Surgical treatment affects health-related quality of life (HRQoL) and increases fatigue symptoms in patients with lung cancer (LC) and colorectal cancer (CRC). We aimed to systematically review the effect of exercise training on HRQoL and fatigue after LC and CRC surgery. Randomized controlled trials published before 21 March 2021, were searched in PubMed, Scopus, Web of Science, SPORTDiscus and PEDro. Eligible trials compared the effect of exercise interventions initiated preoperatively or in the first 3 months after surgery versus usual care on postoperative HRQoL and fatigue. Standardized mean differences (SMD) were pooled using random-effects models. Twelve studies with a total of 777 patients were included. In LC patients (10 studies, n = 651), exercise training in general led to a moderate improvement in the physical domain of HRQoL (0.68: 95% CI: [0.47; 0.89]) and a small reduction in fatigue levels after surgery (SMD = 0.28: 95% CI: [0.02; 0.53]), while no effects were found in other HRQoL domains. In CRC (two studies, n = 126), exercise training showed no effects on HRQoL and fatigue after surgery. Exercise training is an effective intervention to improve physical function and fatigue after LC surgery. Further studies are necessary to clarify the effects of exercise on HRQoL and fatigue after CRC surgery.

Background: Clinical guidelines recommend prehabilitation with exercise training to optimize recovery after lung cancer surgery. However, the lack of access to facility-based exercise programs is a major barrier to routine participation. This study aimed to assess the feasibility of a home-based exercise intervention before lung cancer resection. Methods: We conducted a prospective, two-site feasibility study, including patients scheduled for lung cancer surgery. Exercise prescription involved aerobic and resistance training with telephone-based supervision. The primary endpoint was overall feasibility (recruitment rate, retention rate, intervention adherence and acceptability). Secondary endpoints included safety and effects on health-related quality of life (HRQOL) and physical performance, evaluated at baseline, after the exercise intervention and 4–5 weeks after surgery. Results: Over three months, 15 patients were eligible, and all agreed to participate (recruitment rate: 100%). A total of 14 patients completed the exercise intervention, and 12 patients were evaluated postoperatively (retention rate: 80%). The median length of the exercise intervention was 3 weeks. Patients performed an aerobic and resistance training volume higher than prescribed (median adherence rates of 104% and 111%, respectively). A total of nine adverse events occurred during the intervention (Grade 1, n = 8; Grade 2, n = 1), the most common being shoulder pain. After the exercise intervention, significant improvements were observed in the HRQOL summary score (mean difference, 2.9; 95% confidence interval [CI], from 0.9 to 4.8; p = 0.049) and the five-times sit-to-stand test score (median difference, −1.5; 95% CI, from −2.1 to −0.9; p = 0.001). After surgery, no significant effects on HRQOL and physical performance were observed. Conclusion: A short-term preoperative home-based exercise intervention is feasible before lung cancer resection and may enhance accessibility to prehabilitation. Clinical effectiveness should be investigated in future studies.

Motivation can be broadly defined as what moves people to act. Low motivation is a frequently reported factor for the reduced physical activity (PA) levels observed in patients with chronic obstructive pulmonary disease (COPD). This study assessed patients’ motives to be physically active, according to three pulmonary rehabilitation (PR) participation groups (Never PR, Previous PR and Current PR) and explored whether these motives were related to the PA levels and clinical characteristics. The motives to be physically active were assessed with the Exercise Motivation Inventory-2 (EMI-2, 14 motivational factors, five dimensions) and PA with accelerometry (PA groups: <5000 steps/day vs. ≥5000 steps/day). The clinical variables included symptoms, impact of the disease, exercise capacity and comorbidities. Ninety-two patients (67.4 ± 8.1 years, 82.6% male, forced expiratory volume in 1s (FEV1) 48.3 ± 18.9% predicted; 30.4% Never PR, 51% Previous PR and 18.5% Current PR) participated. The motivational dimensions related to health/fitness presented the highest scores (3.8 ± 1.1; 3.4 ± 1.3). The motives to be active were not significantly different between PA groups (p > 0.05) but having less symptoms and ≥two comorbidities were associated with higher scores in psychological/health and body-related motives, respectively (p < 0.05). The findings may encourage health professionals to actively explore with patients their motives to be physically active to individualise PA promotion.

Pulmonary rehabilitation (PR) is a cost-effective intervention with well-known benefits on exercise capacity, symptoms and quality of life in patients with chronic respiratory diseases. Despite the compelling evidence of its benefits, PR implementation is still suboptimal, and maintenance of PR benefits is challenging. To overcome these pitfalls, there has been a growing interest to develop novel models for PR delivery. Digital health is a promising solution, as it has the potential to address some of the most reported barriers to PR uptake and adherence (such as accessibility issues), help maintain the positive results following a PR programme, and/or promote patients’ adherence to a more active lifestyle through physical activity (tele-)coaching. Despite the accelerated use of digital health to deliver PR during the COVID-19 pandemic, there are still several factors that contribute to the resistance in the adoption of digital health, such as the lack of evidence on its effectiveness, low acceptability by patients and healthcare professionals, concerns about implementation and maintenance costs, inequalities in access to the internet and technological devices, and data protection issues. Nevertheless, the trend towards reducing technology costs and the higher availability of digital devices, as well as the greater ease and simplicity of use of devices, enhance the opportunities for future development of digitally enabled PR interventions. This narrative review aimed to examine the current evidence on the role of digital health in the context of PR, including strengths and weaknesses, and to determine possible threats and opportunities, as well as areas for future work.

Effectiveness of technology-based interventions to improve physical activity (PA) in people with COPD is controversial. Mixed results may be due to participants' characteristics influencing their use of and engagement with mobile health apps. This study compared demographic, clinical, physical and PA characteristics of patients with COPD using and not using mobile apps in daily life. Patients with COPD who used smartphones were asked about their sociodemographic and clinic characteristics, PA habits and use of mobile apps (general and PA-related). Participants performed a six-minute walk test (6MWT), gait speed test and wore an accelerometer for 7 days. Data were compared between participants using (App Users) and not using (Non-App Users) mobile apps. A sub-analysis was conducted comparing characteristics of PA–App Users and Non-Users. 59 participants were enrolled (73% Male; 66.3 ± 8.3 yrs; FEV1 48.7 ± 18.4% predicted): 59% were App Users and 25% were PA-App Users. Significant differences between App Users and Non-App Users were found for age (64.2 ± 8.9 vs. 69.2 ± 6.3yrs), 6MWT (462.9 ± 91.7 vs. 414.9 ± 82.3 m), Gait Speed (Median 1.5 [Q1–Q3: 1.4–1.8] vs. 2.0 [1.0–1.5]m/s), Time in Vigorous PA (0.6 [0.2–2.8] vs. 0.14 [0.1–0.7]min) and Self-Reported PA (4.0 [1.0–4.0] vs. 1.0 [0.0–4.0] Points). Differences between PA–App Users and Non-Users were found in time in sedentary behavior (764.1 [641.8–819.8] vs. 672.2 [581.2–749.4] min) and self-reported PA (4.0 [2.0–6.0] vs. 2.0 [0.0–4.0] points). People with COPD using mobile apps were younger and had higher physical capacity than their peers not using mobile apps. PA-App Users spent more time in sedentary behaviors than Non-Users although self-reporting more time in PA.