Karin Valkenet

Background: Hospital admission is associated with increased sedentary behavior and low levels of physical activity. Hospitals have developed several strategies and interventions to address this unwanted inactivity and increase patient movement during admission. Self-monitoring of physical activity is a promising approach to support activity during hospital stays. Objective: This study investigated whether providing patients with real-time physical activity feedback, compared to a context where only health care practitioners had access to activity data, supported patients in maintaining activity levels in the cardiology ward. Methods: A Hybrid Type 2 interrupted time series design was applied. In phase 1 (24 wk), patients wore accelerometers (Physical Activity Monitor [PAM] AM400) with data visible only to health care professionals. In phase 2 (24 wk), self-monitoring was introduced using a ward-based screen that provided patients with real-time feedback on daily physical activity. Implementation outcomes were evaluated within the RE-AIM (Reach, Effectiveness, Adoption, and Implementation) framework, with “Maintenance,” defined as daily physical activity trends over time, serving as the primary outcome. The other RE-AIM dimensions were assessed as secondary outcomes. Results: A total of 159 patients were included (n=75 in phase 1 and n=84 in phase 2). Daily physical activity levels were expressed as active minutes per day. No significant immediate change in daily activity occurred at the start of phase 2 vs the end of phase 1 (β=–0.127, P =.81). In phase 1, physical activity declined statistically significantly over time (β=–0.002, P <.001; ~6% decrease per month). In phase 2, following the introduction of the self-monitoring intervention, this decline was no longer observed, and activity levels were maintained. A significant phase interaction (β=0.002, P =.03) confirmed stabilization of physical activity levels in phase 2. Secondary RE-AIM outcomes did not differ between phases. Conclusions: The decline observed when only health care professionals accessed the data was no longer present once patients could monitor their own physical activity. Although seasonal influences cannot be excluded, these findings suggest that patient self-monitoring may support the maintenance of physical activity during hospital stays. Sustainability is complex, and determining the effect of patient self-monitoring alone remains challenging. Larger studies are needed to confirm these results.

Background and Methods: The role of early and increased activity on postoperative recovery is well established, yet the impact of its day‐to‐day variability remains unclear. This retrospective cohort study examined associations between early in‐hospital postoperative physical activity trajectories and postoperative outcomes among 218 surgical oncology patients from the University Medical Center Utrecht. Group‐based trajectory modelling identified subgroups based on daily activity patterns over the first five postoperative days. Primary analysis assessed associations between trajectory and length of stay (LOS), complications, and 30‐day readmission. Secondary analysis explored sociodemographic and clinical predictors of trajectory. Results: Three trajectories were identified: Minimal ( n = 72), Moderate ( n = 97), and Rapid Activity Recovery ( n = 49). Compared with the Minimal group, Rapid Activity Recovery patients had a 38% shorter LOS (MR: 0.62, 95% CI: 0.50–0.77). Trajectory was not associated with complications or readmissions. Female sex and higher American Society of Anesthesiologists Physical Status Classification were associated with lower odds of belonging to the Rapid Activity Recovery group (OR: 0.33, 95% CI: 0.14–0.78 and OR: 0.38, 95% CI: 0.17–0.84, respectively). Conclusions: Favorable early postoperative activity trajectories were associated with shorter hospital stay. Discussion: Further exploration of real‐time trajectory‐based assessment towards the improvement of postoperative care is needed.

Background: Immune fitness (IF) reflects the body’s ability to mount appropriate immune responses. Monitoring IF could improve tailored treatment in oncological rehabilitation. The Immune Status Questionnaire (ISQ) and the Single-Item Scale (SIS) were developed to assess IF, but their clinimetric properties in cancer rehabilitation remain unknown. Aims: To evaluate the construct validity, responsiveness, and correlation between the ISQ and the SIS in oncological rehabilitation. Methods: The study population included people participating in oncological rehabilitation during or within one year after medical treatment. Data were collected prospectively via questionnaires. Construct validity and responsiveness were assessed through predefined hypotheses, including correlations with fatigue, sleep problems, malnutrition risk, activity impairment, and physical functioning. Results: In total, 97 individuals were included in the analyses. Median ISQ and SIS scores were 8/10 and 7/10, respectively. Correlations ranged from r = −0.21 to r = −0.50. Only the SIS correlations with fatigue and physical functioning, and the ISQ correlation with fatigue, met the predefined thresholds. Responsiveness hypotheses were not confirmed. Conclusions: The ISQ and the SIS demonstrated low construct validity and responsiveness in this population. IF scores were higher than expected. Correlations showed links between fatigue, physical functioning, and IF. Future research should develop tools tailored to the complex immune disturbances experienced by cancer survivors.

