Objective: To examine implementation of virtual reality (VR) and Fitbit wearable activity devices in postoperative recovery.

Methods: This was a prospective, 4-arm, randomized controlled trial of patients undergoing inpatient head and neck surgery at a tertiary academic center from November 2021 to July 2022. Patients were randomized to Control, VR, Fitbit, or combined VR + Fitbit groups. Patients in the VR groups were brought VR headsets to use throughout each day, and patients in the Fitbit groups wore Fitbit devices and were encouraged to achieve 2,000 daily steps. The primary outcome was average daily opioid use, measured as milligram morphine equivalents (MME).

Results: There were 80 patients included. The majority of patients were male (68.8%), and mean age was 58.8 ± 14.4 years. Only the combined VR + Fitbit cohort was associated with reduced average daily opioid use (VR + Fitbit: 8.8 [20.6] MME vs. Control: 26.4 [37.4] MME, p = 0.02). Patients in intervention groups also had higher hospital satisfaction (p = 0.02). VR was utilized 26% of the time it was provided, with mean use time of 23.8 ± 7.8 min. Mean post-VR subjective pain reduction was 1.0 ± 1.3, and there were three mild adverse events of neck or nasal discomfort. Among the Fitbit groups, there were no adverse events and daily step counts ≥2,000 steps were achieved 45% of the time.

Conclusion: Implementation of VR and wearable activity devices in postoperative recovery appears well tolerated and may facilitate further development of Enhanced Recovery After Surgery (ERAS) protocols, though there are challenges to maximizing device usage.

Level Of Evidence: II. Laryngoscope, 2025.

Download full-text PDF

Source
http://dx.doi.org/10.1002/lary.31989DOI Listing

Publication Analysis

Top Keywords

implementation virtual
8
virtual reality
8
wearable activity
8
activity devices
8
devices postoperative
8
combined vr + fitbit
8
fitbit groups
8
average daily
8
daily opioid
8
adverse events
8

Similar Publications

Background: Advanced technologies are becoming increasingly accessible in rehabilitation. Current research suggests technology can increase therapy dosage, provide multisensory feedback, and reduce manual handling for clinicians. While more high-quality evidence regarding the effectiveness of rehabilitation technologies is needed, understanding of how to effectively integrate technology into clinical practice is also limited.

View Article and Find Full Text PDF

Background: Objective and sensitive measures of everyday function are needed for accurate clinical diagnosis and evaluation of outcomes in clinical trials for dementia. However, most objective everyday function measures are difficult to administer and have not been validated against biomarkers of Alzheimer's disease (AD) neuropathology. This study evaluated the neuroimaging correlates of a highly sensitive, ecologically valid, and easily implementable performance-based test of function called the Virtual Kitchen Challenge (VKC).

View Article and Find Full Text PDF

Objective: To examine implementation of virtual reality (VR) and Fitbit wearable activity devices in postoperative recovery.

Methods: This was a prospective, 4-arm, randomized controlled trial of patients undergoing inpatient head and neck surgery at a tertiary academic center from November 2021 to July 2022. Patients were randomized to Control, VR, Fitbit, or combined VR + Fitbit groups.

View Article and Find Full Text PDF

Background: Pain management after childbirth is widely variable, increasing risk of untreated pain, opioid harms, and inequitable experiences of care. The Creating Optimal Pain Management FOR Tailoring Care (COMFORT) clinical practice guideline (CPG) seeks to promote evidence-based, equitable acute peripartum pain management in the United States. We aimed to identify contextual conditions (i.

View Article and Find Full Text PDF

The Biomedical Applications of Artificial Intelligence: An Overview of Decades of Research.

J Drug Target

January 2025

Sunirmal Bhattacharjee, Bharat Pharmaceutical Technology, Amtali, Agartala, Tripura, India.

A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attracted significant interest in biomedical research due to its features: (i) better patient care through early diagnosis and detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) lowering medical costs; (vi) reducing morbidity and mortality; (vii) enhancing performance; (viii) enhancing precision; and (ix) time efficiency. Quantitative metrics are crucial for evaluating AI implementations, providing insights, enabling informed decisions, and measuring the impact of AI-driven initiatives, thereby enhancing transparency, accountability, and overall impact.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!