomi Scholten, Marjan de Vries, Harry van Goor, Vincent Stirler

Bibliographic record

VenueJMIR Serious Games · 2024
Typearticle
Languageen
FieldMedicine
TopicTrauma Management and Diagnosis
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintBluntRandomized controlled trialMedicinePhysical therapySurgeryComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Adequate pain relief, early restoration of breathing, and rapid mobilization pose a clinical challenge in patients with blunt chest trauma. Virtual reality (VR) has the potential to achieve these 3 interrelated treatment objectives with enhanced self-efficacy and autonomy of patients and limited support by clinicians. OBJECTIVE: This study aimed to assess the effectivity of breathing and physical exercises using VR on the pulmonary recovery of patients with blunt chest trauma at the ward. METHODS: A pilot randomized controlled trial was performed. The control group received usual physiotherapy consisting of protocolized breathing exercises (8 times daily for 10 minutes) and physical exercises (2 times daily for 10 minutes). The VR group was instructed to perform these exercises using VR. The primary outcome was vital lung capacity at day 5 or earlier at discharge. Secondary outcomes were patient mobility (time standing, lying, and sitting), clinical outcomes (length of hospital stay, pulmonary complications, transfer to intensive care unit, and readmission within 30 days), pain, activities of daily living, patient-reported outcome measures (satisfaction and quality of recovery). Patient experiences and barriers and facilitators toward implementation were assessed through interviews. RESULTS: The study was prematurely ended due to enrollment failure combined with poor protocol adherence to exercises in both groups. A total of 27 patients were included, of which 19 patients completed 3 or more days. Vital lung capacity at 5 days (or last measurement) was equal between groups with 1830 (SD 591) mL and 1857 (SD 435) mL in the control and VR groups, respectively. No marked differences were observed in secondary outcomes. Patient interviews showed positive attitudes toward the use of VR, describing that visualization of the exercises helped patients to perform the exercises correctly and to continue the exercises for a longer duration. Also, patients experienced the immersiveness of VR as an analgesic. However, patients did not experience added value over usual care and reported that better integration in treatment and the hectic hospital environment could improve the use of the VR exercises. CONCLUSIONS: The suitability of patients to use virtual reality therapy (VRx) in a hospital (trauma) ward setting is lower than generally expected. Effective application of VRx requires professional guidance and needs thorough alignment with clinical practice. For future research, we recommend to chart adherence to study protocol before designing a VR clinical trial. Patient-reported experiences need to be prioritized in evaluating VR acceptance, usability, and effectiveness. In line, we recommend performing a systematic analysis (eg, using the technology acceptance model) on the acceptance before pilot or main effectiveness studies. Finally, the eligibility of patients and exclusion of patients due to the inability to use VRx should be routinely reported. TRIAL REGISTRATION: ClinicalTrials.gov NCT05194176; https://tinyurl.com/2bzh4tzx.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.350
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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