BACKGROUND Hospital admission is associated with increased sedentary behavior and low levels of physical activity. Hospitals have developed several strategies and interventions to address this unwanted inactivity and increase patient movement during admission. Self-monitoring of physical activity is a promising approach to support activity during hospital stays. OBJECTIVE This study investigated whether providing patients real time-physical activity feedback, compared to receiving no real time physical activity feedback, supported patients in maintaining activity levels in the cardiology ward. METHODS A Hybrid Type 2 interrupted time series design was applied. In Phase 1 (24 weeks), patients wore accelerometers (PAM AM400) with data visible only to healthcare professionals. In Phase 2 (24 weeks), self-monitoring was introduced using a ward-based screen that provided patients real-time feedback on daily physical activity. Implementation outcomes were evaluated within the RE-AIM framework, with “Maintenance,” defined as daily physical activity trends over time, serving as the primary outcome. The other RE-AIM dimensions (Reach, Effectiveness, Adoption, and Implementation) were assessed as secondary outcomes. RESULTS A total of 159 patients were included (75 in Phase 1, 84 in Phase 2). Daily physical activity levels were expressed as active minutes per day. No significant immediate change in daily activity occurred at the start of Phase 2 versus the end of Phase 1 (β = –0.127, p = 0.811). In Phase 1, physical activity declined statistically significantly over time (β = –0.002, p < 0.001; ~6% decrease per month). In Phase 2, following introduction of the self-monitoring intervention, this decline was no longer observed, and activity levels were maintained. A significant phase interaction (β = 0.002, p = 0.027) confirmed stabilization of physical activity levels in Phase 2. Secondary RE-AIM outcomes did not differ between phases. CONCLUSIONS The decline observed when only healthcare professionals accessed the data was no longer present once patients could monitor their own physical activity. Although seasonal influences cannot be excluded, these findings suggest that patient self-monitoring may support the maintenance of physical activity during hospital stays. Sustainability is complex, and determining the effect of patient self-monitoring alone remains challenging. Larger studies are needed to confirm these results. CLINICALTRIAL Trial registration was not required.

Objective: This study aims to explore the role of patient activity in the clinical decision-making processes of various health care practitioners working in hospital care. Design: Qualitative research study. Setting: The study was conducted in the hospital care setting of UMC Utrecht, the Netherlands. Participants: Health Care Practitioners working in the hospital setting were selected through purposive sampling. Doctors, nurses, and physiotherapists were included if their professional activity centered on inpatient care, they had worked in the hospital for over four weeks and were not students in the department. Main measures: Data were collected through observations and interviews. Interview recordings were transcribed, and both the interview transcripts and observation fieldnotes were coded and analyzed using reflexive thematic analysis, following Braun and Clarke's approach. Themes were iteratively reviewed and refined, leading to the development of core themes, which were constructed by synthesizing subthemes and examining their interrelationships. Results: The study involved forty-two participants working at UMC Utrecht. Four core themes were identified: 1) Patient activity influences clinical decision-making, 2) clinical decision-making influences patient activity, 3) multidisciplinary dynamics influence how patient activity is valued in clinical decisions, and 4) limited use of objective measurements influences how patient activity informs clinical decisions. Conclusion: This study explores the complex interaction between clinical decision-making and patient activity and how patient activity is integrated from a multidisciplinary perspective in the hospital setting. The results highlight the importance of interdisciplinary communication, barriers and facilitators for improved decision-making and examines both implicit and explicit processes involved.

Objective: To investigate the feasibility and preliminary effectiveness of an intervention for family participation in physiotherapy-related tasks of critically ill patients. Design: This quasi-experimental pilot study with a non-equivalent control group was conducted within a mixed adult Intensive Care Unit (ICU). Included were first-degree relatives of critically ill patients who were admitted to the ICU for more than three days and received physiotherapy. Study parameters: The primary outcome was feasibility, based on a minimal 1) recruitment rate; 2) percentage of relatives who chose physiotherapy-related tasks; 3) usage of physiotherapy-related tasks; 4) usability; and 5) maximum number of adverse events. Secondary outcomes were patients’ physical functioning and symptoms of anxiety, depression and post-traumatic stress disorder in family members, at ICU discharge. Results: Between March and June 2021, 34 family members (19 intervention, 15 control) of 27 critically ill patients (16 intervention, 11 control) were included. The recruitment rate was 75.6% (34 out of 45). The percentage of family members who chose physiotherapy-related tasks at baseline was 94.7% (18 out of 19). The average percentage of days that these family members performed physiotherapy-related tasks was 56.7%. The mean System Usability Scale score was 77.1. No adverse events occurred. At ICU discharge there was a significant difference in the mean Hospital Anxiety and Depression Scale - depression score (P=0.030) and mean Impact of Event Scale – Revised (P=0.047) score between the intervention and control group, in favor of the intervention group. Conclusion: Family participation in physiotherapy-related tasks of critically ill patients seems feasible.

