Introduction. Despite the high number of inactive patients with COPD, not all inactive patients are referred to physical therapy, unlike recommendations of general practitioner (GP) guidelines. It is likely that GPs take other factors into account, determining a subpopulation that is treated by a physical therapist (PT). The aim of this study is to explore the phenotypic differences between inactive patients treated in GP practice and inactive patients treated in GP practice combined with PT. Additionally this study provides an overview of the phenotype of patients with COPD in PT practice. Methods. In a cross-sectional study, COPD patient characteristics were extracted from questionnaires. Differences regarding perceived health status, degree of airway obstruction, exacerbation frequency, and comorbidity were studied in a subgroup of 290 inactive patients and in all 438 patients. Results. Patients treated in GP practice combined with PT reported higher degree of airway obstruction,more exacerbations, more vascular comorbidity, and lower health status compared to patients who were not referred to and treated by a PT. Conclusion. Unequalpatient phenotypes in different primary care settings have important clinical implications. It can be carefully concluded that other factors, besides the level of inactivity, play a role in referral to PT.
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Background: Despite the increasing attention for the positive effects of physical activity (PA), nearly half of the Dutch citizens do not meet the national PA guidelines. A promising method for increasing PA are mobile exercise applications (apps), especially if they are embedded with theoretically supported persuasive strategies (e.g., goal setting and feedback) that align with the needs and wishes of the user. In addition, it is argued that the operationalization of the persuasive strategies could increase the effectiveness of the app, such as the actual content or visualization of feedback. Although much research has been done to examine the preferences for persuasive strategies, little is known about the needs, wishes, and preferences for the design and operationalization of persuasive strategies.Objective: The purpose of this study was to get insight in the needs, wishes, and preferences regarding the practical operationalization of persuasive strategies in a mobile application aimed at promoting PA in healthy inactive adults.Methods: Five semistructured focus groups were performed. During the focus groups, the participants were led into a discussion about the design and operationalization of six predefined theory-based persuasive strategies (e.g., self-monitoring, feedback, goal setting, reminders, rewards, and social support) directed by two moderators. The audio-recorded focus groups were transcribed verbatim and analyzed following the framework approach.Results: Eight men and 17 women between 35 and 55 years (mean age, 49.2) participated in the study. Outcomes demonstrated diverse preferences for implementation types and design characteristics of persuasive strategies in mobile applications. Basic statistics (such as distance, time and calories), positive feedback based on easy-to-achieve goals that relate to health guidelines, and motivating reminders on a relevant moment were preferred. Participants had mixed preferences regarding rewards and a social platform to invite other users to join PA.Conclusions: Findings indicated that in mHealth applications for healthy but inactive adults, persuasive strategies should be designed and implemented in a way that they relate to health guidelines. Moreover, there is a need for an app that can be adapted or can learn based on personal preferences as, for example, preferences with regard to timing of feedback and reminders differed between people.
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The consequences of cardiovascular diseases are substantial and include increasing numbers of morbidity and mortality. With a population getting more and more inactive and having a sedentary lifestyle, the risk for cardiovascular disease and type 2 diabetes rises. This dissertation reports on people with one or more cardiovascular risk factor(s) and who are having an inactive lifestyle, and how healthcare professionals can encourage these people at risk to become and stay physically active in a way that cardiovascular fitness is improved. The assumption is that if an intervention can reduce the prevalence of risk factors, it can also reduce the prevalence of disease. When cardiovascular fitness improves and a person is capable of keeping a physically active lifestyle, levels and number of cardiovascular risk factors can decrease in a population.
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Background: Osteoarthritis is one of the most common chronic joint diseases, mostly affecting the knee or hip through pain, joint stiffness and decreased physical functioning in daily life. Regular physical activity (PA) can help preserve and improve physical functioning and reduce pain in patients with osteoarthritis. Interventions aiming to improve movement behaviour can be optimized by tailoring them to a patients' starting point; their current movement behaviour. Movement behaviour needs to be assessed in its full complexity, and therefore a multidimensional description is needed. Objectives: The aim of this study was to identify subgroups based on movement behaviour patterns in patients with hip and/or knee osteoarthritis who are eligible for a PA intervention. Second, differences between subgroups regarding Body Mass Index, sex, age, physical functioning, comorbidities, fatigue and pain were determined between subgroups. Methods: Baseline data of the clinical trial 'e-Exercise Osteoarthritis', collected in Dutch primary care physical therapy practices were analysed. Movement behaviour was assessed with ActiGraph GT3X and GT3X+ accelerometers. Groups with similar patterns were identified using a hierarchical cluster analysis, including six clustering variables indicating total time in and distribution of PA and sedentary behaviours. Differences in clinical characteristics between groups were assessed via Kruskall Wallis and Chi2 tests. Results: Accelerometer data, including all daily activities during 3 to 5 subsequent days, of 182 patients (average age 63 years) with hip and/or knee osteoarthritis were analysed. Four patterns were identified: inactive & sedentary, prolonged sedentary, light active and active. Physical functioning was less impaired in the group with the active pattern compared to the inactive & sedentary pattern. The group with the prolonged sedentary pattern experienced lower levels of pain and fatigue and higher levels of physical functioning compared to the light active and compared to the inactive & sedentary. Conclusions: Four subgroups with substantially different movement behaviour patterns and clinical characteristics can be identified in patients with osteoarthritis of the hip and/or knee. Knowledge about these subgroups can be used to personalize future movement behaviour interventions for this population.
