4.1. Strengths and Limitations
dyspnea, illness, fatigue, illness severities, pain
REGRESSION
To our knowledge, the current study is the first to explore the effectiveness of a multimodal mHealth tool on the PA behavior of patients receiving physiotherapy during hospitalization at the departments of Pulmonology or Internal Medicine. This study has a number of strengths, amongst which are the use of a randomized controlled study design and correcting for missing data. Missing data related to PA monitoring could affect the accuracy of the reported outcomes, and missing data related to functional dependence (mILAS scores) could affect the adjustment for this potential confounding variable and lead to biased results. To correct for the impact of missing data, stochastic regression imputation was performed. While imputation introduces some uncertainty, it enhances the completeness of the dataset, potentially reducing biases and leading to more reliable results. We have accounted for the uncertainty introduced by imputation by providing confidence intervals and conducting sensitivity analyses. Moreover, we also acknowledge some limitations. First, we did not monitor how often patients used Hospital Fit or which functionalities patients used. Therefore, we cannot establish a relationship between the frequency of using Hospital Fit and its different functionalities on patients’ PA behavior. The effect of Hospital Fit may have been influenced by patient compliance and engagement. If patients did not consistently use Hospital Fit or did not follow the personalized exercise programs, this could have limited the effectiveness of the intervention. Second, a heterogeneous patient population was included in this study, consisting of patients admitted for acute as well as elective reasons with a variety of diagnoses, illness severities, and symptoms. This heterogeneity may have introduced variations in the outcomes and responses to Hospital Fit. Differences in diagnoses may have led to variations in baseline health, varying mobility levels and different treatment plans, potentially influencing the effect of Hospital Fit. Moreover, illness severity and symptoms (e.g., pain, fatigue, dyspnea) may have influenced patients’ ability to engage in PA. Additionally, some patients were dependent on healthcare professionals to assist them during walking and their PA behavior may have been influenced by a shortage in staffing. In the current study, we did not correct for these potentially confounding factors. Third, selection bias may have been introduced as patients with a lower motivation to be physically active or a higher illness severity may not have been willing to participate in this study. Fourth, the current study was powered to detect an effect with 66 patients. Although sufficient patients were included on day two and three, a number of patients were discharged every day. While clinically relevant effects can be seen from day four on, we lack the power to reach significance. We expect that if we had had sufficient power on days four to seven, we might have been able to detect a significant effect of Hospital Fit use. Lastly, patients received a median (IQR) number of 2 (2–3) physiotherapy sessions. For some patients, this may not have been sufficient to create an effect of using Hospital Fit.