Oncology physiotherapists frequently provide care for patients experiencing severe immunosuppression. Exercise immunology, the science that studies the effects of exercise on the immune system, is a rapidly evolving field with direct relevance to oncology physiotherapists. Understanding oncology physiotherapists’ perspectives on the subject of immune functioning is essential to explore its possible integration into clinical reasoning. This study aimed to assess the perspectives of oncology physiotherapists concerning immune functioning in oncology physiotherapy. For this qualitative research, semi-structured interviews were performed with Dutch oncology physiotherapists. Results were analyzed via inductive thematic analysis, followed by a validation step with participants. Fifteen interviews were performed. Participants’ ages ranged from 30 to 63 years. Emerging themes were (1) the construct ‘immune functioning’ (definition, and associations with this construct in oncology physiotherapy), (2) characteristics related to decreased immune functioning (in oncology physiotherapy), (3) negative and positive influences on immune functioning (in oncology physiotherapy), (4) tailored physiotherapy treatment, (5) treatment outcomes in oncology physiotherapy, (6) the oncology physiotherapist within cancer care, and (7) measurement and interpretation of immune functioning. In conclusion, oncology physiotherapists play an important role in the personalized and comprehensive care of patients with cancer. They are eager to learn more about immune functioning with the goal of better informing patients about the health effects of exercise and to tailor their training better. Future exercise-immunology research should clarify the effects of different exercise modalities on immune functioning, and how physiotherapists could evaluate these effects.

Background: Patients undergoing major surgery are at risk of complications and delayed recovery. Prehabilitation has shown promise in improving postoperative outcomes. Offering prehabilitation by means of mHealth can help overcome barriers to participating in prehabilitation and empower patients prior to major surgery. We developed the Be Prepared mHealth app, which has shown potential in an earlier pilot study. Objective: This study aims to evaluate the effectiveness of the Be Prepared app on postoperative recovery of physical functioning (PF) in patients undergoing major elective surgery. Methods: This study was a multicenter randomized controlled trial with 2 arms. Adults scheduled for major elective surgery were randomly assigned to the control (usual care) or intervention group (Be Prepared app in addition to usual care). The Be Prepared app is a smartphone app with pre- and postoperative information and instructions on changing risk behavior for patients undergoing major elective surgery. The primary outcome was recovery of postoperative PF up to 12 weeks after hospital discharge measured with the Computer Adaptive Test Patient-Reported Outcomes Measurement Information System-PF. Secondary outcomes included social participation, self-reported recovery, health-related quality of life, postoperative outcomes, and patient satisfaction. Measurements were performed at 5 time points: before random assignment and 1, 3, 6, and 12 weeks after hospital discharge. Results: A total of 369 patients were analyzed, 181 in the control group and 188 in the intervention group. The result of the linear mixed effects model showed a mean slope difference in recovery of PF over 12 weeks of 2.97 (95% CI 0.90-5.02) in favor of the intervention group. However, this effect was not clinically relevant and was negated by the significantly lower PF score 1 week after hospital discharge in the intervention group (mean difference –1.72, 95% CI –3.38 to –0.07). Most secondary outcome measures did not show significantly greater improvements in the intervention group compared to the control group. Patient satisfaction with overall perioperative care was significantly higher in the intervention group compared to the control group and satisfaction with the Be Prepared app was high. Conclusions: The use of the Be Prepared app as a stand-alone intervention does not seem beneficial for improving postoperative recovery in patients undergoing major surgery. However, satisfaction with perioperative care was higher in patients using the app. Given the advantages of digital technology in health care, it can be considered a basis for prehabilitation care pathways, complemented by guidance from health care professionals as needed.

Background: Early detection of postsurgical complications is critical for improving surgical outcomes, yet current monitoring methods are invasive, time-consuming, and may delay intervention. Advances in machine learning (ML) and artificial intelligence (AI) enable using real-time data, such as accelerometer-derived physical activity, as potential early warning signs. This exploratory study evaluated whether activity trends can predict postsurgical complications in oncology patients using ML models. Methods: Usual care data from a surgical oncology ward (October 2020–December 2024) were analyzed. Three classifiers were evaluated—Random Forest (RF), eXtreme Gradient Boosting (XGB), and Logistic Regression (LR)—within a nested cross-validation framework. Two modeling strategies were compared: (1) training/testing without undersampling and (2) training with undersampling at varying factors to balance complication versus noncomplication days. Models were assessed for next-day complication prediction using area under the ROC curve (AUC), precision, recall, and F1-score with bootstrap confidence intervals. Results: Data were collected from 965 patients, of whom 189 were included. The best performance for RF was observed at an undersampling factor of 1 (AUC = 0.66, 95% confidence interval (CI) 0.64–0.67; recall = 0.63, 95% CI 0.27–0.91; precision = 0.05, 95% CI 0.03–0.07). LR achieved its highest AUC without undersampling (0.68, 95% CI 0.67–0.69), while XGB performed consistently lower (AUC ≈ 0.63–0.64). Conclusions: This exploratory study showed that postoperative activity trends alone were insufficient to predict complications after major oncological surgery. Combining accelerometer, physiological, and laboratory data may improve predictive accuracy and overall clinical value in perioperative care.