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BackgroundPhysical exercise in cancer patients is a promising intervention to improve cognition and increase brain volume, including hippocampal volume. We investigated whether a 6-month exercise intervention primarily impacts total hippocampal volume and additionally hippocampal subfield volumes, cortical thickness and grey matter volume in previously physically inactive breast cancer patients. Furthermore, we evaluated associations with verbal memory.MethodsChemotherapy-exposed breast cancer patients (stage I-III, 2–4 years post diagnosis) with cognitive problems were included and randomized in an exercise intervention (n = 70, age = 52.5 ± 9.0 years) or control group (n = 72, age = 53.2 ± 8.6 years). The intervention consisted of 2x1 hours/week of supervised aerobic and strength training and 2x1 hours/week Nordic or power walking. At baseline and at 6-month follow-up, volumetric brain measures were derived from 3D T1-weighted 3T magnetic resonance imaging scans, including hippocampal (subfield) volume (FreeSurfer), cortical thickness (CAT12), and grey matter volume (voxel-based morphometry CAT12). Physical fitness was measured with a cardiopulmonary exercise test. Memory functioning was measured with the Hopkins Verbal Learning Test-Revised (HVLT-R total recall) and Wordlist Learning of an online cognitive test battery, the Amsterdam Cognition Scan (ACS Wordlist Learning). An explorative analysis was conducted in highly fatigued patients (score of ≥ 39 on the symptom scale ‘fatigue’ of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire), as previous research in this dataset has shown that the intervention improved cognition only in these patients.ResultsMultiple regression analyses and voxel-based morphometry revealed no significant intervention effects on brain volume, although at baseline increased physical fitness was significantly related to larger brain volume (e.g., total hippocampal volume: R = 0.32, B = 21.7 mm3, 95 % CI = 3.0 – 40.4). Subgroup analyses showed an intervention effect in highly fatigued patients. Unexpectedly, these patients had significant reductions in hippocampal volume, compared to the control group (e.g., total hippocampal volume: B = −52.3 mm3, 95 % CI = −100.3 – −4.4)), which was related to improved memory functioning (HVLT-R total recall: B = −0.022, 95 % CI = −0.039 – −0.005; ACS Wordlist Learning: B = −0.039, 95 % CI = −0.062 – −0.015).ConclusionsNo exercise intervention effects were found on hippocampal volume, hippocampal subfield volumes, cortical thickness or grey matter volume for the entire intervention group. Contrary to what we expected, in highly fatigued patients a reduction in hippocampal volume was found after the intervention, which was related to improved memory functioning. These results suggest that physical fitness may benefit cognition in specific groups and stress the importance of further research into the biological basis of this finding.
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Objective: To evaluate the preliminary effectiveness of a goal-directed movement intervention using a movement sensor on physical activity of hospitalized patients. Design: Prospective, pre-post study. Setting: A university medical center. Participants: Patients admitted to the pulmonology and nephrology/gastro-enterology wards. Intervention: The movement intervention consisted of (1) self-monitoring of patients' physical activity, (2) setting daily movement goals and (3) posters with exercises and walking routes. Physical activity was measured with a movement sensor (PAM AM400) which measures active minutes per day. Main measures: Primary outcome was the mean difference in active minutes per day pre- and post-implementation. Secondary outcomes were length of stay, discharge destination, immobility-related complications, physical functioning, perceived difficulty to move, 30-day readmission, 30-day mortality and the adoption of the intervention. Results: A total of 61 patients was included pre-implementation, and a total of 56 patients was included post-implementation. Pre-implementation, patients were active 38 ± 21 minutes (mean ± SD) per day, and post-implementation 50 ± 31 minutes per day (Δ12, P = 0.031). Perceived difficulty to move decreased from 3.4 to 1.7 (0-10) (Δ1.7, P = 0.008). No significant differences were found in other secondary outcomes. Conclusions: The goal-directed movement intervention seems to increase physical activity levels during hospitalization. Therefore, this intervention might be useful for other hospitals to stimulate inpatient physical activity.
