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Purpose: Measuring exercise adherence is important in patients with chronic obstructive pulmonary disease (COPD). For this, the Rehabilitation Adherence Measure for Athletic Training (RAdMAT) seems to be a promising instrument, and a Dutch version (RAdMAT-NL) is available. The aim of this study was to explore the dimensionality and construct validity of the RAdMAT-NL in patients with COPD. Secondly, we examined whether the items of the RAdMAT-NL could be summed to a single score. Patients and Methods: This prospective study included 193 patients with COPD from 53 primary physiotherapy practices in The Netherlands and Belgium. Patients and their physiotherapist provided data including the RAdMAT-NL, at one, two, and three months after inclusion. Horn's parallel analysis and exploratory factor analysis (EFA) were used to assess the dimensionality of the RAdMAT-NL. Fit to the dichotomous Rasch model for measurement was used to confirm the unidimensionality of the extracted RAdMAT-NL subscales and total scale. To evaluate construct validity, Spearman correlations with other indicators of adherence were calculated, including SIRAS score, percentage attendance and change in exercise skills. Results: EFA identified two dimensions of the RAdMAT-NL, "Participation" (13 items) and "Communication" (3 items), explaining 50.8% of the total variance. Rasch analysis confirmed the unidimensionality of the two dimensions. The unidimensional Rasch model was rejected for a summed score of all 16 RAdMAT-NL items. Medium to large significant positive correlations between the RAdMAT-NL subscale participation and different measures of adherence supported its convergent validity. Conclusion: The RAdMAT-NL exhibited two subscales that fitted the unidimensional Rasch model for objective measurement. Construct validity was supported by convergence with other established measures of adherence.
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Background: As population ageing accelerates worldwide, chronic diseases will place an increasing burden on society and healthcare systems. Self-management interventions may become a key strategy for addressing chronic disease burden and healthcare costs, also in pulmonary rehabilitation (PR). One of the challenges here is long-term adherence. Understanding the level of adherence to PR may help inform clinical decision-making to focus more on self-management and less on clinical supervision. For this reason, a prediction model (PATCH) was developed. The presented protocol concerns a study that aims 1. to evaluate the safety and effectiveness of self-management within pulmonary rehabilitation (PR) on health outcomes in patients with chronic obstructive pulmonary disease (COPD), 2. to evaluate the predictive validity of the PATCH tool, and 3. to evaluate feasibility and acceptability of self-management and the PATCH tool by patients and physiotherapists. Methods and analysis: This is a protocol of a hybrid type 1 effectiveness-implementation design, performed in primary physiotherapy practices in The Netherlands. The aim is to include 108 patients with COPD who have already followed PR for at least six weeks (maintenance stage of PR). According to the Dutch KNGF Guideline COPD, physiotherapists should reduce the number of supervised treatments after the maintenance phase and support self-management. In practice, this does not (always) happen. This protocol is based on implementing guideline advice: clinical supervision will be halved but patients are stimulated to engage in self-management by exercising unsupervised, leading to no change in the total planned exercise frequency. During the supervised sessions physiotherapists will assess and stimulate self-management. At baseline, and after 3, 6, 9 and 12 months, health outcomes (including adherence) will be evaluated as the primary outcome of this study. At each measurement, the physiotherapist will decide on the basis of individual scores whether the patient needs more clinical supervision or not. Secondary outcomes are the discriminatory power of the PATCH tool (can patients be correctly classified as adherent or non-adherent), and feasibility and acceptability of self-management and the PATCH tool by patients and physiotherapists. Questionnaires and semi-structured interviews will be used for assessment of the outcomes.Trial registration number: METc 2023/074.
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Background: Patients with a chronic disease may have an increased risk of non-adherence to prescribed home-based exercise therapy. We performed a systematic review with the aim to identify variables associated with adherence to home-based exercise therapy in patients with chronic diseases and to grade the quality of evidence for the association between these prognostic factors and adherence. Methods: Cohort studies, cross-sectional studies and the experimental arm of randomized trials were identified using a search strategy applied to PubMed, Embase, PsychINFO and CINAHL from inception until August 1, 2022. We included studies with participants ≥18 years with a chronic disease as an indication for home-based exercise therapy and providing data on prognostic factors of adherence to home-based exercise. To structure the data, we categorized the identified prognostic factors into the five WHO-domains; (1) Patient-related, (2) Social/economic, (3) Therapy-related, (4) Condition-related, and (5) Health system factors. Risk of bias was assessed using the Quality in Prognostic Studies (QUIPS) tool. Prognostic factors of adherence were identified and the quality of the evidence between the prognostic factors and adherence were graded using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework for predictor studies. We performed a meta-analysis of the obtained information. Results: A total of 57 studies were included. Within patient-related factors moderate- and high-quality evidence suggested that more self-efficacy, exercise history, motivation and perceived behavioral control predicted higher adherence. Within social-economic factors moderate-quality evidence suggested more education and physical health to be predictive of higher adherence and within condition-related factors moderate- and low-quality evidence suggested that less comorbidities, depression and fatigue predicted higher adherence. For the domains therapy-related and health-system factors there was not enough information to determine the quality evidence of the prognostic factors. Conclusion: These findings might aid the development of future home-based exercise programs as well as the identification of individuals who may require extra support to benefit from prescribed home-based exercise therapy. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=277003, identifier PROSPERO CRD42021277003.
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Purpose: Pulmonary rehabilitation (PR) is considered a cost-effective method of improving health-related quality of life in patients with chronic obstructive pulmonary disease (COPD). However, increasing demand and increasing costs of supply demands for sustainable and affordable care. One of the possible solutions to keep care affordable is self-management. A challenge here is non-adherence. Understanding who are adherent and who are non-adherent could be helpful to differentiate between patients who need more or less support. Therefore, the aim of this study was to develop and validate a model to predict adherence to PR in patients with COPD. Patients and methods: A multivariable logistic regression model for exercise adherence was developed. Eight candidate predictors, that were prespecified, were obtained in a prospective cohort study from 196 patients with COPD following PR in 53 primary physiotherapy practices in the Netherlands and Belgium, between January 2021 and August 2022. To create a parsimonious model, variable selection using backward selection was performed with a p-value of >0.05 for elimination. Model performance was assessed by discrimination, calibration and clinical utility. Internal validation was assessed by bootstrapping (n = 500). Results: The final model included four predictors: intention, depression, MRC-score and alliance. The optimism-corrected AUC after bootstrap internal validation was 0.79 (95% CI, 0.72-0.85). Calibration plots suggested good calibration and decision curve analysis showed great net benefit in a wide range of risk thresholds. Conclusion: The exercise adherence prediction model has potential for clinical utility to predict adherence in patients with COPD. Information from such a model can be used to manage the patient instead of managing the disease, and thereby to determine the treatment frequency for each individual patient. As a result, healthcare capacity might be better distributed, potentially reducing pressure on healthcare without compromising the effectiveness of PR for the individual patient.
