Improvement of mobility and motivation in patients with elective colorectal resection using tracking devices and utilizing self-awareness (IMPETUS): a randomized controlled trial in a traditional non-ERAS clinical setting
Clinical Snapshot
PICO Framework
| P — Population | 62 patients undergoing elective colorectal resection in a traditional non-ERAS clinical setting |
| I — Intervention | Smart wearable devices with hourly active reminders to mobilize |
| C — Comparator | Passive monitoring with wearable devices only (no active reminders) |
| O — Outcomes | Primary: total step counts within five postoperative days. Secondary: complication rates, length of hospital stay, subjective motivation |
Bottom Line
This small RCT suggests that smartwatch reminders may increase postoperative mobility and motivation in colorectal surgery patients. While the intervention showed statistically significant benefits for step counts and patient motivation without increasing complications, the study has significant methodological limitations including small sample size, lack of detailed randomisation description, and absence of effect size reporting. The intervention appears safe and feasible, potentially offering a low-cost adjunct to traditional mobilisation strategies. However, larger, more rigorously designed trials with proper sample size calculations and detailed methodology are needed before widespread implementation. The retrospective trial registration raises concerns about selective outcome reporting.
Key Findings
P Value: p = 0.039 for step counts, p = 0.016 for motivation
Effect Size: Not reported
Primary Outcome: Significantly higher step counts in intervention group
Nnt Or Sensitivity: Not calculable from available data
Confidence Interval: Not reported
Clinical Application
High - smartwatches are widely available and intervention is low-cost Highly applicable to Australian practice; aligns with RACGP guidelines on digital health tools and perioperative care standards Patients undergoing elective colorectal surgery in non-ERAS settings
Abstract
BACKGROUND: Early postoperative mobilization is a cornerstone of modern perioperative care, including in elective colorectal surgery. Here we evaluated the effectiveness of smart wearables for improving patients' mobility and motivation during the recovery period after elective colorectal resection. METHODS: This prospective randomized two-armed clinical trial enrolled 62 patients undergoing elective colorectal resection. These patients were randomized into an intervention group that received hourly active reminders to mobilize via a smartwatch, and a control group that received only passive monitoring. All patients were given a wearable device that tracked their daily step counts. The primary end-point was the total number of steps taken within five postoperative days. Secondary end-points included complication rates, length of hospital stay, and subjective motivation, assessed using a structured questionnaire. RESULTS: Compared to the control group, the intervention group achieved significantly higher step counts (p = 0.039), and reported increased motivation for mobilization (p = 0.016). The groups did not significantly differ in overall complication rates or duration of hospital stay. CONCLUSION: Smart wearable devices with hourly active reminder functionalities effectively promoted postoperative mobility and motivation. TRIAL REGISTRATION: German Clinical Trials Register (DRKS), DRKS00039731. Registered 24.03.2026. Retrospectively registered.
References
- 1.Zimniak, L., Soufiah, E., Ha, C. S. R., Gretschel, S., & Paschold, M. (2024). Improvement of mobility and motivation in patients with elective colorectal resection using tracking devices and utilizing self-awareness (IMPETUS): a randomized controlled trial in a traditional non-ERAS clinical setting. BMC Surgery. https://doi.org/10.1007/s00423-024-03442-5
Related Research
Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.
3 Aug 2026
Journal of pediatric surgery
Interpretable deep learning model for pediatric strangulated small bowel obstruction on CT: A multicenter study
3 Aug 2026
European journal of radiology
A CT-based deep learning model to differentiate between benign and malignant adrenal lesions
3 Aug 2026
This content is for educational purposes for healthcare professionals only and does not constitute clinical advice. Clinical decisions should be based on individual patient assessment, current guidelines, and appropriate specialist consultation. Editorial Standards · Privacy Policy · Terms of Service