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BACKGROUND: Although physical activity is beneficial for Parkinson's disease (PD) patients, many do not meet the recommended levels. The range of physical activity among sedentary PD patients is unknown, as are factors that determine this variability. Hence, we aimed to (1) assess daily physical activity in self-identified sedentary PD patients; (2) compare this with criteria of a daily physical activity guideline; and (3) identify determinants of daily physical activity. METHODS: Daily physical activity of 586 self-identified sedentary PD patients was measured with a tri-axial accelerometer for seven consecutive days. Physical fitness and demographic, disease-specific, and psychological characteristics were assessed. Daily physical activity was compared with the 30-min activity guideline. A linear mixed-effects model was estimated to identify determinants of daily physical activity. RESULTS: Accelerometer data of 467 patients who fulfilled all criteria revealed that >98% of their day was spent on sedentary to light-intensity activities. Eighty-two percent of the participants were 'physically inactive' (0 days/week of 30-min activity); 17% were 'semi-active' (1-4 days/week of 30-min activity). Age, gender, physical fitness, and scores on the Unified Parkinson's Disease Rating Scale explained 69% of the variability in daily physical activity. CONCLUSIONS: Performance-based measurements confirmed that most self-identified sedentary PD patients are 'physically inactive'. However, the variance in daily physical activity across subjects was considerable. Higher age, being female, and lower physical capacity were the most important determinants of reduced daily physical activity. Future therapeutic interventions should aim to improve daily physical activity in these high-risk patients, focusing specifically on modifiable risk factors.
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Patients with cardiovascular risk factors can reduce their risk of cardiovascular disease by increasing their physical activity and their physical fitness. According to the guidelines for cardiovascular risk management, health professionals should encourage their patients to engage in physical activity. In this paper, we provide insight regarding the systematic development of a Web-based intervention for both health professionals and patients with cardiovascular risk factors using the development method Intervention Mapping. The different steps of Intervention Mapping are described to open up the “black box” of Web-based intervention development and to support future Web-based intervention development.
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PurposeTo determine which factors are associated with physical inactivity in hospitalized adults of all ages.MethodsA cross-sectional sample of 114 adults admitted to a gastrointestinal surgery, internal medicine or cardiology hospital ward (median age 60, length of stay 13 days) were observed during one random day from 8 am to 8 pm using wireless accelerometers and behavioral mapping protocols. Factors (e.g., comorbidities, self-efficacy, independence in mobility, functional restraints) were collected from medical records, surveys, and observations.ResultsPatients were physically active for median(IQR) 26 (13–52.3) min and were observed to lie in bed for 67.3%, sit for 25.2%, stand for 2.5%, and walk for 5.0% of the time. Multivariable regression analysis revealed that physical inactivity was 159.87% (CI = 89.84; 255.73) higher in patients dependent in basic mobility, and 58.88% (CI = 10.08; 129.33) higher in patients with a urinary catheter (adjusted R2 = 0.52). The fit of our multivariable regression analysis did not improve after adding hospital ward to the analysis (p > 0.05).ConclusionsIndependence in mobility and urine catheter presence are two important factors associated with physical inactivity in hospitalized adults of all ages, and these associations do not differ between hospital wards. Routine assessments of both factors may therefore help to identify physically inactive patients throughout the hospital.IMPLICATIONS FOR REHABILITATIONHealthcare professionals should be aware that physical inactivity during hospital stay may result into functional decline.Regardless of which hospital ward patients are admitted to, once patients require assistance in basic mobility or have a urinary catheter they are at risk of physical inactivity during hospital stay.Implementing routine assessments on the independence of basic mobility and urine catheter presence may therefore assist healthcare professionals in identifying physically inactive patients before they experience functional decline.
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PURPOSE: To investigate factors that influence participation in and needs for work and other daytime activities among individuals with severe mental illnesses (SMI). METHODS: A latent class analysis using routine outcome monitoring data from 1069 patients was conducted to investigate whether subgroups of individuals with SMI can be distinguished based on participation in work or other daytime activities, needs for care in these areas, and the differences between these subgroups. RESULTS: Four subgroups could be distinguished: (1) an inactive group without daytime activities or paid employment and many needs for care in these areas; (2) a moderately active group with some daytime activities, no paid employment, and few needs for care; (3) an active group with more daytime activities, no paid employment, and mainly met needs for care; and (4) a group engaged in paid employment without needs for care in this area. Groups differed significantly from each other in age, duration in MHC, living situation, educational level, having a life partner or not, needs for care regarding social contacts, quality of life, psychosocial functioning, and psychiatric symptoms. Differences were not found for clinical diagnosis or gender. CONCLUSIONS: Among individuals with SMI, different subgroups can be distinguished based on employment situation, daytime activities, and needs for care in these areas. Subgroups differ from each other on patient characteristics and each subgroup poses specific challenges, underlining the need for tailored rehabilitation interventions. Special attention is needed for individuals who are involuntarily inactive, with severe psychiatric symptoms and problems in psychosocial functioning.
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