Little is known about which self-management behaviors have the highest potential to influence exacerbation impact in COPD patients. We aimed to reach expert consensus on the most relevant set of self-management behaviors that can be targeted and influenced to maximize reduction of exacerbation impact. Materials and methods A 2-round Delphi study was performed using online surveys to rate the relevance and feasibility of predetermined self-management behaviors identified by literature and expert opinion. Descriptive statistics and qualitative analyses were used. Results An international expert panel reached consensus on 17 self-management behaviors focusing on: stable phase (n=5): pharmacotherapy, vaccination, physical activity, avoiding stimuli and smoking cessation; periods of symptom deterioration (n=1): early detection; during an exacerbation (n=5): early detection, health care contact, self-treatment, managing stress/anxiety and physical activity; during recovery (n=4): completing treatment, managing stress/anxiety, physical activity and exercise training; and after recovery (n=2): awareness for recurrent exacerbations and restart of pulmonary rehabilitation. Conclusion This study has provided insight into expert opinion on the most relevant and feasible self-management behaviors that can be targeted and influenced before, during and after an exacerbation to exert the highest magnitude of influence on the impact of exacerbations. Future research should focus at developing more comprehensive patient-tailored interventions supporting patients in these exacerbation-related self-management behaviors.
Introduction Around 25% of metastatic breast cancer (mBC) patients develop brain metastases, which vastly affects their overall survival and quality of life. According to the current clinical guidelines, regular magnetic resonance imaging screening is not recommended unless patients have recognized central nervous system-related symptoms. Patient Presentation The patient participated in the EFFECT study, a randomized controlled trial aimed to assess the effects of a 9-month structured, individualized and supervised exercise intervention on quality of life, fatigue and other cancer and treatment-related side effects in patients with mBC. She attended the training sessions regularly and was supervised by the same trainer throughout the exercise program. In month 7 of participation, her exercise trainer detected subtle symptoms (e.g., changes in movement pattern, eye movement or balance), which had not been noticed or reported by the patient herself or her family, and which were unlikely to have been detected by the oncologist or other health care providers at that point since symptoms were exercise related. When suspicion of brain metastases was brought to the attention of the oncologist by the exercise trainer, the response was immediate, and led to early detection and treatment of brain metastases. Conclusion and clinical implications The brain metastases of this patient were detected earlier due to the recognition of subtle symptoms detected by her exercise trainer and the trust and rapid action by the clinician. The implementation of physical exercise programs for cancer patients requires well-trained professionals who know how to recognize possible alterations in patients and also, good communication between trainers and the medical team to enable the necessary actions to be taken.
Maintaining mental health can be quite challenging, especially when exposed to stressful situations. In many cases, mental health problems are recognized too late to effectively intervene and prevent adverse outcomes. Recent advances in the availability and reliability of wearable technologies offer opportunities for continuously monitoring mental states, which may be used to improve a person’s mental health. Previous studies attempting to detect and predict mental states with different modalities have shown only small to moderate effect sizes. This limited success may be due to the large variability between individuals regarding e.g., ways of coping with stress or behavioral patterns associated with positive or negative feelings. A study was set up for the detection of mental states based on longitudinal wearable and contextual sensing, targeted at investigating between-subjects variations in terms of predictors of mental states and variations in how predictors relate to mental states. At the end of March 2022, 16 PhD candidates from the Netherlands started to participate in the study. Over nine months, we collected data in terms of their daily mental states (valence and arousal), continuous physiological data (Oura ring) and smartphone data (AWARE framework including GPS and smartphone usage). From the raw data, we aggregated daily values for each participant in terms of sleep, physical activity, mental states, phone usage and GPS movement. First results (six months into the study at the time of writing) indicate that almost all participants show a large variability in ratings of daily mental states, which is a prerequisite for predictive modeling. Direction, strength and standard deviations of Spearman correlations between valence, arousal and the different variables suggest that several predictors of valence and arousal are more subject dependent than others. In future analyses, we will test and compare different versions of predictive modeling to highlight the potential of wearable technologies for mental state monitoring and the personalized prediction of the development of mental problems.
